Collaborative Research: Coordinated Real-Time Traffic Management based on Dynamic Information Propagation and Aggregation under Connected Vehicle Systems

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Advances in wireless communication technologies have enabled communications among vehicles, and between vehicles and the associated infrastructure. These technologies can be significantly leveraged to enhance the safety and performance of current roadway transportation systems. This study seeks to understand how traffic information spreads among vehicles and between vehicles and the roadside infrastructure, and how that data can be efficiently collected and used to develop real-time traffic management strategies, so as to improve safety, mobility, and sustainability. Further, through the education programs at Illinois Institute of Technology and Purdue University, this study will aid the development of new skills for the workforce that can leverage these emerging technologies for innovative applications, and broaden research and educational opportunities for under-represented groups.This study seeks to develop real-time coordinated traffic management strategies built upon dynamic information propagation and aggregation in connected vehicle systems. To achieve this goal, it investigates three interrelated research challenges: (i) information propagation dynamics, (ii) distributed information aggregation, and (iii) coordinated real-time traffic management. These methods bridge advanced scientific knowledge in computer science, transportation science, and operations research. Further, they adapt well-known and/or emerging concepts in traffic flow theory, network modeling, wireless communication, optimization theory, stochastic modeling, and algorithm design. The novelty of this research is highlighted through the holistic consideration of the unique features of a connected vehicle system: a distributed system with dynamic information propagating therein. At a fundamental level, the study outcomes will contribute to scientific knowledge and technologies for connected vehicle systems in the following aspects: (i) a better understanding of the interactions between information dynamics and traffic flow dynamics; (ii) the opening of a new research venue related to distributed information processing methods; and (iii) the understanding of real-time traffic management through the coordination of individual vehicle knowledge and centralized traffic control.