Two-Phase Model for Demand-Responsive Transit Considering the Cancellation Behavior of Boundedly Rational Passengers
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 5
Abstract
The resurgence of demand-responsive transit (DRT) has been pushed toward a more sharable and user-friendly mobility service to reshape the urban mobility ecosystem. Nevertheless, to fulfill the swiftly growing diversified and personalized demand, how to depict the cancellation behavior of passengers remains an often overlooked but extremely significant challenge. This paper attempts to discuss the cancellation behavior in the two-phase optimization process. With regard to the unconfirmed reservation cancellation, bounded rationality is incorporated to portray the decision-making process of passengers. Bernoulli random variable is utilized to discuss the stochastic possibility of order cancellation. Simultaneously, a two-phase biobjective model considering the cancellation behavior is constructed to balance the inherent trade-off between passengers and operators. In addition, the algorithm based on multidirectional local search is constructed to achieve the Pareto front for the proposed model. Small-scale experiments in the Nguyen-Dupuis network are illustrated to validate the effectiveness of the algorithm. Subsequently, the Beijing case is further exemplified to evaluate the performance of DRT service considering the cancellation behavior. A reasonable penalty mechanism contributes to ensuring operating profit while substantially diminishing the penalty cost. Therefore, this paper facilitates not only capturing the cancellation behavior of passengers but also developing a more flexible and cost-effective DRT service.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This research was funded by the National Natural Science Foundation of China (No. 71971005), Beijing Municipal Natural Science Foundation (No. 8202003), and Beijing Municipal Natural Science Foundation (No. 8212002). We would like to thank Jie Xiong and Yuan Zhang for providing guidance.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 5 • May 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Sep 4, 2022
Accepted: Dec 29, 2022
Published online: Feb 28, 2023
Published in print: May 1, 2023
Discussion open until: Jul 28, 2023
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