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Article Dans Une Revue Frontiers of Computer Science in China Année : 2012

Prediction of urban human mobility using large-scale taxi traces and its applications

Résumé

This paper investigates human mobility patterns in an urban taxi transportation system. This work focuses on predicting human mobility from discovering patterns of in the number of passenger pick-ups quantity (PUQ) from urban hotspots. This paper proposes an improved ARIMA based prediction method to forecast the spatial-temporal variation of passengers in a hotspot. Evaluation with a large-scale realworld data set of 4 000 taxis' GPS traces over one year shows a prediction error of only 5.8%. We also explore the application of the prediction approach to help drivers find their next passengers. The simulation results using historical real-world data demonstrate that, with our guidance, drivers can reduce the time taken and distance travelled, to find their next passenger, by 37.1% and 6.4%, respectively.
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Dates et versions

hal-00751328 , version 1 (13-11-2012)

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Xiaolong Li, Gang Pan, Zhaohui Wu, Guande Qi, Shijian Li, et al.. Prediction of urban human mobility using large-scale taxi traces and its applications. Frontiers of Computer Science in China, 2012, 6 (1), pp.111-121. ⟨10.1007/s11704-011-1192-6⟩. ⟨hal-00751328⟩
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