Ambulance-to-Traffic Light Controller Communications for Rescue Mission Enhancement:A Thailand Use Case

During rescue missions, transferring injured people from accident scenes to rescue sites is considered crucial and time-sensitive. In particular, a one-second delay could put more lives in danger. Though ambulances are commonly equipped with standard siren devices, such siren signals are not recognized by traffic light controllers. Therefore, rescue missions could be delayed at intersections due to an urgency-unaware traffic light control system. In the worst case, pile-up accidents could also happen when the ambulances lawfully ignores the traffic lights. This paper proposes A2T to enhance the efficiency of rescue missions, by establishing a communication mechanism among ambulances and infrastructures (e.g., traffic light controllers). Thailand, which had the highest road traffic death rate in the world in 2015, is selected as a use case in this paper. A2T promotes information sharing between ambulances and traffic light controllers along the rescue path in advance. Such information, including speeds, locations, and emergency routes, allows the traffic light controllers to launch a prioritized green traffic light accordingly. This allows the ambulances to go through any road intersection efficiently and safely. Our comprehensive performance evaluation shows that A2T achieves 100 percent waiting time reduction for the ambulances, with only 2.48 percent increase in delay of other vehicles at the intersections

Heurísticas inteligentes para el problema de reubicación de vehículos de emergencias sanitarias.

[ES] El principal objetivo de los servicios de urgencias y emergencias extrahospitalarias es brindar una atención cualificada en el menor tiempo posible. Es esencial ubicar estratégicamente las bases donde se localizan los vehículos de emergencia, para poder cubrir el mayor número de puntos de demanda en un tiempo razonable. Aun en el caso de contar con la ubicación óptima de los vehículos, a medida que estos se mueven para atender emergencias, algunas zonas podrían quedarse sin cobertura, siendo difícil mantener un nivel de servicio adecuado. Con un mayor número de vehículos se podría resolver este problema, pero hay que tener en cuenta que esto implicaría una gran inversión inicial y unos costes operativos elevados, por ello, no es una opción conveniente. Una solución alternativa sería reubicar los vehículos disponibles para alcanzar la mayor cobertura posible. Obtener la solución óptima en un tiempo razonable no es viable para este problema. Por ello, en este trabajo se aborda el problema de reubicación de ambulancias mediante el diseño y desarrollo de herramientas heurísticas inteligentes. Se resuelve un caso real, del Servicio de Emergencias Sanitarias de la provincia de Valencia, con un previo análisis estadístico de los datos históricos de las emergencias, con la finalidad de obtener información relevante, que posteriormente se utiliza para desarrollar las heurísticas.[EN] The main objective of the emergency services and out-of-hospital emergencies is to provide qualified care in the shortest possible time. It is essential to strategically locate the bases where emergency vehicles are located in order to cover the greatest number of demand points in a reasonable time. Even in the case of having the optimal location of the vehicles, as they move to attend to emergencies, some areas could be left without coverage, making it difficult to maintain an adequate level of service. With a greater number of vehicles, this problem could be solved, but it must be considered that this would imply a large initial investment and high operating costs, therefore, it is not a suitable option. Relocating the available vehicles to achieve the highest possible coverage would be an alternative solution. Obtaining the optimal solution in a reasonable time is not feasible in this case. For this reason, this work addresses the problem of ambulance relocation through the design and development of intelligent heuristic tools. A real case is solved, from the Health Emergencies Service of the province of Valencia, with a previous statistical analysis of the historical data of the emergencies, in order to obtain relevant information, which is later used to develop the heuristics.Karpova Krylova, Y. (2020). Heurísticas inteligentes para el problema de reubicación de vehículos de emergencias sanitarias. Universitat Politècnica de València. http://hdl.handle.net/10251/15832