基于多目标优化的智能网联汽车队列换道方法

Lane Change Method of Intelligent Networked Vehicle Platoon Based on Multi-Objective Optimization

为了解决智能网联汽车队列在强制换道场景下的通行效率低、舒适性差、燃油消耗大等问题,提出一种考虑多种优化目标的智能网联汽车队列强制换道方法。综合考虑道路通行效率、驾乘舒适性以及燃油经济性等优化目标,并结合换道距离、行车安全及车辆动力学等约束条件,将强制换道场景下的换道轨迹规划问题转化为多优化目标下的最优轨迹问题加以求解。设计了基于滑模控制的智能网联汽车队列跟踪控制算法,实现了多约束条件下面向多种优化目标的稳定换道。仿真结果验证了所提方法的可行性和有效性。

In order to solve the problems of low traffic efficiency,poor comfort and large fuel consumption of intelligent networked vehicle platoon in the mandatorylane change scenario,this paper proposes a mandatorylane change method considering multiple optimization objectives.Considering the optimization objectives of traffic efficiency,driving comfort and fuel economy,and combining with the constraints of lanechanging distance,driving safety and vehicle dynamics,the lanechanging trajectory planning problem in mandatorylanechanging scenario was transformed into the optimal trajectory problem with multiple optimization objectives.On this basis,an intelligent networked vehicle platoon tracking control Algorithm based on sliding mode control was designed to achieve stable lane change for multiple optimization objectivesunder multiple constraints.Simulation results verify the feasibility and effectiveness of the proposed method.