Abstract: This study evaluates the spatiotemporal vulnerability of fire and medical services in the Atlanta metropolitan area by incorporating real-time traffic congestion data collected at 10-minute intervals. Congestion-derived traffic speeds from map imagery were integrated with distance-weighted average speeds (DWAS) from an OpenStreetMap road network to construct a high-resolution, time-varying speed database. Using the Dijkstra algorithm, minimum travel times were estimated from each emergency facility under dynamic traffic conditions. Results show that congestion increases emergency response time by up to 46 seconds for fire services and 41 seconds for medical services. Fire service vulnerable areas were concentrated in dense urban centers, whereas medical services exhibited higher vulnerability in suburban areas where facilities are spatially sparse. Hot spot and temporal trend analyses revealed expanding clusters of long travel times and increasing long-term risk in several suburban regions. This study highlights the importance of incorporating real-time mobility patterns into emergency service planning and provides a dynamic analytical framework for congestion-adaptive resource allocation and urban resilience enhancement.

Recommended citation: Lee, S., Hwang, C. S., & Seong, J. C. (2026). Dynamic Coverage Analysis of Fire and Medical Services Based on Traffic Congestion and Time-Series Hot spot Trends. In Preparation.