Paper Info
Title
Autonomous Parking Of Vehicle Fleet In Tight Environments
Abstract
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 observe that when parking large vehicle fleets, a phenomenon similar to Braess's paradox occurs.
Year
DOI
Venue
2020
10.23919/ACC45564.2020.9147671
2020 AMERICAN CONTROL CONFERENCE (ACC)
DocType
ISSN
Citations 
Conference
0743-1619
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Shen Xu100.68
Zhang Xiaojing200.34
Francesco Borrelli31466147.53