Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
9-2023
Abstract
With their flexibility and convenience, taxis play a vital role in urban transportation systems. Understanding how human drivers make decisions in a context of uncertainty and competition is crucial for taxi fleets that depend on drivers to provide their services. As part of this paper, we propose modeling taxi drivers’ behaviors based on behavioral game theory. Based on real-world data, we demonstrate that the behavioral game theory model we select is superior to state-of-the-art baselines. These results provide a solid foundation for improving taxi fleet efficiency in the future.
Discipline
Artificial Intelligence and Robotics | Theory and Algorithms | Transportation
Research Areas
Intelligent Systems and Optimization
Publication
2023 IEEE International Conference on Intelligent Transportation Systems, ITSC: Bilbao, Spain, September 24-28: Proceedings
First Page
3016
Last Page
3021
ISBN
9798350399462
Identifier
10.1109/ITSC57777.2023.10422246
Publisher
IEEE
City or Country
Piscataway, NJ
Citation
JI, Mengyu; XU, Yuhong; and CHENG, Shih-Fen.
Quantifying taxi drivers' behaviors with behavioral game theory. (2023). 2023 IEEE International Conference on Intelligent Transportation Systems, ITSC: Bilbao, Spain, September 24-28: Proceedings. 3016-3021.
Available at: https://ink.library.smu.edu.sg/sis_research/8554
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/ITSC57777.2023.10422246
Included in
Artificial Intelligence and Robotics Commons, Theory and Algorithms Commons, Transportation Commons