Advertisement

Transportation

, 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
Article

Abstract

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.

Keywords

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

Notes

Acknowledgments

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.

References

  1. Agence métropolitaine de transport: Enquête origine-destination 2003. Montréal, QC (2003)Google Scholar
  2. Alshalalfah, B., Shalaby, A.: Case study: relationship of walk access distance to transit with service, travel, and personal characteristics. J. Urban Plan. Dev. 133(2), 114–118 (2007)CrossRefGoogle Scholar
  3. Daniels, R., Mulley, C.: Explaining walking distance to public transport: the dominance of public transport supply. J. Transp. Land Use 6(2), 5–20 (2013)CrossRefGoogle Scholar
  4. El-Geneidy, A., Strathman, J., Kimpel, T., Crout, D.: The effects of bus stop consolidation on passenger activity and transit operations. Transp. Res. Rec. 1971, 32–41 (2006)CrossRefGoogle Scholar
  5. Fan, W., Machemehi, R.: Do transit users just wait for buses or wit with strategies? Transp. Res. Rec. 2111, 169–176 (2009)CrossRefGoogle Scholar
  6. Fielding, G., Glauthier, R., Lave, C.: Performance indicators for transit management. Transportation 7, 365–379 (1978)CrossRefGoogle Scholar
  7. Fitzpatrick, K., Perkinson, D., Hall, K.: Findings from a survey on bus stop design. J. Public Transp. 1(3), 17–27 (1997)Google Scholar
  8. Furth, P., Rahbee, A.: Optimal bus stop spacing through dynamic programming and geographic modeling. Transp. Res. Rec. 1731, 15–22 (2000)CrossRefGoogle Scholar
  9. Gutiérrez, J., García-Palomares, J.C.: Distance-measure impacts on the calculation of transport service areas using GIS. Environ. Plan. B 35, 480–503 (2008)CrossRefGoogle Scholar
  10. Hall, R.: Passenger wait time and information acquisition using automatic vehicle location for verification. Transp. Plan. Technol. 24, 249–269 (2001)CrossRefGoogle Scholar
  11. Hsiao, S., Lu, J., Sterling, J., Weatherford, M.: Use of geographic information system for analysis of transit pedestrian access. Transp. Res. Rec. 1604, 50–59 (1997)CrossRefGoogle Scholar
  12. Kimpel, T., Dueker, K., El-Geneidy, A.: Using GIS to measure the effect of overlapping service areas on passenger boardings at bus stops. Urban Region. Inf. Syst. Assoc. J. 19(1), 5–11 (2007)Google Scholar
  13. Kuby, M., Barranda, A., Upchurch, C.: Factors influencing light rail station boardings in the United States. Transp. Res. Part A 38, 223–247 (2004)Google Scholar
  14. Lam, W., Morrall, J.: Bus passenger walking distances and waiting times: a summer-winter comparison. Transp. Quart. 36(3), 407–421 (1982)Google Scholar
  15. Levinson, H., Brown-West, O.: Estimating bus ridership. Transp. Res. Rec. 994, 8–12 (1984)Google Scholar
  16. Loutzenheiser, D.: Pedestrian access to transit: modeling of walk trips and theor design and urban form determination around bay area rapid transit stations. Transp. Res. Rec. 1604, 40–49 (1997)CrossRefGoogle Scholar
  17. Murray, A., Davis, R., Stimson, R., Ferreira, L.: Public transportation access. Transp. Res. Part D 3(5), 319–328 (1998)CrossRefGoogle Scholar
  18. Murray, A., Wu, X.: Accessibility tradeoffs in public transit planning. J. Geogr. Syst. 5(1), 93–107 (2003)CrossRefGoogle Scholar
  19. Neilson, G., Fowler, W.: Relation between transit ridership and walking distances in a low-density Florida retirement area. Highway Res. Rec. 403, 26–34 (1972)Google Scholar
  20. O’Neill, W., Ramsey, D., Chou, J.: Analysis of transit service areas using geographic information systems. Transp. Res. Rec. 1364, 131–139 (1992)Google Scholar
  21. O’Sullivan, S., Morrall, J.: Walking distance to and from light-rail transit stations. Transp. Res. Rec. 1538, 19–26 (1996)CrossRefGoogle Scholar
  22. Schlossberg, M., Agrawal, A., Irvin, K., Bekkouche, V.: How far, by which route, and why? A spatial analysis of pedestrian preference MTI Report 06-06. Mineta Transportation Institute & College of Business, San José State University, San José (2007)Google Scholar
  23. Upchurch, C., Kuby, M., Zoldak, M., Barranda, A.: Using GIS to generate mutually exclusive service areas linking travel on and off a network. J. Transp. Geogr. 12, 23–33 (2004)CrossRefGoogle Scholar
  24. Zhao, F., Chow, L., Li, M., Ubaka, I., Gan, A.: Forecasting transit walk accessibility: regression model alternative to buffer. Transp. Res. Rec. 1835, 34–41 (2003)CrossRefGoogle Scholar

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

Personalised recommendations