Ran, Changhao (Intelligent Transportation Systems Research Center, Wuhan Univer), WU, Chaozhong (Wuhan University of Technology), Zhang, Hui (Wuhan University of Technology), Ding, Naikan (Wuhan University of Technology), Tian, Kai (Wuhan University of Technology), Wu, Huiyu (Wuhan University of Technology), Huang, Zhen (Wuhan University of Technology), Wang, Xu (Shandong University)

Mainline Lane Management Strategies for Mixed Traffic with Connected Autonomous Vehicles on Urban Expressway Merging Areas

Scheduled for presentation during the Poster Session "Road Traffic Control I" (WeBT15), Wednesday, September 25, 2024, 14:30−16:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 3, 2024

Abstract

With the rapid advancement of autonomous driving technology, the impact of connected autonomous vehicles (CAVs) on traffic safety and stability has garnered significant attention. This study aims to evaluate different mainline lane management strategies and CAV penetration rates on mixed traffic safety at urban expressway merging areas. Utilizing measured vehicle trajectory data from an urban expressway merging area, a deep learning-based mandatory lane changing model is established for human-driven vehicles’ (HDVs) merging behavior. Considering the overall effect of CAV dedicated lanes or priority lanes layout and CAV penetration rates on mixed traffic distribution on the mainline, a series of simulations are conducted in SUMO with secondary development. Compared to various mainline lane management strategies, designating the outer mainline lane as the CAV dedicated lane results in fewer conflicts between vehicles. In this scenario, as the CAV penetration rate increases from 20% to 80%, the number of conflicts decreases by 3.47% to 9.81% compared to no lane management strategy. Implementing a proper mainline lane management strategy can enhance the safety of mixed traffic at urban expressway merging areas.