报告题目：A capacity maximization scheme for intersection management with automated vehicles

报告时间：2018年01月17日（周三）14:00

报告地点：屏峰校区A1区块计算机大楼A401#

报  告 人：孙伟力

报告人简介：

孙伟力，博士，现为滴滴出行智慧交通资深专家。曾先后在北京航空航天大学交通学院及美国密西根大学土木与环境工程系及交通研究所从事博士后研究，主要研究方向为交通信号控制，特别是城市过饱和交叉口管控、车联网和自动驾驶环境下的协同控制，先后主持或参与国家自然科学基金、国家高技术研究发展计划（863计划）、国家科技支撑计划、中国博士后基金项目、美国能源部课题等相关项目多项，在交通领域期刊及国际会议上共发表论文10余篇。

报告摘要：

he rapid development of connected and automated vehicle (CAV) technologies will undoubtedly revolutionize the traffic control system. On one hand, CAVs provide richer traffic information with a good coverage of urban road network. On the other hand, CAVs themselves can be coordinated controlled to pursue a system optimum, even without the guidance of traffic signals. In this talk, an innovative intersection operation scheme named as MCross: Maximum Capacity inteRsection Operation Scheme with Signals will be proposed. This new scheme maximizes intersection capacity by utilizing all lanes of a road simultaneously. Lane assignment and green durations are dynamically optimized by solving a multi-objective mixed-integer non-linear programming problem. The demand conditions under which full capacity can be achieved in MCross is derived analytically. Numerical examples show that MCross can almost double the intersection capacity (increase by as high as 99.51% in comparison to that in conventional signal operation scheme).