Research on Active Obstacle Avoidance of Intelligent Networked Vehicles Based on Adaptive Model Prediction
This paper takes intelligent networked vehicles as the research object,designs an adaptive model,and uses MPC control algorithm to accurately and intelligently schedule obstacle avoidance strategies and related behaviors during vehicle driving.With the help of PSD triangulation method,the position information of related obstacles in the road is collected,and the data processing and control based on AT89C52 module is carried out to carry out active obstacle avoidance predictive control for vehicles.The simulation experiments under different working conditions show that the active obstacle avoidance strategy of intelligent networked vehicles based on MPC adaptive model prediction has good application value,and the obstacle avoidance is accurate,which verifies the effective libido practicability of the method.
NETL
NSTL
万方数据
维普
