The Research About Path Planning And Tracking Control Of The Intelligent Vehicle

Vehicle is indispensable in people’s daily life. While providing convenience for us, it also brings about a great challenge to the traffic safety. The intelligent vehicle attracts more and more attentions, and has been one research hotspot in the field of vehicle. Its core technology mainly includes environmental perception, path planning and tracking control. The path planning algorithm and tracking control algorithm have been studied in this paper. Work is as follows.(1) The path planned by the original intelligent water drops is not smooth. The selection strategy and updating mechanism of the original intelligent water drops algorithm are improved to strengthen its ability. Furthermore, the comparative analysis of the simulation results, which are about the original intelligent water drops algorithm, the improved intelligent water drops algorithm, the ant colony optimization algorithm, the particle swarm optimization and artificial fish swarm algorithm, verified the effectiveness of the improved intelligent water drops algorithm. In addition, the improved algorithm was applied in the local path planning field of autonomous vehicle, which showed the satisfied results.(2) To control a vehicle model to track a path, a steering control block was constructed according to the model predictive control algorithm. The multiple points preview principle and the rolling optimization improve its adaptation performance about speed. The different Path following experiments on different speeds showed that the controller can simulate an actual driver to steer a car. It is feasible to be used in steering a car because it is better than the steering control block of the Carsim.(3) At present the research about speed control is mainly focused on the constant speed cruise, which may not be safe in a sharp turn. This paper has come up with the adaptive velocity control function based on the multiple points prediction. This method can predict the limit speed ahead in real time and calculate the target speed using the Quadratic Programming. The experimental results showed that the speed control algorithm can avoid the danger of the instability when in a tight corners.(4) For controlling a vehicle to drive by itself completely, the steering control algorithm and the velocity control algorithm are used to control a vehicle together. The experimental results showed that the method can improve the driving safety because of its adaptive speed control.