Pedestrian Road Traffic Accidents in Metropolitan Areas: GIS-Based Prediction Modelling of Cases in Mashhad, Iran
نویسندگان
چکیده
This study utilised multi-year data from 5354 incidents to predict pedestrian–road traffic accidents (PTAs) based on twelve socioeconomic and built-environment factors. The research employed the logistic regression model (LRM) fuzzy-analytical hierarchy process (FAHP) techniques evaluate assign weights each factor. susceptibility map for PTAs is generated using “Technique Order of Preference by Similarity Ideal Solution (TOPSIS)”. Subsequently, probability in 2020 was predicted real accident Markov chain (MC) cellular automata (CA-MC) models, with prediction accuracy assessed Kappa index. Building upon promising results, extrapolated forecast 2023. findings LRM demonstrated significance selected variables as predictors likelihood. approaches identified areas prone high-risk accidents. Additionally, no information (KNO) statistical value calculated both MC CA-MC which yielded values 0.94 0.88, respectively, signifying a high level accuracy. proposed methodology generalizable, identification locations can aid urban planners devising appropriate preventive measures.
منابع مشابه
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An up-to-date review of rural road accident statistics for Iran is presented The review considers sources of accident statistics in Iran and the means by which they are collected. The statistics are considered in relation to accident causal and risk factors. A comparison is made with statistics available for other countries at a similar stage of development and countries with highly developed e...
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ژورنال
عنوان ژورنال: Sustainability
سال: 2023
ISSN: ['2071-1050']
DOI: https://doi.org/10.3390/su151310576