Spatial Analysis of Pedestrian Crashes at Intersections Using Geospatial Information Systems (GIS) (Case Study: Rasht City)

Document Type : Original Article

Authors
Meysam Effati 1
Iraj Ghanbari 2
1 Assistant Professor, Department of Civil Engineering (Road and Transportation), Faculty of Engineering, The University of Guilan, Guilan, Iran.
2 Department of Civil Engineering (Road and Transportation), Faculty of Engineering, The University of Guilan, Guilan, Iran
10.22034/road.2023.361924.2091
Abstract
Intersections as traffic junctions of inner-city thoroughfares are one of the most important geometric locations of pedestrian and vehicle interference, where a large number of pedestrian accidents occur every year. Therefore, the main purpose of this study is to analyze the effective factors in pedestrian accidents based on previous accident records and to investigate the impact of each factor on the number of pedestrian accidents at intersections using Poisson regression and Multivariate regression statistical analysis. Another purpose of this study is to present a GIS-based approach in order to identify and Spatial distribution of high-traffic intersections in Rasht metropolitan areas. In this study, fourteen independent factors obtained from police reports and fieldwork were divided into three general groups: human factors, weather conditions, and traffic-geometric factors. Accordingly, Poisson regression was used to analyze the direct effect of these factors on the number of pedestrian accidents at intersections, and multivariate regression was used to analyze the effect of three general categories of pedestrian crossings on pedestrian accidents at intersections. The results of the study showed that the factors of driver age 11%, rainy weather conditions 7%, and lack of traffic lights 40% had the greatest impact on increasing the number of pedestrian accidents at intersections. Also, the highest frequency of intersections with pedestrian accidents occurred in the second and fourth urban areas and the intersections of Toshiba Square, Heshmat Crossroads, and Gas Square were recognized as the most accident-prone intersections in Rasht.
Keywords
Intercity Intersections
Pedestrian Accidents
Geospatial Information Systems (GIS)
Poisson Regression
Multivariate Regression
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