Urban cities are getting more congested with vehicular traffic and most of the traffic control systems are not smart to detect and give priority to emergency vehicles. The effect results to inadequate services delivered by the public emergency agencies, and unnecessary traffic congestion to other road users at intersection points. In this paper we present an effective reinforced road traffic control policy that reduces the waiting time of emergency vehicles at road intersection points, and also reduce the travel time of other vehicles. The work involved simulation of traffic control at an intersection using a multi-agent system development framework (JADE) and an agent-based traffic simulator (SUMO). In order to exploit the full potential of SUMO, a third tool (TraSMAPI) was used to connect JADE and SUMO and also, to provide a higher abstraction of SUMO. In this way, the simulation is not restricted to only what SUMO can offer, but also permits us to control and manipulate the behaviour of the simulation runs. The result shows that intelligent traffic control fulfils its objectives by significantly reducing the travel time of emergency vehicles or other normal vehicles. It is shown in the paper that intelligent traffic control is at least 96% better in reducing the waiting time of emergency vehicles at intersections than nonintelligent fixed traffic control.


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    Titel :

    Simulation of intelligent traffic control for autonomous vehicles


    Beteiligte:


    Erscheinungsdatum :

    01.07.2017


    Format / Umfang :

    1125076 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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