To enhance the comfort and safety of intelligent vehicles during obstacle avoidance and lane changing,a trajectory planning method was proposed using an artificial bee colony algorithm that considers comfort.By sampling positions in the speed-time space,a time-based speed sequence was obtained.New honey source search and update strategies were designed to improve the search accuracy and convergence speed of the artificial bee colony algorithm.The lane-changing trajectory was derived by combining a fifth-order polynomial fit of the speed sequence with honey source positions.Taking into account vehicle acceleration and jerk for comfort,a trajectory comfort evaluation function was designed and integrated into the fitness function to optimize the lane-changing trajectory based on collision detection results.The effectiveness of the algorithm was validated using the Simulink-PreScan-CarSim jointsimulation platform.The results show that under various conditions,the proposed method can plan collision-free lane-changing trajectories that comply with acceleration and jerk constraints,outperforming trajectories planned without considering comfort.In real vehicle tests,the proposed method can achieve obstacle avoidance trajectory planning for static obstacles and low-speed moving obstacles in low-speed scenarios,with all trajectories meeting comfort requirements and demonstrating good trackability.
维普
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