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Testing the proportionality condition with taxi trajectory data

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  • Xie, Jun
  • (Marco) Nie, Yu
  • Liu, Xiaobo

Abstract

The proportionality condition has been widely used to produce a unique path flow solution in the user equilibrium traffic assignment problem. However, it remains an open question whether and to what extent this condition accords to real travel behavior. This paper attempts to validate the behavioural realism of the proportionality condition using more than 27 million route choice observations obtained by mining a large taxi trajectory data set. A method is first developed to uncover more than three hundred valid paired alternative segments (PAS), on which the proportionality condition is tested by performing linear regression analysis and chi-square tests. The results show that the majority of the PASs tested (up to 85%) satisfy the proportionality condition at a reasonable level of statistical significance.

Suggested Citation

  • Xie, Jun & (Marco) Nie, Yu & Liu, Xiaobo, 2017. "Testing the proportionality condition with taxi trajectory data," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 583-601.
    • Handle: RePEc:eee:transb:v:104:y:2017:i:c:p:583-601
    DOI: 10.1016/j.trb.2017.05.003
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    References listed on IDEAS

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    1. Liu, Siyuan & Qu, Qiang, 2016. "Dynamic collective routing using crowdsourcing data," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 450-469.
    2. Bar-Gera, Hillel & Boyce, David & Nie, Yu (Marco), 2012. "User-equilibrium route flows and the condition of proportionality," Transportation Research Part B: Methodological, Elsevier, vol. 46(3), pages 440-462.
    3. Hillel Bar-Gera, 2006. "Primal Method for Determining the Most Likely Route Flows in Large Road Networks," Transportation Science, INFORMS, vol. 40(3), pages 269-286, August.
    4. Xie, Chi, 2016. "New insights and improvements of using paired alternative segments for traffic assignmentAuthor-Name: Xie, Jun," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 406-424.
    5. Bar-Gera, Hillel, 2010. "Traffic assignment by paired alternative segments," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1022-1046, September.
    6. Borchers, Marlies & Breeuwsma, Paul & Kern, Walter & Slootbeek, Jaap & Still, Georg & Tibben, Wouter, 2015. "Traffic user equilibrium and proportionality," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 149-160.
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    Cited by:

    1. Zheng, Hongyu & Zhang, Kenan & Nie, Yu (Marco), 2021. "Plunge and rebound of a taxi market through COVID-19 lockdown: Lessons learned from Shenzhen, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 349-366.
    2. Jun Xie & Yu (Marco) Nie, 2019. "A New Algorithm for Achieving Proportionality in User Equilibrium Traffic Assignment," Transportation Science, INFORMS, vol. 53(2), pages 566-584, March.
    3. Yu, Xinlian & Gao, Song & Hu, Xianbiao & Park, Hyoshin, 2019. "A Markov decision process approach to vacant taxi routing with e-hailing," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 114-134.
    4. Wang, Jianbiao & Miwa, Tomio & Morikawa, Takayuki, 2023. "Recursive decomposition probability model for demand estimation of street-hailing taxis utilizing GPS trajectory data," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 171-195.
    5. Jiayang Li & Qianni Wang & Liyang Feng & Jun Xie & Yu Marco Nie, 2024. "A Day-to-Day Dynamical Approach to the Most Likely User Equilibrium Problem," Papers 2401.08013, arXiv.org.
    6. Noruzoliaee, Mohamadhossein & Zou, Bo & Zhou, Yan (Joann), 2021. "Truck platooning in the U.S. national road network: A system-level modeling approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).

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