Using spatial network analysis to model pedal cycle flows, risk and mode choice. (January 2017)

• Record Type: Journal Article
• Authors: Cooper, Crispin H.V.
• Is Part Of: Journal of transport geography. Volume 58(2017)
• Page Start: 157
• Page End: 165
• Publication Date: 2017-01
• Subjects: Spatial network analysis -- Cycling -- Modelling -- Gis; Transportation -- Periodicals; Telecommunication -- Periodicals; Transport -- Périodiques; Télécommunications -- Périodiques; Telecommunication; Transportation; Periodicals; 388
• DOI: 10.1016/j.jtrangeo.2016.12.003
• Languages: English
• ISSNs: 0966-6923

Abstract

Abstract: Spatial network analysis (SpNA) provides a promising alternative to traditional transport models for the modelling of active travel, because walking and cycling behaviour is influenced by features smaller than the scale of zones in a traditional model. There is currently a need for link-level, city wide modelling of cycling, both to ensure the needs of existing cyclists are catered for in planning, and to model the effects of changing infrastructure in shaping cyclist behaviour. Existing SpNA models treat cyclists and car drivers as if they make navigational decisions in a similar way, which in reality is not the case. This paper presents an SpNA model using hybrid betweenness, which fits cyclist flows in Cardiff, Wales using distance, angular distance, motor vehicle traffic and slope as predictors of route choice. SpNA betweenness is also shown to implicitly capture the effect of urban density on mode choice. As it handles route finding decisions of drivers and cyclists separately, the model presented is also applicable to road safety models examining the interaction between the two classes of road user. The model has low cost of data collection and is reproducible using publicly available network analysis software and open mapping data. Further avenues for modelling the effect of infrastructure on cycling are discussed. Graphical abstract: Highlights: Link level, city wide modelling of cyclist flows with spatial network analysis Motor vehicle flows simulated first to inform cyclist model Cycle model based on distance, motor traffic, slope, turns Methodology bridges gap between spatial network analysis and transport modelling