Autonomous driving: Queueing game, information design and human-AI interactions
Speaker:
Dr. Qiaochu He, Southern University of Science and Technology
Date: 12 December 2024 (Thursday)
Time: 11:00 am - 12:30 pm
Venue: Innovation Wing Two, G/F Run Run Shaw Building, HKU
Abstract
I am presenting recent research on service operations and business models within a mixed autonomy paradigm, focusing on navigation algorithms influenced by differentiated information and driver-algorithm interactions. Leveraging queueing game models, Bayesian persuasion-based information design, and reinforcement learning for experimental validation, this research examines complex traffic flows, platform operation strategies, the effectiveness of intelligent navigation models, and behavioral patterns in human-machine interaction. These efforts aim to enhance traffic system efficiency and social welfare, thereby advancing the development and application of autonomous driving technologies.
Specifically, I will present findings from five (working) papers. At the micro level, we had a POM paper explores the interaction between autonomous vehicles (AVs) and human-driven vehicles (HVs) using queueing game frameworks. In another POM paper, we proposed smart navigation algorithms through information design methods to mitigate traffic congestion in routing games. A third working paper extends this framework to incorporate targeted algorithms for further theoretical development. Additionally, two ongoing projects employ experimental economics and artificial intelligence (AI) techniques to investigate behavioral interactions between navigation algorithms and human drivers, thereby validating theoretical models of human-AI interaction. These experiments also assess whether AI algorithms can optimize traffic flow via implicit cooperation, even in the absence of centralized control. Furthermore, the studies attempt to explain algorithm aversion behaviors through a dynamic information design framework.
Speaker Bio:
Qiao-Chu He is a tenured Associate Professor at the SUSTech Business School. His primary research interests lie in operations management, with applications in areas such as smart cities, marketplaces and platforms, and human-algorithm/AI interactions. He serves as the principal investigator for several research projects funded by the National Natural Science Foundation of China (NSFC), the National “Ten-Thousand” Program for Young Scholars (2019), and the Hong Kong General Research Fund (HK-GRF). He holds a Bachelor of Engineering from Tsinghua University and a Ph.D. in Operations Research from the University of California, Berkeley. He has previously taught at HKUST and UNC Charlotte. His students hold faculty positions at Business School including HUST (Huazhong), USTC (Hefei) and the University of Liverpool (UK).
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