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Analysis of Taxi Drivers’ Working Characteristics Based on GPS Trajectory Data

  • Jing YouEmail author
  • Zhen-xian Lin
  • Cheng-peng Xu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 891)

Abstract

Using the large-scale taxi GPS trajectory data mining to analyze working characteristics of taxi drivers, it can provide reference help for those who want to work in taxis. This paper proposes a method for analyzing the working characteristics of taxi drivers based on Spark data processing platform. Firstly, the GPS trajectory data are cleaned and then imported into HDFS. Secondly, taxi drivers’ work indicators and taxis’ stop points are extracted. Then, the statistical method is applied to analyze the work indicators to obtain drivers’ work feature, and the K-Means algorithm is used to cluster the stay points to get the drivers’ three meals rest and then drivers’ rest feature can be get. The results show that the Spark platform can quickly and accurately analyze the working characteristics of taxi drivers.

Keywords

Spark data processing platform Taxi GPS trajectory data Taxi drivers’ work characteristics 

Notes

Acknowledgements

This research was supported in part by Key Research and Application of Big Data Trading Market in Shaanxi Province (2016KTTSGY01-01).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Communication and Information EngineeringXi’an University of Posts and TelecommunicationsXi’anChina
  2. 2.School of ScienceXi’an University of Posts and TelecommunicationsXi’anChina
  3. 3.Institute of Internet of Things and IT-Based IndustrializationXi’an University of Posts and TelecommunicationsXi’anChina

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