Traffic Collisions: Temporal Patterns and Severity-Weighted Hotspot Analysis

Abstract: Understanding traffic collision patterns is of high importance for effective road safety planning in fast-growing urban environments. This study examines the temporal and spatial patterns of traffic collisions in Dubai, UAE, with a particular focus on collision severity. To this end, traffic collision records from November 2024 to June 2025 were analyzed to examine hourly, daily, and monthly variations in collision frequency and severity for both overall traffic collisions and pedestrian-related accidents. Temporal associations with severity were evaluated using chi-square tests and Cramer's V, while spatial patterns were analyzed using severity-weighted hotspot analysis based on the Getis-Ord Gi* statistic, complemented by inverse distance weighting (IDW) interpolation. The results show a clear temporal variation in overall collision frequency and severity, with higher collision frequencies during evening and nighttime periods with 44% higher probability of high-severity outcomes at night compared to the afternoon. On the other hand, pedestrian-related accidents showed a distinct temporal profile, characterized by higher occurrence during late-evening hours and relatively limited variation across days of the week and months. Spatial analysis identified statistically significant severity hotspots for overall collisions in the northern and northwestern parts of Dubai and along the Al Ain-Dubai Highway, while pedestrian severity hotspots were concentrated near industrial areas in the southwestern region. Several policy measures are proposed based on the findings including, reducing nighttime speed limits, enhancing automated enforcement, improving roadway lighting, and implementing pedestrian-focused treatments in statistically significant hotspots.