GIS-Based Identification of Traffic Incident Hot Spots and Severity Index in Khartoum, Sudan

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Hamid Abdrhman ,Yanjun Qiu , Hamza Shams , Mohamed A. Damos

Abstract

Most road traffic accidents (RTA) are fatal or injury-related, particularly in low and moderate-income countries. As a low-income nation, Sudan is significantly impacted by a high rate of traffic accidents, subsequent in numerous fatalities and many individuals suffering severe or permanent injuries, which has direct repercussions for individuals, communities, and governments. This study aimed to identify areas of Khartoum, Sudan, that experience traffic accidents frequently. Geographic Information Systems (GIS) tools have been employed to measure the severity of those accidents from 2020 to 2022. Moreover, the Getis-Ord Gi*, Average of Nearest Neighbor (ANN), and Kernel Density Estimation (KDE) were used to investigate spatial distribution and clustering of traffic accidents. In addition, the study incorporated factors such as the severity of accidents to assess better the risks associated with roads. The results revealed significant clustering patterns of incidents with a high severity indicator in specific locations in the study area, characterized by traffic law violations and inadequate infrastructure in particular zones. Moreover, the ANN approach underscored a statistically significant clustering pattern with a P-value less than 1.0. This emphasized that accidents were spatially concentrated rather than randomly distributed. Therefore, the stability of this clustering throughout the investigation underscores the significance of executing long-term interventions in these high-risk zones.

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