Rebalancing the rebalancers: Optimally routing vehicles and drivers in mobility-on-demand systems

In this paper we study rebalancing strategies for a mobility-on-demand urban transportation system blending customer-driven vehicles with a taxi service. In our system, a customer arrives at one of many designated stations and is transported to any other designated station, either by driving themsel...

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Bibliographic Details
Main Authors: Smith, Stephen L., Pavone, Marco, Schwager, Mac, Frazzoli, Emilio, Rus, Daniela L.
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: American Automatic Control Council 2013
Online Access:http://hdl.handle.net/1721.1/81786
https://orcid.org/0000-0001-5473-3566
https://orcid.org/0000-0002-0505-1400