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.
Highlights
As a low-carbon travelling mode, walking has acquired more and more attention
On the basis of trying to consider the comprehensive influencing factors of Pedestrian Level of Service (PLOS) on sidewalks, the significant influencing factors under different pedestrian flow rates were extracted with Spearman rank correlation method
In order to better describe the influencing degree of different factors and to present the integrated affecting result, a comprehensive evaluation model with multi-factors for PLOS on sidewalks was established based on different pedestrian flow rates, and the fuzzy neural network method was used to train it
Summary
As a low-carbon travelling mode, walking has acquired more and more attention. A scientific evaluation method for Pedestrian Level of Service (PLOS) on sidewalks provides the most fundamental theoretical support for creating excellent walking environment. The Traffic Engineering Manual (CHTS 1998) adjusted the classification criteria according to the actual road conditions in China This kind of model only considered pedestrians’ travelling demand from the perspective of traffic flow, while it neglected other influencing factors on pedestrians. Bian et al (2007) comprehensively considered traffic conditions, road facility conditions and environmental conditions and established a linear regression model for evaluating PLOS. Pedestrian flow rate can present the result of the interaction of pedestrian volume and the width of sidewalks effectively, so that it could be considered as the basic influencing factor affecting PLOS on sidewalks. This paper classified the levels of pedestrian flow rate according to the pedestrians’ traffic states On this basis, significant influencing factors of pedestrians’ satisfaction were extracted. The evaluation index system and the evaluation model with the impact of multi-factors of PLOS on sidewalks could be established under each levels of pedestrian flow rate
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