Evaluation method for pedestrian level of service on sidewalks based on fuzzy neural network model

For the purpose of creating excellent walking environment, increasing the proportion of pedestrians and providing a planning and designing basis for the newly-built and rebuilt sidewalks, this paper proposed a comprehensive multi-factor evaluation method for pedestrian level of service on sidewalks based on the quantification of environmental factors. Firstly, pedestrians' satisfaction questionnaires survey was conducted with intercept survey method on 87 typical sidewalks covering different regions, road grades, road facility and environmental conditions. The rating scale form of the questionnaires was 10 grades and 4300 valid questionnaires were obtained. Then, the factors of traffic conditions, road facility conditions and environmental conditions which affected pedestrians' satisfaction were analyzed in detail. Image recognition and edge detection methods were used to quantify the environmental factors. Combined with Spearman rank correlation method, the 10 significant influencing factors obtained were verified. The more comprehensive and quantified multi-factors evaluation index system for pedestrian level of service on sidewalks could be proposed. Finally, aiming at the characteristics that pedestrian level of service on sidewalks and its influencing factors were multi-type variables, the fuzzy neural network method was used to establish the comprehensive evaluation model for pedestrian level of service on sidewalks. The error result showed that the accuracy of the model in this research was 0.94 which had a significant improvement compared with the existing linear regression models.