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Where do cyclists ride? A route choice model developed with revealed preference GPS data

Author

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  • Broach, Joseph
  • Dill, Jennifer
  • Gliebe, John

Abstract

To better understand bicyclists’ preferences for facility types, GPS units were used to observe the behavior of 164 cyclists in Portland, Oregon, USA for several days each. Trip purpose and several other trip-level variables recorded by the cyclists, and the resulting trips were coded to a highly detailed bicycle network. The authors used the 1449 non-exercise, utilitarian trips to estimate a bicycle route choice model. The model used a choice set generation algorithm based on multiple permutations of path attributes and was formulated to account for overlapping route alternatives. The findings suggest that cyclists are sensitive to the effects of distance, turn frequency, slope, intersection control (e.g. presence or absence of traffic signals), and traffic volumes. In addition, cyclists appear to place relatively high value on off-street bike paths, enhanced neighborhood bikeways with traffic calming features (aka “bicycle boulevards”), and bridge facilities. Bike lanes more or less exactly offset the negative effects of adjacent traffic, but were no more or less attractive than a basic low traffic volume street. Finally, route preferences differ between commute and other utilitarian trips; cyclists were more sensitive to distance and less sensitive to other infrastructure characteristics for commute trips.

Suggested Citation

  • Broach, Joseph & Dill, Jennifer & Gliebe, John, 2012. "Where do cyclists ride? A route choice model developed with revealed preference GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1730-1740.
  • Handle: RePEc:eee:transa:v:46:y:2012:i:10:p:1730-1740
    DOI: 10.1016/j.tra.2012.07.005
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Bagloee, Saeed Asadi & Sarvi, Majid & Wallace, Mark, 2016. "Bicycle lane priority: Promoting bicycle as a green mode even in congested urban area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 87(C), pages 102-121.
    2. repec:eee:transa:v:100:y:2017:i:c:p:53-64 is not listed on IDEAS
    3. Peer, Stefanie & Knockaert, Jasper & Verhoef, Erik T., 2016. "Train commuters’ scheduling preferences: Evidence from a large-scale peak avoidance experiment," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 314-333.
    4. repec:kap:transp:v:44:y:2017:i:4:d:10.1007_s11116-016-9682-x is not listed on IDEAS
    5. repec:eee:transa:v:101:y:2017:i:c:p:30-50 is not listed on IDEAS
    6. Sanders, Rebecca L., 2016. "We can all get along: The alignment of driver and bicyclist roadway design preferences in the San Francisco Bay Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 120-133.
    7. Wang, Jenhung & Tsai, Ching-Hui & Lin, Pei-Chun, 2016. "Applying spatial-temporal analysis and retail location theory to public bikes site selection in Taipei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 45-61.
    8. repec:eee:transa:v:101:y:2017:i:c:p:252-263 is not listed on IDEAS
    9. Felipe González & Carlos Melo-Riquelme & Louis Grange, 2016. "A combined destination and route choice model for a bicycle sharing system," Transportation, Springer, vol. 43(3), pages 407-423, May.
    10. repec:eee:transa:v:105:y:2017:i:c:p:66-78 is not listed on IDEAS
    11. Lowry, Michael B. & Furth, Peter & Hadden-Loh, Tracy, 2016. "Prioritizing new bicycle facilities to improve low-stress network connectivity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 124-140.
    12. Damant-Sirois, Gabriel & El-Geneidy, Ahmed M., 2015. "Who cycles more? Determining cycling frequency through a segmentation approach in Montreal, Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 113-125.
    13. Jan-Dirk Schmöcker & Tsuyoshi Hatori & David Watling, 2014. "Dynamic process model of mass effects on travel demand," Transportation, Springer, vol. 41(2), pages 279-304, March.
    14. Bhat, Chandra R. & Dubey, Subodh K. & Nagel, Kai, 2015. "Introducing non-normality of latent psychological constructs in choice modeling with an application to bicyclist route choice," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 341-363.
    15. Minaei, Negin, 2014. "Do modes of transportation and GPS affect cognitive maps of Londoners?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 162-180.
    16. Sanders, Rebecca L, 2013. "Examining the Cycle: How Perceived and Actual Bicycling Risk Influence Cylcing Frequency, Roadway Design Preferences, and Support for Cycling Among Bay Area Residents," University of California Transportation Center, Working Papers qt1tf5v738, University of California Transportation Center.
    17. Duarte, Fábio & Procopiuck, Mario & Fujioka, Kelli, 2014. "‘No bicycle lanes!’ Shouted the cyclists. A controversial bicycle project in Curitiba, Brazil," Transport Policy, Elsevier, vol. 32(C), pages 180-185.
    18. repec:eee:trapol:v:57:y:2017:i:c:p:79-89 is not listed on IDEAS
    19. Sanders, Rebecca Lauren, 2013. "Examining the Cycle: How Perceived and Actual Bicycling Risk Influence Cycling Frequency, Roadway Design Preferences, and Support for Cycling Among Bay Area Residents," University of California Transportation Center, Working Papers qt6ct7x8hp, University of California Transportation Center.

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