CAREER: Robust Traffic Management for Connected Vehicle Systems

该学院早期职业发展（Career）项目将通过增强互联车辆系统（CVS）的稳健性，确保交通管理在可预见和不可预见的广泛条件下按预期工作，从而为国家经济和生活质量做出贡献。互联汽车技术为合作出行提供了独特的机会，通过创新的交通管理程序提高机动性和安全性。然而，这些程序引入了信息和交通之间的耦合效应，可能会降低交通流的稳定性。这些耦合效应是信息和交通之间的反馈回路的结果，这些反馈回路是高度动态的，容易受到从一个系统传输到另一个系统的干扰。确保交通流量稳定应对这些影响既重要又具有挑战性。该职业奖支持的研究将为稳健的交通管理设计和运营带来新的范例，以促进机动性、安全性和可持续性。研究结果将在更有效地利用网络和物理基础设施方面直接造福社会，从而实现更可持续、更高效的交通规划和运营，充分考虑动态供需互动。该奖项还支持教育工作，通过培训具有交通工程动态系统视角的专业人员，为交通运输劳动力做出贡献。该项目将向广泛的受众传播研究和教育成果，包括K-12学生、专业人士和使用基于虚拟现实和仿真平台的公众。本CAREER项目的研究目标是建立一个具有坚实科学基础的理论框架，对信息流量协同进化过程进行建模，以应对CVS带来的挑战。该框架建立在一个随机的、耦合的动力系统上，该系统可以在局部和网络尺度上对互联车辆的交通动态进行建模。本项目采用的主要工具是非平衡流鲁棒性的概念，这将促进耦合动力系统的不稳定性分析和吸引域分析。以非平衡流分析为基础，利用复杂网络理论、随机最优控制和变分原理，帮助开发非平衡流转换检测、CVS鲁棒性量化和预测以及自适应控制原理设计等相关算法。研究成果将通过广泛的渠道传播，并融入先进的课程，以帮助培养下一代工程师和科学家，以应对物联网时代的挑战。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Faculty Early Career Development (CAREER) project will contribute to the nation's economy and quality of life by enhancing the robustness of connected vehicle systems (CVS) to ensure that traffic management works as expected in a wide range of conditions, both foreseen and unforeseen. Connected vehicle technologies provide unique opportunities for cooperative travel to improve mobility and safety through innovative traffic management procedures. However, these procedures introduce coupling effects between information and traffic that could reduce traffic flow stability. These coupling effects are the result of the feedback loops between information and traffic that are highly dynamic and prone to disturbances transmitted from one system to the other. It is both important and challenging to ensure traffic flows are robust in response to these effects. This CAREER award supports research that will lead to new paradigms for the design and operation of robust traffic management to foster mobility, safety, and sustainability. The findings will directly benefit society in terms of more effective use of both cyber and physical infrastructures, leading to more sustainable and efficient transportation planning and operations that fully consider dynamic supply-demand interactions. The award also supports educational efforts contributing to transportation workforce by training the professionals with the dynamic systems perspective in traffic engineering. The project will disseminate research and educational outcomes to a wide audience, including K-12 students, professionals, and the public using Virtual Reality-based and simulation platforms. The research goal of this CAREER project is to develop a theoretical framework with solid scientific foundations to model the information-traffic co-evolutionary process to address the challenges created by CVS. The framework is built on a stochastic, coupled dynamical system that can model connected vehicle traffic dynamics at the local and network scales. The primary tool used in this project is the notion of non-equilibrium flow robustness, which will advance the instability analysis and attraction domain analysis of the coupled dynamical system. As the foundation, the non-equilibrium flow analyses help the algorithmic development related to detecting non-equilibrium flow transition, quantification and prediction of CVS robustness, and design of adaptive control principles by leveraging the complex network theory, stochastic optimal control, and variational principle. Research findings will be disseminated through a wide range of channels and integrated into advanced curricula to help cultivate the next generation of engineers and scientists to meet the challenges of the Internet-of-Things era.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.