This study proposes a motion planning and control system based on collision risk potential prediction
characteristics of experienced drivers. Recently, automatic braking systems have been deployed in current automotive markets. However, the existing systems cannot avoid collisions in critical scenario such as a pedestrian suddenly darting out from a poor-visibility blind corner. By optimizing the potential field function in the framework of optimal control theory, the desired yaw rate and the desired longitudinal deceleration are theoretically calculated. Finally, the validity of the proposed motion planning and control system is verified by comparing the simulation results with the actual driving data by experienced drivers.
This paper presents a trajectory generation method for the automatic parallel parking. In the first place, a continuouscurvature path satisfying geometric constraints is generated. During the automated tracking of the trajectory, following errors might appear. Then, if necessary, a new trajectory is generated to correct these errors. The regeneration method presents the same advantages as for the initial path generation (continuous curvature) and allows correcting the deviation of the vehicle. Moreover, the complete functional architecture including the path generation is presented in this article to illustrate the execution of the parking maneuver.