Mode Choice between Bus and Bike-Sharing for the Last-Mile Connection to Urban Rail Transit
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 5
Abstract
Previous studies show that the popularity of bike-sharing systems has a significant impact on public transit ridership, mainly reflected in two aspects: substitution and supplement. However, a mode choice of the users between bike-sharing and bus for the last-mile connection to urban rails has not been sufficiently studied using actual traffic sensor data. Therefore, in this study, the binomial choice behavior between bike-sharing and buses as a last-mile connection to urban rails in Beijing, China, is analyzed and modeled using the feeder subchain information of bus and bike-sharing for 1 week that is extracted from transit smart card data, cycling record data, and station location information data. We specifically focus on the moderate distance (0.5–3 km), within which distance the bike-sharing is a rival and suitable alternative to the bus. A binomial logit model is constructed to examine the mode choice between buses and shared bikes as a last-mile connection to urban rail. In addition to the general explanatory variables (i.e., travel distance, travel time, and cost), built environments such as housing density, land uses, and bike-lane conditions are also considered in our study. Results show that the walking distance from the metro station has a stronger effect on the users’ mode choice than the total subchain distance. A longer travel time increases the preference for taking the bus. We also find that users are most likely to choose the bus in the evening rush hours, followed by offpeak times and the morning rush hours. The existence of bike lanes, especially with isolation belts alongside them, increases the probability that people choose shared bikes. As bus and bike-sharing are the two most popular and economically competitive urban rail egress modes for a moderate distance in China, understanding the determinants of mode choice contributes to better planning and operational strategies for both feeder bus and bike-sharing systems.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This paper is supported by the Beijing Natural Science Foundation (Grant No. 8212010) and the National Natural Science Foundation of China (Grant No. 71771007). The authors also thank Joint Laboratory for Future Transport and Urban Computing of Amap for data support.
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Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 5 • May 2022
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© 2022 American Society of Civil Engineers.
History
Received: Sep 16, 2021
Accepted: Dec 22, 2021
Published online: Feb 25, 2022
Published in print: May 1, 2022
Discussion open until: Jul 25, 2022
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