Exploring Traffic Crash Dynamics at Unsignalized Intersections: Insights from Dhaka Metropolitan Area

Morshed, Md. Rashel; Akter, Rocksana; Hossain, M. Afzal; Zinnurain, Mahiman; Alam, Morshedul · 2025 · Crossref

DOI: 10.2991/978-94-6463-884-4_6

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Summary

This study investigates the dynamics of traffic crashes at unsignalized intersections within the Dhaka Metropolitan Area (DMA), addressing the disproportionate risk these locations pose compared to signalized counterparts. Motivated by the high prevalence of intersection-related fatalities globally and the limited understanding of specific influencing factors in dense urban environments like Dhaka, the research aims to identify high-risk locations and evaluate parameters such as collision type, road geometry, lighting conditions, and demographic factors. The methodology utilized traffic crash data compiled by the Accident Research Institute (ARI) at the Bangladesh University of Engineering and Technology (BUET), covering the period from 2018 to 2020. Data were collected using MAAP5 software in collaboration with the Bangladesh Road Transport Authority (BRTA) and local police departments. The analysis focused on 34 thanas (administrative units) where unsignalized intersection crashes occurred, filtering out 16 crash-free areas. Statistical analysis and graphical representations were employed to categorize crashes by severity, collision type, environmental conditions, day of the week, and casualty demographics. Key findings reveal that pedestrian-vehicle collisions dominate, accounting for 59% of total crashes, with Jatrabari recording the highest fatality rate for this category. T-junctions emerged as a critical geometric factor, contributing to 12% of crashes despite lower traffic volumes, while direct non-junction areas accounted for 40%. Environmental analysis showed that 54.5% of accidents occurred during daylight, with weekdays—particularly Monday (27%) and Thursday (22%)—exhibiting higher crash frequencies due to increased commuter traffic. Casualty data indicated that 76% of incidents resulted in fatal injuries, with males comprising 79% of fatal casualties and 86% of grievous injuries. Hotspots for severe casualties were identified in Jatrabari, Tejgaon, and Uttara West thanas. The study concludes that unsignalized intersections in Dhaka present elevated risks, particularly for pedestrians and male road users during daylight hours on weekdays. The authors recommend improving intersection design and strictly enforcing traffic rules to mitigate these risks. The findings establish a foundational framework for future research, suggesting that advanced techniques, including AI, should be applied to analyze additional variables such as vehicle speed, surface type, and driving behavior to further enhance urban road safety.

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Topics

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• incidence prevalence
• crash typology
• demographic disparities
• vru crash typology
• roadway lighting effects
• fatality injury trends

Information type

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• Empirical Findings: crash risk outcomes