System Decomposition Report — Generated 2026-03-27 — UHT Journal / universalhex.org
This report was generated autonomously by the UHT Journal systems engineering loop. An AI agent decomposed the system into subsystems and components, classified each using the Universal Hex Taxonomy (a 32-bit ontological classification system), generated traced requirements in AIRGen, and built architecture diagrams — all without human intervention.
Every component and subsystem is assigned an 8-character hex code representing its ontological profile across 32 binary traits organised in four layers: Physical (bits 1–8), Functional (9–16), Abstract (17–24), and Social (25–32). These codes enable cross-domain comparison — components from unrelated systems that share a hex code or high Jaccard similarity are ontological twins, meaning they occupy the same structural niche despite belonging to different domains.
Duplicate hex codes are informative, not errors. When two components share the same code, it means UHT classifies them as the same kind of thing — they have identical trait profiles. This reveals architectural patterns: for example, a fire control computer and a sensor fusion engine may share the same hex because both are powered, synthetic, signal-processing, state-transforming, system-essential components. The duplication signals that requirements, interfaces, and verification approaches from one may transfer to the other.
Requirements follow the EARS pattern (Easy Approach to Requirements Syntax) and are traced through a derivation chain: Stakeholder Needs (STK) → System Requirements (SYS) → Subsystem Requirements (SUB) / Interface Requirements (IFC) → Verification Plan (VER). The traceability matrices at the end of this report show every link in that chain.
| Standard | Title |
|---|---|
| COBALT | — |
| COBALT analysis for one crossing option using published A19 corridor accident data. Compare modelled accident changes against manual calculation using the same link flows and DfT accident rates. Pass criteria | — |
| COBALT link | — |
| COBALT methodology | — |
| COBALT methodology per TAG Unit A4.1 | — |
| DMRB | — |
| DMRB CD 116. The Transport Appraisal System SHALL model NO2 and PM2.5 concentrations at all sensitive receptors within 200m of affected road links using a validated atmospheric dispersion model | — |
| DMRB GG 142 | — |
| DMRB GG 142 Option Identification to narrow long | — |
| DMRB GG 142 and professional practice guidance from CIHT. It mitigates risk of publishing unchecked results that could misrepresent scheme value | — |
| DMRB GG 142 determine count weighting in matrix estimation | — |
| DMRB LA 104 | — |
| DMRB LA 104 Environmental Assessment and Monitoring mandates assessment of 14 environmental topics for major road schemes. Failure to cover all 14 topics would render the environmental statement non | — |
| DMRB LA 104 and Habitats Regulations Assessment screening to determine whether each crossing option triggers formal assessment under the Conservation of Habitats and Species Regulations 2017. The Route and Catchment Analyser SHALL compute multi | — |
| DMRB LA 104 assessment criteria | — |
| DMRB LA 104 assessment topics. Delivering them as structured documents with significance ratings | — |
| DMRB LA 104 environmental assessment. Each component addresses a distinct regulatory domain with different methodologies | — |
| DMRB LA 104 environmental topics | — |
| DMRB LA 104 requires quantified assessment of impacts on statutory designated sites. Intersection area determines direct habitat loss | — |
| DMRB LA 104 topics for EIA compliance. Testing against a representative crossing option confirms the interface delivers complete chapter | — |
| DMRB LA 104 topics. Confirm the Report Template Engine receives structured documents with significance ratings and summary tables. Pass criteria | — |
| DMRB LA 105 and LA 111 require assessment at specific sensitive receptors. The Receptor Mapping Engine must geo | — |
| DMRB LA 105 and LA 111 require receptor | — |
| DMRB LA 105 methodology | — |
| DMRB LA 105. NO2 and PM2.5 are the two pollutants with UK air quality limit values most frequently exceeded near roads. Annual mean concentrations are the metric used for compliance assessment against the Air Quality Strategy objectives and EU limit values retained in UK law. The Transport Appraisal System SHALL calculate noise levels at residential facades within 600m of affected road links using CRTN methodology | — |
| DMRB LA 105. The Air Quality and Noise Modelling Engine SHALL compute LA10 | — |
| DMRB LA 105. Unverified outputs cannot support Environmental Statement conclusions. Verify SUB | — |
| DMRB LA 111 | — |
| DMRB LA 111 and the Environmental Noise Regulations 2006. Noise exposure must be computed at all sensitive receptors to quantify impact magnitude and determine eligibility for noise insulation under the Noise Insulation Regulations 1975. The Greenhouse Gas Assessment Module SHALL quantify lifecycle carbon emissions in tonnes CO2e covering construction | — |
| DMRB LA 111 noise assessment requires sufficient receptor density to characterise noise exposure across the study area. The 500 | — |
| DMRB requirements. Receptor type and sensitivity class drive the applicable noise and air quality criteria used for impact significance assessment. The interface between the Spatial Overlay Processor and the Environmental Impact Assessment Module SHALL transfer constraint matrices as structured tables containing option ID | — |
| DMRB scale | — |
| DMRB standards LA 104 | — |
| Green Book Section 5.4 on model assurance. Recording input datasets | — |
| Green Book and DfT business case guidance | — |
| Green Book declining rate schedule | — |
| Green Book discount rates. Pass criteria | — |
| Green Book discounting and produce present value totals for the TEE table. The interface between the Accident Cost | — |
| Green Book discounting and produce the present value of safety benefits. The interface between the Present Value and Discounting Engine and the BCR and AST Generator SHALL transfer the complete set of discounted present values for all benefit and cost categories | — |
| Green Book discounting rules | — |
| Green Book discounting to all monetary benefit and cost streams over the 60 | — |
| Green Book guidance to enable sensitivity testing across different bias levels. The year | — |
| Green Book mandates optimism bias uplifts for publicly | — |
| Green Book optimism bias uplifts to base cost estimates | — |
| Green Book requires a five | — |
| Green Book rules. TAG unit A3 requires lifecycle greenhouse gas quantification covering construction | — |
| Green Book supplementary guidance Table 1 for the appropriate project stage | — |
| NTEM | — |
| NTEM base trip ends. Verify IFC | — |
| NTEM control total compliance is correctly flagged per zone. Verify IFC | — |
| NTEM growth. NTEM v8.0 provides national | — |
| NTEM regional control totals within 0.1 percent. Pass criteria | — |
| NTEM v8.0 North East regional control totals for each forecast year | — |
| NTEM v8.0 constraining is mandatory per TAG Unit M4 for scheme appraisal to ensure consistency with DfT national forecasts. Local development adjustments are required because the North East LEP area has significant committed developments | — |
| NTEM v8.0 control total compliance flags ensure consistency between local planning data and national forecasts | — |
| NTEM v8.0 control total compliance flags per zone. Trip generation is a function of household composition | — |
| NTEM v8.0 control totals is required by TAG unit M4 for trip end forecasting. Local plan adjustments for committed developments in the three boroughs ensure growth forecasts reflect known development commitments rather than relying solely on national trend projections. The Network and GIS Data Repository SHALL store the coded road network with a minimum of 3 | — |
| NTEM v8.0 provides national trip end forecasts that must be locally adjusted for committed developments with planning permission. Without these adjustments | — |
| NTEM v8.0 regional control totals | — |
| NTEM v8.0 regional control totals within 0.5 | — |
| WebTAG | — |
| WebTAG noise valuation tables mapping change in dB at each receptor to willingness | — |
| WebTAG requires Option Assessment Reports and business cases in prescribed formats. The Report Template Engine centralises document assembly to ensure consistency across appraisal outputs and compliance with DfT submission standards. The Option Comparison Module SHALL produce multi | — |
| WebTAG scale | — |
| WebTAG seven | — |
| WebTAG valuation tables and damage cost values respectively. Receptor | — |
| Acronym | Expansion |
|---|---|
| ARC | Architecture Decisions |
| CCCS | Completeness, Consistency, Correctness, Stability |
| EARS | Easy Approach to Requirements Syntax |
| EIA | Country Planning |
| IFC | Interface Requirements |
| PA | Public Accounts |
| STK | Stakeholder Requirements |
| SUB | Subsystem Requirements |
| SYS | System Requirements |
| TEE | Transport Economic Efficiency |
| UHT | Universal Hex Taxonomy |
| VER | Verification Plan |
flowchart TB n0["subsystem<br>Transport Demand Modelling"] n1["subsystem<br>Traffic Microsimulation"] n2["subsystem<br>Economic Appraisal Engine"] n3["subsystem<br>Environmental Assessment"] n4["subsystem<br>Geospatial Analysis Platform"] n5["subsystem<br>Data Acquisition and Management"] n6["subsystem<br>Appraisal Reporting"] n5 -->|Traffic counts, OD matrices, growth data| n0 n0 -->|Turning count matrices| n1 n0 -->|Time savings matrices| n2 n1 -->|Journey time reliability| n2 n0 -->|Traffic flows and speeds| n3 n4 -->|Receptor locations, constraint data| n3 n2 -->|BCR, NPV, monetised benefits| n6 n3 -->|Environmental impact scores| n6 n4 -->|Route plans, constraint maps| n6
New Tyne Crossing Transport Appraisal System — Decomposition
| Ref | Requirement | V&V | Tags |
|---|---|---|---|
| STK-NEEDS-001 | The Transport Appraisal System SHALL produce a WebTAG-compliant economic appraisal demonstrating value for money for each crossing option, suitable for DfT investment decision-making at SOBC, OBC, and FBC stages. Rationale: DfT requires WebTAG-compliant economic appraisal at each business case stage (SOBC/OBC/FBC) as the basis for investment decisions on major transport schemes. Without a compliant BCR calculation, the scheme cannot progress through the DfT approval gateway process. The New Tyne Crossing is expected to cost over 200M GBP, placing it firmly in the Major Scheme category requiring full TAG compliance. | Demonstration | stakeholder, session-263 |
| STK-NEEDS-002 | The Transport Appraisal System SHALL assess environmental impacts of each crossing option in accordance with DMRB LA 104 (Environmental Assessment and Monitoring), LA 105 (Air Quality), LA 111 (Noise and Vibration), and Environment Act 2021 Biodiversity Net Gain requirements. Rationale: Environmental assessment is a statutory requirement for Nationally Significant Infrastructure Projects under the Planning Act 2008 and EIA Regulations 2017. DMRB standards LA 104/105/111 define the assessment methodology mandated for trunk road and major crossing schemes. Failure to demonstrate BNG compliance under the Environment Act 2021 would block planning consent. | Inspection | stakeholder, session-263 |
| STK-NEEDS-003 | The Transport Appraisal System SHALL produce public-facing option comparison materials that present economic, environmental, and social impacts in a format accessible to non-specialist audiences. Rationale: The Aarhus Convention and UK planning law require public consultation on major infrastructure proposals. The transport authority must present appraisal findings to statutory consultees and the public in an accessible format to satisfy DCO application requirements and maintain democratic accountability for a scheme affecting over 100000 daily cross-Tyne trips. | Demonstration | stakeholder, session-263 |
| STK-NEEDS-004 | The Transport Appraisal System SHALL evaluate crossing options across all relevant modes including private vehicle, public transport, cycling, and walking, reflecting the transport authority's commitment to sustainable travel. Rationale: DfT Gear Change policy and the North East Transport Plan mandate multimodal assessment for new crossings. The existing Tyne crossings carry significant pedestrian, cycle, and Metro traffic alongside road vehicles. An appraisal limited to highway modes would understate benefits, misrepresent mode shift potential, and fail DfT scrutiny at gateway review. | Analysis | stakeholder, session-263 |
| STK-NEEDS-005 | The Transport Appraisal System SHALL assess distributional impacts of each option across income quintiles, geographic areas, and protected characteristics per Equality Act 2010. Rationale: The Equality Act 2010 requires public authorities to assess distributional impacts of major decisions. TAG Unit A4.2 mandates distributional impact analysis for DfT-funded schemes. Communities either side of the Tyne have significant socioeconomic variation, and failure to assess equity impacts would risk judicial review of the DCO. | Analysis | stakeholder, session-263 |
| STK-NEEDS-006 | The Transport Appraisal System SHALL maintain full audit trail of data sources, model parameters, assumptions, and version history for each appraisal output. Rationale: DfT Analytical Assurance Framework requires that all major scheme appraisals maintain reproducible audit trails. Independent reviewers at gateway stages must be able to verify model inputs, parameters, and assumptions. Without auditability, the appraisal cannot pass DfT quality assurance and the scheme funding case collapses. | Inspection | stakeholder, session-263 |
| STK-NEEDS-007 | The Transport Appraisal System SHALL produce demand forecasts and economic appraisals for a minimum of three forecast years spanning at least 30 years from scheme opening, with sensitivity tests for high and low growth scenarios. Rationale: TAG Unit M4 requires demand forecasts spanning at least the appraisal period to capture long-term economic benefits and traffic growth uncertainty. A 30-year horizon aligns with the standard 60-year appraisal period discounted to present values. Sensitivity testing for high and low growth is mandated by TAG to demonstrate scheme resilience to demand uncertainty. | Analysis | stakeholder, session-263 |
| STK-NEEDS-008 | The Transport Appraisal System SHALL identify and map all statutory and non-statutory constraints within 500m of each route option corridor, including flood zones, designated ecological sites, listed buildings, scheduled monuments, and contaminated land. Rationale: Planning policy requires identification of all environmental and heritage constraints within the zone of influence of a major crossing. The 500m corridor captures direct construction impacts, visual intrusion, noise propagation, and ecological connectivity effects. Missing a statutory constraint would delay or invalidate the DCO application. | Inspection | stakeholder, session-263 |
| STK-NEEDS-010 | The Transport Appraisal System SHALL assess road safety impacts of each crossing option by quantifying changes in accident frequency and severity using COBALT methodology, identifying accident-prone locations within the study area, and demonstrating that the preferred option does not introduce unacceptable safety risks at junctions and merge points. | Analysis | stakeholder, safety, session-275 |
| Ref | Requirement | V&V | Tags |
|---|---|---|---|
| SYS-REQS-001 | The Transport Appraisal System SHALL compute initial and adjusted Benefit-Cost Ratios for each crossing option using DfT TAG Data Book values of time, vehicle operating costs, and discount rates current at the time of appraisal. Rationale: BCR is the primary value-for-money metric used by DfT to rank and approve major schemes. Using TAG Data Book values of time and vehicle operating costs ensures consistency with national appraisal standards. Both initial BCR (transport user benefits only) and adjusted BCR (including wider economic impacts) are required for the economic case at each gateway stage. | Test | system, session-263 |
| SYS-REQS-002 | The Transport Appraisal System SHALL implement a variable demand model with elastic response to generalised cost changes, incorporating mode choice between car, bus, Metro, rail, cycling, and walking. Rationale: A fixed-demand model would overestimate benefits for a crossing that changes generalised cost significantly. Variable demand with elastic response captures induced traffic, mode shift, and trip redistribution. The Tyne corridor has six competing modes and elastic responses are material: Metro ridership and Shields Ferry usage are directly sensitive to new road crossing provision. | Test | system, session-263 |
| SYS-REQS-003 | The Transport Appraisal System SHALL model traffic operations at all junctions within 2km of each crossing option using microsimulation with a minimum 1-second time step, producing queue length, delay, and level of service metrics per junction arm for AM peak (0800-0900), interpeak (1000-1600), and PM peak (1700-1800) periods. Rationale: The 2km junction influence area captures the traffic redistribution and rat-running effects of a new crossing. Microsimulation at 1-second time steps is required for accurate queue and delay modelling at signal-controlled junctions where platoon dispersion matters. AM/interpeak/PM periods cover the three distinct demand patterns that drive junction capacity assessment per DMRB CD 116. | Test | system, session-263 |
| SYS-REQS-004 | The Transport Appraisal System SHALL model NO2 and PM2.5 concentrations at all sensitive receptors within 200m of affected road links using a validated atmospheric dispersion model, with outputs expressed as annual mean concentrations for comparison against Air Quality Strategy objectives. Rationale: Air quality assessment at sensitive receptors within 200m of affected links is mandated by DMRB LA 105. NO2 and PM2.5 are the two pollutants with UK air quality limit values most frequently exceeded near roads. Annual mean concentrations are the metric used for compliance assessment against the Air Quality Strategy objectives and EU limit values retained in UK law. | Test | system, session-263 |
| SYS-REQS-005 | The Transport Appraisal System SHALL calculate noise levels at residential facades within 600m of affected road links using CRTN methodology, producing LA10,18h for daytime and Lnight for night-time assessment, with results mapped to Noise Important Areas. Rationale: CRTN methodology is the UK statutory method for road traffic noise assessment. The 600m study area captures the zone where road traffic noise from a major crossing exceeds background levels. LA10,18h is the daytime noise index used in UK noise policy and Lnight is required under the Environmental Noise Directive. Noise Important Areas are Defra-designated locations where noise action is prioritised. | Test | system, session-263 |
| SYS-REQS-006 | The Transport Appraisal System SHALL calculate Biodiversity Net Gain using the DEFRA Biodiversity Metric for each crossing option, demonstrating a minimum 10% net gain as required by the Environment Act 2021. Rationale: The Environment Act 2021 mandates a minimum 10 percent Biodiversity Net Gain for all Nationally Significant Infrastructure Projects. The DEFRA Biodiversity Metric is the mandated calculation tool. Failure to demonstrate BNG compliance would prevent DCO consent. The crossing corridor includes Tyne riverside habitats that require careful BNG calculation. | Analysis | system, session-263 |
| SYS-REQS-007 | The Transport Appraisal System SHALL generate Appraisal Summary Tables per TAG Unit A1 for each crossing option, consolidating economy, environment, social, and public accounts impacts into a standardised seven-point assessment scale. Rationale: TAG Unit A1 defines the Appraisal Summary Table as the standard format for presenting scheme impacts to DfT decision-makers. The seven-point scale (large beneficial to large adverse) enables consistent comparison across options and against other schemes in the national pipeline. ASTs are a mandatory deliverable for SOBC, OBC, and FBC submissions. | Demonstration | system, session-263 |
| SYS-REQS-008 | The Transport Appraisal System SHALL produce distributional impact analysis tables showing user benefits and disbenefits disaggregated by income quintile, LSOA geography, age group, disability status, and ethnicity for each crossing option. Rationale: TAG Unit A4.2 requires disaggregation of user benefits by income quintile, geography, and protected characteristics. The Tyne corridor spans areas ranging from IMD decile 1 (most deprived, parts of South Shields and Wallsend) to decile 9 (Jesmond, Gosforth). Without distributional analysis, the appraisal would mask regressive impacts on deprived communities. | Test | system, session-263 |
| SYS-REQS-009 | The Transport Appraisal System SHALL record the source, version, date of extraction, and any transformations applied to every dataset used in the appraisal, such that an independent reviewer can reproduce any intermediate or final result. Rationale: DfT Analytical Assurance Framework requires complete data provenance for independent reproducibility. Every dataset used in the appraisal must be traceable to source, version, and extraction date. Without this, the appraisal fails DfT quality assurance at gateway review, and any challenged outputs cannot be defended at public inquiry. | Inspection | system, session-263 |
| SYS-REQS-010 | The Transport Appraisal System SHALL produce demand forecasts for opening year, design year (opening + 15 years), and a long-term horizon (opening + 30 years), with core, high growth (+20%), and low growth (-20%) sensitivity tests for each. Rationale: TAG Unit M4 requires demand forecasts at opening year, a design year 15 years after opening, and a long-term horizon. The plus-or-minus 20 percent sensitivity tests bracket the range of plausible traffic growth given uncertainty in economic growth, remote working trends, and EV adoption rates. These are standard TAG sensitivity ranges for major schemes. | Test | system, session-263 |
| SYS-REQS-011 | The Transport Appraisal System SHALL maintain a geospatial constraint database covering flood zones (EA Flood Map for Planning), designated ecological sites (SSSI, SAC, SPA, Ramsar, LWS), heritage assets (listed buildings, scheduled monuments, conservation areas, registered parks), and contaminated land registers for all route option corridors. Rationale: A geospatial constraint database is essential for route option sifting and environmental impact assessment. The Tyne corridor contains Environment Agency flood zone 2 and 3 areas, SSSIs at Jarrow Slake and the Tyne estuary, Grade I and II listed structures, and legacy industrial contamination. Missing any statutory constraint would invalidate the environmental chapter of the DCO application. | Inspection | system, session-263 |
| SYS-REQS-012 | The Transport Appraisal System SHALL calculate lifecycle greenhouse gas emissions for each crossing option using TAG Unit A3 methodology, including construction-phase embodied carbon, operational carbon from changed traffic patterns, and a monetised carbon cost using BEIS traded and non-traded carbon values. Rationale: TAG Unit A3 mandates lifecycle greenhouse gas assessment for major schemes. Construction-phase embodied carbon is significant for a river crossing involving substantial concrete and steel. Operational carbon from traffic redistribution captures the net effect on vehicle-km. Monetisation using BEIS carbon values enables inclusion in the BCR and economic case. | Analysis | system, session-263 |
| SYS-REQS-013 | The Transport Appraisal System SHALL produce five-case business case documentation (strategic, economic, commercial, financial, management cases) per HM Treasury Green Book and DfT business case guidance, with outputs structured for SOBC, OBC, and FBC submission formats. Rationale: HM Treasury Green Book requires a five-case business case for all public spending above the delegated limit. DfT business case guidance specifies the structure for SOBC, OBC, and FBC submissions. The five cases ensure strategic fit, value for money, commercial viability, financial affordability, and deliverability are each assessed. Without five-case documentation, the scheme cannot secure Treasury approval. | Demonstration | system, session-263 |
| SYS-REQS-015 | The Transport Appraisal System SHALL calculate the change in personal injury accidents by severity (fatal, serious, slight) for each crossing option using COBALT link-based accident analysis, applying DfT-published accident rates and monetising safety benefits using current-year accident cost values per TAG Unit A4.1. | Analysis | system, safety, session-275 |
| Ref | Requirement | V&V | Tags |
|---|---|---|---|
| SUB-REQS-001 | The Network Coding Module SHALL represent all road links within 2km of each crossing option with coded speed, capacity, number of lanes, gradient, and link type attributes matching observed conditions to within 10 percent of surveyed values. Rationale: 2km buffer around crossing options ensures all affected local road links are represented, capturing route choice and diversion effects. The 10% accuracy threshold for coded attributes vs surveyed values is consistent with TAG M3.1 network coding guidance — less accurate coding would introduce systematic bias in journey time estimates along competing routes. | Test | subsystem, traffic-microsim, session-264 |
| SUB-REQS-002 | The Signal Controller Emulator SHALL replicate UTC/SCOOT adaptive signal control for all signalised junctions within the study area, with modelled green times within 3 seconds of observed stage durations for each time period. Rationale: UTC/SCOOT adaptive control operates at most signalised junctions on Tyneside's strategic network. Replicating adaptive behaviour (rather than fixed time plans) is essential because a new crossing will change traffic patterns and SCOOT will respond by adjusting green times. The 3-second stage duration tolerance ensures modelled junction operations match observed conditions closely enough for reliable delay estimation. | Test | subsystem, traffic-microsim, session-264 |
| SUB-REQS-003 | The Vehicle Behaviour Engine SHALL reproduce observed speed-flow relationships on the A19, A1058, and Tyne Tunnel approach corridors with modelled journey times within 15 percent of observed journey times (from ANPR or Trafficmaster data) for at least 85 percent of calibration routes across all time periods. Rationale: Speed-flow calibration on A19, A1058, and Tyne Tunnel approach is critical because these corridors carry the traffic most affected by a new crossing. The 15% journey time tolerance and 85% route coverage threshold are consistent with TAG M3.1 microsimulation validation criteria. ANPR/Trafficmaster data provides reliable observed journey times for calibration. | Test | subsystem, traffic-microsim, session-264 |
| SUB-REQS-004 | The Simulation Execution Manager SHALL execute a minimum of 10 random seed runs per scenario per time period, and SHALL report mean, standard deviation, and 95th percentile values for journey time, delay, and queue length metrics. Rationale: Microsimulation is stochastic — single runs are not representative. TAG M3.1 requires multiple random seed runs (minimum 10) to quantify variability. Reporting mean, standard deviation, and 95th percentile captures both average conditions and worst-case performance, which is essential for economic appraisal (mean) and operational assessment (95th percentile). | Test | subsystem, traffic-microsim, session-264 |
| SUB-REQS-005 | The Results Extraction and Reporting Module SHALL produce origin-destination journey time matrices and junction turning movement matrices in formats directly importable by the Economic Appraisal Engine, with outputs disaggregated by vehicle type (car, LGV, HGV, bus) and time period. Rationale: The Economic Appraisal Engine requires OD journey time matrices from microsimulation to calculate user benefits at the detailed network level. Disaggregation by vehicle type is needed because DfT values of time differ by vehicle class. Direct importability avoids manual data transformation that could introduce errors into the economic case. | Test | subsystem, traffic-microsim, session-264 |
| SUB-REQS-006 | The Simulation Execution Manager SHALL implement a warm-up period of at least 15 minutes simulation time before the assessment period, with network loading from a demand profile representative of pre-peak traffic build-up, to ensure stable initial conditions. Rationale: Warm-up eliminates the artificial empty-network conditions at simulation start that would understate delays and queue lengths. The 15-minute minimum represents approximately one signal cycle clearing time for the longest-cycle junctions in the study area. Pre-peak demand profiling ensures queues and platoon patterns are realistic when the assessment period begins. | Test | subsystem, traffic-microsim, session-264 |
| SUB-REQS-007 | The Trip End Forecasting Module SHALL produce zonal trip productions and attractions constrained to NTEM v8.0 regional control totals, with local adjustments for committed developments in the North East LEP area, for opening year (2031), design year (2046), and horizon year (2061). Rationale: NTEM v8.0 constraining is mandatory per TAG Unit M4 for scheme appraisal to ensure consistency with DfT national forecasts. Local development adjustments are required because the North East LEP area has significant committed developments (e.g., Gateshead Quays, Newcastle Helix) not captured in NTEM. Three forecast years provide opening, design, and horizon year assessments required by TAG Unit A1.1 for economic appraisal. | Analysis | subsystem, demand-modelling, session-265 |
| SUB-REQS-008 | The Trip Distribution Engine SHALL implement a doubly-constrained gravity model with purpose-specific deterrence functions calibrated to observed trip length distributions from the 2021 National Travel Survey North East regional dataset, achieving Furness convergence within 0.1% residual across all zone pairs. Rationale: Doubly-constrained gravity model is TAG M2 standard practice for synthesising trip distribution from zonal trip ends. Purpose-specific deterrence functions are needed because commuting trips have different length distributions to leisure trips. NTS North East calibration data provides regional specificity. The 0.1% Furness convergence tolerance ensures matrix balancing does not distort the synthetic distribution, which would propagate errors into assignment and economic appraisal. | Test | subsystem, demand-modelling, session-265 |
| SUB-REQS-009 | The Mode-Destination Choice Model SHALL implement an incremental hierarchical logit model with mode choice (car driver, car passenger, public transport, walk, cycle) nested above destination choice, using lambda scale parameters calibrated to observed cross-river mode shares at Tyne crossings within 2 percentage points per mode. Rationale: Incremental logit is required by TAG M2 for variable demand modelling in scheme appraisal — it captures traveller response to changes in generalised cost without requiring absolute calibration of all mode utilities. Hierarchical nesting (mode above destination) reflects the behavioural assumption that mode choice is less sensitive to small cost changes than destination choice. The 2-percentage-point calibration tolerance on cross-river mode shares is critical because the economic case depends on correctly modelling diversion between Tyne crossings. | Test | subsystem, demand-modelling, session-265 |
| SUB-REQS-010 | The Highway Assignment Engine SHALL implement Wardrop user equilibrium assignment on a coded network of at least 3,000 links covering the Tyneside conurbation, achieving convergence to a percentage gap of less than 0.1% using BPR speed-flow curves calibrated to observed journey times on the A19, A1058, A1 Western Bypass, and Tyne Tunnel approach within 10% of observed values. Rationale: Wardrop equilibrium assignment is the standard for strategic highway modelling per TAG M3.1. The 3,000-link minimum covers the Tyneside network at sufficient detail to represent route choice between competing crossings. 0.1% gap convergence is TAG guidance for assignment stability. BPR curve calibration to observed journey times on the four key corridors is essential because these corridors are the primary routes affected by a new Tyne crossing — inaccurate speeds here directly corrupt the user benefit calculation. | Test | subsystem, demand-modelling, session-265 |
| SUB-REQS-011 | The Matrix Estimation Processor SHALL adjust prior gravity model matrices to reproduce observed traffic counts at a minimum of 120 count sites across the study area, with at least 85% of modelled-vs-observed comparisons achieving GEH less than 5.0, and SHALL preserve trip length distributions within 5% of the prior matrix mean trip length per purpose. Rationale: Matrix estimation adjusts synthetic gravity model matrices to observed counts, closing the gap between modelled and surveyed flows. TAG M3.1 requires GEH < 5.0 at 85% of count sites as the acceptance criterion. The 5% trip length preservation constraint prevents ME2 from distorting the underlying distribution pattern — excessive perturbation of trip lengths invalidates the economic appraisal because user benefits depend on realistic trip length distributions. | Test | subsystem, demand-modelling, session-265 |
| SUB-REQS-012 | The Demand-Supply Convergence Controller SHALL iterate the variable demand model and highway assignment until simultaneous convergence is achieved: total demand change less than 0.1% between successive iterations AND highway assignment percentage gap less than 0.1%, using Method of Successive Averages with adaptive step sizes. Rationale: Variable demand models require simultaneous convergence of both demand responses and network assignment because the two interact — demand depends on costs which depend on demand. Without joint convergence, the model oscillates and the economic appraisal uses inconsistent demand-cost pairs. MSA with adaptive step sizes is standard practice per TAG M2 to ensure stable convergence without excessive iterations. | Test | subsystem, demand-modelling, session-265 |
| SUB-REQS-013 | The Public Transport Skim Generator SHALL produce generalised cost matrices for public transport covering all zone pairs, incorporating in-vehicle time, waiting time (half headway), interchange penalty (5 minutes per interchange), walk access/egress time, and fare, using published timetable data from Nexus (Metro), and BODS/GTFS feeds for bus operators serving Tyneside. Rationale: PT skims are essential for mode choice — without accurate public transport generalised costs, the model cannot correctly predict mode shift between car and PT in response to a new crossing. Nexus Metro and BODS/GTFS bus data provide the most current timetable information for Tyneside. The five generalised cost components (IVT, wait, interchange, walk, fare) allow the mode choice model to apply different behavioural weights per TAG M2 guidance, reflecting that travellers perceive waiting time as more onerous than in-vehicle time. | Test | subsystem, demand-modelling, session-265 |
| SUB-REQS-014 | The Highway Assignment Engine SHALL reproduce observed two-way traffic flows across the Tyne screenline (Tyne Bridge, Tyne Tunnel, A1 Western Bypass, Scotswood Bridge, Redheugh Bridge) within 5% of observed total screenline flow AND within GEH 5.0 for each individual crossing. Rationale: The Tyne screenline is the critical validation point for this appraisal because the new crossing directly affects cross-river traffic distribution. The five crossings listed carry all motorised cross-Tyne traffic. The 5% total screenline tolerance and per-crossing GEH < 5.0 are TAG M3.1 calibration criteria. Failure to reproduce observed cross-river flows would invalidate the economic case, as user benefits are driven by reassignment between crossings. | Test | subsystem, demand-modelling, session-265 |
| SUB-REQS-015 | The Environmental Impact Assessment Module SHALL assess all 14 DMRB LA 104 environmental topics (air quality, noise and vibration, landscape and visual, biodiversity, road drainage and water environment, geology and soils, cultural heritage, materials and waste, population and human health, climate, cumulative effects, combined effects, major accidents and disasters, and the assessment of alternatives) for each crossing option against do-minimum, producing topic-by-topic significance assessments on the prescribed 5-point scale (large adverse, moderate adverse, slight adverse, neutral, slight beneficial, moderate beneficial, large beneficial). Rationale: DMRB LA 104 Environmental Assessment and Monitoring mandates assessment of 14 environmental topics for major road schemes. Failure to cover all 14 topics would render the environmental statement non-compliant, risking planning refusal or judicial review. | Analysis | subsystem, environmental-assessment, session-267 |
| SUB-REQS-016 | The Air Quality and Noise Modelling Engine SHALL compute annual mean NO2 and PM2.5 concentrations at all sensitive receptors within 200m of affected road links using DMRB LA 105 methodology, with dispersion modelling validated against at least 3 local monitoring sites achieving R-squared of 0.8 or greater and RMSE less than 4 micrograms per cubic metre for NO2. Rationale: Annual mean NO2 and PM2.5 are the statutory air quality metrics under the Air Quality Standards Regulations 2010. The assessment must compare modelled concentrations against objectives at sensitive receptors to determine significance of impact per DMRB LA 105. | Test | subsystem, environmental-assessment, session-267 |
| SUB-REQS-017 | The Air Quality and Noise Modelling Engine SHALL compute LA10,18h and Lnight noise levels at all noise-sensitive receptors within 600m of affected road links using CRTN methodology per DMRB LA 111, and SHALL classify impacts against SOAEL (68 dB LA10,18h) and LOAEL (55 dB LA10,18h) thresholds specified in the Noise Policy Statement for England. Rationale: LA10,18h and Lnight are the statutory noise metrics under DMRB LA 111 and the Environmental Noise Regulations 2006. Noise exposure must be computed at all sensitive receptors to quantify impact magnitude and determine eligibility for noise insulation under the Noise Insulation Regulations 1975. | Test | subsystem, environmental-assessment, session-267 |
| SUB-REQS-018 | The Greenhouse Gas Assessment Module SHALL quantify lifecycle carbon emissions in tonnes CO2e covering construction, maintenance, and 60-year operational phases, using EFT v12 emission factors with fleet decarbonisation projections aligned to the Sixth Carbon Budget, and SHALL monetise carbon using BEIS non-traded carbon values discounted per Green Book rules. Rationale: TAG unit A3 requires lifecycle greenhouse gas quantification covering construction, maintenance, and operational phases. Carbon emissions are a material consideration in planning decisions and NPSNN compliance, and must be monetised using BEIS carbon values for inclusion in the BCR. | Analysis | subsystem, environmental-assessment, session-267 |
| SUB-REQS-019 | The Biodiversity and Water Environment Assessor SHALL calculate Biodiversity Net Gain using the Defra Biodiversity Metric 4.0, achieving a minimum 10% net gain in biodiversity units as required by the Environment Act 2021, and SHALL assess impacts on all statutory designated sites within 2km of the scheme including River Tyne SSSI and Northumbria Coast SPA. Rationale: Biodiversity Net Gain is a mandatory requirement under the Environment Act 2021 for all NSIPs. The BNG metric calculation requires baseline and post-development habitat surveys valued using the statutory Defra metric. Water Framework Directive assessment is required to demonstrate no deterioration of waterbody status. | Analysis | subsystem, environmental-assessment, session-267 |
| SUB-REQS-020 | The Distributional Impact Assessor SHALL evaluate distributional impacts across 8 TAG A4.2 impact categories (user benefits, noise, air quality, accidents, severance, accessibility, personal affordability, option and non-use values) for population quintiles defined by IMD 2019 ranks, and SHALL produce a distributional impact matrix scored on the 7-point TAG A4.2 scale for each option. Rationale: TAG unit A4.2 mandates distributional impact analysis across income quintiles, protected characteristics, and geographic areas. This analysis must cover all five impact categories (user benefits, noise, air quality, accidents, accessibility) to demonstrate whether the scheme is progressive or regressive. | Analysis | subsystem, environmental-assessment, session-267 |
| SUB-REQS-021 | The Traffic Survey Data Processor SHALL validate all ingested ATC count data against DMRB-compliant quality thresholds, rejecting records with more than 5 percent zero-flow hours in a 24-hour period or with total daily flows deviating more than 20 percent from the rolling 12-month average at the same site, and SHALL log all rejected records with rejection reason codes. Rationale: Automated validation of ATC count data is essential because raw count data commonly contains errors from equipment malfunction, occlusion, or miscounting. TAG unit M1.2 requires documented data quality assurance. Without validation, corrupted counts could propagate through matrix estimation into demand forecasts, silently biasing appraisal results. | Test | subsystem, data-acquisition, session-269 |
| SUB-REQS-022 | The Traffic Survey Data Processor SHALL apply TAG-compliant seasonal, day-of-week, and vehicle type expansion factors to convert short-period counts into Annual Average Daily Traffic, using factors derived from permanent ATC sites within the study area with a minimum of 12 months continuous data. Rationale: TAG unit M1.2 requires that traffic survey data be adjusted for seasonal, day-of-week, and vehicle class effects to produce representative annual average values. Without these adjustments, counts collected on atypical days or seasons would bias matrix estimation and demand forecasting. | Analysis | subsystem, data-acquisition, session-269 |
| SUB-REQS-023 | The Network Data Repository SHALL maintain a coded highway network covering all A-roads and B-roads within the Tyneside conurbation plus motorway and trunk road connections to the study area boundary, comprising at least 3,000 links, with each link attributed with free-flow speed, capacity, number of lanes, gradient, and link type, updated within 3 months of any permanent network change. Rationale: The coded highway network is the spatial foundation for traffic assignment. Coverage of all A and B roads plus key C roads within the study area is necessary for correct route choice modelling. A minimum 500m link resolution in urban areas ensures junction-level detail for scheme assessment. | Inspection | subsystem, data-acquisition, session-269 |
| SUB-REQS-024 | The Cost Data Manager SHALL apply HM Treasury Green Book optimism bias uplifts to base cost estimates, using category-specific factors: 66 percent for tunnels and underground works, 44 percent for standard road construction, and 51 percent for structures, and SHALL reduce these factors only when supported by quantified risk assessment evidence in accordance with the Reference Class Forecasting approach. Rationale: HM Treasury Green Book mandates optimism bias uplifts for publicly-funded capital projects. The uplift percentages vary by cost category and project stage. Failure to apply correct uplifts would understate the true cost to government and produce an artificially inflated BCR. | Inspection | subsystem, data-acquisition, session-269 |
| SUB-REQS-025 | The Planning and Land Use Data Manager SHALL constrain all local trip end forecasts to NTEM v8.0 North East regional control totals for each forecast year, with local development adjustments applied as re-distributions within the constrained totals, not as additions above NTEM growth. Rationale: NTEM v8.0 provides national-level trip end forecasts that do not account for local committed developments. TAG unit M4 requires local adjustments to be constrained by local plan allocations with planning permission. Without this constraint, trip ends would be double-counted or misallocated across zones. | Analysis | subsystem, data-acquisition, session-269 |
| SUB-REQS-026 | The External Data Feed Connector SHALL maintain a version-controlled parameter registry recording source, version identifier, retrieval date, and SHA-256 content hash for every external dataset ingested, and SHALL prevent any downstream component from consuming a dataset whose version differs from the approved parameter set for the current appraisal iteration. Rationale: TAG parameter values (e.g., values of time, fuel costs, vehicle occupancies) are updated periodically by DfT. A version-controlled parameter repository ensures all subsystems use the same parameter vintage, preventing appraisal inconsistencies that would invalidate the BCR. Automated change notifications trigger re-runs of affected analyses. | Test | subsystem, data-acquisition, session-269 |
| SUB-REQS-027 | The Socioeconomic Data Integrator SHALL provide IMD 2019 deprivation scores and quintile classifications for all LSOAs within the study area, mapped to the model zone system via population-weighted centroid assignment, with at least 95 percent of zones assigned a single dominant LSOA deprivation quintile. Rationale: IMD 2019 deprivation scores are the standard measure for distributional analysis under TAG A4.2. Ethnic composition and disability prevalence data from the 2021 Census are required for protected characteristics analysis under the Public Sector Equality Duty. These datasets must be zone-referenced to enable spatial overlay with scheme impacts. | Analysis | subsystem, data-acquisition, session-269 |
| SUB-REQS-028 | The Cost Data Manager SHALL produce 60-year whole-life cost profiles for each crossing option, covering capital construction, land acquisition, statutory undertaker diversions, environmental mitigation, routine maintenance, periodic renewal, and structural inspection, with all costs expressed in both outturn prices and discounted present values using HM Treasury discount rates of 3.5 percent for years 0-30 and 3.0 percent for years 31-60. Rationale: 60-year whole-life cost profiles are required because the TAG appraisal period for major transport infrastructure is 60 years. Costs must be disaggregated by category to enable correct application of category-specific optimism bias uplifts and to populate the TAG A1 Public Accounts table. | Analysis | subsystem, data-acquisition, session-269 |
| SUB-REQS-029 | The Traffic Count Database SHALL store and serve classified directional traffic counts from a minimum of 120 permanent and temporary count sites across the Tyneside study area, with data disaggregated by vehicle type (car, LGV, HGV, bus, cycle), direction, and 15-minute interval, covering at least 3 years of historical data for seasonal adjustment. Rationale: Classified directional counts are the primary data source for matrix estimation and model validation. The 120-site minimum ensures sufficient spatial coverage for reliable estimation across the Tyneside study area. Vehicle type disaggregation and 15-minute intervals enable time-period-specific and vehicle-class-specific modelling. | Inspection | subsystem, data-acquisition, session-268, superseded-by-SUB-REQS-032 |
| SUB-REQS-030 | The Travel Survey Processor SHALL compute trip rates, trip length distributions, and mode shares from the National Travel Survey North East regional dataset and local household interview surveys, with sample expansion factors validated against 2021 Census journey-to-work data to within 5% of total commuting trips per district. Rationale: Trip rates, trip length distributions, and mode shares from travel surveys are the basis of demand model calibration. Census journey-to-work validation to within 5% ensures that the model reproduces observed commuting patterns, which is the primary demand driver for cross-Tyne travel. | Analysis | subsystem, data-acquisition, session-268, superseded-by-SUB-REQS-033 |
| SUB-REQS-031 | The Land Use and Planning Data Manager SHALL maintain zonal population, employment, and household data aligned to NTEM v8.0 regional control totals, with local adjustments for committed developments identified in the Newcastle, Gateshead, and North Tyneside local plans, and SHALL produce growth factor sets for opening year (2031), design year (2046), and horizon year (2061). Rationale: Zonal demographic data aligned to NTEM v8.0 control totals is required by TAG unit M4 for trip end forecasting. Local plan adjustments for committed developments in the three boroughs ensure growth forecasts reflect known development commitments rather than relying solely on national trend projections. | Analysis | subsystem, data-acquisition, session-268, superseded-by-SUB-REQS-034 |
| SUB-REQS-035 | The Network and GIS Data Repository SHALL store the coded road network with a minimum of 3,000 links covering the Tyneside conurbation, junction geometries with signal staging data, and the zone system with centroid connectors, with all spatial data georeferenced in British National Grid (EPSG:27700) and traceable to OS MasterMap Integrated Transport Network source data. Rationale: A minimum 500m link resolution ensures that junction-level details affecting route choice and delay are captured. Attribute completeness enables speed-flow relationships for assignment. The coded network must extend at least 5km beyond the study boundary to prevent artificial traffic reassignment at boundary links. | Inspection | subsystem, data-acquisition, session-268 |
| SUB-REQS-036 | The Data Validation and Quality Assurance Engine SHALL apply automated validation rules to all incoming traffic count, survey, planning, and network data before release to the modelling pipeline, flagging records that fail range checks, temporal consistency checks, or spatial consistency checks, and SHALL produce data quality reports with pass/fail status per dataset within 10 minutes of data submission. Rationale: Automated validation against 10 data quality rules prevents corrupted or inconsistent data from entering the modelling pipeline. A single undetected data error in traffic counts or network coding can propagate through assignment, demand estimation, and economic appraisal, silently invalidating the BCR. | Test | subsystem, data-acquisition, session-268 |
| SUB-REQS-037 | The Scenario Configuration Manager SHALL define and store a minimum of 12 appraisal scenarios (do-minimum plus at least 3 crossing options crossed with 3 forecast years plus sensitivity tests), each specifying the network coding variant, demand growth factors, toll regime, and public transport assumptions, and SHALL enforce consistency of assumptions across all analytical subsystems consuming the scenario definition. Rationale: TAG requires comparison of do-minimum and do-something scenarios across multiple forecast years. A minimum of 12 scenarios covers the combination of 3 forecast years (opening, design, horizon) with do-minimum and do-something for each plus high and low growth sensitivity tests as required by TAG unit M4. | Demonstration | subsystem, data-acquisition, session-268 |
| SUB-REQS-038 | The Receptor Mapping Engine SHALL identify and geo-reference all sensitive receptors within DMRB-specified buffer distances of each crossing option alignment: residential properties and schools within 200m for air quality assessment, noise-sensitive receptors within 600m for noise assessment, statutory ecological sites within 2km for biodiversity assessment, and heritage assets within 500m for cultural heritage assessment. Rationale: DMRB LA 105 and LA 111 require assessment at specific sensitive receptors. The Receptor Mapping Engine must geo-reference all receptors to enable spatial linkage with modelled pollutant concentrations and noise levels. Receptor type classification determines which air quality objectives and noise criteria apply. | Inspection | subsystem, geospatial, session-269 |
| SUB-REQS-039 | The Spatial Overlay Processor SHALL compute the intersection area between each crossing option corridor and all statutory environmental designations (SSSI, SPA, SAC, Ramsar, Flood Zone 2, Flood Zone 3, Conservation Area, Scheduled Monument, ancient woodland, Green Belt), reporting land-take in hectares per designation type per option to 0.01 hectare precision. Rationale: Intersection area quantifies direct habitat loss or disturbance within statutory designations. This calculation is required by DMRB LA 104 and Habitats Regulations Assessment screening to determine whether each crossing option triggers formal assessment under the Conservation of Habitats and Species Regulations 2017. | Test | subsystem, geospatial, session-269 |
| SUB-REQS-040 | The Route and Catchment Analyser SHALL compute multi-modal accessibility isochrones at 15, 30, 45, and 60 minute thresholds from major employment centres (Newcastle city centre, Team Valley, Cobalt Business Park) and hospitals (RVI, QE Gateshead, North Tyneside General) for both do-minimum and each crossing option, and SHALL quantify the change in population within each isochrone to 100-person resolution. Rationale: Multi-modal accessibility isochrones quantify the catchment area reached from each crossing option by different modes. This analysis underpins the economic case for connectivity benefits and the distributional impact assessment, comparing how accessibility changes across different population groups. | Test | subsystem, geospatial, session-269 |
| SUB-REQS-041 | The GIS Data Repository SHALL store all geospatial datasets in OSGB36 British National Grid projection with positional accuracy of 1m or better for vector features, and SHALL serve data via OGC-compliant WFS and WMS interfaces to ensure interoperability between analysis engines without format conversion errors. Rationale: OSGB36 British National Grid is the standard coordinate reference system for UK mapping and all Ordnance Survey products. Storing all geospatial data in a single CRS eliminates on-the-fly reprojection errors during spatial overlay operations and ensures consistent spatial relationships across datasets. | Test | subsystem, geospatial, session-269 |
| SUB-REQS-042 | The Report Template Engine SHALL assemble TAG-compliant Option Assessment Reports, Strategic Outline Business Cases, and Outline Business Cases by pulling structured outputs from the Economic Appraisal Engine, Environmental Assessment Subsystem, Traffic Microsimulation Subsystem, and Geospatial Analysis Platform into DfT-standard document structures with automated section numbering and cross-referencing. Rationale: TAG/WebTAG requires Option Assessment Reports and business cases in prescribed formats. The Report Template Engine centralises document assembly to ensure consistency across appraisal outputs and compliance with DfT submission standards. | Demonstration | subsystem, appraisal-reporting, session-273 |
| SUB-REQS-043 | The Option Comparison Module SHALL produce multi-criteria sifting matrices for all crossing options under assessment, scoring each option against economic, environmental, social, and deliverability criteria using the WebTAG seven-point scale (large beneficial to large adverse), with at least one quantitative metric per criterion where available. Rationale: Multi-criteria sifting is mandated by DMRB GG 142 Option Identification to narrow long-lists of scheme options. Structured scoring matrices with economic, environmental, social, and deliverability criteria provide auditable evidence for option selection decisions presented to DfT. | Test | subsystem, appraisal-reporting, session-273 |
| SUB-REQS-044 | The Sensitivity and Uncertainty Reporter SHALL compute switching values for demand growth, construction cost, values of time, and discount rate, identifying the percentage change in each parameter required to move the preferred option's VfM category across each boundary (poor/low/medium/high). Rationale: TAG Unit A1 Section 7 requires sensitivity testing to identify switching values — the parameter changes that would reverse the scheme value-for-money category. Without quantified switching values, DfT cannot assess the robustness of the economic case. | Test | subsystem, appraisal-reporting, session-273 |
| SUB-REQS-045 | The Sensitivity and Uncertainty Reporter SHALL generate scenario comparison matrices testing at minimum the TAG-mandated core scenarios (high growth, low growth, central) combined with construction cost uncertainty (+20%/-10%) and toll level variants, producing a minimum of 12 BCR variants per crossing option. Rationale: TAG Unit M4 mandates scenario testing across specified growth and cost assumptions. The core scenario matrix (high/low/central growth x cost variants) ensures the appraisal tests the scheme under the range of futures DfT considers plausible. | Test | subsystem, appraisal-reporting, session-273 |
| SUB-REQS-046 | The Audit Trail and Provenance Tracker SHALL record, for every published result table, the input dataset identifiers, model software version, parameter configuration hash, network scenario variant, and timestamp of the model run that produced it, enabling forward and reverse traceability queries within 5 seconds. Rationale: Transport appraisal audit trail requirements originate from Treasury Green Book Section 5.4 on model assurance. Recording input datasets, software versions, parameter hashes, and timestamps for every published result enables independent reviewers to reproduce and verify calculations. | Test | subsystem, appraisal-reporting, session-273 |
| SUB-REQS-047 | The Audit Trail and Provenance Tracker SHALL enforce a three-stage approval workflow (author, checker, approver) for all report sections before they can be marked as issued, recording the approver identity, approval timestamp, and any conditions attached to the approval. Rationale: Three-stage approval workflow (author, checker, approver) is standard QA practice for transport studies per DMRB GG 142 and professional practice guidance from CIHT. It mitigates risk of publishing unchecked results that could misrepresent scheme value-for-money. | Demonstration | subsystem, appraisal-reporting, session-273 |
| SUB-REQS-048 | The Non-Technical Summary Generator SHALL produce a statutory Non-Technical Summary compliant with the Town and Country Planning (Environmental Impact Assessment) Regulations 2017, translating all technical environmental assessment outputs into plain language at a reading level no higher than Flesch-Kincaid Grade 10. Rationale: The Town and Country Planning (EIA) Regulations 2017 require a Non-Technical Summary for any EIA-accompanied application. Translating technical environmental assessments into plain language is a statutory obligation for public consultation. | Inspection | subsystem, appraisal-reporting, session-273 |
| SUB-REQS-049 | The Non-Technical Summary Generator SHALL produce all public-facing consultation materials in HTML, PDF, and large-print formats conforming to WCAG 2.1 Level AA accessibility standards, including alt-text for all scheme visualisations and charts. Rationale: Equality Act 2010 and Public Sector Bodies Accessibility Regulations 2018 mandate WCAG 2.1 Level AA compliance for public-facing consultation materials. Multi-format outputs (HTML, PDF, large-print) ensure all stakeholders can participate in the statutory consultation process. | Test | subsystem, appraisal-reporting, session-273 |
| SUB-REQS-050 | The Transport User Benefit Calculator SHALL compute the Transport Economic Efficiency (TEE) table per TAG Unit A1.1 for each crossing option, calculating user benefits as the difference in consumer surplus between do-something and do-minimum scenarios, disaggregated by user class (commuting, other, business), mode (car, public transport), and time period (AM peak, interpeak, PM peak, off-peak), with all monetary values expressed in the DfT-specified market price base year. Rationale: The TEE table is the core economic output mandated by TAG Unit A1.1. Consumer surplus disaggregation by user class, mode, and time period is required because DfT values of time differ by purpose and the distributional impact analysis requires separation of commuting from business travel. Market price base year consistency prevents inflation-induced distortion of the BCR. | Test | subsystem, economic-appraisal, session-275, duplicate-of-SUB-EAE-051 |
| SUB-REQS-052 | The Accident Cost-Benefit Module SHALL calculate road safety benefits using the COBALT methodology per TAG Unit A4.1, computing the change in accident numbers by severity (fatal, serious, slight) for each crossing option based on link-level traffic flow changes and published accident rates per billion vehicle-kilometres, with monetisation using DfT accident cost values updated to the current price year. Rationale: COBALT link-based analysis is mandated by TAG Unit A4.1 for monetising safety impacts. Severity disaggregation is essential because the monetary value of a prevented fatality is approximately 60 times higher than a slight injury — aggregating would mask the true safety benefit. Published accident rates per billion vehicle-km provide nationally standardised risk estimates. | Analysis | subsystem, economic-appraisal, session-275 |
| SUB-REQS-053 | The Environmental Impact Monetisation Module SHALL convert physical environmental impacts into monetary values per TAG Unit A3: noise impacts monetised using WebTAG noise valuation tables mapping change in dB at each receptor to willingness-to-pay values, and air quality impacts monetised using damage cost values for NO2 and PM2.5 per TAG databook, with all outputs disaggregated by receptor and aggregated to produce noise and air quality rows of the Appraisal Summary Table. Rationale: TAG Unit A3 requires separate monetisation of noise and air quality using WebTAG valuation tables and damage cost values respectively. Receptor-level disaggregation is needed because willingness-to-pay for noise reduction is non-linear with dB change, and air quality damage costs vary by pollutant. The AST requires these as separate line items, not aggregated environmental benefits. | Analysis | subsystem, economic-appraisal, session-275 |
| SUB-REQS-054 | The Greenhouse Gas Valuation Module SHALL monetise transport-related greenhouse gas emissions using BEIS traded and non-traded carbon values per TAG Unit A3, applying the correct carbon price trajectory (low, central, high) over the 60-year appraisal period, with outputs expressed as present value of carbon costs in the specified price year for each crossing option. Rationale: BEIS carbon values with traded/non-traded split are the mandatory basis for GHG monetisation in UK transport appraisal per TAG Unit A3. Low/central/high carbon price trajectories are required for sensitivity testing. The 60-year period matches the standard appraisal horizon and the declining discount rate schedule. | Analysis | subsystem, economic-appraisal, session-275 |
| SUB-REQS-055 | The Public Accounts Calculator SHALL compute the Public Accounts (PA) table per TAG Unit A1, calculating government revenue impacts from fuel duty, VAT, and toll revenue changes between do-minimum and do-something scenarios, and combining these with scheme costs to produce the net public sector cost for each crossing option, with all values expressed in discounted present values. Rationale: The Public Accounts table is a mandatory component of the DfT business case per TAG Unit A1. Fuel duty and VAT changes from traffic redistribution represent fiscal impacts that must be separated from user benefits. For a tolled crossing, toll revenue is a key PA table input that directly affects the net public sector cost and the funding case. | Test | subsystem, economic-appraisal, session-275 |
| SUB-REQS-056 | The Wider Economic Impacts Module SHALL calculate Level 2 wider economic impacts per TAG Unit A2.1, including agglomeration benefits (effective density changes for each industry sector), labour supply impacts (commuting cost changes affecting labour market participation), and output change in imperfectly competitive markets, using the DfT-published elasticity parameters and BRES employment data for the Tyne and Wear functional economic area. Rationale: Level 2 wider economic impacts per TAG Unit A2.1 are required for schemes above the DfT monetised costs and benefits threshold. Agglomeration benefits are particularly significant for the Tyne crossing because improved connectivity between Newcastle and Gateshead labour markets directly increases effective employment density. BRES data provides the sectoral employment inputs needed for the DfT agglomeration model. | Analysis | subsystem, economic-appraisal, session-275 |
| SUB-REQS-057 | The Present Value and Discounting Engine SHALL apply HM Treasury Green Book discounting to all monetary benefit and cost streams over the 60-year appraisal period, using the declining discount rate schedule (3.5 percent for years 0-30, 3.0 percent for years 31-75), and SHALL convert all values to the DfT-specified price base year using GDP deflators, ensuring consistent treatment across all monetisation modules feeding the BCR. Rationale: Centralised discounting ensures all benefit and cost streams use the identical Green Book declining rate schedule (3.5%/3.0% at year 30). Distributing discounting across individual monetisation modules would risk inconsistent rate application — a systematic error that compounds over 60 years and could shift the BCR by 5-10%. GDP deflator conversion to a common price year prevents inflation-induced distortion. | Test | subsystem, economic-appraisal, session-275 |
| SUB-REQS-058 | The BCR and AST Generator SHALL compute the initial BCR (present value of benefits divided by present value of costs to the public sector) and adjusted BCR (including wider economic impacts) for each crossing option, and SHALL assemble the complete Appraisal Summary Table per TAG Unit A1 consolidating impacts across all monetisation modules with DfT-prescribed rounding, sign conventions, and presentation format. Rationale: The BCR and AST are the headline outputs of the economic case that DfT Ministers and the Treasury use to compare competing schemes. Initial and adjusted BCRs serve different decision purposes: initial BCR covers conventional benefits while adjusted includes wider impacts for schemes meeting the TAG A2.1 threshold. DfT-prescribed AST format with specific rounding and sign conventions is mandatory for scheme submission. | Test | subsystem, economic-appraisal, session-275 |
| Ref | Requirement | V&V | Tags |
|---|---|---|---|
| IFC-DEFS-001 | The interface between the Network Coding Module and the Vehicle Behaviour Engine SHALL transfer the complete network model including link attributes, junction geometries, and signal staging data in a validated format, with the Network Coding Module producing a model integrity checksum that the Vehicle Behaviour Engine verifies before simulation start. Rationale: The vehicle behaviour engine cannot simulate traffic without a complete and valid network model. Integrity checksums prevent simulation on corrupted or incomplete network data — a partially loaded network would produce silently wrong results rather than obvious failures. This interface transfers the largest and most complex dataset in the microsimulation subsystem. | Test | interface, traffic-microsim, session-264 |
| IFC-DEFS-002 | The interface between the Signal Controller Emulator and the Vehicle Behaviour Engine SHALL provide signal state updates at each simulation time step (1 second), with the emulator delivering current stage, phase, and remaining green time for every signalised junction in the network. Rationale: Signal state updates must synchronise with the simulation timestep to ensure vehicles respond to the correct signal phase. Stage, phase, and remaining green time are the minimum information the vehicle behaviour engine needs to model approach and departure behaviour at signalised junctions. 1-second updates match the typical microsimulation timestep resolution. | Test | interface, traffic-microsim, session-264 |
| IFC-DEFS-003 | The interface between the Results Extraction and Reporting Module and the Economic Appraisal Engine SHALL transfer origin-destination journey time matrices in CSV format with columns for origin zone, destination zone, vehicle type, time period, mean journey time (seconds), and standard deviation, at a minimum zone granularity matching the demand model zone system. Rationale: The Economic Appraisal Engine requires journey time matrices from microsimulation to compute user benefits at the detailed network level per TAG Unit A1.3. Standard deviation enables the appraisal to account for journey time reliability benefits. Zone granularity must match the demand model to avoid aggregation errors when computing consumer surplus. | Test | interface, traffic-microsim, session-264 |
| IFC-DEFS-004 | The interface between the Trip End Forecasting Module and the Trip Distribution Engine SHALL transfer zonal trip productions and attractions as vectors indexed by zone number (1 to N_zones), disaggregated by 5 trip purposes (HB work, HB employer business, HB other, NHB employer business, NHB other) and 3 time periods (AM peak 0700-1000, interpeak 1000-1600, PM peak 1600-1900), in CSV format with zone ID as the key column. Rationale: The trip end to distribution interface must preserve full disaggregation by purpose and time period because the distribution model applies different deterrence functions per purpose and the assignment uses time-period-specific demand. CSV with zone ID key enables straightforward validation and audit trail. The 5 purposes and 3 time periods match TAG M2 standard segmentation for strategic transport modelling. | Test | interface, demand-modelling, session-265 |
| IFC-DEFS-005 | The interface between the Highway Assignment Engine and the Mode-Destination Choice Model SHALL transfer zone-to-zone highway generalised cost skims as square matrices (N_zones x N_zones) comprising travel time (minutes), distance (km), and toll cost (pence) components separately, enabling the choice model to apply DfT values of time by purpose and income group. Rationale: Separate time, distance, and toll components are essential because the mode choice model must apply purpose-specific and income-group-specific values of time per TAG M3.1 Appendix A. Transmitting composite costs would prevent this disaggregation. Square matrix format (N x N) ensures completeness for all zone pairs. This interface is architecturally critical because inaccurate highway skims directly corrupt mode choice predictions and hence the economic appraisal. | Test | interface, demand-modelling, session-265 |
| IFC-DEFS-006 | The interface between the Mode-Destination Choice Model and the Demand-Supply Convergence Controller SHALL transfer updated demand matrices as zone-to-zone trip tables per user class (car driver, car passenger, LGV, HGV) with a convergence report containing total trips per matrix, maximum zonal change from previous iteration, and percentage demand change. Rationale: The convergence report accompanying updated matrices enables the convergence controller to assess whether demand-supply equilibrium has been reached. Per-user-class matrices are required because assignment uses separate car, LGV, and HGV vehicle operating cost parameters. Maximum zonal change and percentage demand change are the two convergence metrics required by TAG M2 to verify that the variable demand loop has stabilised. | Test | interface, demand-modelling, session-265 |
| IFC-DEFS-007 | The interface between the Matrix Estimation Processor and the Highway Assignment Engine SHALL operate iteratively: the processor SHALL submit adjusted OD matrices to assignment, and the assignment SHALL return modelled link flows at all count site locations, with the cycle repeating until the GEH convergence criterion (85% of sites with GEH less than 5.0) is satisfied or a maximum of 50 iterations is reached. Rationale: Matrix estimation requires iterative feedback between ME2 adjustments and assignment because adjusted matrices change link flows, which may require further matrix adjustments. The GEH 85% criterion at count sites is the TAG M3.1 acceptance standard. The 50-iteration cap prevents infinite loops when the count set contains internally inconsistent data, which occurs when count sites have different survey dates or seasonal patterns. | Test | interface, demand-modelling, session-265 |
| IFC-DEFS-008 | The interface between the Highway Assignment Engine and the Traffic Microsimulation Subsystem SHALL transfer origin-destination matrices extracted at microsimulation cordon boundaries as 15-minute time-slice trip tables, with vehicle class disaggregation (car, LGV, HGV), for each modelled scenario. Rationale: Microsimulation requires finer temporal granularity (15-minute slices) than strategic assignment (1-3 hour periods) because queue dynamics and signal interactions vary significantly within a peak period. Vehicle class disaggregation is needed because HGVs have different acceleration and gap-acceptance behaviour. Cordon boundary extraction ensures microsimulation demand is consistent with the strategic model rather than independently estimated. | Test | interface, demand-modelling, cross-subsystem, session-265 |
| IFC-DEFS-009 | The interface between the Mode-Destination Choice Model and the Economic Appraisal Engine SHALL transfer do-minimum and do-something demand matrices with zone-to-zone generalised cost changes, enabling computation of consumer surplus (rule of half) user benefits per TAG Unit A1.3, disaggregated by trip purpose and user class. Rationale: Consumer surplus calculation via rule-of-half requires both do-minimum and do-something demand matrices plus generalised cost changes, as specified in TAG Unit A1.3. Disaggregation by purpose and user class is mandatory because DfT values of time differ by purpose and income group. This interface is the primary data path for the economic case — errors here directly corrupt the BCR. | Test | interface, demand-modelling, cross-subsystem, session-265 |
| IFC-DEFS-010 | The interface between the Air Quality and Noise Modelling Engine and the Environmental Impact Assessment Module SHALL transfer receptor-level results as a georeferenced dataset containing receptor ID, easting, northing, receptor type (residential, school, hospital, ecological), baseline concentration or noise level, do-something concentration or noise level, and change, for each pollutant (NO2, PM2.5) and noise metric (LA10,18h, Lnight). Rationale: DMRB LA 105 and LA 111 require receptor-level reporting for air quality and noise impacts. The georeferenced format with receptor type and baseline/do-something values enables direct compliance checking against air quality objectives and noise criteria at specific sensitive locations. | Test | interface, environmental-assessment, session-267 |
| IFC-DEFS-011 | The interface between the Greenhouse Gas Assessment Module and the Environmental Impact Assessment Module SHALL transfer annual CO2e emissions by source category (construction, maintenance, operational-tailpipe, operational-embedded) for each forecast year, cumulative lifecycle totals, and monetised carbon NPV using BEIS carbon values, in a format compatible with TAG A3 reporting tables. Rationale: TAG unit A3 mandates lifecycle carbon accounting disaggregated by source category for scheme appraisal. BEIS traded and non-traded carbon values are the official appraisal basis. The EIA Module requires both annual profiles and cumulative totals to produce the required TAG A3 reporting tables and carbon NPV for inclusion in the AST. | Test | interface, environmental-assessment, session-267 |
| IFC-DEFS-012 | The interface between the Transport Demand Modelling Subsystem and the Environmental Assessment Subsystem SHALL transfer link-level AADT flows, average speeds, and percentage HGV by vehicle type for each modelled scenario and forecast year, covering all road links within the air quality and noise study areas, in a format directly importable by ADMS-Roads and the CRTN noise calculation. Rationale: ADMS-Roads air quality dispersion modelling requires link-level AADT and average speed inputs. CRTN noise calculation requires traffic flow, speed, and percentage HGV by vehicle type. Without these link-level parameters from the demand model, the Environmental Assessment Subsystem cannot compute receptor-level air quality concentrations or noise levels. | Test | interface, environmental-assessment, cross-subsystem, session-267 |
| IFC-DEFS-013 | The interface between the Traffic Survey Data Processor and the Matrix Estimation Processor SHALL transfer observed traffic count data as site-by-time-period matrices in CSV format, with each record containing site ID, link reference, direction, time period (AM peak 0700-1000, interpeak 1000-1600, PM peak 1600-1900), vehicle type (car, LGV, OGV1, OGV2, PSV), and observed flow, covering a minimum of 120 count sites across the study area. Rationale: Matrix estimation requires observed traffic counts as constraints to adjust prior demand matrices. The site-by-time-period format with vehicle disaggregation matches the standard SATURN ME2 input specification. The 120-site minimum ensures sufficient independent observations for reliable estimation across the Tyneside network. | Test | interface, data-acquisition, session-269 |
| IFC-DEFS-014 | The interface between the Network Data Repository and the Highway Assignment Engine SHALL transfer the coded highway network as SATURN-format .dat files containing node coordinates, link definitions with speed-flow parameters, turn penalties, and junction coding, with network checksums verified at each transfer to ensure model consistency. Rationale: SATURN highway assignment requires network data in its native .dat format including speed-flow curves and junction coding. Network checksums at transfer prevent model corruption from partial or stale network files, which would silently produce incorrect assignment results without any obvious error indicators. | Test | interface, data-acquisition, session-269 |
| IFC-DEFS-015 | The interface between the Cost Data Manager and the Public Accounts Calculator SHALL transfer scheme cost data as TUBA-compatible cost tables containing capital costs, maintenance costs, and operating costs disaggregated by year and cost category, in both factor-cost and market-price bases, with optimism bias applied as separate line items to enable sensitivity testing. Rationale: TAG unit A1 Public Accounts table requires costs in both factor-cost and market-price bases. Optimism bias must be applied as separate line items per HM Treasury Green Book guidance to enable sensitivity testing across different bias levels. The year-by-category disaggregation enables correct discounting across the 60-year appraisal period. | Test | interface, data-acquisition, session-269 |
| IFC-DEFS-016 | The interface between the Socioeconomic Data Integrator and the Distributional Impact Assessor SHALL transfer zone-level socioeconomic attribute tables containing population count, IMD quintile, car ownership rate, economic activity rate, and proportion of residents in protected characteristic groups, for all zones in the study area, in a tabular format keyed by zone ID. Rationale: TAG unit A4.2 requires distributional analysis across income quintiles and protected characteristic groups. The zone-level socioeconomic data enables the Distributional Impact Assessor to determine which population groups are affected by each crossing option and whether impacts are progressive or regressive. | Test | interface, data-acquisition, session-269 |
| IFC-DEFS-017 | The interface between the Planning and Land Use Data Manager and the Trip End Forecasting Module SHALL transfer zone-level trip end adjustments as a table containing zone ID, forecast year, trip purpose, and adjustment factor representing the ratio of locally-adjusted to NTEM-base trip ends, for all zones with committed development within the study area. Rationale: NTEM v8.0 provides national trip end forecasts that must be locally adjusted for committed developments with planning permission. Without these adjustments, trip end forecasts would undercount growth from known local developments such as those in Newcastle, Gateshead, and North Tyneside local plans, producing inaccurate demand forecasts. | Test | interface, data-acquisition, session-269 |
| IFC-DEFS-018 | The interface between the Traffic Count Database and the Matrix Estimation Processor SHALL transfer observed traffic counts as a structured dataset containing site ID, direction, vehicle class (car, LGV, HGV, bus), time period (AM peak, interpeak, PM peak), and observed flow, with each count record accompanied by a data quality grade (A to D per DMRB GG 142) and the Data Validation Engine pass/fail flag. Rationale: Data quality grades per DMRB GG 142 determine count weighting in matrix estimation — lower-quality counts receive less weight. The Data Validation Engine pass/fail flag ensures that counts failing automated QA checks are excluded from matrix estimation, preventing corrupted data from biasing the estimated demand matrices. | Test | interface, data-acquisition, session-268 |
| IFC-DEFS-019 | The interface between the Travel Survey Processor and the Trip End Forecasting Module SHALL transfer observed trip rates as a dataset indexed by zone type (urban, suburban, rural), trip purpose (5 TAG purposes), person type (employed, non-employed, retired), and time period, with associated 95% confidence intervals, in CSV format with zone type as the key column. Rationale: Trip rates are the foundation of trip generation and must be differentiated by zone type, purpose, person type, and time period to capture spatial variation in travel behaviour. The 95% confidence intervals enable sensitivity testing and uncertainty quantification in demand forecasts as required by TAG unit M4. | Test | interface, data-acquisition, session-268 |
| IFC-DEFS-020 | The interface between the Land Use and Planning Data Manager and the Trip End Forecasting Module SHALL transfer zonal planning data as records containing zone ID, population by age band, households by car ownership (0, 1, 2+), employment by sector (office, retail, industrial, other), and area type classification, for each forecast year, with NTEM v8.0 control total compliance flags per zone. Rationale: Trip generation is a function of household composition, car ownership, employment mix, and area type per TAG unit M4. NTEM v8.0 control total compliance flags ensure consistency between local planning data and national forecasts, which is mandatory for DfT model certification. | Test | interface, data-acquisition, session-268 |
| IFC-DEFS-021 | The interface between the Network and GIS Data Repository and the Highway Assignment Engine SHALL transfer the coded road network as a link-node dataset with attributes per link: free-flow speed (km/h), practical capacity (PCU/hr), number of lanes, gradient (%), link type, and BPR alpha/beta parameters, with junction turn penalties and banned turns defined at node level, in a format compatible with SATURN or equivalent assignment software. Rationale: BPR speed-flow parameters and junction turn penalties are critical inputs that drive assignment convergence and route choice accuracy. An incompatible or incomplete network transfer would cause assignment failure or misrouted traffic. SATURN compatibility is required because the existing Tyneside transport model is built in SATURN. | Test | interface, data-acquisition, session-268 |
| IFC-DEFS-022 | The interface between the Receptor Mapping Engine and the Air Quality and Noise Modelling Engine SHALL transfer receptor point datasets as GeoPackage files containing receptor ID, easting, northing, receptor type (residential, school, hospital, care home, ecological), sensitivity class, ground floor height, and number of floors, with a minimum of 500 receptors per crossing option for noise assessment and 200 receptors per option for air quality assessment. Rationale: DMRB LA 111 noise assessment requires sufficient receptor density to characterise noise exposure across the study area. The 500-receptor minimum for noise and 200 for air quality ensures spatial coverage that meets DMRB requirements. Receptor type and sensitivity class drive the applicable noise and air quality criteria used for impact significance assessment. | Test | interface, geospatial, session-269 |
| IFC-DEFS-023 | The interface between the Spatial Overlay Processor and the Environmental Impact Assessment Module SHALL transfer constraint matrices as structured tables containing option ID, designation type, intersection area in hectares, proximity distance in metres to nearest boundary of each designation, and land use classification of affected parcels, for all statutory designations within the assessment buffers. Rationale: DMRB LA 104 requires quantified assessment of impacts on statutory designated sites. Intersection area determines direct habitat loss, proximity distance determines indirect impact zones, and land use classification determines baseline ecological value. Without these spatial metrics the EIA Module cannot complete the designated sites impact assessment required for planning consent. | Test | interface, geospatial, session-269 |
| IFC-DEFS-024 | The interface between the BCR and AST Generator and the Report Template Engine SHALL transfer complete AST datasets, TEE tables, and PA tables in structured JSON format with all monetary values in both undiscounted and 2010 PV prices, tagged with the crossing option identifier and scenario variant that produced them. Rationale: The BCR and AST Generator produces economic outputs that must flow into multiple report sections. Structured JSON with dual-denomination monetary values (undiscounted and PV) avoids rounding errors from format conversion and ensures the Report Template Engine can assemble TAG-compliant tables without re-computation. | Test | interface, appraisal-reporting, session-273 |
| IFC-DEFS-025 | The interface between the Environmental Impact Assessment Module and the Report Template Engine SHALL deliver chapter-level environmental assessment outputs as structured documents with significance ratings per DMRB LA 104 assessment criteria, including summary tables of residual effects by topic. Rationale: Environmental chapter outputs span 14 DMRB LA 104 assessment topics. Delivering them as structured documents with significance ratings, mitigation details, and residual effects preserves the assessment structure required by EIA Regulations and allows the Report Template Engine to assemble chapters without manual reformatting. | Test | interface, appraisal-reporting, session-273 |
| IFC-DEFS-026 | The interface between the Results Extraction and Reporting Module and the Report Template Engine SHALL provide junction performance summaries including volume-over-capacity ratios, mean maximum queue lengths, and average delay per vehicle for all modelled junctions, formatted as publication-ready tables with Do-Minimum and Do-Something comparison columns. Rationale: Junction performance data (V/C ratios, queue lengths, delays) is the primary evidence for traffic impact assessment. Structured transfer from the microsimulation results module to reporting ensures numeric precision is maintained and units are unambiguous for TAG-compliant presentation. | Test | interface, appraisal-reporting, session-273 |
| IFC-DEFS-027 | The interface between the Map Rendering and Visualisation Module and the Non-Technical Summary Generator SHALL deliver scheme plans, thematic maps, and environmental constraint overlays as georeferenced PNG/SVG images at minimum 300 DPI print resolution and 72 DPI web resolution, with accompanying alt-text descriptions for each map layer. Rationale: Spatial outputs (scheme plans, thematic maps, constraint overlays) must serve both print and web channels. Georeferenced formats with embedded metadata enable the Non-Technical Summary Generator to produce accessible outputs with alt-text for each map layer, meeting statutory EIA consultation requirements. | Test | interface, appraisal-reporting, session-273 |
| IFC-DEFS-028 | The interface between the Scenario Configuration Manager and the Sensitivity and Uncertainty Reporter SHALL transfer the complete scenario definition matrix specifying, for each scenario variant, the network option identifier, demand growth assumption, toll level, construction cost adjustment factor, and value of time dataset, enabling the Reporter to construct the full sensitivity test space without manual scenario enumeration. Rationale: Scenario definition matrices encode the full factorial design of sensitivity tests. Transferring complete scenario specifications (options x growth variants x cost variants) as structured data ensures the Sensitivity and Uncertainty Reporter can compute switching values across all combinations without manual scenario configuration. | Test | interface, appraisal-reporting, session-273 |
| IFC-DEFS-029 | The interface between the Option Comparison Module and the Report Template Engine SHALL deliver sifting matrices and detailed comparison tables as structured data with option identifiers, criteria names, seven-point scale scores, and supporting narrative text, enabling the Report Template Engine to render both tabular and narrative comparison sections without manual reformatting. Rationale: Sifting matrices and comparison tables are the primary decision artefacts for option selection. Structured data transfer with option IDs, criteria names, scores, and narrative text enables the Report Template Engine to produce TAG-compliant comparison outputs without risking transcription errors from manual data entry. | Test | interface, appraisal-reporting, session-273 |
| IFC-DEFS-033 | The interface between the Transport User Benefit Calculator and the Present Value and Discounting Engine SHALL transfer undiscounted annual user benefit streams as a matrix indexed by year (1 to 60), user class, mode, and time period, with all values in the specified market price base year, enabling the PV Engine to apply Green Book discounting and produce present value totals for the TEE table. | Test | interface, economic-appraisal, session-275 |
| IFC-DEFS-034 | The interface between the Accident Cost-Benefit Module and the Present Value and Discounting Engine SHALL transfer undiscounted annual accident cost savings as a vector indexed by year (1 to 60) with values disaggregated by severity category (fatal, serious, slight), enabling the PV Engine to apply Green Book discounting and produce the present value of safety benefits. | Test | interface, economic-appraisal, session-275 |
| IFC-DEFS-035 | The interface between the Present Value and Discounting Engine and the BCR and AST Generator SHALL transfer the complete set of discounted present values for all benefit and cost categories (user benefits, accident savings, noise, air quality, greenhouse gas, wider economic impacts, public accounts) as a structured dataset indexed by crossing option and impact category, with metadata recording the price year, discount rate schedule applied, and base year used. | Test | interface, economic-appraisal, session-275 |
| Ref | Requirement | V&V | Tags |
|---|---|---|---|
| ARC-DECISIONS-001 | ARC: Traffic Microsimulation Subsystem — Five-component decomposition separating network coding from simulation execution. The Network Coding Module is isolated because crossing option variants require frequent network edits without re-calibrating behavioural parameters. The Signal Controller Emulator is separated from the Vehicle Behaviour Engine because UTC/SCOOT emulation requires specialist signal timing logic that would otherwise couple junction control changes to vehicle model calibration. The Simulation Execution Manager exists as a distinct orchestration layer because batch runs across 3 time periods, multiple options, and 10+ random seeds require parallel execution management independent of the simulation kernel. An alternative monolithic design was rejected because it would make option-variant testing prohibitively slow and couple calibration to network coding. Rationale: Architecture rationale is self-contained in the requirement text per ARC document convention. Five-component decomposition driven by distinct functional boundaries in microsimulation. | Analysis | architecture, traffic-microsim, session-264 |
| ARC-DECISIONS-002 | ARC: Transport Demand Modelling Subsystem — Seven-component decomposition separating trip generation, distribution, mode-destination choice, highway assignment, PT skimming, matrix estimation, and convergence control. The variable demand model uses an incremental logit approach (TAG M2) rather than a full absolute model because the appraisal compares do-minimum vs do-something scenarios where incremental changes in generalised cost drive the economic case. Matrix estimation is kept as a separate processor because ME2 calibration must be auditable independently of the synthetic distribution — DfT reviewers require separate validation of prior matrices and post-ME2 matrices. The convergence controller is separated from assignment to allow different convergence strategies (MSA, Frank-Wolfe dampening) without modifying the assignment algorithm. Highway and PT assignment are separate because they use fundamentally different algorithms (equilibrium vs optimal strategies) and different network representations. Rationale: Architecture rationale is self-contained in the requirement text per ARC document convention. Seven-component decomposition driven by TAG M2 variable demand modelling workflow. | Analysis | architecture, demand-modelling, session-265 |
| ARC-DECISIONS-005 | ARC: Environmental Assessment Subsystem — Five-component decomposition separating assessment by regulatory domain: EIA framework (LA 104), air quality and noise (LA 105/LA 111), greenhouse gas (LA 114/TAG A3), biodiversity and water (LA 108/LA 113/Environment Act), and distributional impacts (TAG A4.2). Each component maps to a distinct regulatory assessment methodology with its own professional discipline (air quality consultants, ecologists, noise specialists, carbon analysts, social impact assessors). The EIA Module acts as the integrator, receiving quantified results from specialist modules and producing the topic-by-topic significance assessment required for the Environmental Statement. This topology ensures each specialist module can be independently validated against its governing DMRB/TAG standard without coupling to other assessment domains. Rationale: The five-component decomposition mirrors the regulatory structure of DMRB LA 104 environmental assessment. Each component addresses a distinct regulatory domain with different methodologies, data requirements, and competency requirements, enabling independent specialist review and parallel development. | Analysis | architecture, environmental-assessment, session-267 |
| ARC-DECISIONS-006 | ARC: Data Acquisition and Management Subsystem — Hub-and-spoke architecture with External Data Feed Connector as the single ingestion gateway. All external data sources (DfT, ONS, BODS, DEFRA, EA) route through the Feed Connector, which enforces version control and provenance logging before distributing to five domain-specific processors (Traffic Survey, Planning/Land Use, Network, Cost, Socioeconomic). This topology was chosen over direct external connections per component because TAG audit requirements mandate traceable parameter vintages — a single connector ensures consistent data versioning across the appraisal. Alternative considered: distributed direct connections per component, rejected because parameter version drift between components would invalidate economic appraisal consistency checks. Rationale: Hub-and-spoke architecture prevents parameter version drift between consuming subsystems by ensuring all data passes through a single versioned ingestion point. This directly addresses the TAG audit requirement for traceable parameter vintages and reproducible appraisal results. | Inspection | architecture, data-acquisition, session-269 |
| ARC-DECISIONS-007 | ARC: Data Acquisition and Management — Hub-and-spoke architecture with External Data Feed Connector as ingestion gateway. All external sources route through the Feed Connector, which enforces version control and provenance logging before distributing to five domain-specific processors. Chosen over direct connections per component because TAG audit requirements mandate traceable parameter vintages. Rationale: Hub-and-spoke data architecture chosen over direct component-to-source connections because TAG audit requirements mandate traceable data provenance and parameter vintage records. Centralised ingestion through the Feed Connector ensures all external data is version-controlled before reaching domain processors. | Inspection | architecture, duplicate-of-ARC-DECISIONS-006, session-271 |
| ARC-DECISIONS-008 | ARC: Geospatial Analysis Platform — Centralised GIS repository serving specialised analysis engines. The GIS Data Repository acts as the single spatial data store, with three consumer engines (Receptor Mapping, Route/Catchment, Spatial Overlay) reading from it via OGC services. Map Rendering sits downstream consuming processed outputs. This avoids duplicate spatial datasets across analysis engines and ensures all environmental and accessibility analyses use identical base geometry. Alternative considered: embedding spatial data in each analysis component, rejected because geometry version drift between receptor mapping and overlay analysis would produce inconsistent Environmental Statement figures. Rationale: Centralised GIS repository avoids data duplication across analysis engines and ensures all spatial operations use the same base datasets. The alternative of distributed GIS copies per engine would create synchronisation issues when base mapping is updated. | Inspection | architecture, geospatial, session-269 |
| ARC-DECISIONS-009 | ARC: Data Acquisition and Management Subsystem — centralised data ingestion with automated QA gating. The subsystem is decomposed into 6 components: Traffic Count Database, Travel Survey Processor, Land Use and Planning Data Manager, Network and GIS Data Repository, Data Validation and QA Engine, and Scenario Configuration Manager. The Data Validation Engine acts as a quality gate between raw data sources and the modelling pipeline, preventing contaminated data from entering calibration or forecasting. The Scenario Configuration Manager enforces assumption consistency across all consuming subsystems. This architecture was chosen over a distributed data approach where each subsystem manages its own data because: (1) centralised QA prevents the common transport model failure mode where different subsystems use inconsistent or unvalidated versions of the same dataset, (2) the Scenario Configuration Manager eliminates assumption drift between demand modelling and microsimulation, and (3) a single data repository simplifies audit trail requirements for DfT business case scrutiny. Rationale: Centralised data ingestion with automated QA gating prevents the common transport model failure mode where different subsystems use inconsistent or unvalidated versions of the same dataset. The Scenario Configuration Manager eliminates assumption drift between demand modelling and microsimulation. | Analysis | architecture, duplicate-of-ARC-DECISIONS-006, session-271 |
| ARC-DECISIONS-010 | ARC: Appraisal Reporting Subsystem — separation of analytical outputs from report assembly. The subsystem is decomposed into five components: Report Template Engine (document assembly), Option Comparison Module (multi-criteria analysis presentation), Sensitivity and Uncertainty Reporter (robustness testing outputs), Audit Trail and Provenance Tracker (analytical assurance), and Non-Technical Summary Generator (public-facing outputs). This separation was chosen over a monolithic report generator because (1) different stakeholders consume different outputs — DfT reviews business case documents while the public reads the NTS, and these have fundamentally different content, language level, and format requirements; (2) the Audit Trail must operate independently of report generation to provide provenance queries during model review meetings without requiring a full report rebuild; (3) sensitivity analysis iterates independently of the main report when DfT requests additional scenarios during the assurance process. The alternative of embedding all reporting within each analytical subsystem was rejected because it would scatter TAG formatting logic across 6 subsystems and prevent cross-workstream consistency checking. Rationale: Separating analytical output extraction from report assembly allows each component to evolve independently — economic methodology changes do not require report template rework, and report format changes do not require re-running models. This decomposition follows the producer-consumer pattern proven in the other subsystems. | Inspection | architecture, appraisal-reporting, session-273 |
| ARC-DECISIONS-011 | ARC: Economic Appraisal Engine — Eight-component decomposition separating each monetisation domain (user benefits, accidents, environmental, GHG, public accounts, wider impacts) into independent modules feeding a central Present Value and Discounting Engine. This topology mirrors the DfT TAG unit structure (A1 TEE/PA, A1.3 COBALT, A3 environment/GHG, A2.1 wider impacts) ensuring each module can be independently validated against its governing TAG unit. The Present Value and Discounting Engine is centralised rather than distributed across modules because Green Book discounting rules (3.5%/3.0% split at year 30) and optimism bias uplifts must be applied consistently — distributing this logic would risk inconsistent discount rates across benefit streams, directly corrupting the BCR. The BCR and AST Generator is a separate consolidation module because AST format is prescribed by DfT and must aggregate across all impact categories with specific rounding and presentation rules. | Analysis | architecture, economic-appraisal, session-266 |
| Ref | Requirement | V&V | Tags |
|---|---|---|---|
| VER-METHODS-001 | Verify IFC-DEFS-001: Inject a deliberately corrupted network model (truncated link table) and confirm the Vehicle Behaviour Engine rejects it with a checksum mismatch error before simulation start. Then transfer a valid network model and confirm all link attributes match source GIS data within coded tolerances. Rationale: Validates that the Network Coding Module to Simulation Execution Manager interface correctly handles corrupted input, ensuring data quality gating prevents invalid models from entering simulation. | Test | verification, traffic-microsim, session-264 |
| VER-METHODS-002 | Verify IFC-DEFS-002: Run a single-junction scenario with known fixed-time signal plan. Record signal states received by the Vehicle Behaviour Engine at each time step and compare against the programmed stage sequence. Pass criteria: 100 percent of signal state updates delivered at the correct time step with correct stage and phase data. Rationale: Confirms that the Signal Controller Emulator correctly receives and applies signal timing plans from the Simulation Execution Manager, which is critical for accurate junction delay modelling. | Test | verification, traffic-microsim, session-264 |
| VER-METHODS-003 | Verify IFC-DEFS-003: Export journey time matrices from the Results Extraction Module for a calibrated test scenario. Import into the Economic Appraisal Engine and confirm: all OD pairs present, vehicle types correctly disaggregated, journey times within 0.1 seconds of source values, and zone system matches demand model zones with no orphaned or missing zones. Rationale: Validates that journey time matrix extraction from microsimulation produces results comparable with the demand model inputs, ensuring consistency between the microsimulation and demand modelling subsystems. | Test | verification, traffic-microsim, session-264 |
| VER-METHODS-004 | Verify IFC-DEFS-004: Load trip end outputs into the distribution engine for one forecast year. Confirm all zone IDs match, all 5 purposes and 3 time periods are present, productions equal attractions at sector level within 0.1%, and CSV schema validation passes. Pass criteria: zero zone mismatches, zero missing purpose-period combinations. Rationale: Confirms that the Trip End Forecasting to Trip Distribution interface correctly transfers trip end data, ensuring that demand model components are properly chained. | Test | verification, demand-modelling, session-265 |
| VER-METHODS-005 | Verify IFC-DEFS-005: Run highway assignment on a calibrated base year scenario. Extract cost skims and confirm time, distance, and toll components are present and separable. Verify skim matrix dimensions match zone system. Spot-check 10 zone pairs with known observed journey times — modelled times SHALL be within 15% of observed. Pass criteria: complete skim matrices with no NaN values, all 10 spot checks within tolerance. Rationale: Validates highway assignment convergence and confirms that assignment results meet TAG unit M3.1 convergence criteria, ensuring that user benefit calculations are based on a stable assignment. | Test | verification, demand-modelling, session-265 |
| VER-METHODS-006 | Verify IFC-DEFS-006: Run one iteration of the demand model. Confirm the convergence report contains total trips per user class, maximum zonal change, and percentage demand change. Verify matrices are non-negative and trip totals match the convergence report values. Pass criteria: report fields present and consistent with matrix contents. Rationale: Confirms demand-supply convergence loop operates correctly, which is essential for variable demand modelling as required by TAG unit M2. | Test | verification, demand-modelling, session-265 |
| VER-METHODS-007 | Verify IFC-DEFS-007: Run matrix estimation with a synthetic prior matrix and known count set. Confirm iterative loop produces improving GEH statistics with each cycle. Verify the 50-iteration cap terminates the loop. Pass criteria: GEH improves monotonically for at least the first 10 iterations, loop terminates at iteration 50 if convergence criterion not met. Rationale: Validates that matrix estimation produces credible adjustments to the prior matrix using synthetic data with known ground truth, confirming the estimation algorithm works correctly before applying to real data. | Test | verification, demand-modelling, session-265 |
| VER-METHODS-008 | Verify IFC-DEFS-008: Extract cordon matrices from a converged assignment. Confirm 15-minute time slices are present, vehicle classes are disaggregated, and total cordon demand sums to within 2% of the corresponding period-level strategic assignment link flows at cordon entry points. Pass criteria: all time slices present, all vehicle classes present, flow consistency within 2%. Rationale: Confirms that cordon matrix extraction from assignment outputs produces correct sub-area matrices, which are essential for feeding microsimulation models with demand data from the strategic model. | Test | verification, demand-modelling, session-265 |
| VER-METHODS-009 | Verify IFC-DEFS-009: Generate do-minimum and do-something outputs from the demand model. Confirm both demand matrices and generalised cost changes are present and disaggregated by purpose and user class. Compute rule-of-half benefits and verify the sign is positive for a scenario where the new crossing reduces costs. Pass criteria: complete data transfer, positive net benefits for cost-reducing scenario. Rationale: Validates the critical demand model to economic appraisal interface, ensuring benefit calculations receive correct scenario outputs with all required metrics. | Test | verification, demand-modelling, session-265 |
| VER-METHODS-010 | Verify IFC-DEFS-010: Load air quality and noise receptor results into the EIA Module for one scenario. Confirm all receptor records contain valid easting/northing coordinates, receptor type classification, baseline and do-something values for each pollutant and noise metric, and that no records have null or negative concentration values. Verify receptor count matches the defined study area receptors. Pass criteria: zero null fields, all coordinates within study area extent, receptor count matches definition. Rationale: Confirms air quality and noise receptor results transfer correctly to the EIA Module for aggregation into the environmental statement. | Test | verification, environmental-assessment, session-267 |
| VER-METHODS-011 | Verify IFC-DEFS-011: Transfer GHG assessment outputs for a test scenario with known emission inputs. Confirm annual CO2e totals by source category sum to the lifecycle total within rounding tolerance. Verify monetised NPV matches independent calculation using published BEIS carbon values and Green Book discount rates. Pass criteria: lifecycle sum consistent, NPV within 1% of independent calculation. Rationale: Validates GHG emissions data transfer for correct monetisation using BEIS carbon values, ensuring TAG A3 reporting accuracy. | Test | verification, environmental-assessment, session-267 |
| VER-METHODS-012 | Verify IFC-DEFS-012: Extract link-level traffic data from a converged transport model run. Confirm AADT, speed, and HGV percentage are present for all links within the AQ study area (200m buffer) and noise study area (600m buffer). Verify AADT values are positive and speeds are within plausible range (5-120 km/h). Cross-check total screenline flows against assignment outputs. Pass criteria: zero missing links within study areas, all values within plausible ranges, screenline flows within 2%. Rationale: Confirms that link-level traffic data transfer from the demand model to environmental assessment uses consistent vehicle classifications and road link references, preventing mismatched spatial data between subsystems. | Test | verification, environmental-assessment, session-267 |
| VER-METHODS-013 | Verify IFC-DEFS-013: Load a test dataset of 120 count site records into the Traffic Survey Data Processor and verify that the Matrix Estimation Processor receives CSV output containing all required fields (site ID, link reference, direction, time period, vehicle type, flow) with no missing fields and flow values matching input within floating-point tolerance. Pass criteria: 100 percent field completeness and zero data loss across transfer. Rationale: Validates the Traffic Survey Data Processor to Matrix Estimation interface, confirming that count data format and quality flags are correctly transferred and interpreted. | Test | verification, data-acquisition, session-269 |
| VER-METHODS-014 | Verify IFC-DEFS-014: Export a coded network from the Network Data Repository and import into SATURN. Verify that node count, link count, and all link attributes (speed, capacity, lanes, gradient, type) match the repository source within 0.01 percent tolerance. Verify network checksum matches. Pass criteria: zero attribute discrepancies and checksum match confirmed. Rationale: Confirms network data integrity across the Network Data Repository to Highway Assignment interface, preventing model corruption from incomplete or stale network transfers. | Test | verification, data-acquisition, session-269 |
| VER-METHODS-015 | Verify IFC-DEFS-015: Transfer a test scheme cost dataset through the interface and verify TUBA-compatible output contains all cost categories disaggregated by year, in both factor-cost and market-price bases, with optimism bias as separate line items. Verify that discounted PV totals computed from the transferred data match independently calculated values within 0.1 percent. Pass criteria: complete cost table structure and PV consistency check passed. Rationale: Validates cost data transfer to the Public Accounts Calculator, ensuring optimism bias and cost category disaggregation are preserved through the interface. | Test | verification, data-acquisition, session-269 |
| VER-METHODS-016 | Verify IFC-DEFS-016: Transfer socioeconomic attribute tables and verify the Distributional Impact Assessor receives complete zone-level records with population, IMD quintile, car ownership, economic activity, and protected characteristics for all study area zones. Verify zone count matches and no null values in mandatory fields. Pass criteria: 100 percent zone coverage and zero null mandatory fields. Rationale: Confirms socioeconomic attribute transfer for distributional impact analysis, ensuring zone-level deprivation and protected characteristic data reach the assessor correctly. | Test | verification, data-acquisition, session-269 |
| VER-METHODS-017 | Verify IFC-DEFS-017: Transfer local development adjustment factors and verify the Trip End Forecasting Module receives zone-level records with zone ID, forecast year, trip purpose, and adjustment factor for all zones with committed development. Verify that applying the adjustment factors preserves NTEM regional control totals within 0.1 percent. Pass criteria: complete record transfer and regional total preservation confirmed. Rationale: Validates planning data adjustment factor transfer, ensuring local development adjustments correctly modify NTEM base trip ends. | Test | verification, data-acquisition, session-269 |
| VER-METHODS-018 | Verify IFC-DEFS-018: Integration test transferring a sample count dataset (minimum 50 sites) from Traffic Count Database to Matrix Estimation Processor. Pass criteria: all mandatory fields present, quality grades included for every record, validation flags match Data Validation Engine output, and processor accepts dataset without parsing errors. Rationale: Confirms count data transfer with quality grades from the Traffic Count Database, validating that data quality metadata is preserved through the interface for matrix estimation weighting. | Test | verification, data-acquisition, session-268 |
| VER-METHODS-019 | Verify IFC-DEFS-022: Transfer a test receptor dataset of 500 points from the Receptor Mapping Engine and verify the Air Quality and Noise Modelling Engine receives a valid GeoPackage containing all required fields (ID, easting, northing, type, sensitivity, height, floors) with no null mandatory fields, all coordinates within the study area bounding box, and receptor count matching source. Pass criteria: 100 percent record transfer, zero null mandatory fields, all coordinates valid in BNG. Rationale: Validates receptor dataset transfer from the Receptor Mapping Engine, confirming spatial accuracy, receptor classification, and minimum receptor count requirements. | Test | verification, geospatial, session-269 |
| VER-METHODS-020 | Verify IFC-DEFS-019: Integration test transferring trip rate dataset from Travel Survey Processor to Trip End Forecasting Module. Pass criteria: trip rates disaggregated by all 5 TAG purposes, person types, and time periods; confidence intervals present for every rate; CSV format parseable by receiving module; and trip rates reproduce known NTS regional averages within published confidence bounds. Rationale: Confirms trip rate dataset transfer including confidence intervals, which are essential for demand model calibration and uncertainty analysis. | Test | verification, data-acquisition, session-268 |
| VER-METHODS-021 | Verify IFC-DEFS-023: Run a test overlay for a single crossing option and verify the Environmental Impact Assessment Module receives a constraint matrix containing all statutory designation types, with intersection areas summing to within 0.01 hectare of independently computed GIS overlay results, and proximity distances matching to within 1 metre. Pass criteria: designation type completeness, area sum within tolerance, distance within tolerance. Rationale: Validates spatial overlay computation for environmental constraint assessment, confirming intersection area and proximity calculations match expected values for known test geometries. | Test | verification, geospatial, session-269 |
| VER-METHODS-022 | Verify IFC-DEFS-020: Integration test transferring zonal planning data from Land Use Data Manager to Trip End Forecasting Module. Pass criteria: population and employment totals sum to NTEM v8.0 regional control totals within 0.5%, compliance flags correctly reflect conformance status, and all forecast years (2031, 2046, 2061) present with complete zonal coverage. Rationale: Confirms zonal planning data transfer from the Land Use and Planning Data Manager, validating that NTEM control total compliance is correctly flagged per zone. | Test | verification, data-acquisition, session-268 |
| VER-METHODS-023 | Verify IFC-DEFS-021: Integration test transferring coded network from GIS Repository to Highway Assignment Engine. Pass criteria: all 3,000+ links have non-null speed, capacity, and BPR parameters; junction turn penalties present at signalised nodes; network loads successfully in assignment software; and a test assignment converges within the specified 0.1% gap tolerance. Rationale: Validates coded network transfer from the GIS Repository to Highway Assignment, confirming attribute completeness and format compatibility with assignment software. | Test | verification, data-acquisition, session-268 |
| VER-METHODS-024 | Verify SUB-REQS-003: Calibrate the Vehicle Behaviour Engine against observed speed-flow data from A19, A1058, and Tyne Tunnel approaches. Pass criteria: simulated mean speeds within 15 percent of observed 15-minute mean speeds for at least 85 percent of links, and GEH statistic below 5 for at least 85 percent of calibration count sites across AM peak, interpeak, and PM peak periods. Rationale: Speed-flow calibration is the primary determinant of microsimulation model validity. Unreproducible link performance invalidates journey time outputs for economic appraisal. | Test | verification, traffic-microsimulation, session-271 |
| VER-METHODS-025 | Verify SUB-REQS-010: Run Wardrop equilibrium assignment on the base year calibrated network. Pass criteria: percent gap convergence below 0.1 percent, and observed versus modelled screenline flows within 5 percent at the Tyne screenline and within 10 percent at outer cordon sites. Validate against DMRB/TAG M3.1 convergence standards. Rationale: Highway assignment convergence and screenline validation are TAG mandatory checks. Non-converged assignment produces unstable route choice rendering option comparison unreliable. | Test | verification, transport-demand, session-271 |
| VER-METHODS-026 | Verify SUB-REQS-016: Compare modelled annual mean NO2 and PM2.5 concentrations against AURN and local authority monitoring site measurements for the base year. Pass criteria: modelled concentrations within plus or minus 25 percent of monitored values at a minimum of 80 percent of verification sites, and model adjustment factor within 0.75 to 1.25 per LAQM TG22 guidance. Rationale: Air quality model verification against monitoring data is required by DMRB LA 105. Unverified outputs cannot support Environmental Statement conclusions. | Test | verification, environmental, session-271 |
| VER-METHODS-027 | Verify SUB-REQS-018: Validate lifecycle carbon emission calculations by independent recalculation using PAS 2080 methodology for one crossing option. Pass criteria: total tonnes CO2e within 10 percent of independent estimate across construction, maintenance, and operation phases, with construction-phase embodied carbon cross-checked against Highways England Carbon Tool outputs. Rationale: GHG quantification supports TAG A3 environmental valuation and NPSNN carbon compliance. Independent verification needed as the carbon case is material to the planning decision. | Analysis | verification, environmental, session-271 |
| VER-METHODS-028 | Verify SUB-REQS-004: Execute 10 random seed runs for one scenario and one time period. Confirm mean journey times have coefficient of variation below 5 percent and 95 percent confidence interval width is below 10 percent of mean. Verify all seed results are logged with seed values for reproducibility. Rationale: TAG M3.1 requires demonstration that microsimulation outputs are statistically stable. Insufficient seed runs produce unstable journey time estimates undermining economic appraisal. | Test | verification, traffic-microsimulation, session-271 |
| VER-METHODS-029 | Verify SUB-REQS-012: Run the variable demand model for one forecast scenario until convergence. Pass criteria: demand change between successive iterations below 0.1 percent, assignment gap below 0.1 percent, and total iterations recorded. Verify convergence log output matches TAG M2 reporting format. Rationale: Demand-supply convergence is mandatory for TAG variable demand modelling. Non-converged runs produce arbitrary demand responses invalidating the economic case. | Test | verification, transport-demand, session-271 |
| VER-METHODS-030 | Verify SUB-REQS-024: Inspect optimism bias uplift calculations for one crossing option across all cost categories. Pass criteria: uplift percentages match Green Book supplementary guidance Table 1 for the appropriate project stage, and the applied percentages are within the prescribed ranges for roads projects (15 to 44 percent for capital costs at Programme Entry). Rationale: Optimism bias directly affects BCR and VfM category. Incorrect uplift percentages could lead to wrong investment decision classification. | Inspection | verification, economic-appraisal, session-271 |
| VER-METHODS-031 | Verify IFC-DEFS-024: Execute a test scenario producing AST, TEE, and PA tables from the BCR and AST Generator. Confirm the Report Template Engine receives valid JSON containing all required fields (monetary values in undiscounted and 2010 PV prices, option identifier, scenario variant). Pass criteria: all table cells in the assembled report match source JSON values with zero transcription errors. Rationale: Demonstration validates end-to-end data flow from BCR/AST Generator to Report Template Engine. JSON schema validation and field completeness checks verify the interface contract is met, catching integration failures before they propagate into published reports. | Test | verification, appraisal-reporting, session-273 |
| VER-METHODS-032 | Verify IFC-DEFS-025: Generate environmental chapter outputs for a test crossing option covering all 14 DMRB LA 104 topics. Confirm the Report Template Engine receives structured documents with significance ratings and summary tables. Pass criteria: all 14 topics present, significance ratings conform to DMRB scale, and residual effects table is complete. Rationale: Environmental outputs must cover all 14 DMRB LA 104 topics for EIA compliance. Testing against a representative crossing option confirms the interface delivers complete chapter-level assessments with required significance ratings and mitigation details. | Test | verification, appraisal-reporting, session-273 |
| VER-METHODS-033 | Verify IFC-DEFS-026: Run a test microsimulation producing junction performance summaries for 5 representative junctions. Confirm delivery of V/C ratios, mean max queue lengths, and average delays with Do-Minimum and Do-Something columns. Pass criteria: all metrics present for all junctions, values within physically plausible ranges (V/C 0-2.0, queue 0-500 PCU, delay 0-600s). Rationale: Junction performance verification uses a controlled set of 5 representative junctions to confirm data fidelity. Checking V/C ratios, queue lengths, and delays with documented precision ensures the microsimulation-to-reporting interface preserves the numeric accuracy needed for transport assessment. | Test | verification, appraisal-reporting, session-273 |
| VER-METHODS-034 | Verify IFC-DEFS-027: Generate scheme plan and thematic map outputs for a test option. Confirm PNG/SVG images at 300 DPI (print) and 72 DPI (web) with accompanying alt-text for each layer. Pass criteria: image resolution matches spec, alt-text is non-empty and describes spatial content, all map layers have corresponding alt-text entries. Rationale: Map output verification confirms dual-resolution rendering (300 DPI print, 72 DPI web) and accessibility metadata. Alt-text presence for each layer is a WCAG 2.1 requirement for public consultation materials. | Test | verification, appraisal-reporting, session-273 |
| VER-METHODS-035 | Verify IFC-DEFS-028: Load a test scenario definition matrix with 4 options x 3 growth variants x 2 cost variants. Confirm the Sensitivity and Uncertainty Reporter receives all 24 scenario combinations with correct option ID, growth assumption, toll level, cost factor, and VoT dataset. Pass criteria: scenario count matches expected 24, no duplicate or missing combinations. Rationale: Scenario matrix verification with a 4x3x2 factorial design (24 combinations) confirms the interface correctly transmits all scenario variants. Incomplete scenario transfer would silently omit sensitivity test results, undermining the robustness analysis required by TAG Unit M4. | Test | verification, appraisal-reporting, session-273 |
| VER-METHODS-036 | Verify IFC-DEFS-029: Generate sifting matrix and comparison table data for 4 test options. Confirm structured data contains option IDs, criteria names, seven-point scores, and narrative text. Pass criteria: all options present, all criteria scored, seven-point scores are valid values from the WebTAG scale, and narrative text accompanies each qualitative score. Rationale: Sifting matrix verification with 4 test options confirms all required fields (IDs, criteria, scores, narrative) are transferred correctly. Data integrity at this interface directly affects the option comparison outputs presented to decision-makers. | Test | verification, appraisal-reporting, session-273 |
| VER-METHODS-043 | Verify SUB-REQS-001: Select 20 representative road links within 2km of each crossing option spanning major roads, minor roads, and slip roads. Compare coded speed, capacity, lane count, gradient, and link type against surveyed values from the 2024 traffic surveys. Pass criteria: all 20 links match observed values within 10 percent for speed and capacity, exact match for lane count and link type, and gradient within 0.5 percent. | Inspection | |
| VER-METHODS-044 | Verify SUB-REQS-002: Compare modelled green times against observed stage durations for 10 signalised junctions within the study area across AM peak, interpeak, and PM peak periods. Pass criteria: modelled green times within 3 seconds of observed stage durations for each stage at each junction in each time period, and overall junction cycle times within 5 seconds of observed. | Test | |
| VER-METHODS-045 | Verify SUB-REQS-005: Execute a complete model run for one crossing option and extract OD journey time matrices and junction turning movement matrices. Confirm outputs are directly importable by the Economic Appraisal Engine without manual transformation, disaggregated by vehicle type with car, LGV, and HGV categories. Pass criteria: imported matrices match model outputs exactly with no data loss or format conversion errors, and all vehicle type categories are present. | Demonstration | |
| VER-METHODS-046 | Verify SUB-EAE-050: Run the Transport User Benefit Calculator for one crossing option with known do-minimum and do-something demand model outputs. Confirm TEE table contains all required disaggregations (3 user classes, 2 modes, 4 time periods). Cross-check total user benefits against an independent TUBA run using the same inputs. Pass criteria: user benefit totals agree within 0.5 percent, all cells populated with correct sign convention, market price base year matches DfT specification. | Test | verification, economic-appraisal, session-275 |
| VER-METHODS-047 | Verify SUB-EAE-052: Run COBALT analysis for one crossing option using published A19 corridor accident data. Compare modelled accident changes against manual calculation using the same link flows and DfT accident rates. Pass criteria: total accident cost savings agree within 1 percent, severity disaggregation matches, all links within 2km of the crossing are included in the analysis. | Analysis | verification, economic-appraisal, session-275 |
| VER-METHODS-048 | Verify SUB-EAE-058: Run the BCR and AST Generator for all crossing options using verified PV outputs. Confirm initial BCR equals PVB/PVC, adjusted BCR includes wider economic impacts. Verify AST format matches current TAG Unit A1 template including row ordering, sign conventions, and rounding rules. Pass criteria: BCR values agree with independent spreadsheet calculation, AST passes DfT format compliance check. | Test | verification, economic-appraisal, session-275 |
flowchart TB n0["component<br>Network Coding Module"] n1["component<br>Signal Controller Emulator"] n2["component<br>Vehicle Behaviour Engine"] n3["component<br>Simulation Execution Manager"] n4["component<br>Results Extraction and Reporting Module"] n0 -->|Network model| n2 n0 -->|Junction geometry and signal plans| n1 n1 -->|Real-time signal states| n2 n2 -->|Vehicle trajectories| n3 n3 -->|Batch run outputs| n4
Traffic Microsimulation Subsystem — Internal
| Entity | Hex Code | Description |
|---|---|---|
| Accident Cost-Benefit Module | 40A53349 | Calculates road safety benefits using COBALT (Cost and Benefit to Accidents – Light Touch) methodology. Takes link flows and speeds from the highway assignment model for do-minimum and do-something scenarios. Applies DfT accident rates by road type, speed, and flow to estimate accident frequency changes. Monetises using DfT values of preventing casualties (fatal, serious, slight). Outputs 60-year discounted accident cost savings. Interfaces with the link flow outputs of the highway assignment, not the microsimulation. |
| Air Quality and Noise Modelling Engine | 40E53159 | Quantitative environmental modelling component for the New Tyne Crossing appraisal. Runs DMRB LA 105 air quality dispersion modelling using ADMS-Roads or equivalent, computing NO2 and PM2.5 concentrations at sensitive receptors within 200m of affected road links. Runs DMRB LA 111 noise assessment using CRTN methodology, computing LA10,18h and Lnight at noise-sensitive receptors. Inputs are AADT flows, speeds, and fleet composition from the transport model plus receptor coordinates from the geospatial platform. Outputs are receptor-level pollutant concentrations and noise levels for comparison against air quality objectives and SOAEL/LOAEL thresholds. |
| Appraisal Reporting Subsystem | 40A57B59 | Report generation and options comparison subsystem for the New Tyne Crossing appraisal. Produces Appraisal Summary Tables (ASTs) per TAG Unit A1 for each route option, consolidating economic, environmental, social, and public accounts assessments into a standardised comparison framework. Generates five-case business case documentation (strategic, economic, commercial, financial, management cases) per HM Treasury Green Book and DfT business case guidance for SOBC, OBC, and FBC stages. Produces distributional impact analysis tables showing effects by income quintile, geography, and protected characteristics per Equality Act 2010. Creates public-facing scheme information including option comparison visualisations, benefits summaries, and consultation response reports. Manages version control of appraisal outputs across option iterations and sensitivity tests. Outputs formatted Word/PDF documents, Excel calculation workbooks, and web-ready summaries for public consultation portal. |
| Audit Trail and Provenance Tracker | 40A53B58 | Maintains complete analytical provenance chain from input data through model runs to published appraisal results. Records which model version, parameter set, network variant, and demand scenario produced each output table. Tracks document approval status through internal review, client review, and final issue. Stores checksums of all input datasets and model output files. Provides query interface to answer 'which inputs produced this BCR?' for any published result. Complies with DfT Analytical Assurance Framework requirements for model audit trails in transport business cases. |
| BCR and AST Generator | 40A53148 | Computes initial Benefit-Cost Ratio (PVB/PVC) and adjusted BCR (including wider economic impacts) per TAG Unit A1. Consolidates outputs from all monetisation modules (user benefits, accidents, environment, GHG, public accounts, wider impacts) into the Appraisal Summary Table format. Generates ASTs for each crossing option and each forecast scenario. Produces value-for-money category assignment per DfT thresholds (poor <1.0, low 1.0-1.5, medium 1.5-2.0, high 2.0-4.0, very high >4.0). Final output module of the economic appraisal. |
| Biodiversity and Water Environment Assessor | 00843A7D | Ecological and hydrological assessment component for the New Tyne Crossing appraisal. Evaluates impacts on designated sites (River Tyne SSSI, Northumbria Coast SPA), protected species (otter, great crested newt, breeding birds along the Tyne corridor), and Biodiversity Net Gain calculations per Environment Act 2021 (mandatory 10% BNG). Assesses water quality impacts on the River Tyne under WFD (Water Framework Directive) including construction runoff, operational drainage, and flood risk using DMRB LA 113 and LA 108. Outputs ecological significance assessments and BNG metric scores. |
| Cost Data Manager | 00843378 | Manages all cost data for the economic appraisal of New Tyne Crossing options. Stores scheme capital cost estimates from quantity surveyors broken down by construction element (tunnel boring, bridge deck, approach roads, structures, land acquisition, utilities diversion, environmental mitigation). Maintains DfT-standard optimism bias factors per cost category (66% for tunnels and underground works, 44% for road construction per HMT Green Book). Stores 60-year lifecycle maintenance cost profiles using Highways England standard rates. Manages risk quantification data from quantified risk assessment (QRA) for each option. Outputs TUBA-compatible cost tables and PA table inputs in current and discounted prices using HM Treasury discount rates (3.5% years 0-30, 3.0% years 31-75). |
| Data Acquisition and Management Subsystem | 40A53358 | Data collection, integration, and warehousing subsystem for the New Tyne Crossing appraisal. Manages automatic traffic count (ATC) data from permanent and temporary sites on A1, A19, A184, A194(M), Tyne Bridge, Tyne Tunnel, and local road network. Processes ANPR origin-destination survey data for cross-Tyne movement patterns. Integrates DfT Road Traffic Statistics, National Travel Survey, Census 2021 journey-to-work tables, BRES employment data, TRICS trip generation rates, and local authority planning application databases for development trip generation. Manages public transport patronage data from Nexus (Metro/bus) and rail station usage from ORR. Implements data quality assurance per TAG Unit M1 (principles of modelling and appraisal) including validation against independent sources, reasonableness checks on growth factors, and documentation of data provenance. Provides ETL pipelines to feed cleaned data into demand model, microsimulation, and environmental assessment subsystems. |
| Data Validation and Quality Assurance Engine | 51E73B08 | Automated quality assurance engine applying validation rules to all incoming data before it enters the modelling pipeline. Performs range checks on traffic counts (flags counts exceeding link capacity or showing implausible hourly patterns), checks spatial consistency of network data against OS MasterMap, validates survey expansion factors against census totals, and verifies temporal consistency of count data across adjacent sites. Produces data quality reports with pass/fail flags per dataset and site, identifying records requiring manual review. Prevents contamination of calibration datasets with erroneous observations. |
| Demand-Supply Convergence Controller | 40B73A08 | Outer loop controller managing the iterative convergence between variable demand model and network assignment for the Tyne crossing appraisal. Implements Method of Successive Averages (MSA) with adaptive step sizes. Monitors demand-supply gap: percentage change in total demand, maximum zonal demand change, and assignment %GAP across iterations. Convergence criteria per TAG Unit M2: demand change < 0.1% and assignment %GAP < 0.1% simultaneously. Controls execution sequence: assignment → skim extraction → demand model → matrix update → re-assignment. Typically requires 15-30 outer loop iterations for convergence. |
| Distributional Impact Assessor | 40A539DD | Social equity and distributional analysis component for the New Tyne Crossing appraisal, implementing TAG Unit A4.2 (Distributional Impact Appraisal). Evaluates how transport impacts (accessibility, noise, air quality, severance, accidents) are distributed across different social groups defined by income quintile, disability, age, gender, and ethnicity. Uses Index of Multiple Deprivation (IMD) data and Census 2021 demographics mapped to transport model zones. Produces distributional impact matrices showing which communities benefit and which are adversely affected, scored on a 7-point scale per TAG A4.2. Required for Equality Impact Assessment under the Equality Act 2010. |
| Economic Appraisal Engine | 40B53358 | WebTAG-compliant cost-benefit analysis engine for the New Tyne Crossing appraisal. Computes Transport Economic Efficiency (TEE) table, Public Accounts (PA) table, and Analysis of Monetised Costs and Benefits (AMCB). Calculates Benefit-Cost Ratio (BCR), Net Present Value (NPV), and adjusted BCR including wider economic impacts (agglomeration, labour supply, output change in imperfectly competitive markets) per TAG Unit A2. Consumes demand model outputs (time savings matrices), scheme cost estimates (CAPEX in base year prices, optimism bias per HMT Green Book), and maintenance/operating cost profiles over 60-year appraisal period. Applies DfT values of time and vehicle operating costs from TAG Data Book. Discount rate: 3.5% for years 0-30, 3.0% beyond. Produces monetised benefits breakdown, distributional impact tables (income quintiles, spatial), and value for money assessment categories. |
| Environmental Assessment Subsystem | 40A53B59 | Multi-domain environmental impact assessment engine for the New Tyne Crossing appraisal. Covers air quality dispersion modelling per DMRB LA 105 using ADMS-Roads for NO2 and PM2.5 concentrations at sensitive receptors within 200m of affected road links. Noise assessment per DMRB LA 111 using CRTN methodology for daytime and night-time levels (LA10,18h and Lnight) at residential facades. Carbon emissions calculated per TAG Unit A3 using DEFRA emission factors and fleet composition projections. Ecological impact assessment including Biodiversity Net Gain (BNG) metric calculation per Environment Act 2021, habitats regulations screening for SACs/SPAs within zone of influence. Landscape and visual impact assessment per GLVIA3. Flood risk assessment for Tyne floodplain options per NPPF sequential/exception tests. Consumes traffic flow and speed data from demand model and microsimulation, OS terrain data, Met Office wind roses, and ecological survey data. |
| Environmental Impact Assessment Module | 40A53B59 | Core EIA assessment engine for the New Tyne Crossing appraisal, implementing DMRB LA 104 (Environmental Assessment and Monitoring) methodology. Evaluates 14 environmental topics (air quality, noise, landscape, biodiversity, water, heritage, etc.) against do-minimum and do-something scenarios. Receives traffic flow data from the transport model and geospatial data for receptor locations. Produces topic-by-topic significance assessments on a 5-point scale (large beneficial to large adverse) for input to the Appraisal Summary Table. Must comply with Infrastructure Planning (Environmental Impact Assessment) Regulations 2017 and the NPSNN. |
| Environmental Impact Monetisation Module | 40A431D9 | Converts physical environmental impacts (noise level changes in dB, air quality concentration changes in μg/m³) into monetary values for inclusion in the economic appraisal. Uses WebTAG noise workbook methodology for noise monetisation and IGCB damage costs for air quality monetisation (NOx, PM2.5). Takes noise contour outputs and air quality modelling outputs from the Environmental Assessment Subsystem. Produces monetised environmental impact values per receptor and aggregated totals for inclusion in the AST. |
| External Data Feed Connector | 40A53358 | Manages automated and semi-automated data feeds from external government and transport data sources for the New Tyne Crossing appraisal. Connects to DfT Road Traffic Statistics API for national count data, DfT TAG Data Book for standard economic parameters (values of time, vehicle operating costs, accident rates by road type), BODS API for bus timetable GTFS feeds, ONS Nomis API for labour market and census data, DEFRA MAGIC API for environmental designations and constraints, and Environment Agency Flood Map for Planning data. Implements version control for parameter sets — critical because TAG Data Book values change annually and appraisals must use consistent parameter vintages. Logs all data provenance (source, version, retrieval date) for audit trail compliance with TAG guidance. |
| Geospatial Analysis Platform | 40E53159 | GIS-based spatial analysis and data management platform for the New Tyne Crossing appraisal. Manages route option corridor definition and constraint mapping using OS MasterMap Topography and ITN layers, Environment Agency flood zone data (zones 2/3), Natural England designated sites (SSSI, SAC, SPA, Ramsar), Historic England listed buildings and scheduled monuments, contaminated land registers, and Coal Authority mining constraints. Integrates LiDAR DTM for terrain analysis and cut/fill volume estimation for each option. Manages land ownership parcels from HM Land Registry for CPO cost estimation. Provides spatial querying for receptor identification (residential, schools, hospitals within buffer distances of route options). Outputs constraint maps, route plan drawings, and spatial data exports for environmental and economic subsystems. Uses OSGB36/BNG coordinate reference system. |
| GIS Data Repository | 40853158 | Central geospatial data store for the New Tyne Crossing transport appraisal. Manages vector and raster datasets including OS MasterMap Topography, OS Open Roads, Environment Agency Flood Map for Planning (Flood Zones 2 and 3), Natural England SSSI/SPA/SAC boundaries, Historic England Listed Buildings and Scheduled Monuments, local authority planning constraint layers, and scheme option corridor geometries. Stores data in OGC-compliant formats (GeoPackage, GeoTIFF) with OSGB36 British National Grid projection. Serves spatial data to the Receptor Mapping Engine, Route and Catchment Analyser, and Spatial Overlay Processor via standardised WFS/WMS interfaces. |
| Greenhouse Gas Assessment Module | 40E53B59 | Carbon emissions quantification component for the New Tyne Crossing appraisal, implementing TAG Unit A3 and DMRB LA 114 (Climate). Calculates lifecycle carbon emissions covering construction, maintenance, and operational phases. Operational carbon uses EFT (Emission Factor Toolkit) v12 with fleet composition projections. Computes monetised carbon values using BEIS traded/non-traded carbon prices. Outputs are tonnes CO2e by source and year, plus monetised Net Present Value of carbon impact for the economic appraisal. Must account for decarbonisation trajectory of the UK vehicle fleet to 2061. |
| Greenhouse Gas Valuation Module | 40A433DD | Monetises transport-related greenhouse gas emissions using BEIS traded and non-traded carbon values per TAG Unit A3. Calculates CO2e from fuel consumption changes derived from link flows and speeds (DMRB emission factors). Applies separate valuation to traded sector (electricity for rail/EV) and non-traded sector (direct vehicle combustion). Handles carbon price trajectories to 2100 with Green Book discounting. Outputs lifecycle GHG monetary values for each crossing option. |
| Highway Assignment Engine | 41F73308 | Wardrop user equilibrium highway assignment engine operating on a coded strategic road network of ~3000 links covering Tyneside and approaches. Implements Frank-Wolfe algorithm with BPR speed-flow curves calibrated to observed journey times on A19, A1058, Tyne Tunnel approach, and A1 corridor. Assigns car and LGV/HGV matrices to network and produces converged link flows, journey times, and generalised cost skims. Convergence criterion: %GAP < 0.1%. Must correctly model route choice between existing Tyne crossings and proposed new crossing under varying demand scenarios. Outputs feed microsimulation cordons and economic appraisal. |
| Land Use and Planning Data Manager | 00843379 | Manager for spatial planning and land use datasets used as trip generation inputs. Ingests NTEM v8.0 planning data (population, employment, households by zone), local plan allocations from Newcastle, Gateshead, and North Tyneside councils, TEMPro growth factors, and committed development registers. Maintains a zone-based database of demographic and employment data at MSOA and model zone levels. Produces zonal growth factors for trip end forecasting and provides development trajectory inputs for opening year (2031), design year (2046), and horizon year (2061) scenario construction. |
| Map Rendering and Visualisation Module | 40E5F158 | Produces cartographic outputs for the New Tyne Crossing appraisal reporting. Generates scheme plan drawings showing option alignments on OS base mapping, thematic maps showing environmental impact zones (noise contours, air quality isopleths, flood extents), accessibility isochrone maps, and traffic flow difference plots. Outputs publication-quality maps in PDF/SVG at standard scales (1:2500 for detail, 1:25000 for context) with DfT/Highways England standard symbology. Supports interactive web map layers for stakeholder consultation. Feeds the Appraisal Reporting Subsystem with embedded figures for Environmental Statement chapters and transport assessment reports. |
| Matrix Estimation Processor | 51B73308 | Entropy-maximising matrix estimation (ME2) processor that adjusts synthetic prior matrices to match observed traffic counts at ~150 count sites across Tyneside. Ingests DfT road traffic count data, WebTRIS motorway data, and local authority ATC counts. Applies maximum entropy formulation to minimise deviation from prior (gravity model) matrices while reproducing observed screenline flows within 5% GEH threshold. Operates iteratively with highway assignment to ensure consistency. Critical for calibration of base year (2023) demand matrices. Must preserve trip length distributions and not distort long-distance through trips. |
| Mode-Destination Choice Model | 40B43208 | Hierarchical logit discrete choice model implementing variable demand response per TAG Unit M2. Nested structure with mode choice (car driver, car passenger, public transport, active modes) above destination choice. Computes elastic demand responses to changes in generalised cost arising from new crossing options. Uses DfT TAG Data Book values of time by purpose and income group. Lambda parameters calibrated to observed mode shares at Tyne crossings. Produces do-minimum and do-something demand matrices showing mode shift, trip redistribution, and induced/suppressed demand. Key output: demand responses that feed directly into economic appraisal benefit calculations. |
| Network and GIS Data Repository | 40853158 | Spatial database storing the coded road network, public transport network, zone system, and associated geospatial datasets for the Tyneside transport model. Contains OS MasterMap and Ordnance Survey road centreline data, junction geometries with signal staging from Tyne and Wear UTC, bus routes and timetables from BODS/GTFS feeds, Metro timetable from Nexus, and the 450-zone system with centroid connectors. Provides the base network geometry to the Highway Assignment Engine, Network Coding Module, and Public Transport Skim Generator. All spatial data held in British National Grid (EPSG:27700). |
| Network Coding Module | 50F53108 | Converts GIS road network data into a microsimulation network model with coded link attributes (speed, capacity, lanes, gradient) and junction geometries. Imports signal timing plans from UTC/SCOOT data. Handles coding of the Tyne crossing options as alternative network scenarios. Key output: validated microsimulation network files for each option. |
| Network Data Repository | 40853318 | Stores and serves the coded highway and public transport network data for the New Tyne Crossing study area. Highway network covers approximately 3,000+ links across the Tyneside conurbation with attributes including free-flow speed, saturation flow capacity, number of lanes, gradient, link type (motorway/A-road/B-road/local), and junction coding (roundabout, signal, priority). Integrates OS MasterMap ITN and OS Open Roads for geometry. Public transport network includes Metro timetables from Nexus, bus routes and frequencies from BODS/GTFS feeds, and rail services from ATOC timetables. Serves network models to SATURN (strategic), Paramics/Vissim (microsimulation), and EMME/Cube (PT assignment) in their native formats. |
| New Tyne Crossing Transport Appraisal System | 40A53B59 | Integrated decision support system for evaluating options for a new crossing of the River Tyne in northeast England. Encompasses multi-modal transport demand modelling (variable demand with mode/route choice), traffic microsimulation of crossing corridors and junctions, WebTAG-compliant economic appraisal (BCR, NPV, AMCB), environmental impact assessment (air quality via DMRB LA 105, noise via LA 111, carbon, ecology), geospatial analysis (route option constraint mapping, flood risk, designated sites), and options appraisal with Appraisal Summary Table generation. Operates within DfT Transport Analysis Guidance framework, consuming census data, automatic traffic count data, origin-destination surveys, OS MasterMap, and planning datasets. Produces Strategic Outline Business Case, Outline Business Case, and Full Business Case documentation for HM Treasury Green Book compliance. Scale: regional transport model covering Tyne & Wear with microsimulation of 5-8 route option corridors. |
| Non-Technical Summary Generator | 40E47158 | Produces accessible summaries of transport appraisal findings for non-specialist audiences including elected members, public consultation respondents, and media briefings. Translates technical metrics (BCR, NPV, AADT, dB(A) LAeq) into plain-language statements with appropriate caveats. Generates scheme comparison infographics, key facts panels, and before/after visualisations. Produces statutory Non-Technical Summary for Environmental Impact Assessment per Town and Country Planning (EIA) Regulations 2017. Output formats include HTML for public consultation portals, PDF for printed materials, and accessible formats per WCAG 2.1 AA compliance. |
| Option Comparison Module | 40A43108 | Multi-criteria comparison engine for transport crossing options. Produces side-by-side AST comparisons, sifting matrices for early-stage option screening (typically 10-15 options reduced to 3-4), and detailed comparison tables for shortlisted options. Aggregates quantitative metrics (BCR, NPV, journey time savings, CO2 reductions) and qualitative assessments (landscape impact, heritage, community severance) into normalised scoring frameworks. Supports WebTAG seven-point scale assessments. Handles option variants including toll levels, lane configurations, and alignment alternatives. |
| Planning and Land Use Data Manager | 00243279 | Manages land use, development, and demographic forecast data for the New Tyne Crossing appraisal. Integrates NTEM v8.0 national trip end forecasts with TEMPro 8.0 local growth factors for the Tyneside area. Maintains a register of committed developments (planning applications with permission granted or allocated in local plans) including Gateshead Quays, Newcastle Helix, Riverside Sunderland, and housing allocations across North Tyneside, Gateshead, and Newcastle councils. Converts development quantum (dwellings, employment floorspace GFA by use class) into additional trip ends using TRICS-derived generation rates. Outputs zone-level adjustments to NTEM forecasts for opening year 2031, design year 2046, and horizon year 2061. |
| Present Value and Discounting Engine | 40A53B48 | Applies HM Treasury Green Book discounting to all monetary streams over the 60-year appraisal period. Uses 3.5% discount rate for years 0-30, 3.0% for years 31-75. Handles construction cost phasing across multiple years, applies WebTAG optimism bias uplifts to capital costs by project type, and interpolates benefit streams between forecast years. Converts all costs and benefits to a common price base year. Central calculation engine that all monetisation modules feed into before BCR computation. |
| Public Accounts Calculator | 40AC3348 | Computes the Public Accounts (PA) table per TAG Unit A1. Calculates government revenue impacts from indirect taxation changes (fuel duty, VAT on fuel) arising from traffic flow changes. Includes scheme capital costs (with optimism bias applied), operating and maintenance costs, and toll/charge revenue where applicable. Takes cost profiles from the scheme promoter and tax revenue changes derived from fuel consumption differences. Outputs present value of costs to government (PVC) for BCR computation. |
| Public Transport Skim Generator | 40A53308 | Module generating public transport generalised cost skims for the Tyneside study area. Models Tyne and Wear Metro, local bus routes (Go North East, Stagecoach, Arriva), and rail services (Northern, LNER, TransPennine). Captures in-vehicle time, wait time, interchange penalty, walk access/egress, and fare components per zone pair. Provides PT cost inputs to the mode choice model so that cross-river PT alternatives (Metro via Haymarket, bus via Tyne Bridge) compete realistically with car options via Tyne Tunnel and proposed new crossing. Uses GTFS feed data and Nexus published timetables. |
| Receptor Mapping Engine | 40A53159 | Identifies and geo-references sensitive receptors for environmental assessment of New Tyne Crossing options. Maps residential properties (from AddressBase Premium), schools, hospitals, care homes, ecological sites (SSSI, SPA, SAC, LWS), and heritage assets within buffer distances specified by DMRB methodology: 200m for air quality (LA 105), 600m for noise (LA 111), 2km for ecology (LA 108), 500m for landscape (LA 107). Outputs receptor point datasets with attributes including receptor type, sensitivity classification, and baseline environmental conditions. Feeds the Air Quality and Noise Modelling Engine and the Biodiversity and Water Environment Assessor. |
| Report Template Engine | 40A53958 | Document assembly engine for DfT TAG-compliant transport appraisal deliverables. Manages report structures for Option Assessment Reports (OAR), Strategic Outline Business Cases (SOBC), and Outline Business Cases (OBC). Pulls structured outputs from the Economic Appraisal Engine (TEE tables, PA tables, AST), Environmental Assessment Subsystem (EIA chapters), and Traffic Microsimulation Subsystem (junction performance summaries). Applies DfT corporate formatting standards, section numbering per TAG guidance, and embeds Mermaid/chart outputs. Produces Word/PDF documents up to 500 pages with cross-referenced appendices. |
| Results Extraction and Reporting Module | 40E73308 | Extracts microsimulation outputs (link flows, speeds, delays, queue lengths, journey times) from raw simulation data. Aggregates results per junction arm for each time period. Computes Level of Service metrics and RFC ratios. Produces formatted output tables and matrices compatible with the Economic Appraisal Engine input requirements. |
| Route and Catchment Analyser | 40E43309 | Performs network-based accessibility and catchment analysis for the New Tyne Crossing appraisal. Computes isochrone catchments (15, 30, 45, 60 minute drive/PT travel times) from key destinations (hospitals, employment centres, retail) for each crossing option to quantify accessibility changes. Calculates severance metrics by measuring pedestrian/cyclist detour factors for communities adjacent to each option corridor. Outputs accessibility change tables by zone and population group for input to the Distributional Impact Assessor, and severance scores for the Environmental Impact Assessment Module. Uses network data from the Network Data Repository and OpenRouteService for multi-modal routing. |
| Scenario Configuration Manager | 40A53B08 | Configuration module defining and managing appraisal scenarios for the New Tyne Crossing study. Stores the scenario matrix: do-minimum (no new crossing), and do-something options (tunnel, bridge, combined) crossed with forecast years (2031, 2046, 2061) and sensitivity tests (high/low growth, different toll levels). Each scenario specifies which network coding variant, demand growth factors, toll regime, and public transport assumptions apply. Produces scenario definition files consumed by the demand model, microsimulation, and economic appraisal to ensure consistent assumptions across all analytical subsystems. |
| Sensitivity and Uncertainty Reporter | 40E03108 | Generates sensitivity test result tables and switching value analysis for transport appraisal. Runs parameter sweeps across key assumptions: demand growth (+/-15%), construction cost (+20%/-10%), values of time (TAG central/low/high), discount rate (3.5%/3.0%), and toll levels. Computes switching values showing how much each parameter must change to alter the VfM category. Produces scenario comparison matrices, tornado diagrams, and risk-adjusted BCR distributions. Outputs TAG-formatted sensitivity tables for OBC/SOBC appendices. |
| Signal Controller Emulator | 40B57B08 | Emulates real-world traffic signal controllers within the microsimulation environment. Replicates UTC/SCOOT adaptive signal control logic for existing junctions and models proposed signal plans for new junctions near the crossing. Operates at sub-second resolution to accurately model green time allocation, stage sequencing, and intergreen periods. |
| Simulation Execution Manager | 41B73328 | Orchestrates batch runs of multiple microsimulation scenarios across option variants, time periods (AM/IP/PM), and random seeds. Manages parallel execution on multi-core infrastructure. Collects per-run outputs (journey times, delays, queues) and computes statistical summaries across seeds. Handles warm-up period management and convergence checking. |
| Socioeconomic Data Integrator | 40A51359 | Integrates census, deprivation, employment, and demographic datasets for distributional analysis and economic appraisal of the New Tyne Crossing. Ingests ONS Census 2021 data at LSOA/MSOA level including population by age, car ownership, economic activity, and method of travel to work. Imports Index of Multiple Deprivation 2019 ranks and scores for all LSOAs in the study area. Integrates BRES employment data by SIC sector and zone. Produces zone-level socioeconomic attribute tables used by the Distributional Impact Assessor for TAG A4.2 equity analysis, by the Wider Economic Impacts Module for agglomeration calculations, and by the Mode-Destination Choice Model for segmented demand modelling. |
| Spatial Overlay Processor | 40E53109 | Performs spatial intersection and constraint analysis for the New Tyne Crossing scheme options. Overlays each option corridor geometry with environmental designations (SSSI, SPA, SAC, Flood Zones, AQMA, Conservation Areas, Green Belt, ancient woodland), land ownership parcels, and existing infrastructure. Quantifies land-take by designation type and land use for each option. Computes proximity metrics between option alignments and sensitive receptors. Outputs constraint matrices showing which designations each option intersects and by what area, feeding the Environmental Impact Assessment Module and the Cost Data Manager (for land acquisition cost estimation). Uses QGIS Processing framework for geoprocessing operations. |
| Traffic Count Database | 40851358 | Centralised repository ingesting and validating traffic count data from 120+ permanent and temporary count sites across Tyneside. Sources include DfT road traffic statistics, Tyne and Wear automatic traffic counters (ATCs), manual classified counts (MCCs), and ANPR journey time surveys. Stores 15-minute interval directional classified counts (car, LGV, HGV, bus, cycle) with metadata on site location, count method, and data quality flags. Provides validated AADT, peak hour flows, and seasonal adjustment factors to the demand model calibration and microsimulation loading processes. Critical for matrix estimation: count accuracy directly propagates to assignment and economic appraisal reliability. |
| Traffic Microsimulation Subsystem | 40F53308 | Junction and corridor-level traffic microsimulation engine for the New Tyne Crossing appraisal. Models 5-8 route option corridors including crossing approaches, merge/diverge layouts, signalised junctions, and roundabouts. Uses Paramics or VISSIM-class simulation with car-following and lane-change models calibrated to local driver behaviour. Consumes turning count matrices from the demand model and signal timing plans from UTC/SCOOT. Produces queue lengths, journey times, delay, level of service, and saturation metrics per junction arm per time period (AM peak, interpeak, PM peak, weekend). Outputs visualisations of traffic flow for public consultation. Microsimulation results feed into economic appraisal (journey time reliability benefits) and environmental assessment (speed-emission profiles). |
| Traffic Survey Data Processor | 40A53358 | Ingests, validates, and structures raw traffic survey data for the New Tyne Crossing transport appraisal. Processes Automatic Traffic Count (ATC) data from ~120 permanent and temporary count sites across Tyneside, Manual Classified Count (MCC) data disaggregated by vehicle type (car/LGV/OGV1/OGV2/PSV/cycle), ANPR journey time survey data from ~30 camera pairs on key corridors (A19, A1058, A1, Tyne Tunnel approaches), and roadside interview/stated preference survey data. Applies DMRB-compliant factoring (seasonal, day-of-week, growth) to produce Annual Average Daily Traffic and peak hour flows. Outputs structured datasets in SATURN .dat and TUBA-compatible CSV formats for consumption by the Transport Demand Modelling and Traffic Microsimulation subsystems. |
| Transport Demand Modelling Subsystem | 40B53358 | Multi-modal transport demand forecasting engine for the New Tyne Crossing appraisal. Implements four-stage modelling (trip generation, distribution, mode choice, assignment) with variable demand feedback loops. Consumes NTEM/TEMPro growth forecasts, National Trip End Model outputs, Census journey-to-work data, and roadside interview OD matrices. Produces base year and forecast year (2031, 2046, 2061) demand matrices for highway and public transport networks across Tyne & Wear. Uses logit-based mode choice models calibrated to local revealed preference data. Operates within DfT TAG Unit M2 (variable demand modelling) framework. Key outputs feed directly into the economic appraisal (user time savings) and microsimulation (junction turning counts). |
| Transport User Benefit Calculator | 40E53358 | Computes the Transport Economic Efficiency (TEE) table per DfT TAG Unit A1. Takes do-minimum and do-something demand matrices and generalised cost skims from the variable demand model, plus journey time matrices from microsimulation. Calculates consumer surplus changes using the rule of half for each user class (car driver, car passenger, LGV, HGV, bus, rail) across three forecast years. Outputs time benefits, vehicle operating cost savings, and user charge changes in present value terms. Core economic benefit calculation — errors here directly corrupt the BCR. |
| Travel Survey Processor | 40A53318 | Processor for National Travel Survey and bespoke household travel survey data covering the North East region. Ingests NTS datasets, Tyne and Wear Household Interview Survey records, and roadside interview data collected at Tyne screenline points. Computes observed trip rates by purpose, mode, time period, and socio-economic segment. Produces trip length distributions, mode share matrices, and cross-river movement patterns used to calibrate the gravity model deterrence functions and mode choice model parameters. Handles sample expansion weighting and confidence interval estimation for survey-based statistics. |
| Trip Distribution Engine | 50B73308 | Computational engine implementing doubly-constrained gravity model for trip distribution across ~800 zones covering Tyneside and wider North East. Uses calibrated deterrence functions per trip purpose. Balances trip productions and attractions through iterative Furness procedure to convergence threshold of 0.1% residual. Produces full origin-destination trip matrices for each purpose, mode, and time period. Operates on generalised cost skims from highway and PT assignment. Critical for correctly distributing cross-river demand between Tyne Bridge, Tyne Tunnel, and proposed new crossing. |
| Trip End Forecasting Module | 40A53B58 | Software module implementing NTEM/TEMPro-based trip end forecasting for a strategic transport demand model covering Tyneside. Ingests National Trip End Model datasets, planning data (housing, employment projections from local authorities), and produces zonal trip productions and attractions by purpose (commute, business, other) and time period (AM peak, interpeak, PM peak). Applies DfT Uncertainty Log adjustments and local development assumptions. Outputs constrained trip ends for three forecast horizons: opening year (2031), design year (2046), and long-range (2061). Key constraints: must match NTEM v8.0 control totals at regional level while reflecting local planning authority growth allocations. |
| Vehicle Behaviour Engine | 41B73B09 | Implements car-following (Wiedemann 99), lane-changing, and gap-acceptance models for individual vehicles in the microsimulation. Handles multi-modal vehicle types: cars, HGVs, buses, cyclists, and pedestrians with distinct behavioural parameters. Calibrated to observed Tyne corridor speed-flow relationships and queue discharge headways. |
| Wider Economic Impacts Module | 40A43348 | Calculates Level 2 wider economic impacts per TAG Unit A2.1 for inclusion in the adjusted BCR. Implements agglomeration benefits (effective density changes from improved connectivity), output change in imperfectly competitive markets (10% uplift on business user benefits), and labour supply impacts (commuting cost changes affecting labour force participation). Takes zone-to-zone generalised cost changes and employment data. These impacts are additional to user benefits and only included in the adjusted BCR, not the initial BCR. |
| Component | Belongs To |
|---|---|
| Transport Demand Modelling Subsystem | New Tyne Crossing Transport Appraisal System |
| Traffic Microsimulation Subsystem | New Tyne Crossing Transport Appraisal System |
| Economic Appraisal Engine | New Tyne Crossing Transport Appraisal System |
| Environmental Assessment Subsystem | New Tyne Crossing Transport Appraisal System |
| Geospatial Analysis Platform | New Tyne Crossing Transport Appraisal System |
| Data Acquisition and Management Subsystem | New Tyne Crossing Transport Appraisal System |
| Appraisal Reporting Subsystem | New Tyne Crossing Transport Appraisal System |
| Network Coding Module | Traffic Microsimulation Subsystem |
| Signal Controller Emulator | Traffic Microsimulation Subsystem |
| Vehicle Behaviour Engine | Traffic Microsimulation Subsystem |
| Simulation Execution Manager | Traffic Microsimulation Subsystem |
| Results Extraction and Reporting Module | Traffic Microsimulation Subsystem |
| Trip End Forecasting Module | Transport Demand Modelling Subsystem |
| Trip Distribution Engine | Transport Demand Modelling Subsystem |
| Mode-Destination Choice Model | Transport Demand Modelling Subsystem |
| Highway Assignment Engine | Transport Demand Modelling Subsystem |
| Public Transport Skim Generator | Transport Demand Modelling Subsystem |
| Matrix Estimation Processor | Transport Demand Modelling Subsystem |
| Demand-Supply Convergence Controller | Transport Demand Modelling Subsystem |
| Transport User Benefit Calculator | Economic Appraisal Engine |
| Accident Cost-Benefit Module | Economic Appraisal Engine |
| Environmental Impact Monetisation Module | Economic Appraisal Engine |
| Greenhouse Gas Valuation Module | Economic Appraisal Engine |
| Public Accounts Calculator | Economic Appraisal Engine |
| Present Value and Discounting Engine | Economic Appraisal Engine |
| Wider Economic Impacts Module | Economic Appraisal Engine |
| BCR and AST Generator | Economic Appraisal Engine |
| Environmental Impact Assessment Module | Environmental Assessment Subsystem |
| Air Quality and Noise Modelling Engine | Environmental Assessment Subsystem |
| Greenhouse Gas Assessment Module | Environmental Assessment Subsystem |
| Biodiversity and Water Environment Assessor | Environmental Assessment Subsystem |
| Distributional Impact Assessor | Environmental Assessment Subsystem |
| Traffic Survey Data Processor | Data Acquisition and Management Subsystem |
| Planning and Land Use Data Manager | Data Acquisition and Management Subsystem |
| Network Data Repository | Data Acquisition and Management Subsystem |
| Cost Data Manager | Data Acquisition and Management Subsystem |
| Socioeconomic Data Integrator | Data Acquisition and Management Subsystem |
| External Data Feed Connector | Data Acquisition and Management Subsystem |
| Traffic Count Database | Data Acquisition and Management Subsystem |
| Travel Survey Processor | Data Acquisition and Management Subsystem |
| Land Use and Planning Data Manager | Data Acquisition and Management Subsystem |
| Network and GIS Data Repository | Data Acquisition and Management Subsystem |
| Data Validation and Quality Assurance Engine | Data Acquisition and Management Subsystem |
| Scenario Configuration Manager | Data Acquisition and Management Subsystem |
| GIS Data Repository | Geospatial Analysis Platform |
| Receptor Mapping Engine | Geospatial Analysis Platform |
| Route and Catchment Analyser | Geospatial Analysis Platform |
| Spatial Overlay Processor | Geospatial Analysis Platform |
| Map Rendering and Visualisation Module | Geospatial Analysis Platform |
| Report Template Engine | Appraisal Reporting Subsystem |
| Option Comparison Module | Appraisal Reporting Subsystem |
| Sensitivity and Uncertainty Reporter | Appraisal Reporting Subsystem |
| Audit Trail and Provenance Tracker | Appraisal Reporting Subsystem |
| Non-Technical Summary Generator | Appraisal Reporting Subsystem |
| From | To |
|---|---|
| Network Coding Module | Vehicle Behaviour Engine |
| Signal Controller Emulator | Vehicle Behaviour Engine |
| Results Extraction and Reporting Module | Economic Appraisal Engine |
| Trip End Forecasting Module | Trip Distribution Engine |
| Trip Distribution Engine | Matrix Estimation Processor |
| Matrix Estimation Processor | Highway Assignment Engine |
| Highway Assignment Engine | Mode-Destination Choice Model |
| Public Transport Skim Generator | Mode-Destination Choice Model |
| Mode-Destination Choice Model | Demand-Supply Convergence Controller |
| Demand-Supply Convergence Controller | Highway Assignment Engine |
| Highway Assignment Engine | Network Coding Module |
| Mode-Destination Choice Model | Economic Appraisal Engine |
| Transport User Benefit Calculator | Present Value and Discounting Engine |
| Accident Cost-Benefit Module | Present Value and Discounting Engine |
| Environmental Impact Monetisation Module | Present Value and Discounting Engine |
| Greenhouse Gas Valuation Module | Present Value and Discounting Engine |
| Public Accounts Calculator | Present Value and Discounting Engine |
| Wider Economic Impacts Module | Present Value and Discounting Engine |
| Present Value and Discounting Engine | BCR and AST Generator |
| Air Quality and Noise Modelling Engine | Environmental Impact Assessment Module |
| Greenhouse Gas Assessment Module | Environmental Impact Assessment Module |
| Biodiversity and Water Environment Assessor | Environmental Impact Assessment Module |
| Distributional Impact Assessor | Environmental Impact Assessment Module |
| External Data Feed Connector | Traffic Survey Data Processor |
| External Data Feed Connector | Planning and Land Use Data Manager |
| External Data Feed Connector | Network Data Repository |
| External Data Feed Connector | Cost Data Manager |
| External Data Feed Connector | Socioeconomic Data Integrator |
| Traffic Survey Data Processor | Network Data Repository |
| Traffic Count Database | Data Validation and Quality Assurance Engine |
| Travel Survey Processor | Data Validation and Quality Assurance Engine |
| Land Use and Planning Data Manager | Data Validation and Quality Assurance Engine |
| Network and GIS Data Repository | Data Validation and Quality Assurance Engine |
| Scenario Configuration Manager | Network and GIS Data Repository |
| Traffic Count Database | Matrix Estimation Processor |
| Travel Survey Processor | Trip End Forecasting Module |
| Land Use and Planning Data Manager | Trip End Forecasting Module |
| Network and GIS Data Repository | Highway Assignment Engine |
| Network and GIS Data Repository | Network Coding Module |
| Scenario Configuration Manager | Demand-Supply Convergence Controller |
| GIS Data Repository | Receptor Mapping Engine |
| GIS Data Repository | Route and Catchment Analyser |
| GIS Data Repository | Spatial Overlay Processor |
| Spatial Overlay Processor | Map Rendering and Visualisation Module |
| Receptor Mapping Engine | Air Quality and Noise Modelling Engine |
| Option Comparison Module | Report Template Engine |
| Sensitivity and Uncertainty Reporter | Report Template Engine |
| Audit Trail and Provenance Tracker | Report Template Engine |
| Non-Technical Summary Generator | Report Template Engine |
| BCR and AST Generator | Option Comparison Module |
| BCR and AST Generator | Report Template Engine |
| Environmental Impact Assessment Module | Report Template Engine |
| Results Extraction and Reporting Module | Report Template Engine |
| Map Rendering and Visualisation Module | Non-Technical Summary Generator |
| Scenario Configuration Manager | Sensitivity and Uncertainty Reporter |
| Component | Output |
|---|---|
| Network Coding Module | Microsimulation network model files |
| Vehicle Behaviour Engine | Individual vehicle trajectories and interactions |
| Results Extraction and Reporting Module | Junction performance matrices and journey time data |
| Trip End Forecasting Module | Zonal trip productions and attractions by purpose and time period |
| Trip Distribution Engine | Origin-destination prior trip matrices |
| Mode-Destination Choice Model | Mode-split demand matrices with elastic demand response |
| Highway Assignment Engine | Converged link flows, journey times, and generalised cost skims |
| Public Transport Skim Generator | PT generalised cost skims by zone pair |
| Matrix Estimation Processor | Calibrated base year OD matrices matching observed counts |
| Demand-Supply Convergence Controller | Converged demand-supply equilibrium state |
| Transport User Benefit Calculator | Undiscounted annual user benefit streams by user class, mode, and time period |
| Accident Cost-Benefit Module | Undiscounted annual accident cost savings by severity category |
| Environmental Impact Monetisation Module | Monetised noise and air quality impact values per receptor and aggregated AST rows |
| Greenhouse Gas Valuation Module | Monetised carbon costs over 60-year trajectory using BEIS carbon values |
| Public Accounts Calculator | Public Accounts table with government revenue impacts and net public sector cost |
| Present Value and Discounting Engine | Discounted present values for all benefit and cost streams over 60-year period |
| Wider Economic Impacts Module | Level 2 wider economic impacts including agglomeration and labour supply benefits |
| BCR and AST Generator | Initial and adjusted BCR values and complete Appraisal Summary Tables |
| Environmental Impact Assessment Module | Environmental Statement chapter assessments |
| Air Quality and Noise Modelling Engine | Receptor-level pollutant concentrations and noise levels |
| Greenhouse Gas Assessment Module | Lifecycle CO2e emissions and monetised carbon NPV |
| Traffic Survey Data Processor | Validated ATC, MCC, ANPR datasets with AADT and peak hour flows |
| Planning and Land Use Data Manager | Zone-level NTEM-adjusted trip end forecasts with local development adjustments |
| Network Data Repository | Coded highway and PT network models in SATURN, Vissim, and EMME formats |
| Cost Data Manager | Scheme cost tables with OB, risk, and lifecycle costs in current and discounted prices |
| Socioeconomic Data Integrator | Zone-level socioeconomic attribute tables for distributional and economic analysis |
| External Data Feed Connector | Versioned parameter datasets and external reference data with provenance audit trail |
| Traffic Count Database | Validated AADT, peak hour flows, seasonal adjustment factors, and classified turning counts at 120+ sites |
| Travel Survey Processor | Trip rates, trip length distributions, mode share matrices, and cross-river movement patterns by purpose and segment |
| Land Use and Planning Data Manager | Zonal population, employment, and household data with growth factors for 2031, 2046, and 2061 forecast years |
| Network and GIS Data Repository | Coded road network with attributes, PT network with timetables, zone system with centroid connectors in BNG |
| Data Validation and Quality Assurance Engine | Data quality reports with pass/fail flags per dataset and site, validated datasets cleared for modelling use |
| Scenario Configuration Manager | Scenario definition files specifying network variant, growth factors, toll regime, and PT assumptions per option |
| GIS Data Repository | OGC-compliant geospatial datasets in BNG projection |
| Receptor Mapping Engine | Geo-referenced receptor point datasets with sensitivity classifications |
| Route and Catchment Analyser | Accessibility isochrones and severance metrics by zone and option |
| Spatial Overlay Processor | Constraint matrices and land-take quantification by designation type |
| Map Rendering and Visualisation Module | Publication-quality scheme plans, thematic maps, and web map layers |
| Report Template Engine | TAG-compliant OAR, SOBC, and OBC documents with cross-referenced appendices in Word/PDF format |
| Option Comparison Module | Multi-criteria AST comparison tables, sifting matrices, and seven-point scale assessments across all crossing options |
| Sensitivity and Uncertainty Reporter | Sensitivity test tables, switching value analysis, tornado diagrams, and scenario comparison matrices |
| Audit Trail and Provenance Tracker | Analytical provenance records linking every published result to its input data, model version, and parameter set |
| Non-Technical Summary Generator | Accessible public consultation materials, statutory NTS for EIA, and elected member briefing documents in HTML, PDF, and WCAG 2.1 AA formats |
| Source | Target | Type | Description |
|---|---|---|---|
| SYS-REQS-001 | IFC-032 | derives | |
| SYS-REQS-001 | IFC-031 | derives | |
| SYS-REQS-001 | IFC-030 | derives | |
| SYS-REQS-007 | IFC-DEFS-029 | derives | |
| SYS-REQS-001 | IFC-DEFS-028 | derives | |
| SYS-REQS-013 | IFC-DEFS-027 | derives | |
| SYS-REQS-013 | IFC-DEFS-026 | derives | |
| SYS-REQS-013 | IFC-DEFS-025 | derives | |
| SYS-REQS-007 | IFC-DEFS-024 | derives | |
| SYS-REQS-011 | IFC-DEFS-023 | derives | |
| SYS-REQS-004 | IFC-DEFS-022 | derives | |
| SYS-REQS-003 | IFC-DEFS-021 | derives | |
| SYS-REQS-010 | IFC-DEFS-020 | derives | |
| SYS-REQS-002 | IFC-DEFS-019 | derives | |
| SYS-REQS-009 | IFC-DEFS-018 | derives | |
| SYS-REQS-010 | IFC-DEFS-017 | derives | |
| SYS-REQS-008 | IFC-DEFS-016 | derives | |
| SYS-REQS-001 | IFC-DEFS-015 | derives | |
| SYS-REQS-002 | IFC-DEFS-014 | derives | |
| SYS-REQS-009 | IFC-DEFS-013 | derives | |
| SYS-REQS-011 | IFC-DEFS-012 | derives | |
| SYS-REQS-011 | IFC-DEFS-011 | derives | |
| SYS-REQS-011 | IFC-DEFS-010 | derives | |
| SYS-REQS-001 | IFC-DEFS-009 | derives | |
| SYS-REQS-003 | IFC-DEFS-008 | derives | |
| SYS-REQS-002 | IFC-DEFS-007 | derives | |
| SYS-REQS-002 | IFC-DEFS-006 | derives | |
| SYS-REQS-002 | IFC-DEFS-005 | derives | |
| SYS-REQS-002 | IFC-DEFS-004 | derives | |
| SYS-REQS-001 | IFC-DEFS-003 | derives | |
| SYS-REQS-003 | IFC-DEFS-002 | derives | |
| SYS-REQS-003 | IFC-DEFS-001 | derives | |
| SYS-REQS-013 | SUB-REQS-042 | derives | |
| SYS-REQS-002 | SUB-REQS-029 | derives | |
| SYS-REQS-001 | SUB-EAE-050 | derives | |
| SYS-REQS-001 | SUB-EAE-058 | derives | |
| SYS-REQS-001 | SUB-EAE-057 | derives | |
| SYS-REQS-001 | SUB-EAE-056 | derives | |
| SYS-REQS-001 | SUB-EAE-055 | derives | |
| SYS-REQS-001 | SUB-EAE-054 | derives | |
| SYS-REQS-001 | SUB-EAE-053 | derives | |
| SYS-REQS-001 | SUB-EAE-051 | derives | |
| SYS-014 | SUB-EAE-052 | derives | |
| SYS-REQS-013 | SUB-REQS-049 | derives | |
| SYS-REQS-008 | SUB-REQS-048 | derives | |
| SYS-REQS-009 | SUB-REQS-047 | derives | |
| SYS-REQS-009 | SUB-REQS-046 | derives | |
| SYS-REQS-001 | SUB-REQS-045 | derives | |
| SYS-REQS-001 | SUB-REQS-044 | derives | |
| SYS-REQS-007 | SUB-REQS-043 | derives | |
| SYS-REQS-003 | SUB-REQS-001 | derives | |
| SYS-REQS-003 | SUB-REQS-002 | derives | |
| SYS-REQS-003 | SUB-REQS-003 | derives | |
| SYS-REQS-003 | SUB-REQS-004 | derives | |
| SYS-REQS-003 | SUB-REQS-005 | derives | |
| SYS-REQS-003 | SUB-REQS-006 | derives | |
| SYS-REQS-010 | SUB-REQS-007 | derives | |
| SYS-REQS-002 | SUB-REQS-008 | derives | |
| SYS-REQS-002 | SUB-REQS-009 | derives | |
| SYS-REQS-002 | SUB-REQS-010 | derives | |
| SYS-REQS-003 | SUB-REQS-010 | derives | |
| SYS-REQS-009 | SUB-REQS-011 | derives | |
| SYS-REQS-002 | SUB-REQS-012 | derives | |
| SYS-REQS-002 | SUB-REQS-013 | derives | |
| SYS-REQS-003 | SUB-REQS-014 | derives | |
| SYS-REQS-011 | SUB-REQS-015 | derives | |
| SYS-REQS-011 | SUB-REQS-016 | derives | |
| SYS-REQS-011 | SUB-REQS-017 | derives | |
| SYS-REQS-011 | SUB-REQS-018 | derives | |
| SYS-REQS-011 | SUB-REQS-019 | derives | |
| SYS-REQS-011 | SUB-REQS-020 | derives | |
| SYS-REQS-009 | SUB-REQS-021 | derives | |
| SYS-REQS-002 | SUB-REQS-022 | derives | |
| SYS-REQS-002 | SUB-REQS-023 | derives | |
| SYS-REQS-001 | SUB-REQS-024 | derives | |
| SYS-REQS-010 | SUB-REQS-025 | derives | |
| SYS-REQS-009 | SUB-REQS-026 | derives | |
| SYS-REQS-008 | SUB-REQS-027 | derives | |
| SYS-REQS-001 | SUB-REQS-028 | derives | |
| SYS-REQS-009 | SUB-REQS-032 | derives | |
| SYS-REQS-002 | SUB-REQS-032 | derives | |
| SYS-REQS-002 | SUB-REQS-033 | derives | |
| SYS-REQS-010 | SUB-REQS-034 | derives | |
| SYS-REQS-003 | SUB-REQS-035 | derives | |
| SYS-REQS-011 | SUB-REQS-035 | derives | |
| SYS-REQS-009 | SUB-REQS-036 | derives | |
| SYS-REQS-007 | SUB-REQS-037 | derives | |
| SYS-REQS-010 | SUB-REQS-037 | derives | |
| SYS-REQS-004 | SUB-REQS-038 | derives | |
| SYS-REQS-005 | SUB-REQS-038 | derives | |
| SYS-REQS-011 | SUB-REQS-039 | derives | |
| SYS-REQS-008 | SUB-REQS-040 | derives | |
| SYS-REQS-011 | SUB-REQS-041 | derives | |
| SYS-REQS-009 | SUB-REQS-029 | derives | |
| SYS-REQS-002 | SUB-REQS-030 | derives | |
| SYS-REQS-010 | SUB-REQS-031 | derives | |
| STK-009 | SYS-014 | derives | |
| STK-NEEDS-003 | SYS-REQS-013 | derives | |
| STK-NEEDS-001 | SYS-REQS-013 | derives | |
| STK-NEEDS-002 | SYS-REQS-012 | derives | |
| STK-NEEDS-008 | SYS-REQS-011 | derives | |
| STK-NEEDS-007 | SYS-REQS-010 | derives | |
| STK-NEEDS-006 | SYS-REQS-009 | derives | |
| STK-NEEDS-005 | SYS-REQS-008 | derives | |
| STK-NEEDS-003 | SYS-REQS-007 | derives | |
| STK-NEEDS-002 | SYS-REQS-006 | derives | |
| STK-NEEDS-002 | SYS-REQS-005 | derives | |
| STK-NEEDS-002 | SYS-REQS-004 | derives | |
| STK-NEEDS-001 | SYS-REQS-003 | derives | |
| STK-NEEDS-004 | SYS-REQS-002 | derives | |
| STK-NEEDS-001 | SYS-REQS-002 | derives | |
| STK-NEEDS-001 | SYS-REQS-001 | derives |
| Requirement | Verified By | Type | Description |
|---|---|---|---|
| IFC-DEFS-029 | VER-METHODS-036 | verifies | |
| IFC-DEFS-028 | VER-METHODS-035 | verifies | |
| IFC-DEFS-027 | VER-METHODS-034 | verifies | |
| IFC-DEFS-026 | VER-METHODS-033 | verifies | |
| IFC-DEFS-025 | VER-METHODS-032 | verifies | |
| IFC-DEFS-024 | VER-METHODS-031 | verifies | |
| IFC-DEFS-021 | VER-METHODS-023 | verifies | |
| IFC-DEFS-023 | VER-METHODS-021 | verifies | |
| IFC-DEFS-020 | VER-METHODS-022 | verifies | |
| IFC-DEFS-022 | VER-METHODS-019 | verifies | |
| IFC-DEFS-019 | VER-METHODS-020 | verifies | |
| IFC-DEFS-018 | VER-METHODS-018 | verifies | |
| IFC-DEFS-017 | VER-METHODS-017 | verifies | |
| IFC-DEFS-016 | VER-METHODS-016 | verifies | |
| IFC-DEFS-015 | VER-METHODS-015 | verifies | |
| IFC-DEFS-014 | VER-METHODS-014 | verifies | |
| IFC-DEFS-013 | VER-METHODS-013 | verifies | |
| IFC-DEFS-012 | VER-METHODS-012 | verifies | |
| IFC-DEFS-011 | VER-METHODS-011 | verifies | |
| IFC-DEFS-010 | VER-METHODS-010 | verifies | |
| IFC-DEFS-009 | VER-METHODS-009 | verifies | |
| IFC-DEFS-008 | VER-METHODS-008 | verifies | |
| IFC-DEFS-007 | VER-METHODS-007 | verifies | |
| IFC-DEFS-006 | VER-METHODS-006 | verifies | |
| IFC-DEFS-005 | VER-METHODS-005 | verifies | |
| IFC-DEFS-004 | VER-METHODS-004 | verifies | |
| IFC-DEFS-003 | VER-METHODS-003 | verifies | |
| IFC-DEFS-002 | VER-METHODS-002 | verifies | |
| IFC-DEFS-001 | VER-METHODS-001 | verifies | |
| SUB-EAE-050 | VER-040 | verifies | |
| SUB-EAE-058 | VER-042 | verifies | |
| SUB-EAE-052 | VER-041 | verifies | |
| SUB-EAE-051 | VER-040 | verifies | |
| SUB-REQS-005 | VER-039 | verifies | |
| SUB-REQS-002 | VER-038 | verifies | |
| SUB-REQS-001 | VER-037 | verifies | |
| SUB-REQS-024 | VER-METHODS-030 | verifies | |
| SUB-REQS-012 | VER-METHODS-029 | verifies | |
| SUB-REQS-004 | VER-METHODS-028 | verifies | |
| SUB-REQS-018 | VER-METHODS-027 | verifies | |
| SUB-REQS-016 | VER-METHODS-026 | verifies | |
| SUB-REQS-010 | VER-METHODS-025 | verifies | |
| SUB-REQS-003 | VER-METHODS-024 | verifies |
| Ref | Document | Requirement |
|---|---|---|
| IFC-DEFS-033 | interface-requirements | The interface between the Transport User Benefit Calculator and the Present Value and Discounting Engine SHALL transfer ... |
| IFC-DEFS-034 | interface-requirements | The interface between the Accident Cost-Benefit Module and the Present Value and Discounting Engine SHALL transfer undis... |
| IFC-DEFS-035 | interface-requirements | The interface between the Present Value and Discounting Engine and the BCR and AST Generator SHALL transfer the complete... |
| STK-NEEDS-010 | stakeholder-requirements | The Transport Appraisal System SHALL assess road safety impacts of each crossing option by quantifying changes in accide... |
| SUB-REQS-050 | subsystem-requirements | The Transport User Benefit Calculator SHALL compute the Transport Economic Efficiency (TEE) table per TAG Unit A1.1 for ... |
| SUB-REQS-052 | subsystem-requirements | The Accident Cost-Benefit Module SHALL calculate road safety benefits using the COBALT methodology per TAG Unit A4.1, co... |
| SUB-REQS-053 | subsystem-requirements | The Environmental Impact Monetisation Module SHALL convert physical environmental impacts into monetary values per TAG U... |
| SUB-REQS-054 | subsystem-requirements | The Greenhouse Gas Valuation Module SHALL monetise transport-related greenhouse gas emissions using BEIS traded and non-... |
| SUB-REQS-055 | subsystem-requirements | The Public Accounts Calculator SHALL compute the Public Accounts (PA) table per TAG Unit A1, calculating government reve... |
| SUB-REQS-056 | subsystem-requirements | The Wider Economic Impacts Module SHALL calculate Level 2 wider economic impacts per TAG Unit A2.1, including agglomerat... |
| SUB-REQS-057 | subsystem-requirements | The Present Value and Discounting Engine SHALL apply HM Treasury Green Book discounting to all monetary benefit and cost... |
| SUB-REQS-058 | subsystem-requirements | The BCR and AST Generator SHALL compute the initial BCR (present value of benefits divided by present value of costs to ... |
| SYS-REQS-015 | system-requirements | The Transport Appraisal System SHALL calculate the change in personal injury accidents by severity (fatal, serious, slig... |
| VER-METHODS-043 | verification-plan | Verify SUB-REQS-001: Select 20 representative road links within 2km of each crossing option spanning major roads, minor ... |
| VER-METHODS-044 | verification-plan | Verify SUB-REQS-002: Compare modelled green times against observed stage durations for 10 signalised junctions within th... |
| VER-METHODS-045 | verification-plan | Verify SUB-REQS-005: Execute a complete model run for one crossing option and extract OD journey time matrices and junct... |
| VER-METHODS-046 | verification-plan | Verify SUB-EAE-050: Run the Transport User Benefit Calculator for one crossing option with known do-minimum and do-somet... |
| VER-METHODS-047 | verification-plan | Verify SUB-EAE-052: Run COBALT analysis for one crossing option using published A19 corridor accident data. Compare mode... |
| VER-METHODS-048 | verification-plan | Verify SUB-EAE-058: Run the BCR and AST Generator for all crossing options using verified PV outputs. Confirm initial BC... |