Here is the code and final result of my Master's thesis in Information and Communication Technology at the Université Libre de Bruxelles (https://www.ulb.be/fr/programme/ma-stic). This work got the highest grade for the 2018-2019 academic year.
"Optimisation d’itinéraires des véhicules médicaux d’urgence à l’aide de données de position. Application aux données du Service d’Incendie et Aide Médicale Urgente de Bruxelles-Capitale"
Author : Alexis Huart
The patients survival rate out-of-hospital depends directly on how quickly emergency medical services (EMS) arrive. Therefore, the vehicle with the shortest estimated time of arrival (ETA) should be sent to the scene. This is a considerable challenge, particularly in urban areas where traffic congestion is significant and the road network complex. Currently, ETA is calculated on a theoretical basis. This work attempts to create a draft navigation system based on position data and therefore actual speeds. The aim is to identify the influence of traffic, improve ETA, enhance vehicle selection and route choice. The concept is applied to Brussels fire and emergency medical service data. The average speeds of EMS vehicles are calculated and input into a navigation system. The experiment uses the Open Source RoutingMachine library for map matching and routing, as well as a Python script for error correction and speed calculation. The procedure and results are compared to the Poulton[78] study, the only work to date using position data for EMS navigation. In Brussels, we observe that automobile congestion clearly modifies the average speed of EMS during peak hours. From the speed analysis, we obtain a draft of a functional navigation system, based on data with a realistic ETA.
Operations research, Intelligent transport systems, ITS, Service d’incendie et d’aide médicale urgente, SIAMU, Estimated time of arrival, ETA, Emergency medical services, EMS, Open source routing machine, OSRM, OpenStreetMap, OSM, Map matching, Bruxelles.