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基于制动转向协同控制的智能车紧急避障研究 被引量:6

A Research on Emergency Obstacle Avoidance of Intelligent Vehicle Based on Braking and Steering Coordinated Control
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摘要 为使车辆在紧急情况下能够快速稳定地完成换道避障,本文中将车辆纵向控制和侧向控制结合在一起,综合考虑车辆在紧急制动转向避障的过程中由于路面附着条件的限制可能会造成车辆失稳问题,在上层进行避障规划过程中加入基于哈密顿能量函数的理想纵向力和侧向力分配,并搭建稳态预测动态校正驾驶员模型跟踪规划的期望路径。然后利用Matlab/Simulink搭建3自由度车辆动力学模型,并基于Carsim和Labview的硬件在环试验对理想纵向力和侧向力的分配进行验证,仿真结果表明,所计算的纵、侧向力分配规律能够在车辆紧急制动转向避障时,在较短的时间和纵向距离条件下行驶到相邻车道。最后通过实车试验进一步验证了所提出方法的有效性。 In order to enable vehicles to change lane quickly and steadily to avoid obstacles in emergencies,this paper combines vehicle longitudinal with lateral control.Considering the stability problems that may be caused by restrictions of road adhesion conditions in an emergency braking steering process of obstacle avoidance.Ideal longitudinal force and lateral force allocation based on Hamilton energy function is added to the planning process of emergency obstacle avoidance,and a steady state prediction with dynamic correction driver model is built to track the desired path of the planning.Then,a three-degree-of-freedom vehicle dynamics model is built by using Matlab/Simulink and the distribution of ideal longitudinal force and lateral force is validated by hardware in-loop test based on Carsim and Labview.The simulation results show that the distribution of the calculated force distribution law can make the vehicle drive to the adjacent lane in a relatively short period of time and longitudinal distance under the condition of emergency braking and steering to avoid obstacles.Finally,a vehicle test is carried out to verify the effectiveness of the proposed method.
作者 王其东 李印祥 陈无畏 赵林峰 谢有浩 Wang Qidong;Li Yinxiang;Chen Wuwei;Zhao Linfeng;Xie Youhao(School of Automotive and Traffic Engineering,Hefei University of Technology,Hefei 230009;Hefei University,Hefei230601;Anhui Cheetah Automobile Co.,Ltd.,Chuzhou 239064)
出处 《汽车工程》 EI CSCD 北大核心 2019年第4期395-403,425,共10页 Automotive Engineering
基金 国家自然科学基金(51675151) 国家自然科学基金联合基金(U1564201) 安徽省科技重大专项(17030901060)资助
关键词 智能车 紧急避障 理想纵、侧向力 路径分割 路径跟踪 intelligent vehicle emergency obstacle avoidance ideal longitudinal and lateral force path segmentation path tracking
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