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Analyzing behavior differences of occupied and non-occupied taxi drivers using floating car data

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Abstract

As the travel purpose of non-occupied taxies is to find new passengers rather than to arrive at the destination, large differences exist in the route choice behavior between the occupied and non-occupied taxies. With the assistance of geographic information system (GIS) and taxi-based floating car data (FCD), this paper investigates the behavior differences between occupied and non-occupied taxi drivers with the same origin and destination. Descriptive statistical indexes from the FCD in Shenzhen, China are explored to identify the route choice characteristics of occupied and non-occupied taxies. Then, a conditional logit model is proposed to model the quantitative relationship between drivers’ route choice and the related significant variables. Attributes of the variables related to non-occupied taxies’ observed routes are compared with the case of occupied ones. The results indicate that, compared with their counterparts, non-occupied taxi drivers generally pay more attention to choosing arterial roads and avoiding congested segments. Additionally, they are also found less sensitive to fewer traffic lights and shorter travel time. Findings from this research can assist to improve urban road network planning and traffic management.

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References

  1. Beijing Transportation Research Center. 2015 Beijing transport annual report [EB/OL]. (2016-04-06). http://www.bjtrc.org.cn/InfoCenter/NewsAttach/ aeb7c878-d31e-4f08-982f-3c17c717c87b.pdf.

    Google Scholar 

  2. BOGERS E A I, VITI F, HOOGENDOORN S P. Joint modeling of ATIS, habit and learning impacts on route choice by laboratory simulator experiments [J]. Transportation Research Record: Journal of the Transportation Research Board, 2004(1926): 189–197.

    Article  Google Scholar 

  3. AVINERI E, PRASHKER J N. Sensitivity to travel time variability: Travelers’ learning perspective [J]. Transportation Research Part C: Emerging Technologies, 2005, 13(2): 157–183.

    Article  Google Scholar 

  4. BOVY P H L, STERN E. Route choice: Way finding in transport networks [M]. Berlin: Springer, 1990.

    Book  Google Scholar 

  5. MIWA T, SAKAI T, MORIKAWA T. Route identification and travel time prediction using probe-car data [J]. International Journal of ITS Research, 2004, 2(1): 21–28.

    Google Scholar 

  6. BEN-ELIA E, EREV I, SHIFTAN Y. The combined effect of information and experience on drivers’ routechoice behavior [J]. Transportation, 2008, 35(2): 165–177.

    Article  Google Scholar 

  7. BEN-ELIA E, SHIFTAN Y. Which road do I take? A learning-based model of route-choice behavior with real-time information [J]. Transportation Research Part A: Policy and Practice, 2010, 44(4): 249–264.

    Google Scholar 

  8. BARRON G, EREV I. Small feedback-based decisions and their limited correspondence to description-based decisions [J]. Journal of Behavioral Decision Making, 2003, 16(3): 215–233.

    Article  Google Scholar 

  9. EREV I, BARRON G. On adaptation, maximization, and reinforcement learning among cognitive strategies [J]. Psychological Review, 2005, 112(4): 912–931.

    Article  Google Scholar 

  10. MOREAU A. Public transport waiting times as experienced by customers [J]. Public Transport International, 1992, 41(3): 52–71.

    Google Scholar 

  11. RAGHUBIR P, MORWITZ V G, CHAKRAVARTI A. Spatial categorization and time perception: Why does it take less time to get home? [J]. Journal of Consumer Psychology, 2011, 21(2): 192–198.

    Article  Google Scholar 

  12. TILAHUN N Y, LEVINSON D M. A moment of time: Reliability in route choice using stated preference [J]. Journal of Intelligent Transportation Systems, 2010, 14(3): 179–187.

    Article  Google Scholar 

  13. BOGERS E A I, BIERLAIRE M, HOOGENDOORN S P. Modeling learning in route choice [J]. Transportation Research Record: Journal of the Transportation Research Board, 2007(2014): 1–8.

    Article  Google Scholar 

  14. PAPINSKI D, SCOTT D M, DOHERTY S T. Exploring the route choice decision-making process: A comparison of planned and observed routes obtained using person-based GPS [J]. Transportation Research Part F: Traffic Psychology and Behavior, 2009, 12(4): 347–358.

    Article  Google Scholar 

  15. SUN D J, LIU Q, PENG Z R. Research and analysis on causality and spatial-temporal evolution of urban traffic congestions: A case study on Shenzhen of China [J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11(5): 86–93.

    Article  Google Scholar 

  16. SUN D J, ZHANG C, ZHANG L H, et al. Urban travel behavior analyses and route prediction based on floating car data [J]. Transportation Letters: The International Journal of Transportation Research, 2014, 6(3): 118–125.

    Article  Google Scholar 

  17. CASCETTA E, RUSSO F, VIOLA F A, et al. A model of route perception in urban road networks [J]. Transportation Research Part B: Methodological, 2002, 36(7): 577–592.

    Article  Google Scholar 

  18. PRATO C G. Route choice modeling: Past, present and future research directions [J]. Journal of Choice Model, 2009, 2(1): 65–100.

    Article  MathSciNet  Google Scholar 

  19. HOOD J, SALL E, CHARLTON B. A GPS-based bicycle route choice model for San Francisco, California [J]. Transportation Letters: The International Journal of Transportation Research, 2011, 3(1): 63–75.

    Article  Google Scholar 

  20. SPISSU E, MELONI I, SANJUST B. A behavioral analysis of daily route choice using GPS-based-data [J]. Transportation Research Record: Journal of the Transportation Research Board, 2011(2230): 96–103.

    Article  Google Scholar 

  21. LI D, MIWA T, MORIKAWA T. Use of private probe data in route choice analysis to explore heterogeneity in drivers’ familiarity with origin-destination pairs [J]. Transportation Research Record: Journal of the Transportation Research Board, 2013(2338): 20–28.

    Article  Google Scholar 

  22. ZHANG D Z, SUN D J, PENG Z R. A comprehensive taxi assessment index using floating car data [J]. Journal of Harbin Institute of Technology, 2014, 21(1): 7–16.

    Google Scholar 

  23. RAHMANI M, JENELIUS E, KOUTSOPOULOS H N. Non-parametric estimation of route travel time distributions from low-frequency floating car data [J]. Transportation Research Part C: Emerging Technologies, 2015, 58: 343–362.

    Article  Google Scholar 

  24. MCFADDEN D. Conditional logit analysis of qualitative choice behavior [C]//Frontiers in Econometrics. New York: Academic Press, 1974: 105–142.

    Google Scholar 

  25. SUN D J, ELEFTERIADOU L. A driver behavior based lane-changing model for urban arterial streets [J]. Transportation Science, 2014, 48(2): 184–205.

    Article  Google Scholar 

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Authors and Affiliations

  1. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Guangyue Nian  (年光跃) & Jian Sun  (孙 健)

  2. Center for UAV Applications and ITS Research, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Guangyue Nian  (年光跃), Zhe Li  (李 喆) & Jian Sun  (孙 健)

  3. Shanghai Municipal Transportation Design Institute Co. Ltd., Shanghai, 200030, China

    Zhe Li  (李 喆)

  4. Shenzhen Transportation Design and Research Institute Co. Ltd., Shenzhen, Guangdong, 518003, China

    Weiquan Zhu  (朱伟权)

Authors
  1. Guangyue Nian  (年光跃)
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  2. Zhe Li  (李 喆)
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  3. Weiquan Zhu  (朱伟权)
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  4. Jian Sun  (孙 健)
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Corresponding author

Correspondence to Jian Sun  (孙 健).

Additional information

Foundation item: the Major Project of National Social Science Foundation of China (No. 16ZDA048), the Shanghai Municipal Natural Science Foundation, China (No. 17ZR1445500), and the Humanities and Social Science Research Project of Ministry of Education, China (No. 15YJCZH148)

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Nian, G., Li, Z., Zhu, W. et al. Analyzing behavior differences of occupied and non-occupied taxi drivers using floating car data. J. Shanghai Jiaotong Univ. (Sci.) 22, 682–687 (2017). https://doi.org/10.1007/s12204-017-1890-9

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  • DOI: https://doi.org/10.1007/s12204-017-1890-9

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