Automated Planning and Control for High-Density Parking Lots

Abstract

Parking is a key component for efficient urban mobility with implications on congestion and the urban landscape. We propose planning strategies for automated, high-density parking lot systems that efficiently execute (i) selection of vehicle destination and (ii) conflict-free motion planning for vehicle input and output operations. The practical performance of the system is demonstrated through simulation using an empirical dataset. The system allows halving the space requirements for parking vehicles while providing fast access to vehicles and keeping low the in-park travel distances when comparing with conventional parking lots.