Electric Vehicles (EVs) is a promising transportation to alleviate traffic congestion and pollution problems and its route planning can save the limited energy. However, designing a reliable route planning strategy to achieve optimal route remains a challenging problem, especially when various objectives of both energy consumption and time cost are taken into consideration. Therefore, based on the traffic signal control technologies in urban areas and an EV energy consumption model, we formulate EV route planning problem as a multi-objective optimization problem and propose a Green wave band-based Multi-objective Ant Colony Optimization (G-MACO) algorithm to solve it. Moreover, relying on the field measurement data, the graphical model of urban road network containing relevant weights is also analyzed. Finally, simulation results show that the proposed algorithm can achieve a trade-off between energy consumption and time cost to realize the multi-objective optimization route planning.


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    Title :

    G-MACO: A Multi-Objective Route Planning Algorithm on Green Wave Effect for Electric Vehicles


    Contributors:
    Liu, Anqi (author) / Li, Changle (author) / Xia, Bing (author) / Yue, Wenwei (author) / Miao, Zhifang (author)


    Publication date :

    2018-06-01


    Size :

    948194 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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