With promising benefits such as emission reduction, traffic congestion alleviation and parking space saving, electric vehicle sharing systems have attracted increasing attentions. This paper proposes a Trip Pricing Scheme (TPS) for a large-scale EV-sharing network with Shared Electric Vehicle (SEV) demand prediction. In the proposed system, the SEV traffic demand is firstly predicted through a model which includes a cascade graph convolutional neural network and a long-short term memory neural network. Based on this, the TPS is modelled as a mixed-integer nonlinear programming problem, which aims at maximizing the total system profit from EV sharing business. The proposed TPS determines the optimal combination of the two price adjustment levels, which provides incentives to the spatial-temporal distribution of SEVs’ traffic flows to maximize the system’s profit. Numerical simulations are conducted to validate the effectiveness of the proposed method.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Trip Pricing Scheme for Electric Vehicle Sharing Network With Demand Prediction


    Contributors:
    Wang, Shu (author) / Yang, Yang (author) / Chen, Yisong (author) / Zhao, Xuan (author)

    Published in:

    Publication date :

    2022-11-01


    Size :

    2038986 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    TRIP PRICING STRATEGY OF ONE-WAY STATION-BASED ELECTRIC CAR SHARING SYSTEM

    Liu, Yuhan / Zeng, Tao / Wang, Xiaowen et al. | TIBKAT | 2019



    Integrated User Matching and Pricing in Round-Trip Car-Sharing

    Brar, Avalpreet Singh / Su, Rong / Zardini, Gioele et al. | IEEE | 2024


    On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment with future requests

    ALONSO-MORA JAVIER / RUS DANIELA L / WALLAR ALEXANDER J | European Patent Office | 2023

    Free access