Understanding Taxi Service Strategies From Taxi GPS Traces

IEEE Transactions on Intelligent Transportation Systems(2015)

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摘要
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,1 which demonstrates that the extracted taxi service strategies with our proposed approach well characterize the driving behavior and performance of taxi drivers.
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关键词
historical time-stamped gps traces,global positioning system,correlation evaluation,passenger-searching strategies,road vehicles,efficient taxi service strategies,taxi gps trace mining,taxi gps traces,traffic engineering computing,service strategies,china,taxi trajectory mining,large-scale gps historical database,matrix algebra,inefficient taxi service strategies,revenue prediction,behavioural sciences computing,feature matrix,data mining,driving behavior,crowd intelligence,service-region preference,passenger-delivery strategies,location,trajectory,handover,revenues,correlation,economic efficiency
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