Modeling and Analysis of Mixed Traffic Networks with Human-Driven and Autonomous Vehicles  

作　　者：Qing Xu Chaoyi Chen Xueyang Chang Dongpu Cao Mengchi Cai Jiawei Wang Keqiang Li Jianqiang Wang 

机构地区：[1]School of Vehicle and Mobility,Tsinghua University,Beijing 10080,China [2]Tsingcloud Co.,Ltd.,Beijing 100083,China [3]State Key Laboratory of Intelligent Green Vehicle and Mobility,Tsinghua University,Beijing 100084,China

出　　处：《Chinese Journal of Mechanical Engineering》2024年第6期495-507,共13页中国机械工程学报(英文版)

基　　金：Supported by National Natural Science Foundation of China(Grant Nos.52072212,52302410);China Postdoctoral Science Foundation(Grant No,2024T170489);Postdoctoral Fellowship Program of CPSF(Grant No.GZB20230354);Research and Development of Autonomous Driving Domain Controller and Its Algorithm(Grant No.2023Z070);Young Elite Scientists Sponsorship Program by CHINA-SAE;Shuimu Tsinghua Scholarship。

摘　　要：The emergence of connected and automated vehicles(CAV)indicates improved traffic mobility in future traffic transportation systems.This study addresses the research gap in macroscopic traffic modeling of mixed traffic networks where CAV and human-driven vehicles coexist.CAV behavior is explicitly included in the proposed traffic network model,and the vehicle number non-conservation problem is overcome by describing the approaching and departure vehicle number in discrete time.The proposed model is verified in typical CAV cooperation scenarios.The performance of CAV coordination is analyzed in road,intersection and network scenario.Total travel time of the vehicles in the network is proved to be reduced when coordination is applied.Simulation results validate the accuracy of the proposed model and the effectiveness of the proposed algorithm.

关 键 词：Macroscopic traffic model Connected and automated vehicle Traffic Coordination 

分 类 号：TN9[电子电信—信息与通信工程]