Intelligent information provision for emerging transportation systems

Abstract

The rapid development of information transmission, vehicular technology, artificial intelligence, machine learning technologies, and computing resources is revolutionizing the transportation sector, making it more intelligent, sustainable, and equitable. These emerging technologies necessitate a paradigm shift in transportation system analysis. Leveraging these technologies is crucial to addressing traditional challenges, requiring customization guided by domain knowledge. This dissertation uniquely focuses on the transformative role of intelligent information provision in emerging transportation systems through both theoretical and practical perspectives. The first part of the dissertation focuses on the within-day dynamic traffic equilibrium with strategic information provision. The theoretical modeling and analysis pave the way for understanding the impacts of advanced and heterogeneous information, information reliability, and information design in emerging transportation systems. The second part of the dissertation focuses on mitigating the conflict between individual goals and system goals by leveraging reinforcement learning and correlated equilibrium. The dissertation proposes and customizes a two-way reinforcement learning framework for intelligent information provision in connected autonomous vehicle systems. This framework not only exemplifies the application of emerging technologies in information design but also provides innovative solutions to the longstanding challenge of achieving both individual- and system-level goals in congestion mitigation. Additionally, the research explores the theoretical foundation behind the effects of the proposed two-way learning framework, i.e., correlated equilibrium, offering a new angle and solution in traffic assignment. The dissertation contributes to advancing a more intelligent transportation system through information provision by establishing both theoretical foundations and groundbreaking applications with emerging technologies.