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Modelling pedestrian level of service on sidewalks with multi-factors based on different pedestrian flow rates

    Shinan Shu Affiliation
    ; Yang Bian Affiliation
    ; Lin Zhao Affiliation
    ; Jian Rong Affiliation
    ; Xiaoming Liu Affiliation

Abstract

Pedestrian Level of Service (PLOS) is influenced by the factors of traffic conditions, road facility conditions and environmental conditions. Pedestrian flow rate was the key factor influencing PLOS for the reason that pedestrians’ visual scopes of pavement and the influencing degree of each influencing factor on sidewalks was differed under different pedestrian flow rates. In order to evaluate PLOS more accurately, this paper classified pedestrian flow rates into 6 stages. Then, significant influencing factors of traffic conditions, road facility conditions and environmental conditions, which influenced pedestrians’ satisfaction, were extracted respectively under each pedestrian flow rate by Spearman rank correlation method. Finally, the evaluation method of PLOS with multi-factors based on classification of pedestrian flow rates was put forward. In addition, the models got training with fuzzy neural network method. The test showed that the accuracy of the comprehensive evaluation model of PLOS under different pedestrian flow rates based on fuzzy neural network reaches to 92%, which is much higher than the model accuracy of previous researches.


First published online 20 January 2022

Keyword : pedestrian level of service (PLOS), pedestrians’ behaviour, pedestrians’ satisfaction, pedestrian flow, evaluation model with multi-factors, fuzzy neural network

How to Cite
Shu, S., Bian, Y., Zhao, L., Rong, J., & Liu, X. (2021). Modelling pedestrian level of service on sidewalks with multi-factors based on different pedestrian flow rates. Transport, 36(6), 486-498. https://doi.org/10.3846/transport.2021.16276
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Dec 31, 2021
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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