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...

Full description

Bibliographic Details
Main Authors: Smith, Stephen L. (Author), Pavone, Marco (Contributor), Schwager, Mac (Author), Frazzoli, Emilio (Contributor), Rus, Daniela L. (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: American Automatic Control Council, 2013-10-25T18:10:55Z.
Subjects:
Online Access:Get fulltext