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Optimization of the Revenue of the New York City Taxi Service using Markov Decision Processes

Authors:
Jacky Li
Sandjai Bhulai
Theresia van Essen

Keywords: New York taxi service; revenue optimization; optimal routing; Markov decision processes

Abstract:
Taxis are an essential component of the transportation system in most urban centers. The ability to optimize the efficiency of routing represents an opportunity to increase revenues for taxi drivers. The vacant taxis cruising on the roads are not only wasting fuel consumption, the time of a taxi driver, and create unnecessary carbon emissions but also generate additional traffic in the city. In this paper, we use Markov Decision Processes to optimize the revenues of taxi drivers by better routing. We present a case study with New York City Taxi data with several experimental evaluations of our model. We achieve approximately 10% improvement in efficiency using data from the month of January. The results also provide a better understanding of the several different time shifts. These data may have important implications in the field of self-driving vehicles.

Pages: 47 to 52

Copyright: Copyright (c) IARIA, 2017

Publication date: November 12, 2017

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-603-3

Location: Barcelona, Spain

Dates: from November 12, 2017 to November 16, 2017