European Transport Research Review (Sep 2024)

Cycle route uptake and scenario estimation (CRUSE): an approach for developing strategic cycle network planning tools

  • Robin Lovelace,
  • Joey Talbot,
  • Eugeni Vidal-Tortosa,
  • Hussein Mahfouz,
  • Elaine Brick,
  • Peter Wright,
  • Gary O’Toole,
  • Dan Brennan,
  • Suzanne Meade

DOI
https://doi.org/10.1186/s12544-024-00668-8
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 17

Abstract

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Abstract This paper describes an approach for developing strategic cycle network planning tools. Based on our experience developing and deploying the Cycle Route Uptake and Scenario Estimation (CRUSE) Tool for Ireland, we outline the underlying methods, including disaggregation of origin–destination data with the open source ‘odjitter’ software, incorporation of additional trip purposes, routing, scenario generation, and development of an intuitive user interface that is tested and used by practitioners. Commissioned by the national infrastructure agency Transport Infrastructure Ireland, CRUSE provides estimates of current and potential future cycling levels under ‘snapshot’ scenarios to inform investment decisions. The publicly available results at https://cruse.bike/ enable planners, engineers, and other stakeholders to make more evidence-based decisions. CRUSE goes beyond previous work by: modeling networks at high spatial resolution; simulating multiple trip purposes (social, shopping, personal utility, recreational, and cycle touring), supplementing official origin–destination datasets on travel for work and education; and providing estimates of ‘quietness’ (a proxy for cyclist comfort and route preference) at the route segment level. Three network types—‘Fastest’, ‘Balanced’, and ‘Quietest’—help plan both arterial and residential cycle networks. Workshops with stakeholders were used to inform the development of the tool. Feedback shows that the tool has a wide range of uses and is already being used in practice to inform urban, inter-urban, and rural cycle network designs. The approach is flexible and open source, allowing the underlying ideas and code to be adapted, supporting more evidence-based and effective cycling policies and interventions internationally.

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