Path Controlling of Automated Vehicles for System Optimum on Transportation Networks with Heterogeneous Traffic Stream

主讲人：陈志斌 博士
时间：2019年10月25日（周五）上午10:00-11:00
地点：通达馆327
主讲人简介:
陈志斌博士于2017年获得佛罗里达大学交通工程博士学位，随后在密歇根大学安娜堡分校从事博士后研究工作。2019年1月加入上海纽约大学成为工程与计算机科学学部助理教授、博导。陈博士的研究方向包括交通路网建模与优化、交通经济分析、智能交通系统、以及新兴车辆技术。其在电动车充电设施建模与优化，先进停车管理系统分析、设计和仿真，以及自动驾驶汽车基础设施规划研究等方面取得了一系列成果，在Transportation Research Part B和Part C等SCI期刊发表论文十余篇。陈博士是2016年美国交通运输研究委员会（TRB）年会Ryuichi Kitamura Paper Award和Stella Dafermos Best Paper Award的获得者。
主讲内容简介:
In the future, when traffic streams comprise a mix of conventional and automated vehicles (AVs), AVs may be employed as mobile actuators to regulate or manage traffic flow across an urban road network to enhance its performance. This paper develops a path-control scheme to achieve the system optimum (SO) of the network by controlling a portion of cooperative AVs (CAVs) as per the SO routing principle. A linear program is formulated to delineate the scheme and determine the minimum control ratio (MCR) of CAVs to achieve SO. The properties of the MCR are mathematically and numerically investigated. Numerical examples based on real-world networks reveal that the SO of most of the tested networks can be achieved with an MCR below 23%. Considering the low market penetration of AVs at early stages of their deployment, we further investigate a joint path-based control and pricing scheme to replicate SO. Numerical examples demonstrate the remarkable synergy of these combined instruments on reducing the MCR with little collected tolling revenue.
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