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A novel approach to independent taxi scheduling problem based on stable matching

Author

Listed:
  • Ruibin Bai

    (University of Nottingham Ningbo, Ningbo, China)

  • Jiawei Li

    (University of Nottingham, Nottingham, UK)

  • Jason A D Atkin

    (University of Nottingham, Nottingham, UK)

  • Graham Kendall

    (1] University of Nottingham, Nottingham, UK[2] University of Nottingham Malaysia Campus, Malaysia)

Abstract

This paper describes a taxi scheduling system, which aims to improve the overall efficiency of the system, both from the perspective of the drivers and the customers. This is of particular relevance to Chinese cities, where hailing a taxi on the street is by far the most common way in which taxis are requested, since the majority of taxi drivers operate independently, rather than working for a company. The mobile phone and Global Positioning System-based taxi scheduling system, which is described in this paper, aims to provide a decision support system for taxi drivers and facilitates direct information exchange between taxi drivers and passengers, while allowing drivers to remain independent. The taxi scheduling problem is considered to be a non-cooperative game between taxi drivers and a description of this problem is given. We adopt an efficient algorithm to discover a Nash equilibrium, such that each taxi driver and passenger cannot benefit from changing their assigned partner. Two computational examples are given to illustrate the effectiveness of the approach.

Suggested Citation

  • Ruibin Bai & Jiawei Li & Jason A D Atkin & Graham Kendall, 2014. "A novel approach to independent taxi scheduling problem based on stable matching," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(10), pages 1501-1510, October.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:10:p:1501-1510
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    Citations

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    Cited by:

    1. André de Palma & Patrick Stokkink & Nikolas Geroliminis, 2020. "Influence of Dynamic Congestion on Carpooling Matching," THEMA Working Papers 2020-12, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    2. Zixuan Peng & Wenxuan Shan & Peng Jia & Bin Yu & Yonglei Jiang & Baozhen Yao, 2020. "Stable ride-sharing matching for the commuters with payment design," Transportation, Springer, vol. 47(1), pages 1-21, February.
    3. de Palma, André & Stokkink, Patrick & Geroliminis, Nikolas, 2022. "Influence of dynamic congestion with scheduling preferences on carpooling matching with heterogeneous users," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 479-498.
    4. Rajendran, Suchithra & Zack, Joshua, 2019. "Insights on strategic air taxi network infrastructure locations using an iterative constrained clustering approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 470-505.
    5. Egan, Malcolm & Jakob, Michal, 2016. "Market mechanism design for profitable on-demand transport services," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 178-195.
    6. Zhan, Xingbin & Szeto, W.Y. & (Michael) Chen, Xiqun, 2022. "The dynamic ride-hailing sharing problem with multiple vehicle types and user classes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).

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