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

Alex Wallar, Wilko Schwarting, Javier Alonso-Mora, Daniela Rus

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
32 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationProceedings of the IEEE Intelligent Transportation Systems Conference (ITSC 2019)
Place of PublicationPiscataway, NJ, USA
ISBN (Electronic)978-1-5386-7024-8
Publication statusPublished - 2019
Event22nd IEEE International Conference on Intelligent Transportation Systems, ITSC 2019 - Auckland, New Zealand
Duration: 27 Oct 201930 Oct 2019


Conference22nd IEEE International Conference on Intelligent Transportation Systems, ITSC 2019
CountryNew Zealand
Internet address


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