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

无线通信技术的进步已经实现了车辆之间以及车辆与相关联的基础设施之间的通信。这些技术可以显著提高当前道路运输系统的安全性和性能。本研究旨在了解交通信息如何在车辆之间以及车辆与路边基础设施之间传播，以及如何有效收集这些数据并用于制定实时交通管理策略，以提高安全性，流动性和可持续性。此外，通过伊利诺伊理工学院和普渡大学的教育计划，这项研究将有助于为劳动力开发新技能，这些技能可以利用这些新兴技术进行创新应用，并为代表性不足的群体扩大研究和教育机会。这项研究旨在发展真实的-时间协调的交通管理策略建立在连接车辆系统中的动态信息传播和聚合的基础上。为了实现这一目标，它调查了三个相互关联的研究挑战：（i）信息传播动力学，（ii）分布式信息聚合，（iii）协调的实时交通管理。这些方法将计算机科学、运输科学和运筹学中的先进科学知识连接起来。此外，他们适应交通流理论，网络建模，无线通信，优化理论，随机建模和算法设计中的知名和/或新兴概念。这项研究的新奇是突出通过整体考虑的独特功能的连接车辆系统：一个分布式系统与动态信息在其中传播。在基础层面上，研究成果将在以下方面为联网车辆系统的科学知识和技术做出贡献：（i）更好地理解信息动态和交通流动态之间的相互作用;（ii）开设与分布式信息处理方法相关的新研究场所;（iii）建立与分布式信息处理方法相关的新研究中心。及（iii）对真实的-通过协调个人车辆知识和集中交通控制进行时间交通管理。该奖项反映了NSF的法定使命，并通过使用基金会的学术价值和更广泛的影响审查标准。

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.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.