Model Predictive Motion Planning for Autonomous Vehicle in Mid-high Overtaking Scene

Planning a safe and comfortable trajectory in complex traffic scenarios is very challenging because there are many constraints to consider, such as vehicle dynamics constraints and traffic rules. The existing method is either to search for the trajectory in the lattice space, or to combine the front-end coarse path searching and the back-end trajectory smoothing. These methods only constrain the position, slope and second derivative of the trajectory externally, so that the planned trajectory is either too conservative to play the vehicle’s motion performance or is so aggressive that the controller cannot track. We propose a motion planning method based on vehicle dynamics model prediction to solve an optimization problem involving vehicle dynamics constraints, safety and comfort requirements. Simulation results demonstrate that the proposed method can plan safe and smooth overtaking trajectory. Also it has good real-time performance and can run stably at 15 Hz.