Optimizing multi-class fleet compositions for shared Mobility-as-a-Service

Optimizing multi-class fleet compositions for shared Mobility-as-a-Service

Wallar, Alex (Massachusetts Institute of Technology)
Schwarting, Wilko (Massachusetts Institute of Technology)
Alonso-Mora, J. (TU Delft Learning & Autonomous Control)
Rus, Daniela (Massachusetts Institute of Technology)

2019

Mobility-as-a-Service (MaaS) systems are transforming the way society moves. The introduction and adoption of pooled ride-sharing has revolutionized urban transit with the potential of reducing vehicle congestion, improving accessibility and flexibility of a city's transportation infrastructure. Recently developed algorithms can compute routes for vehicles in realtime for a city-scale volume of requests, as well as optimize fleet sizes for MaaS systems that allow requests to share vehicles. Nonetheless, they are not capable of reasoning about the composition of a fleet and their varying capacity classes. In this paper, we present a method to not only optimize fleet sizes, but also their multi-class composition for MaaS systems that allow requests to share vehicles. We present an algorithm to determine how many vehicles of each class and capacity are needed, where they should be initialized, and how they should be routed to service all the travel demand for a given period of time. The algorithm maximizes utilization while reducing the total number of vehicles and incorporates constraints on wait- times and travel-delays. Finally, we evaluate the effectiveness of the algorithm for multi-class fleets with pooled ride-sharing using 426,908 historical taxi requests from Manhattan and 187,243 downtown Singapore. We show fleets comprised of vehicles with smaller capacities can reduce the total travel delay by 10% in Manhattan whereas larger capacity fleets in downtown Singapore contribute to a 9% reduction in the total waiting time.

http://resolver.tudelft.nl/uuid:4ead7363-1f60-4dc1-8eda-d0a99b39135c

https://doi.org/10.1109/ITSC.2019.8916904

IEEE, Piscataway, NJ, USA

2020-05-28

978-1-5386-7024-8

Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC 2019)

22nd IEEE International Conference on Intelligent Transportation Systems, ITSC 2019, 2019-10-27 → 2019-10-30, Auckland, New Zealand

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.

Institutional Repository

conference paper

© 2019 Alex Wallar, Wilko Schwarting, J. Alonso-Mora, Daniela Rus