CAREER: Integrated Online Coordinated Routing and Decentralized Control for Connected Vehicle Systems

职业：互联车辆系统的集成在线协调路由和分散控制

• 批准号: 1818526
• 负责人: Lili Du
• 金额: $ 45.56万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-17 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1818526&HistoricalAwards=false
• 关键词: CAREER; Integrated; Online; Coordinated; Routing

Traffic congestion jeopardizes the function of urban transportation systems and has a growing negative effect on the health of urban economies. It also increases air pollution with numerous negative health impacts on our citizenry. A promising solution to alleviating traffic congestion is to establish coordinated driving mechanisms. This is enabled by recent connected or even autonomous vehicle technologies and advanced onboard computing facilities. However, engineers who design such mechanisms are still lacking scientific knowledge and effective tools that can be proven as efficient and reliable for use by the general public. The goal of this Faculty Early Career Development (CAREER) program award is to develop innovative approaches to the coordination of connected vehicle drivers- online route choices. This will be done by exploiting emerging information and computing technologies equipped in connected transportation infrastructure. This approache will improve transportation system mobility, safety, and environmental sustainability without sacrificing the interests of the individual vehicles. This research will deepen our understanding of the competition among vehicles on limited traffic resources. It should also reveal the impacts of the decisions of individual vehicles on traffic congestion, and offer a new paradigm of real-time traffic control. The specific research objectives of this CAREER project are: (a) developing coordinated mechanisms for drivers - route choices to mitigate over-competition; (b) engineering collective effects of drivers - decisions to improve system-level performance; and (c) implementing the coordinated routing mechanisms and decentralized traffic control in an online environment. If successful, this project will lead to: (1) game-theory based modeling, analysis, and design techniques for coordinated routing mechanisms; (2) innovative methods for integrating decentralized control into individual routing decisions via intentional information perturbation techniques; and (3) better understanding of convergence, efficiency and robustness of distributed algorithms for decentralized congestion control. The reseach approaches include: (a) using game theory, optimization, and traffic dynamics to design and analyze coordination mechanisms; (b) using equilibrium analysis, price of anarchy, bounded rationality, and decentralized control for the study of collective effects; and (c) developing distributed algorithms for implementation and carrying out a theoretical analysis of these algorithms. This project will involve underrepresented K-12 students, undergraduate and graduate college students in numerous research tasks, and disseminate research findings through multiple channels, such as national/international workshops and conferences, as well as journal publications.

交通拥堵危害城市交通系统的功能，并对城市经济的健康产生越来越大的负面影响。 它还增加了空气污染，对我们公民的健康产生许多负面影响。 缓解交通拥堵的一个有希望的解决方案是建立协调驾驶机制。 这是通过最新的互联甚至自动驾驶汽车技术和先进的车载计算设施实现的。 然而，设计此类机制的工程师仍然缺乏科学知识和有效的工具，以供公众使用，以证明其高效可靠。 该学院早期职业发展（CAREER）计划奖项的目标是开发创新方法来协调联网车辆驾驶员的在线路线选择。 这将通过利用互联交通基础设施中配备的新兴信息和计算技术来实现。这种方法将改善交通系统的机动性、安全性和环境可持续性，而不会牺牲单个车辆的利益。这项研究将加深我们对有限交通资源上车辆之间竞争的理解。 它还应该揭示单个车辆的决策对交通拥堵的影响，并提供实时交通控制的新范例。该职业项目的具体研究目标是： (a) 为司机制定协调机制——路线选择，以减轻过度竞争； (b) 设计驱动因素的集体效应——提高系统级绩效的决策； (c) 在在线环境中实施协调的路由机制和分散的流量控制。 如果成功，该项目将带来：（1）基于博弈论的协调路由机制的建模、分析和设计技术； (2) 通过有意的信息扰动技术将分散控制集成到个体路由决策中的创新方法； (3)更好地理解分布式拥塞控制分布式算法的收敛性、效率和鲁棒性。研究方法包括：（a）利用博弈论、优化和交通动力学来设计和分析协调机制； (b) 使用均衡分析、无政府状态的代价、有限理性和分散控制来研究集体效应； (c) 开发用于实现的分布式算法并对这些算法进行理论分析。该项目将让代表性不足的 K-12 学生、本科生和研究生参与众多研究任务，并通过多种渠道传播研究成果，例如国家/国际研讨会和会议以及期刊出版物。

项目成果

cooperative trajectory control for synchronizing the movement of two connected and autonomous vehicles separated in a mixed traffic flow

协作轨迹控制，用于同步混合交通流中分离的两辆联网自动驾驶车辆的运动

• DOI: 10.1016/j.trb.2023.05.006
• 发表时间: 2023
• 期刊: Transportation Research Part B: Methodological
• 作者: Qiu, Jiahua;Du, Lili
• 通讯作者: Du, Lili

Robust and resilient equilibrium routing mechanism for traffic congestion mitigation built upon correlated equilibrium and distributed optimization

• DOI: 10.1016/j.trb.2022.12.006
• 发表时间: 2023-02
• 期刊: Transportation Research Part B: Methodological
• 作者: Yuqi Ning;Lili Du

Identifying critical transfer zones to coordinate transit with on-demand services using crowdsourced trajectory data

• DOI: 10.1080/15472450.2022.2132389
• 发表时间: 2022-11
• 期刊: Journal of Intelligent Transportation Systems
• 影响因子: 3.6
• 作者: Jiahua Qiu;Yue Jing;Wang Peng;L. Du;Yujie Hu

A Traffic Flow Dependency and Dynamics based Deep Learning Aided Approach for Network-Wide Traffic Speed Propagation Prediction

• DOI: 10.1016/j.trb.2022.11.009
• 发表时间: 2023-01
• 期刊: Transportation Research Part B: Methodological
• 作者: Hanyi Yang;Lili Du;Guohui Zhang;Tianwei Ma