文献类型：期刊文献

英文题名：Pinning Controlled Nodes Detection in Urban Traffic Networks via an Improved WVoteRank Approach

作者：Xiao, Yuting[1]; Guo, Lu[1]; Liang, Haili[1]; Zhou, Zhao[2]

机构：[1] School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Power Station Automation Technology, Shanghai University, Shanghai, 200444, China; [2] Ministry of Education, Key Laboratory of Smart Manufacturing in Energy Chemical Process, East China University of Science and Technology, Shanghai, 200237, China

年份：2023

卷号：2023-July

起止页码：899

外文期刊名：Chinese Control Conference, CCC

收录：EI(收录号：20234515015794)

语种：英文

外文关键词：Motor transportation - Roads and streets - Street traffic control - Traffic congestion

摘要：Urban traffic networks are complex systems, where intersections are interconnected by road links, and the dynamics of traffic flow is controlled by traffic lights. Macroscopic fundamental diagrams based traffic control pave the way for alleviating urban traffic congestion problems at the networked level. In order to have better control of the traffic network, the more important areas of the urban road network could be operated via pinning control after dividing it into several homogeneous sub-regions. In this paper, we identify the pinning controlled nodes of the traffic road network based on the extended VoteRank. The improved WVoteRank is obtained based on WVoteRank and VoteRank ++. The characteristics of the regional road network itself and the road segments connecting two regions are taken into account. In this way, a pinning controlled nodes identification algorithm applicable to traffic networks is formed. With the simulation experiments based on the real traffic network, several pinning controlled regions are obtained. The simulation results show that the improved WVoteRank can identify the key regions in the traffic network. ? 2023 Technical Committee on Control Theory, Chinese Association of Automation.