人工智能前沿讲座第7讲——美国普渡大学冯毅恒助理教授学术报告

发布时间:2023-04-11 点击:

报告题目: 车路协同环境下的智能交通管理:数据,优化和网络安全 (Intelligent Traffic Management Under Cooperative Driving Automation: Data, Control, and Cybersecurity)

报告摘要:

With the development of next-generation transportation system with connected and automated vehicles (CAVs), the transportation infrastructure will also be equipped with sensors, communication devices, and edge computing capabilities, which enables cooperative driving automation (CDA). Under CDA, the traffic control paradigm will also be significantly changed. In this talk, I will introduce our recent work in intelligent traffic management under CDA with examples in cooperative perception based data acquisition, spatiotemporal intersection management, and V2X cybersecurity.

随着智能网联车辆的下一代交通系统的发展,交通基础设施也将配备传感器、通信设备和边缘计算能力,进而实现车路协同。在车路协同的环境下,交通控制范式也将发生重大变化。在本次演讲中,我将介绍我们在基于车路协同环境下智能交通管理的最新工作,包括基于合作式感知的数据采集和分析、时空交叉口管理和车路协同网络安全等方面的案例。

个人简介:

Dr. Yiheng Feng is an assistant professor at Lyles School of Civil Engineering, Purdue University. He received his Ph.D. from Department of Systems and Industrial Engineering at University of Arizona. His research areas include traffic operations and control, connected and automated vehicles (CAVs) and smart transportation infrastructure, with a focus on cooperative driving automation and transportation system cybersecurity. He has served as PI and Co-PI in many research projects funded by NSF, USDOT, and USDOE. His work appeared in many top journals and conferences and won several best paper awards from INFORMS, and NDSS. He is serving as an editor of multiple transportation journals. He is a member of the Traffic Signal Systems Committee (ACP25) at Transportation Research Board and co-chair of Simulation Subcommittee.

冯毅恒博士是普渡大学莱尔斯土木工程学院的助理教授。他在亚利桑那大学系统和工业工程系获得博士学位。他的研究领域包括交通控制和管理,自动驾驶和智能交通基础设施,重点研究车路协同和交通系统的网络安全。他曾主持多个由美国国家科学基金会(NSF)、美国运输部(USDOT)和美国能源部(USDOE)资助的研究项目。他的研究成果发表在多个顶级期刊和会议上,并获得了INFORMS和NDSS等多个最佳论文奖项。他还担任多个交通运输期刊的编辑。他是美国交通研究委员会(TRB)交通信号系统委员会(ACP25)的成员,以及交通仿真子委员会的联合主席。

报告时间:2023年4月18日 星期二 早8:00-9:30

报告地点:腾讯会议:785-214-797