Parking Planning

Parking planning research focuses on developing efficient and reliable automated parking systems for autonomous vehicles and optimizing parking allocation in large-scale events. Current efforts concentrate on improving path planning algorithms, such as A* and its variants, incorporating computer vision (e.g., Bird's Eye View perception and fisheye cameras) and leveraging machine learning techniques like imitation learning and reinforcement learning for both single and multi-agent parking scenarios. These advancements aim to enhance parking success rates, reduce parking time, and improve safety, ultimately impacting the design of autonomous vehicles and the management of parking infrastructure in urban environments.