Application of Particle Swarm Optimization Algorithm in Intelligent Vehicle Trajectory Tracking
Aiming at the cooperative control problem of local planning and path tracking of intelligent vehicles,a model predic-tive control(MPC)method based on Improved Particle Swarm Optimization(IPSO)is proposed.Firstly,the model predictive control is combined with the artificial potential field(APF),and the time-varying safety constraint is regarded as the range of repulsion force and the asymmetric Lane potential field function.The collision free path is obtained by treating the time-varying safety constraint as the range of repulsion force and the asymmetric Lane potential field function.On this basis,APF is combined with IPSO-MPC.The pseudo speed programming algorithm is used to deal with the constraints of traffic lights and moving ob-stacles,so as to effectively solve the path optimization problem.Simulation results verify the effectiveness of the algorithm,which has obvious advantages compared with general algorithms.
Particle Swarm OptimizationVehicle Track TrackingLocal PlanningArtificial Potential FieldModel Predictive Control
NETL
NSTL
万方数据
维普
