  The problem of autonomous parking of vehicle fleets is addressed in this
paper. We present a system-level modeling and control framework which allows
investigating different vehicle parking strategies while taking into account
path planning and collision avoidance. The proposed approach decouples the
problem into a centralized parking spot allocation and path generation, and a
decentralized collision avoidance control. This paper presents the hierarchical
framework and algorithmic details. Extensive simulations are used to assess
several allocation strategies in terms of total fleet parking time and queue
length. In particular, we describe how Braess's paradox can be observed for
parking vehicle fleets.
