Travel Mode Choices for Connecting Urban Rail Transit System During Irregular Time Periods: A Case Study in Beijing

The varying operating schedules of urban rail transit (URT) lines, combined with the distance between travelers’ origins and the URT stations, pose challenges for selecting their travel modes during irregular time periods such as early mornings and late evenings (EMLE). The choices during these special time periods may be influenced by personal attributes, travel attributes, environmental attributes, and psychological perceptions. We first conduct a questionnaire survey to explore travelers’ choice behaviors when they commute to or from URT stations, considering various influencing factors. After completing the statistical analysis, we then proceed with a preliminary assessment of the factors impacting travel mode preferences. Subsequently, a hybrid methodology that integrates structural equation modeling (SEM) and a random parameter logit model (RPLM) is introduced to investigate the impacts of factors. Notably, the interaction terms among travel time, cost, and psychological perception are considered as random variables. As a result, the heightened interaction between travel time and safety perception leads to a reduced probability of opting for walking or bike‐sharing as transportation modes. Similarly, there is a notable decrease in the probability of selecting a taxi when the interaction terms of travel cost and safety perception increase. The above results identify that travelers prefer to take safer and more convenient travel modes during the EMLE period.

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Publication Details

Journal
Journal of Advanced Transportation
Published
2025-01-01
DOI
https://doi.org/10.1155/atr/6691768
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Travel Mode Choices for Connecting Urban Rail Transit System During Irregular Time Periods: A Case Study in Beijing

Danni Cao, Songpo Yang, Haodong Yin, Jianjun Wu et al.
Journal of Advanced Transportation
Transportation Planning and Optimization
article

Travel Mode Choices for Connecting Urban Rail Transit System During Irregular Time Periods: A Case Study in Beijing

Danni Cao, Songpo Yang, Haodong Yin, Jianjun Wu, Yu Song
article en

Abstract

The varying operating schedules of urban rail transit (URT) lines, combined with the distance between travelers’ origins and the URT stations, pose challenges for selecting their travel modes during irregular time periods such as early mornings and late evenings (EMLE). The choices during these special time periods may be influenced by personal attributes, travel attributes, environmental attributes, and psychological perceptions. We first conduct a questionnaire survey to explore travelers’ choice behaviors when they commute to or from URT stations, considering various influencing factors. After completing the statistical analysis, we then proceed with a preliminary assessment of the factors impacting travel mode preferences. Subsequently, a hybrid methodology that integrates structural equation modeling (SEM) and a random parameter logit model (RPLM) is introduced to investigate the impacts of factors. Notably, the interaction terms among travel time, cost, and psychological perception are considered as random variables. As a result, the heightened interaction between travel time and safety perception leads to a reduced probability of opting for walking or bike‐sharing as transportation modes. Similarly, there is a notable decrease in the probability of selecting a taxi when the interaction terms of travel cost and safety perception increase. The above results identify that travelers prefer to take safer and more convenient travel modes during the EMLE period.

Journal of Advanced TransportationVol. 2025(1)
Beijing University of Posts and Telecommunications (CN), Beijing Jiaotong University (CN), Dalian University of Technology (CN), Beijing University of Technology (CN), Dalian University (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 88%
Transportation Planning and Optimization
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