Road traffic crashes (RTCs) pose a growing threat to transportation safety, particularly in rapidly developing countries like Bangladesh. This study aims to identify and analyze crash hotspots along the Dhaka–Mawa Expressway (N804), the country’s first expressway, using a geospatial approach. A total of 260 crash records from March 2022 to November 2024 were collected from local police stations. The analysis applied both qualitative and quantitative techniques, including severity index (SI) and kernel density estimation (KDE), to assess crash patterns, severity, and spatial concentration. Results revealed 154 fatalities, 259 serious injuries, and 278 minor injuries during the study period. Buses were the most frequently involved vehicle type (35.7%), and male victims accounted for the highest proportion of casualties across all severity levels. Using KDE and the SI score, this study identified 18 high‐risk black spots among 69 crash‐prone locations. The findings underscore the necessity for targeted safety interventions, enhanced infrastructure, and data‐driven enforcement strategies to decrease crash frequency and severity along high‐risk segments of the expressway.
Billah et al. (Thu,) studied this question.
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