Dynamic taxi pricing

Cheng Zeng, Nir Oren

Research output: Contribution to conferenceUnpublished paperpeer-review

13 Citations (Scopus)
59 Downloads (Pure)

Abstract

Taxi journeys are usually priced according to the distance covered and time taken for the trip. Such a fixed cost strategy is simple to understand, but does not take into account the likelihood that a taxi can pick up additional pas- sengers at the original passenger’s destination. In this paper we investigate dynamic taxi pricing strategies. By using do- main knowledge, such strategies discount trips to locations containing many potential passengers, and increase fares to those areas with few potential passengers. Identifying a closed form optimal dynamic pricing strategy is difficult, and by rep- resenting the domain as an MDP, we can identify an optimal strategy for specific domains. We empirically compare such dynamic pricing strategies with fixed cost strategies, and sug- gest future extensions to this work.
Original languageEnglish
Pages1135-1136
Number of pages2
DOIs
Publication statusPublished - Aug 2014
EventEuropean Conference on Artificial Intelligence (ECAI-2014) - Prague, United Kingdom
Duration: 18 Aug 201422 Aug 2014

Conference

ConferenceEuropean Conference on Artificial Intelligence (ECAI-2014)
Country/TerritoryUnited Kingdom
CityPrague
Period18/08/1422/08/14

Bibliographical note

This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License.

This research is supported by the award made by the RCUK Digital
Economy theme to the dot.rural Digital Economy Hub, award
reference: EP/G066051/1.

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