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

• Published in: Chinese journal of mechanical engineering 2024-11, Vol.37 (1), p.134-13, Article 134
• Main Authors: Xu, Qing, Chen, Chaoyi, Chang, Xueyang, Cao, Dongpu, Cai, Mengchi, Wang, Jiawei, Li, Keqiang, Wang, Jianqiang
• Format: Article
• Language: English
• Subjects: Advanced Transportation Equipment; Algorithms; Automation; Autonomous vehicles; Connected and automated vehicle; Cooperation; Coordination; Efficiency; Electrical Machines and Networks; Electronics and Microelectronics; Engineering; Engineering Thermodynamics; Heat and Mass Transfer; Instrumentation; Integer programming; Machines; Macroscopic traffic model; Manufacturing; Mechanical Engineering; Methods; Modelling; Optimization; Original Article; Power Electronics; Processes; R&D; Research & development; Roads & highways; Simulation; Theoretical and Applied Mechanics; Traffic control; Traffic Coordination; Traffic flow; Transportation networks; Transportation systems; Travel time
• ISSN: 2192-8258; 1000-9345; 2192-8258
• DOI: 10.1186/s10033-024-01118-1

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.