Vision Approach towards Fully Self-Reverse Parking System

Some commercial vehicle models have been equipped with semi-autonomous parking systems to a certain extent. But gaps to fully automated solutions still exist and cost considerations further constrain their acceptance among consumers. In this paper, we propose a low-cost vision-based approach to a fully self-reverse parking system. It consists of four key modules: image processing incorporated with Kalman filter for consistent vehicle pose estimation, path planning ensuring a feasible path under any starting pose, a modified sliding mode controller (SMC) for smooth path following and an overall control scheme to ensure final parking accuracy. Experiment results based on 200 on-field tests under different illumination conditions showed that the system can park the vehicle accurately and consistently in all cases with a 4.8cm RMS offset distance from center line and 1.23 degrees RMS orientation deviation. With its easy setup and excellent performance, it can be implemented onto existing vehicles practically and robustly with minimal additional cost.