Allocation strategy for an ambulance base under traffic congestion

Abstract

One of crucial issues for emergency medical service (EMS) is to reduce response time. However, in metropolis city, a traffic congestion is an obstacle for an ambulance to responsively reach at the scene, then patient mortality and disability rates increase. Traffic congestion is considered as a complex spatial-temporal situation. It is often triggered by repeating factors, such as car lane capacity, weather, and unexpected events. Therefore, a real-time traffic condition is required to effectively determine the location of an ambulance. The current ambulance base allocation strategy model considers only demand point, resulting inability to handle high traffic congestion. This paper proposed a covering model based on traffic congestion (using Google map API) to allocate ambulance bases that covering all demand point, while minimizing the number of the ambulance. In addition, our model was applied to the case study of Bangkok EMS.