, Volume 41, Issue 1, pp 193–210 | Cite as

New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas

  • Ahmed El-Geneidy
  • Michael Grimsrud
  • Rania Wasfi
  • Paul Tétreault
  • Julien Surprenant-Legault


The percentage of the population being served by a transit system in a metropolitan region is a key system performance measure but depends heavily on the definition of service area. Observing existing service areas can help identify transit system gaps and redundancies. In the public transit industry, buffers at 400 m (0.25 miles) around bus stops and 800 m (0.5 miles) around rail stations are commonly used to identify the area from which most transit users will access the system by foot. This study uses detailed OD survey information to generate service areas that define walking catchment areas around transit services in Montreal, Canada. The 85th percentile walking distance to bus transit service is found to be around 524 m for home-based trip origins, 1,259 m for home-based commuter rail trip origins. Yet these values are found to vary based on our analysis using two statistical models. Walking distances vary based on route and trip qualities (such as type of transit service, transfers and wait time), as well as personal, household, and neighbourhood characteristics. Accordingly, service areas around transit stations should vary based on the service offered and attributes of the people and places served. The generated service areas derived from the generalized statistical model are then used to identify gaps and redundancies at the system and route level using Montreal region as an example. This study can be of benefit to transport engineers and planners trying to maximize transit service coverage in a region while avoiding oversupply of service.


Walking distance Transit stops Service area Accessibility to transit Redundancy in transit service Gaps in transit service 



This research was partially funded by the Agence métropolitaine de transport (AMT) and Natural Sciences and Engineering Research Council of Canada (NSERC). We would like to thank Ludwig Desjardins of the AMT and his research team for their support and feedback throughout the project. We wish to acknowledge Mr. Daniel Bergeron and Alfred Ka Kee Chu of the AMT for providing the detailed Montréal OD survey used in the analysis as well as the transit network. We would also like to thank Ehab Diab for his help with the final figures. Last but not least we would like to thank David Hartgen, US Co-Editor of Transportation and the five anonymous reviewers for their comments on the earlier version of the manuscript.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Ahmed El-Geneidy
    • 1
  • Michael Grimsrud
    • 2
  • Rania Wasfi
    • 3
  • Paul Tétreault
    • 4
  • Julien Surprenant-Legault
    • 5
  1. 1.School of Urban PlanningMcGill UniversityMontrealCanada
  2. 2.Transportation Research at McGillMcGill UniversityMontrealCanada
  3. 3.Department of GeographyMcGill UniversityMontrealCanada
  4. 4.GENIVARMontrealCanada
  5. 5.McGill UniversityMontrealCanada

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