Congestion growth problem is a daily life experience all over the world, especially in large cities. The motion of Emergency Vehicles (EVs) like Ambulances, police, and firefighting vehicles are highly affected by traffic Congestion, by which rescue time may cost a life. The Priority Level Mutualism for Emergency Vehicle (PLMEV) algorithm aims to reduce the waiting time by giving higher priority for the EVs at the intersection. According to the vehicle's priorities, The Game Theory will control the traffic at the intersection. The PLMEV classifies EVs according to their emergency levels. The algorithm has a highly scalable property with a different number of vehicles. Also, has adaptive property to different vehicle type distribution and work with multiple EVs. Simulation evaluates the PLMEV's performance by comparing it with the Fixed Traffic Control System. The Simulation's results proved that The PLMEV reduced the waiting time for EVs to 42.7% on average, on the other hand, the normal vehicle's time has been reduced to 15.1% on average, while the maximum vehicle waiting time is reduced to 22.3% on average. In case there is no EVs at the intersection, the PLMEV works in optimising the traffic flow.


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    Title :

    Priority level mutualism for emergency vehicle using game theory


    Contributors:


    Publication date :

    2017-06-01


    Size :

    1606788 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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