Design of a SUMO-Based Simulator for Optimal Location of Emergency Vehicles in the Emergency Medical Systems

Abstract

The response time between an accident happening and an ambulance reaching the incident place is a very delicate and crucial time. The time elapsed between those two events could be the determining factor of whether the injured person gets to live or die. Therefore, the response time of the ambulance assisting in the accident should be as small as possible. Response time can directly affect a person’s recovery time and can make the difference between the patient suffering temporary or prolonged disability, or even death. Locating the best position for ambulance bases is a challenge for emergency medical systems (EMSs). This will improve the EMS service in assigning the ambulance that arrives sooner to a given incident, thus reducing the risks associated with long response times. In this paper, we design a SUMO-based simulation framework named SEMSIM (Sistema d’Emergències Mèdiques SIMulator) that mimics the management of ambulances done by the EMS. The goal is to develop a tool to easily explore alternatives of stationing the available ambulances at the available bases, following different configuration settings (i.e., distributing the ambulances in different ways in the current bases or including new base locations), and analyze the average response time for each of those alternative configurations in comparison to the current configuration. The designed tool will help the EMS to explore dynamic configurations that are optimal throughout time, e.g. for different seasons, type of day, or time of the day. The SEMSIM simulation tool accurately replicates the ambulance assignments and response times of the EMS, validating its effectiveness. This allows SEMSIM to test new ambulance distribution configurations, including the addition of new bases, which would be costly or impractical to explore in real life. SEMSIM provides a valuable resource for EMS to optimize their operations using real incident data and maps from OpenStreetMap. The aim in this paper is to design a methodology based on dynamic SUMO simulations to analyze the optimal dynamic configuration of the fleet of ambulances that offers the smallest average response time and thus helps to improve the EMS service. As a case study, we explored various alternative configurations reducing response time by more than 2 min.