A Dispatching Method for Demand Responsive Transit With Passengers’ Hidden Preference Exploitation Capability
Demand Responsive Transit (DRT) emerges as one of the most promising public transit operating patterns, which operates without fixed stations or routes, aiming to provide flexible and passenger-oriented services. However, the current DRT dispatching hardly achieves a balance between the operating costs and service flexibility, leading to a high failure rate of DRT operation. To address this issue, this research proposes a dispatching method for DRT with passengers’ hidden preference exploitation capability. The proposed DRT dispatching method overcomes the imbalance shortcomings of conventional method and bears the following features: 1) With the capability of exploiting the passengers’ hidden preference; 2) With the capability of making the most of the passengers’ room for compromise. To evaluate the proposed dispatching method, a numerical experiment compared with conventional DRT dispatching model is conducted, and sensitivity analysis is performed for passenger satisfaction level threshold. The evaluation results show that with the capability of exploiting the passengers’ hidden preference, the proposed DRT dispatching method is able to improve the average travel time by 27.8%~47.5% and reduce the average waiting time by 26.4%~47.4%; via making the most of the passengers’ room for compromise, the proposed DRT dispatching method is able to enhance the passenger average satisfaction by 65.3%~85.7%. The benefit range is caused by different values of passenger satisfaction level threshold.
Authors
- Jia Hu (ORCID: https://orcid.org/0000-0002-0900-7992)
- Zihan Zhang
- Arno Eichberger (ORCID: https://orcid.org/0000-0001-8246-8085)
- Guan Wang (ORCID: https://orcid.org/0000-0001-5719-5417)
- Chang Liu (ORCID: https://orcid.org/0000-0002-8264-5261)
- Yixuan Dong (ORCID: https://orcid.org/0009-0000-0228-7613)
Institutions
- Tongji University (CN)
- Shanghai Innovative Research Center of Traditional Chinese Medicine (CN)
- Graz University of Technology (AT)
- HUN-REN Institute for Computer Science and Control (HU)
- SAIC Motor (China) (CN)
Publication Details
- Journal
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2025-04-15
- DOI
- https://doi.org/10.1109/tits.2025.3558297
- Citations
- 1
- Primary Topic
- Transportation and Mobility Innovations
- Type
- article
- Field-Weighted Citation Impact
- 0.68
Funders
- Shanghai Automotive Industry Science and Technology Development Foundation
- National Natural Science Foundation of China
- National Key Research and Development Program of China