Considering that it is difficult for a single PID controller to adapt to different vehicle speeds in the context of vehicle path lateral tracking control, this paper proposes a segmented fuzzy PID controller based on particle swarm optimization (PSO) and on the genetic algorithm (GA), namely the hybrid optimization algorithm PCAG. Firstly, the vehicle speed is divided into several intervals, and different PID controller parameters are used for each interval. Secondly, in order to reduce the overshoot and stabilization time, the proposed PCAG algorithm is employed, which is a combination of PSO, particle swarm optimization with convergence factor (PSO-CF), adaptive particle swarm optimization (APSO) and GA. Further on, the PID controller parameters of different speed ranges are adjusted through this algorithm. Finally, in order to make up for the shortcomings of a single PID controller in the context of time-varying vehicle speed control, a fuzzy controller is employed with the purpose of compensating the parameters of the PID controller, so that the controller could adapt to a wider range of vehicle speeds. The simulation results show that the convergence speed and optimization ability of the proposed PCAG are higher than those of PSO. In addition, the segmented fuzzy PID controller optimized by PCAG can adapt to different vehicle speeds and features an excellent path tracking accuracy.

In order to increase speed and efficiency of making line markings, a vision-navigation-based self-optimizing control system is proposed for an unmanned line marking machine (ULMM). A new Haar-like-feature based algorithm is used to detect a guide line (GL) for the ULMM, and to reduce the influence of complex road surfaces and light. For the problems of an inaccurate ULMM model and local navigation information, an online self-optimizing control algorithm is presented, and its self-learning rules are given. Results of simulations and real machine experiments reveal that the proposed navigation algorithm accurately detects the GL, and the precision of the control system satisfies the requirements of the line marking work.