The Intelligent Vehicle Path Planning And Motion Control Research Based On The Immune Mechanism

Intelligent vehicles are a hot topic at the present stage, and in a number of key technologies to achieve a breakthrough, there will likely be officially driving on the road in the next decade. The path planning as one of the important technologies in intelligent vehicle, it’s not only in vehicles but also in intelligent mobile robot that has a wide range of applications. With the development of artificial intelligence, it’s resulting in a lot of intelligent algorithms and applications in various fields. Artificial immune system is designed based on biological immune system model. It has a strong learning and memory, information processing, feature extraction and host defense capability. It provides new concepts, theories and methods for engineering applications, so it is widely used in many industries.In this paper, using the grid method establish a model of intelligent vehicle work environment, in which build an intelligent vehicle dynamic dual-mode global path planning based on clonal selection algorithm. In the static obstacles environment, the model used for simple and complex path planning under both environments and simulation experiments show that the algorithm can simultaneously achieve local optimization global convergence and plan out an optimal path. The presence of dynamic obstacles environment, first using the first heavy clonal selection algorithm path planning; Using the second re-clonal selection algorithm obstacle avoidance generate a new path when obstacle during exercise in a feasible path.Global path planning can not be achieved partial details of the deal, so local path planning algorithm studied further to find local optimal path under global optimal path. It is established a vehicle model in matlab, using dynamic selection immune network model, variability, addresses how to automatically solve the real-time online adjustment parameters and having strong adaptability, and can effectively and fast path planning. Immune network added into fuzzy PID controller, that make it have a strong anti-interference, fast response and make the PID parameter tuning function has been greatly enhanced.It designed a real-time data acquisition system about Gyroscope, and format a test platform which achieve vehicle heading and position. In this paper, combining the path planning algorithm and the test platform,we have a comparative test platform for intelligent vehicle control by adding artificial immune into fuzzy PID algorithm, that improve the response speed of the vehicle to control the direction、 shorten the path and travel time distance in the planning process.