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Modeling park-and-ride location choice of heterogeneous commuters

Author

Listed:
  • Hao Pang

    (University of Texas at Austin)

  • Alireza Khani

    (University of Minnesota)

Abstract

There is extensive literature on drive-to-transit trips, yet very few studies focus on commuters’ park-and-ride location choice decisions. This study investigates park-and-ride location choice behavior of heterogeneous commuters in the Austin Metropolitan Statistical Area. Data from a transit on-board survey conducted by Capital Metro in 2010 were used. Besides, schedule-based transit networks and a detailed regional highway network were used to calculate path attributes. A thorough analysis on the choice set generation was conducted, and two criteria were used to determine the most appropriate park-and-ride choice set for each observed trip. Finally, user heterogeneity was accounted by adding interaction terms in the utility functions and by using mixed logit models. Empirical models reveal that designation of a park-and-ride facility by transit agency and the frequency of transit paths to destination have the highest positive effect, while transit transfers, auto travel time, and walking time have the most significant negative impact on the utility of a park-and-ride location. More specifically, correlation analysis reveals that travelers who are more likely to be motivated by short auto travel time are also more likely to be motivated by few transfers and short walking time. In addition, this study implies that non-Caucasians prefer higher fraction of their auto path on freeways; and commuters with higher income are less motivated by high transit service frequency. The estimated models in this study can have immediate application in travel forecasting, specifically for drive-to-transit trip assignment, as well as in setting policy for park-and-rides service design.

Suggested Citation

  • Hao Pang & Alireza Khani, 2018. "Modeling park-and-ride location choice of heterogeneous commuters," Transportation, Springer, vol. 45(1), pages 71-87, January.
  • Handle: RePEc:kap:transp:v:45:y:2018:i:1:d:10.1007_s11116-016-9723-5
    DOI: 10.1007/s11116-016-9723-5
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    References listed on IDEAS

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    Cited by:

    1. Jairo Ortega & János Tóth & Tamás Péter & Sarbast Moslem, 2020. "An Integrated Model of Park-And-Ride Facilities for Sustainable Urban Mobility," Sustainability, MDPI, vol. 12(11), pages 1-15, June.
    2. Pramesh Kumar & Alireza Khani, 2021. "Adaptive Park-and-ride Choice on Time-dependent Stochastic Multimodal Transportation Network," Networks and Spatial Economics, Springer, vol. 21(4), pages 771-800, December.
    3. Xinyuan Chen & Ruyang Yin & Qinhe An & Yuan Zhang, 2021. "Modeling a Distance-Based Preferential Fare Scheme for Park-and-Ride Services in a Multimodal Transport Network," Sustainability, MDPI, vol. 13(5), pages 1-14, March.
    4. Songyot Kitthamkesorn & Anthony Chen & Sathaporn Opasanon & Suwicha Jaita, 2021. "A P-Hub Location Problem for Determining Park-and-Ride Facility Locations with the Weibit-Based Choice Model," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    5. Kimpton, Anthony & Pojani, Dorina & Sipe, Neil & Corcoran, Jonathan, 2020. "Parking Behavior: Park ‘n’ Ride (PnR) to encourage multimodalism in Brisbane," Land Use Policy, Elsevier, vol. 91(C).
    6. Zhao, Xinwei & Chen, Peng & Jiao, Junfeng & Chen, Xiaohong & Bischak, Chris, 2019. "How does ‘park and ride’ perform? An evaluation using longitudinal data," Transport Policy, Elsevier, vol. 74(C), pages 15-23.
    7. Kitthamkesorn, Songyot & Chen, Anthony & Ryu, Seungkyu & Opasanon, Sathaporn, 2024. "Maximum capture problem based on paired combinatorial weibit model to determine park-and-ride facility locations," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).

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