重庆理工大学学报2025，Vol.39Issue(5)：1-9,9.DOI:10.3969/j.issn.1674-8425(z).2025.03.001
人机混驾环境下交叉口自动驾驶车辆轨迹优化
Trajectory optimization of connected automated vehicles at intersection under semi-autonomous environment
摘要
Abstract
To address the large computational volume and difficulty in solving the model of the current trajectory optimization techniques employed by connected automated vehicle(CAV)at the signal-controlled intersections as well as the negative impacts on CAV's trajectories in a mixed human and autonomous driving environment,we propose a two-phase asynchronous trajectory optimization model.It optimizes the CAV's trajectory and its longitudinal trajectory under specified signal timing conditions.The trajectory optimization model is solved dynamically using a rolling optimization algorithm.To improve the trajectory optimization model's efficiency,the best possible trajectory for the vehicle in the future time domain is found at each time step.With the use of the Matlab platform,a simulation environment is created for our experiments,which shows our proposed cooperative optimization control strategy effectively improves the performance of human-driving vehicles and mixed traffic.With a growing presence of CAVs,both human-driving vehicles and CAVs witness a downward trend in average journey time and the number of stops,as well as a decrease in delays.Moreover,the human-driving vehicles further improve access efficiency at the intersections with a growing number of CAVs.关键词
智能交通/自动驾驶车辆/交叉口/轨迹优化/混合交通流Key words
intelligent transportation/connected automated vehicles/intersection/trajectory optimization/mixed traffic flow分类
交通工程引用本文复制引用
秦雅琴,刘小云,刘拥华,张森,谢济铭,赵仕林..人机混驾环境下交叉口自动驾驶车辆轨迹优化[J].重庆理工大学学报,2025,39(5):1-9,9.基金项目
国家自然科学基金项目(72261021) （72261021）
