Modeling park-and-ride location choice of heterogeneous commuters

Hao Pang, Alireza Khani

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)71-87
Number of pages17
JournalTransportation
Volume45
Issue number1
DOIs
StatePublished - Jan 1 2018

Keywords

  • Mixed logit model
  • On-board transit survey
  • Park-and-ride location choice
  • Schedule-based transit network
  • User heterogeneity

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