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Detecting urban road network accessibility problems using taxi GPS data

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  • Cui, JianXun
  • Liu, Feng
  • Janssens, Davy
  • An, Shi
  • Wets, Geert
  • Cools, Mario

Abstract

Urban population growth and economic development have led to the creation of new communities, jobs and services at places where the existing road network might not cover or efficiently handle traffic. This generates isolated pockets of areas which are difficult to reach through the transport system. To address this accessibility problem, we have developed a novel approach to systematically examine the current urban land use and road network conditions as well as to identify poorly connected regions, using GPS data collected from taxis. This method is composed of four major steps. First, city-wide passenger travel demand patterns and travel times are modeled based on GPS trajectories. Upon this model, high density residential regions are then identified, and measures to assess accessibility of each of these places are developed. Next, the regions with the lowest level of accessibility among all the residential areas are detected, and finally the detected regions are further examined and specific transport situations are analyzed.

Suggested Citation

  • Cui, JianXun & Liu, Feng & Janssens, Davy & An, Shi & Wets, Geert & Cools, Mario, 2016. "Detecting urban road network accessibility problems using taxi GPS data," Journal of Transport Geography, Elsevier, vol. 51(C), pages 147-157.
    • Handle: RePEc:eee:jotrge:v:51:y:2016:i:c:p:147-157
    DOI: 10.1016/j.jtrangeo.2015.12.007
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    References listed on IDEAS

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    10. Xuanxuan Xia & Kexin Lin & Yang Ding & Xianlei Dong & Huijun Sun & Beibei Hu, 2020. "Research on the Coupling Coordination Relationships between Urban Function Mixing Degree and Urbanization Development Level Based on Information Entropy," IJERPH, MDPI, vol. 18(1), pages 1-24, December.
    11. Sharma, Ishant & Mishra, Sabyasachee & Golias, Mihalis M. & Welch, Timothy F. & Cherry, Christopher R., 2020. "Equity of transit connectivity in Tennessee cities," Journal of Transport Geography, Elsevier, vol. 86(C).
    12. Xing, Jiping & Wu, Wei & Cheng, Qixiu & Liu, Ronghui, 2022. "Traffic state estimation of urban road networks by multi-source data fusion: Review and new insights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
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