Target Vehicle Selection Algorithm for Adaptive Cruise Control Based on Lane-changing Intention of Preceding Vehicle

Chinese Journal of Mechanical Engineering

Jun Yao¹  Zhenhai Gao¹  Guoying Chen¹ 

[1] State Key Laboratory of Automotive Simulation and Control, Jilin University, 130022, Changchun, China;

关键词: Lane-changing intention;    Target vehicle selection;    Support vector machine;    Adaptive cruise control;   

DOI  :  10.1186/s10033-021-00650-8

来源: Springer

【 摘 要 】

To improve the ride comfort and safety of a traditional adaptive cruise control (ACC) system when the preceding vehicle changes lanes, it proposes a target vehicle selection algorithm based on the prediction of the lane-changing intention for the preceding vehicle. First, the Next Generation Simulation dataset is used to train a lane-changing intention prediction algorithm based on a sliding window support vector machine, and the lane-changing intention of the preceding vehicle in the current lane is identified by lateral position offset. Second, according to the lane-changing intention and collision threat of the preceding vehicle, the target vehicle selection algorithm is studied under three different conditions: safe lane-changing, dangerous lane-changing, and lane-changing cancellation. Finally, the effectiveness of the proposed algorithm is verified in a co–simulation platform. The simulation results show that the target vehicle selection algorithm can ensure the smooth transfer of the target vehicle and effectively reduce the longitudinal acceleration fluctuation of the subject vehicle when the preceding vehicle changes lanes safely or cancels their lane change maneuver. In the case of a dangerous lane change, the target vehicle selection algorithm proposed in this paper can respond more rapidly to a dangerous lane change than the target vehicle selection method of the traditional ACC system; thus, it can effectively avoid collisions and improve the safety of the subject vehicle.

【 授权许可】

CC BY