Congestion constitutes a major problem in modern urban traffic networks if not well managed. Its monstrous effects, on occasions, can paralyze a traffic network eating deep into the productive hours of commuters as well as vehicles and persons on essential services. Particularly affected are incidence-intervention vehicles such as emergency vehicles and fire-fighting vehicles. Whatever the cause of the congestion, its effect is counter-productive and an indication of an inefficient traffic network. This work, as presented in this paper, is concerned about the issue of traffic route management for emergency service (emergency vehicle) for which a delay of few minutes may cause tremendous loss of lives and properties. The route management scheme built for this purpose integrates information obtained from the use of Radio Frequency Signals for Traffic Light Preemption at Intersections in a Proteus Simulator environment and the use Arc GIS as a mode of routing the emergency vehicle from base to the incidence location, then to Health Facilities and from thence back to the emergency vehicle base in an optimal routing time. Traffic information are loaded into the Arc GIS environment which predicts the required tri-legged optimal routing and its duration using Dijkstra’s algorithm. Different scenarios of emergency vehicle, incidence and health facility locations were exploited using the scheme and compared with situations without their implementation. The proposed scheme outperforms the trial and error routing of emergency vehicles and can be embedded into traffic advisory system or as stand-alone emergency vehicle management system.Keywords: GIS, Dijkstra’s algorithm, Facility Location, Emergency-Vehicle, Optimal Routing


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    Title :

    Optimal routing for automated emergency vehicle response for incident intervention in a traffic network


    Contributors:
    Ogunwolu, L (author) / Sosimi, A (author) / Jagun, O (author) / Onyedikam, C (author)

    Publication date :

    2019-01-15


    Remarks:

    Journal of Applied Sciences and Environmental Management; Vol 22, No 12 (2018); 1941-1946 ; 1119-8362


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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