Fundamental performance limits and efficient polices for Transportation-On-Demand systems
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Frazzoli-2010-Fundamental performance limits and efficient.pdf
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339.39 KB
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Author(s)
Pavone, Marco
Treleaven, Kyle Ballantyne
Frazzoli, Emilio
Date Issued
February 2011
Journal
49th IEEE Conference on Decision and Control (CDC), 2010
Publisher
Institute of Electrical and Electronics Engineers
Citation
Pavone, Marco, Kyle Treleaven, and Emilio Frazzoli. “Fundamental Performance Limits and Efficient Polices for Transportation-On-Demand Systems.” 49th IEEE Conference on Decision and Control (CDC). Atlanta, GA, USA, 2010. 5622-5629. © 2011 IEEE
Version
Final published version
Abstract
Transportation-On-Demand (TOD) systems, where users generate requests for transportation from a pick-up point to a delivery point, are already very popular and are expected to increase in usage dramatically as the inconvenience of privately-owned cars in metropolitan areas becomes excessive. Routing service vehicles through customers is usually accomplished with heuristic algorithms. In this paper we study TOD systems in a formal setting that allows us to characterize fundamental performance limits and devise dynamic routing policies with provable performance guarantees. Specifically, we study TOD systems in the form of a unit-capacity, multiple-vehicle dynamic pick-up and delivery problem, whereby pick-up requests arrive according to a Poisson process and are randomly located according to a general probability density. Corresponding delivery locations are also randomly distributed according to a general probability density, and a number of unit-capacity vehicles must transport demands from their pick-up locations to their delivery locations. We derive insightful fundamental bounds on the steady-state waiting times for the demands, and we devise constant-factor optimal dynamic routing policies. Simulation results are presented and discussed.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/CDC.2010.5717552
