基于V2V的智能车辆换道轨迹规划方法研究

Research on intelligent vehicle lane changing trajectory planning method based on V2V

针对传统车辆换道轨迹算法实时性差与换道效率低的问题,提出一种基于V2V的智能车辆动态自主换道轨迹规划算法。换道起始时刻,智能车辆通过V2V通信技术获取周围交通车辆运动状态信息,在换道条件允许的情况下,采用多项式函数对车辆换道过程的横纵向运动进行描述,通过构建基于双圆车体近似模型的避障算法筛选无碰撞的换道轨迹,以车辆换道舒适性、换道效率等换道性能指标构建多目标优化价值函数,通过求解约束化问题求得最优换道轨迹。为验证算法的有效性,利用CarSim和Matlab/Simulink等软件进行联合仿真验证。结果表明:对于不同的换道工况,基于V2V的换道轨迹规划算法比传统非V2V的换道轨迹规划算法所规划出的换道轨迹需要的换道空间更小,具有更高的换道效率。

To address poor real-time and low efficiency of traditional vehicle lane-changing trajectory algorithm,this paper proposes a dynamic autonomous lane-changing trajectory planning algorithm for intelligent vehicles based on V2V.At the starting moment of lane-changing,the intelligent vehicle obtains the surrounding traffic vehicle motion state information through V2V communication technology,and under the permitted conditions of lane-changing,adopts a polynomial function to describe the transverse and longitudinal motion of the vehicle lane-changing process.It filters the collision-free lane-changing trajectory by constructing the obstacle avoidance algorithm based on the double-circle body approximation model and builds a multi-objective optimization function by constructing the multi-objective optimization function based on the lane-changing performance indexes of the comfort of vehicle lane-changing and lane-changing efficiency.The optimal lane-changing trajectory is obtained by solving the constrained problem.To verify the effectiveness of the algorithm,CarSim and Matlab/Simulink software are employed.Our results show for different lane-changing conditions,the lane-changing trajectory planning algorithm based on V2V requires less lane-changing space than the traditional non-V2V lane-changing trajectory planning algorithm.Moreover,it achieves a higher lane-changing efficiency.