As cities get overcrowded, commuters are spending most of their time in traveling and insane amount of time gets wasted in unnecessary traffic jams. A large number of countries are adopting various traffic management techniques to deal with traffic congestion. The objective of this research article is to develop a smart and intelligent road navigation system in a cost-effective way that dynamically adapts to the congestion of the route, and hence contribute to the development of smarter cities. Besides finding shortest route, congestion factor is computed to find an optimized route from source to destination. Congestion factor has been evaluated through numerical modeling in dense traffic scenario. Experiment results reveal that the travel time of a vehicle is reduced by up to 33% if it follows optimized route obtained from proposed approach. This can also be helpful for the emergency vehicles to identifying the best route in any emergency conditions. The proposed analytical model is further extended to identifying the optimal route for formation of on-demand green corridor in emergency situation.


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    Titel :

    A Real-Time Road Congestion-Based Hybrid Approach for Finding the Optimized Route


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Nath, Vijay (Herausgeber:in) / Mandal, J. K. (Herausgeber:in) / Rajak, Biru (Autor:in) / Tripathi, Aprna (Autor:in) / Kushwaha, Dharmender Singh (Autor:in)


    Erscheinungsdatum :

    2020-09-20


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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