Title
Vehicle rebalancing for Mobility-on-Demand systems with ride-sharing
Author
Wallar, Alex (Massachusetts Institute of Technology)
Van Der Zee, Menno (Student TU Delft)
Alonso-Mora, J. (TU Delft Learning & Autonomous Control) 
Rus, Daniela (Massachusetts Institute of Technology)
Contributor
Balaguer, Carlos (editor)
Asama, Hajime (editor)
Kragic, Danica (editor)
Lynch, Kevin (editor)
Date
2018
Abstract
Recent developments in Mobility-on-Demand (MoD) systems have demonstrated the potential of road vehicles as an efficient mode of urban transportation Newly developed algorithms can compute vehicle routes in real-time for batches of requests and allow for multiple requests to share vehicles. These algorithms have primarily focused on optimally producing vehicle schedules to pick up and drop off requests. The redistribution of idle vehicles to areas of high demand, known as rebalancing, on the contrary has received little attention in the context of ride-sharing. In this paper, we present a method to rebalance idle vehicles in a ride-sharing enabled MoD fleet. This method consists of an algorithm to optimally partition the fleet operating area into rebalancing regions, an algorithm to determine a real-time demand estimate for every region using incoming requests, and an algorithm to optimize the assignment of idle vehicles to these rebalancing regions using an integer linear program. Evaluation with historical taxi data from Manhattan shows that we can service 99.8% of taxi requests in Manhattan using 3000 vehicles with an average waiting time of 57.4 seconds and an average in-car delay of 13.7 seconds. Moreover, we can achieve a higher service rate using 2000 vehicles than prior work achieved with 3000. Furthermore, with a fleet of 3000 vehicles, we reduce the average travel delay by 86%, the average waiting time by 37%, and the amount of ignored requests by 95% compared to earlier work at the expense of an increased distance travelled by the fleet.
Subject
Schedules
Real-time systems
Delays
Partitioning algorithms
Public transportation
Automobiles
To reference this document use:
http://resolver.tudelft.nl/uuid:5e90d72c-6402-4761-a2f5-ef8fc66991cf
DOI
https://doi.org/10.1109/IROS.2018.8593743
Publisher
IEEE, Piscataway, NJ, USA
Embargo date
2019-07-07
ISBN
978-1-5386-8095-7
Source
Proceedings 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018)
Event
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018, 2018-10-01 → 2018-10-05, Madrid, Spain
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
conference paper
Rights
© 2018 Alex Wallar, Menno Van Der Zee, J. Alonso-Mora, Daniela Rus