State-statistical model based trajectory-band planning in urban environment

In the traditional trajectory planning methods, a feasible, collision-free trajectory is generated to guide the vehicle. But generally the vehicle cannot follow the trajectory without tracking deviation because of the vehicle kinematical constraints and the performance of control algorithm. In this paper, State-Statistical Model (SSM) based trajectory-band planning method is proposed to predict the vehicle motion during the vehicle tracks the trajectory. In this method, the statistics of historical states are used to build the SSM which is a normal distribution model of tracking deviation in different segments of curvature radius and velocity. According to the SSM, the inaccessible states of vehicle can be obtained to search the best trajectory and the tracking deviation boundary can be calculated on the trajectory. Then the best trajectory is used as the base line to generate the trajectory-band of which the halfband width is the deviation boundary value. As a result, the trajectory-band can represent the maximum range of vehicle motion accurately.