Automatic Parking Model Based on Segmented Multi-Objective Optimal Trajectory Planning

The automatic parking function of an unmanned vehicle is studied, which provides a parking trajectory with high precision, high safety, high comfort, high efficiency and low complexity. Firstly, an unmanned passenger car and an open parking lot in a city are selected as the research objects. Secondly, an optimal trajectory is defined, proposing four indicators of rationality, safety, ergonomics and comfort, and quantifying each indicator to construct an optimal trajectory decision model. Thirdly, segmented multi-objective optimal trajectory planning is carried out, by reversing the trajectory planning and discretizing the trajectory arc length, and by subdividing the optimal decision into each step length, front wheel rotation angle and driving direction at each moment to form a combined decision. Finally, the trajectory is simulated by MATLAB simulation, and the optimal parking trajectory for parallel, perpendicular and inclined parking spaces is obtained by solving.