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Level of Service Model of the Non-Motorized Vehicle Crossing the Signalized Intersection Based on Riders’ Perception Data

Author

Listed:
  • Xiaofei Ye

    (Ningbo Port Trade Cooperation and Development Collaborative Innovation Center, Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China)

  • Yi Zhu

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China)

  • Tao Wang

    (School of Architecture and Transportation, Guilin University of Electronic Technology, Guilin 541004, China)

  • Xingchen Yan

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Jun Chen

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Bin Ran

    (Department of Civil and Environmental Engineering, University of Wisconsin–Madison, Madison, WI 53706, USA)

Abstract

This article aims to analyze the factors affecting the LOS (level of service) of non-motorized vehicles crossing the signalized intersection and to construct an appropriate method to evaluate the LOS. Aiming at the mixed non-motorized traffic flow of electric vehicles and bicycles in the Chinese metropolis, the delay model in the highway capacity manual (HCM) was modified by taking two new factors into account: the pedestrian traffic rule compliance rate and the fuzzy perception of arrival rate in reality. The results show that the data obtained by the modified model are more consistent with the actual one. Next, a comparison was established between the linear regression method and cumulative logistic regression to determine the variables that affect the LOS, and finally, a LOS evaluation index system based on threshold schemes was defined. The recommended LOS model can provide corresponding references for traffic engineers who seek to improve the level of service in urban intersections.

Suggested Citation

  • Xiaofei Ye & Yi Zhu & Tao Wang & Xingchen Yan & Jun Chen & Bin Ran, 2022. "Level of Service Model of the Non-Motorized Vehicle Crossing the Signalized Intersection Based on Riders’ Perception Data," IJERPH, MDPI, vol. 19(8), pages 1-17, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4534-:d:790191
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    References listed on IDEAS

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    Cited by:

    1. Lining Liu & Xiaofei Ye & Tao Wang & Xingchen Yan & Jun Chen & Bin Ran, 2022. "Key Factors Analysis of Severity of Automobile to Two-Wheeler Traffic Accidents Based on Bayesian Network," IJERPH, MDPI, vol. 19(10), pages 1-17, May.
    2. Hiroki Onishi & Makoto Fujiu & Yuma Morisaki & Junichi Takayama, 2022. "Analysis of the Relationship between Age and Violation of Traffic Laws and Ordinances in Traffic Accidents on Children," Sustainability, MDPI, vol. 14(19), pages 1-13, October.

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