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Analyzing Spatiotemporal Characteristics of Taxi Drivers’ Cognition to Passenger Source Based on Trajectory Data

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Web and Wireless Geographical Information Systems (W2GIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12473))

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Abstract

Seeking passengers is a kind of behavior of taxi drivers with clear purposes. They always need to make decisions on where to seek the next passenger after finishing a trip. Experienced drivers are capable to capture passenger source within a short time to reduce no-load time. Most of the existing literatures focus on simulating or analyzing movement patterns of taxi drivers. This research proposes a method of analyzing spatiotemporal characteristics of taxi drivers’ cognition to passenger source. Using a seven-day taxi trajectory data set collected in Beijing, an index CLPS is introduced to evaluate taxi drivers’ cognitive level to passenger source. Based on this, spatiotemporal distribution of top drivers’ cognition to passenger source is explored. The results of the research show that top drivers’ cognition to passenger source has obvious spatiotemporal distribution features. This research is expected to provide new ways for understanding human spatial cognition.

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Acknowledgement

This research was funded by National Natural Science Foundation of China (No. 41971355), the Open Project of State Key Laboratory of Resources and Environmental Information System and Yueqi Young Scholar Project of China University of Mining and Technology at Beijing.

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Authors and Affiliations

  1. College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, Beijing, 100083, China

    Zihao Wang, Jun Li, Yan Zhu, Zhenwei Li & Wenle Lu

  2. State Key Laboratory of Resources and Environmental Information System, Chinese Academy of Sciences, Beijing, 100101, China

    Jun Li

Authors
  1. Zihao Wang
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  2. Jun Li
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  3. Yan Zhu
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  4. Zhenwei Li
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  5. Wenle Lu
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Corresponding author

Correspondence to Jun Li .

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Editors and Affiliations

  1. University of Naples Federico II, Naples, Italy

    Sergio Di Martino

  2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

    Zhixiang Fang

  3. Department of Computer Science and Engineering, Pusan National University, Pusan, Korea (Republic of)

    Ki-Joune Li

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Wang, Z., Li, J., Zhu, Y., Li, Z., Lu, W. (2020). Analyzing Spatiotemporal Characteristics of Taxi Drivers’ Cognition to Passenger Source Based on Trajectory Data. In: Di Martino, S., Fang, Z., Li, KJ. (eds) Web and Wireless Geographical Information Systems. W2GIS 2020. Lecture Notes in Computer Science(), vol 12473. Springer, Cham. https://doi.org/10.1007/978-3-030-60952-8_9

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  • DOI: https://doi.org/10.1007/978-3-030-60952-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60951-1

  • Online ISBN: 978-3-030-60952-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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