Modelling cyclists’ route choice using Strava and OSMnx: A case study of the City of Glasgow

Previous research has demonstrated the influence of street layout on travel behaviour; however, little research has been undertaken to explore these connections using detailed and robust street network analysis or cycling data. In this study, the authors harness state-of-the-art datasets to model cyclists’ route choice based on a case study of the City of Glasgow, Scotland. First, the social fitness network Strava was used to obtain datasets containing the number of cycling trips on each street intersection for the years 2017 and 2018. Second, the authors employed a Python toolkit to acquire and analyse the street networks. OSMnx was subsequently employed to quantify several commonly used centrality indices (degree, eigenvector, betweenness and closeness) to measure street layout. Due to the presence of spatial dependence, a spatial error model was used to model route choices. Model results demonstrate that: (1) cyclists’ movement models were consistent for the years 2017 and 2018; (2) the presence of a spillover effect suggests that cyclists tend to cycle in proximity to each other; and (3) cyclists avoid streets with high degree centrality values and prefer streets with high eigenvector centrality, betweenness centrality and closeness centrality. These findings reveal cyclists’ desired street layouts and can be taken into consideration for future interventions.

• Record URL:
  • https://doi.org/10.1016/j.trip.2021.100301
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2590198221000051
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/25901982
• Supplemental Notes:
  • © 2021 Mohammad Anwar Alattar et al. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Alattar, Mohammad Anwar
  • Cottrill, Caitlin
  • 0000-0002-1638-8113
  • Beecroft, Mark
• Publication Date: 2021-3

Language

• English

Media Info

• Media Type: Web
• Features: Figures; Maps; References; Tables;
• Serial:
  • Transportation Research Interdisciplinary Perspectives
  • Volume: 9
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2590-1982
  • Serial URL: https://www.journals.elsevier.com/transportation-research-interdisciplinary-perspectives
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Case studies; Computer models; Cyclists; Geographic information systems; Route choice; Spatial analysis; Streets
• Geographic Terms: Glasgow (Scotland)
• Subject Areas: Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting;

Filing Info

• Accession Number: 01767671
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 23 2021 11:13AM