Flexible Route Optimization for Demand-Responsive Public Transit Service
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 12
Abstract
Traditional customized buses travel on fixed routes, which cannot satisfy passengers’ flexibility and convenience requirements. This paper studies a demand-responsive transit (DRT) service that can continuously adjust the path based on passengers’ dynamic demand. The path optimization model is established with more realistic constraints to create a bus travel plan within a specified area, and the model not only considers the preferred time windows of passengers but also maximizes the benefits of the system. Based on simulated annealing, a dynamic genetic algorithm is designed to generate the static initial travel path, and the dynamic travel path is continuously updated to satisfy the real-time demand. To evaluate the proposed model and algorithm, a case study in a typical residential community of Beijing, China, is conducted based on transit smart card records. According to the case study results, the convenience, travel time, and economic and environmental benefits of the DRT service are assessed via comparison with traditional buses and private cars. The analysis results demonstrate the feasibility and significance of the method, and it can be used by transit planners to design a superior DRT service.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request (algorithm code, boarding and alighting data in the studied area, stop coordinates, and distance matrix).
Acknowledgments
This study is funded by the National Key R&D Program of China (Grant No. 2018YFB1601200) and the Foundation for Innovative Research Groups of the National Nature Science Foundation of China (Grant No. 71621001). The authors are grateful to the anonymous reviewers for providing helpful suggestions for the study.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 12 • December 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Sep 25, 2019
Accepted: Jun 15, 2020
Published online: Sep 17, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 17, 2021
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