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Citation |
Azari M, Paydar A, Feizizadeh B, Hasanlou VG. Appl. Geomat. 2023; 15(1): 127-139. |
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Copyright |
(Copyright © 2023, Holtzbrinck Springer-Nature) |
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DOI |
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PMID |
unavailable |
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Abstract |
According to crash statistics, traffic crashes along mountain roads are the third leading cause of death in Iran. Road safety reports given by the Iran Statistics Research and training center demonstrate the correlation between mountain road crash severity concerning environmental effects, which involve season-related and geometric parameters. Therefore, countermeasures are needed to identify crash hotspots and related contributing parameters affecting such crashes. In this research, the geometric parameters in the cold season were involved in recognizing accident hotspots on the Karaj-Chalus mountain road. Spatial multi-level modeling based on analytical hierarchy process, fuzzy membership function, weighted linear combination, and, also, high-resolution radar image was adopted to determine crash hotspots since use of the combined approach and applied data improves accident hotspot prediction accuracy. Spatial traffic accident analysis by comparing police-recorded traffic crash reports in winter's months between 2018 and 2020 was conducted to validate hotspot zones and model accuracy. The results showed that about 20 sections of Karaj-Chalus Mountain Road were considered accident-prone sections based on the predicted model, and 46 out of 50 (92%) accidents in cold months take place in the hotspot-predicted sections. Therefore, the practical significance of this research can be applied to mountain road safety, especially in cold months since the findings of this study are more precise in order to identify accurate traffic accident hotspots. Furthermore, this paper is the first study of accident hotspots on mountain roads in Iran, so the findings will help the traffic decision-makers in Iran to solve this problem on Karaj-Chalus Road and other mountain roads. Language: en |
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Keywords |
GIS; Mountainous roads; Remote sensing; Road safety; Seasonal related and geometric effects; Spatial multi-level modeling |