Understanding taxi service strategies from taxi GPS traces

Daqing Zhang, Lin Sun, Bin Li, Chao Chen, Gang Pan, Shijian Li, Zhaohui Wu

Research output: Contribution to journalArticlepeer-review

Abstract

Taxi service strategies, as the crowd intelligence of massive taxi drivers, are hidden in their historical time-stamped GPS traces. Mining GPS traces to understand the service strategies of skilled taxi drivers can benefit the drivers themselves, passengers, and city planners in a number of ways. This paper intends to uncover the efficient and inefficient taxi service strategies based on a large-scale GPS historical database of approximately 7600 taxis over one year in a city in China. First, we separate the GPS traces of individual taxi drivers and link them with the revenue generated. Second, we investigate the taxi service strategies from three perspectives, namely, passenger-searching strategies, passenger-delivery strategies, and service-region preference. Finally, we represent the taxi service strategies with a feature matrix and evaluate the correlation between service strategies and revenue, informing which strategies are efficient or inefficient. We predict the revenue of taxi drivers based on their strategies and achieve a prediction residual as less as 2.35 RMB/h, The currency unit in China; 1 RMB U.S. 0.17.

Original languageEnglish
Article number6841047
Pages (from-to)123-135
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Volume16
Issue number1
DOIs
Publication statusPublished - 1 Feb 2015
Externally publishedYes

Keywords

  • Revenue prediction
  • Taxi trajectory mining
  • service strategies
  • taxi GPS traces

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