Lane-Exchanging Driving Strategy for Autonomous Vehicle via Trajectory Prediction and Model Predictive Control

被引:10
作者
Chen, Yimin [1 ,3 ]
Yu, Huilong [2 ]
Zhang, Jinwei [3 ]
Cao, Dongpu [4 ]
机构
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Peoples R China
[2] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China
[3] Univ Waterloo, Dept Mech & Mechatron Engn, Waterloo, ON, Canada
[4] Tsinghua Univ, Sch Vehicle & Mobil, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Autonomous vehicle; Lane-exchanging; Vehicle trajectory prediction; Potential field; Model predictive control; TRACKING CONTROL; DRIVER; SYSTEM;
D O I
10.1186/s10033-022-00748-7
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the lane-exchanging scenario. The nearby vehicle trajectory needs to be predicted, from which the autonomous vehicle is controlled to prevent possible collisions. This paper proposes a lane-exchanging driving strategy for the autonomous vehicle to cooperate with the nearby vehicle by integrating vehicle trajectory prediction and motion control. A trajectory prediction method is developed to anticipate the nearby vehicle trajectory. The Gaussian mixture model (GMM), together with the vehicle kinematic model, are synthesized to predict the nearby vehicle trajectory. A potential-field-based model predictive control (MPC) approach is utilized by the autonomous vehicle to conduct the lane-exchanging maneuver. The potential field of the nearby vehicle is considered in the controller design for collision avoidance. On-road driving data verification shows that the nearby vehicle trajectory can be predicted by the proposed method. CarSim (R) simulations validate that the autonomous vehicle can perform the lane-exchanging maneuver and avoid the nearby vehicle using the proposed driving strategy. The autonomous vehicle can thus safely perform the lane-exchanging maneuver and avoid the nearby vehicle.
引用
收藏
页数:12
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