Distributed automatic driving trajectory tracking control strategy based on PP algorithm based on ABMSSA
Aiming at the problem that the forward looking distance of the lateral pure tracking control algorithm is greatly affected by the vehicle speed,this paper designs an improved Salp optimization algorithm to adjust and optimize the forward looking distance in the pure tracking control in real time.Firstly,based on the pure tracking control model,the objective function of the improved Salp optimization algorithm is designed with the lateral error as the main decision parameter,and Brownian motion and adaptive weights are introduced into the algorithm to prevent falling into the local optimal solution and improve the convergence speed of the algorithm.Secondly,the longitudinal double-loop PID control algorithm is designed to track the reference speed of the vehicle.Finally,the proposed pure tracking control algorithm based on distributed longitudinal double-loop PID control algorithm and lateral forward distance optimization is verified experimentally on the actual platform of the agent vehicle,and multiple groups of comparison experiments are set up.The results show that the pure tracking trajectory tracking control algorithm based on forward looking distance optimization has the best control performance,in which the maximum lateral error is 0.068 m and the average lateral error is 0.014 m,and the control accuracy is improved by 24.73％compared with fuzzy optimization.
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