Research on Destination Prediction for Urban Taxi based on GPS Trajectory

doi:10.23940/ijpe.17.04.p20.530539

Abstract

Abstract:

Researching on destination prediction has a particularly important influence on the location-based services' popularization. The traditional destination prediction algorithm is to retrieve the historical trajectory data to find the same trajectory sequences as the query trajectory and then derive the most likely location to be the predicted result. However, due to the limitation of the historical trajectory data, this method has low efficiency and accuracy. Thus, in this paper, we propose the Prediction algorithm based on time (PBT algorithm), which considers the influence of the factor of time on destination prediction. Experiments based on real data show that in terms of destination prediction, the PBT algorithm not only alleviates the limitation of the historical data in the traditional algorithm to make the results more realistic, but also is more effective.

Submitted on February 14, 2017; Revised on May 3, 2017; Accepted on June 15, 2017
References: 11

Meng Zhang, Yongjian Yang, Liping Huang, and Xiaopeng Zhang. Research on Destination Prediction for Urban Taxi based on GPS Trajectory [J]. Int J Performability Eng, 2017, 13(4): 530-539.

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References 0

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