Path Tracking Control Of Unmanned Vehicle Based On Driver Model

With the accelerated integration of the automobile industry and electronic information industry, automobile began to develop to the direction of electronic, multimedia and intelligent. So, unmanned vehicles have become one of the h world’s automotive research hotspots gradually. The path tracking is one of the main contents of the unmanned vehicle; its main purpose is to track the target path, at the same time, ensuring traffic safety and comfort. It is the underlying control system in the unmanned vehicle architecture, which directly affects the ability to execute of the intelligent behavior of unmanned vehicle; the main content which is controller designing in order to ensure automobile’s actual path in accordance with the pre-designed path.This thesis studies the basic content of the path tracking control of unmanned vehicle based on driver model in detail. Because driver model of path tracking with high precision does not consider driver’s neural response lag and handling response lag, in this thesis, considering on the basis of these two lag, designing a model reference adaptive PID controller to correct this driver model, get the general model to reflect the characteristics of driver’s behavior, in order to verify this model can better track the target path, for the pre-designed path-double lane change and sine simulation path, using CARSIM and MATLAB/SIMULINK software conduct co-simulation, the simulation results show:model reference adaptive PID controller of the driver optimal preview lateral acceleration model tracks the target path well under the different speeds, when the speed is30km/h, the controller’s error is less than0.1m. Compared with PID controller of the driver optimal preview lateral acceleration model, the former tracks better.