Quantifying taxi drivers' behaviors with behavioral game theory

• Main Authors: JI, Mengyu, XU, Yuhong, CHENG, Shih-Fen
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Artificial Intelligence and Robotics; Theory and Algorithms; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/8554; https://ink.library.smu.edu.sg/context/sis_research/article/9557/viewcontent/taxi_ipl_itsc2023.pdf
• Institution: Singapore Management University

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.