Transforming Strategic Active Travel Network Planning Internationally

Impact Case Study Report for REF 2029

Author

Robin Lovelace and Team

Published

September 3, 2026

1 Summary of Impact

The Propensity to Cycle Tool (PCT) has become a foundational piece of evidence for active travel network planning and capital investment across the United Kingdom. A comprehensive 2026 re-run and funding linkage analysis of English Local Cycling and Walking Infrastructure Plans (LCWIPs) and related active-travel strategies demonstrates that:

  1. 91% of analysed transport authority regions explicitly embed the PCT in their strategic active travel planning, citing the tool an average of 12 times per strategy document.
  2. 95% of assessed authorities demonstrate substantive use (scoring \(\ge 2\) on depth of application), employing the tool directly for corridor design, desire line validation, and route prioritisation rather than cursory citation.
  3. 93% of historical Active Travel Fund (ATF) investment (2020/21–2024/25) and 95% of future multi-year allocations (2026–2030) flow to local authorities whose planning frameworks embed the PCT.
  4. Authorities adopting the PCT received an average of £9.4m in historical funding (vs £4.5m for non-adopting authorities) and £9.2m in future allocations (vs £3.5m for non-adopting authorities).

This evidence demonstrates that open-source, reproducible planning tools developed at the University of Leeds have become an indispensable standard shaping transport policy and guiding hundreds of millions of pounds in active-travel infrastructure investment.

2 Underpinning Research

The Propensity to Cycle Tool (PCT) for England and Wales has continued to be the main tool for cycle network planning in England and Wales, but has limitations that we have addressed in subsequent work:

  • To tackle the issue that networks generated by the PCT were too sparse due to using population-weighted centroids as origin and destination points, we developed a new spatial method called ‘jittering’ (Lovelace et al. 2022).
  • The original PCT focused on commuting and travel-to-school trips; to support all trip purposes, we developed simulation methods for social, leisure, and shopping trips incorporated into the CRUSE tool across the Republic of Ireland (Lovelace et al. 2024).
  • To address multi-modal journeys involving public transport, we collaborated with colleagues at the University of Lisbon to calculate cycling potential to transit hubs in the biclaR platform (Félix et al. 2025).

3 References to the Research

Félix, Rosa, Filipe Moura, and Robin Lovelace. 2025. “Reproducible Methods for Modeling Combined Public Transport and Cycling Trips and Associated Benefits: Evidence from the biclaR Tool.” Computers, Environment and Urban Systems 117 (April): 102230. https://doi.org/10.1016/j.compenvurbsys.2024.102230.
Lovelace, Robin, Rosa Félix, and Dustin Carlino. 2022. “Jittering: A Computationally Efficient Method for Generating Realistic Route Networks from Origin-Destination Data.” Findings, April 8, 33873. https://doi.org/10.32866/001c.33873.
Lovelace, Robin, Joey Talbot, Eugeni Vidal-Tortosa, et al. 2024. “Cycle Route Uptake and Scenario Estimation (CRUSE): An Approach for Developing Strategic Cycle Network Planning Tools.” European Transport Research Review 16 (1): 55. https://doi.org/10.1186/s12544-024-00668-8.

4 Details of Engagement

Engagement for this project spans desk-based research, practitioner surveys, stakeholder interviews, and an automated, reproducible evidence-ingest pipeline:

  • Stakeholder Identification and Scoping: A typology of key stakeholders was established across local transport authorities, combined authorities, national government bodies (DfT, Active Travel England), and advocacy organisations.
  • Survey Development and Feedback: Online survey questionnaires and interview protocols were piloted with practitioners to capture qualitative feedback on tool usability and impact on planning decisions.
  • Automated Systematic Review of Planning Documents: A reproducible data-ingest pipeline was executed in 2026, downloading strategy documents and extracting a 21-field schema with an open local LLM (gemma4-12b-hermes via Ollama) without external API dependencies.
  • Data Integration with Funding Allocations: Extracted records were matched against higher-tier transport authority boundaries (uktransportauthorities) and official DfT Active Travel Fund (ATF) historical and future multi-year allocations, enabling spatial and financial impact assessment.

5 Details of the Impact

The evidence base provides quantifiable verification of the PCT’s widespread impact on policy, infrastructure design, and capital investment.

5.1 Pervasive National Adoption

Analysis of published LCWIPs confirms that 91% of analysed transport authorities in England use the PCT as a core analytical foundation [1]. Reports from major regional bodies—such as the Liverpool City Region Combined Authority [2] and Oxfordshire County Council for Kidlington [3]—demonstrate that the PCT is routinely used to map desire lines, evaluate future scenarios (e.g. ‘Go Dutch’ and ‘Government Target’), and justify capital investment bids.

5.2 Shaping Network Design and Route Prioritisation

The PCT directly influences the physical design of proposed cycling networks:

  • Corridor Selection: In Portsmouth City Council’s LCWIP Background Report, the PCT’s ‘Government Target’ scenario was used to identify highest forecast future commuter flows, directly determining the primary cycle routes [4].
  • Validating Desire Lines: In Cumberland and Westmorland & Furness (formerly Cumbria County Council) reports for Carlisle [5] and Workington [6], ‘Go Dutch’ scenario outputs validated the strategic desire lines forming the backbone of the proposed network.
  • Prioritisation Matrices: In Durham County Council’s LCWIP for Shildon, PCT demand scores were directly incorporated into the multi-criteria prioritisation matrix, directly determining which schemes received delivery funding [7].

5.3 Geographic Distribution of Depth of Use

The interactive map below illustrates the depth of PCT adoption across all 74 Local Transport Authorities in England. Hover over any authority boundary to inspect its classification, document count, mention count, and Active Travel Fund (ATF) historical and future allocations.

6 Sources to Corroborate the Impact

[1] Research Project Repository and Data Pipeline: https://github.com/itsleeds/ics (see also the 2026 Ingest & Funding Analysis technical report)

[2] Liverpool City Region Combined Authority LCWIP: https://api.liverpoolcityregion-ca.gov.uk/wp-content/uploads/2023/09/LCR-LCWIP-Final.pdf

[3] Oxfordshire County Council Kidlington LCWIP: https://www.oxfordshire.gov.uk/sites/default/files/file/roads-and-transport-major-projects/Kidlington_LCWIP.pdf

[4] Portsmouth City Council LCWIP Background Report: https://travel.portsmouth.gov.uk/wp-content/uploads/2020/08/Background-Report.pdf

[5] Cumberland Council Carlisle LCWIP Technical Report: https://www.cumberland.gov.uk/sites/default/files/2025-04/carlisle_lcwip_technical_report.pdf

[6] Westmorland and Furness Council Workington LCWIP Report: https://legacy.westmorlandandfurness.gov.uk/elibrary/Content/Internet/538/18110/38384/4481911413.pdf

[7] Durham County Council Shildon LCWIP Report: https://democracy.durham.gov.uk/documents/s174868/Item%207%20Shildon%20LCWIP%20Final%20inc%20Appendices_opt.pdf

[8] DfT Active Travel Local Transport Authority Allocations: https://www.gov.uk/government/publications/active-travel-local-transport-authority-allocations/active-travel-local-transport-authority-allocations

[9] Active Travel England Capability Ratings 2025: https://assets.publishing.service.gov.uk/media/6939a16933c7ace9c4a41f8b/local-authority-active-travel-capability-ratings-2025.pdf