摘要
为了解决复杂道路状况下车辆防碰撞及保持侧向稳定性的问题,提出一种自动紧急制动控制策略。采用碰撞时间(time-to-collision,TTC)模型评估车辆碰撞风险,利用名义和实际横摆角速度偏差判别车辆侧向稳定性,结合反向传播(back propagation,BP)神经网络和增量式比例-积分-微分(proportion-integral-derivative,PID)求解维持车辆侧向稳定性的附加横摆力矩,进而计算同时满足车辆防碰撞所需期望减速度及避免侧向失稳所需附加横摆力矩的四轮制动力。仿真结果表明,车辆紧急制动过程中,其横摆角速度及质心侧偏角大幅度减小,所提控制策略能够在防止车辆碰撞的同时避免其侧向失稳。
In order to solve the problem of vehicle collision avoidance and maintaining lateral stability under complex road conditions,the time-to-collision(TTC)model was used to assess the risk of vehicle collision,and the deviation of the nominal and actual yaw rate was utilized to judge the lateral stability of the vehicle.The back propagation(BP)neural network combined incremental proportion-integral-derivative(PID)was employed to obtain the additional yaw moment maintaining the lateral stability of the vehicle,and then the four-wheels braking force that met the desired deceleration required for vehicle collision avoidance and the additional yaw moment required to avoid lateral instability were calculated.The simulation results show that the yaw rate and the side slip angle vehicle are greatly reduced during the emergency braking process.The automatic emergency braking control strategy proposed in this paper can prevent the vehicle from colliding and avoiding its lateral instability.
作者
刘哲
程硕
王树凤
LIU Zhe;CHENG Shuo;WANG Shufeng(College of Transportation, Shandong University of Science and Technology, Qingdao, Shangdong 266590, China;State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China)
出处
《中国科技论文》
CAS
北大核心
2022年第2期221-227,共7页
China Sciencepaper
基金
山东省自然科学基金资助项目(ZR2019MF056)。
关键词
自动紧急制动
侧向稳定性
BP神经网络
PID
automatic emergency braking
lateral stability
BP neural network
proportion-integral-derivative(PID)
作者简介
第一作者:刘哲(1994—),男,硕士研究生,主要研究方向为高级驾驶辅助系统;通信作者:王树凤,副教授,主要研究方向为车辆系统动力学,shufengwang@sdust.edu.cn。
