Electrification of vehicles as well as mobility-on-demand (MoD) services are two important trends these years. Hence, the supply of charging infrastructure (CI) becomes a necessity to ensure a smooth transition. While private vehicle owners expect a high availability of charging possibilities, the utilization of CI often suffers. Including charging processes of MoD vehicles could benefit the charging operator as well as the MoD operator: Charging processes of MoD vehicles can be planned centrally thereby increasing public CI utilization while MoD operators do not have to invest in their own CI. We study the effects of an electric MoD fleet using public CI to investigate the following questions: What are the effects of using public CI on the MoD performance? How do these charging processes influence public CI usage? To quantify the effects, we use an agent-based fleet simulation framework to model a ride-pooling MoD service and incorporate a rule-based charging strategy. With the case study of Munich, Germany, we test three different charging scenarios: 1) MoD vehicles charge at a single depot, 2) MoD vehicles charge at a variety of depots and 3) MoD vehicles charge at public CI. Results suggest that an MoD service can use public CI without degrading the level of service given today's charging processes of private vehicles. The study implies that MoD providers can decrease empty fleet mileage for the trips towards the CI without the investment costs of owning multiple depots throughout the city.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Simulating Charging Processes of Mobility-On-Demand Services at Public Infrastructure: Can Operators Complement Each Other?


    Beteiligte:
    Zhang, Yunfei (Autor:in) / Engelhardt, Roman (Autor:in) / Syed, Arslan-Ali (Autor:in) / Dandl, Florian (Autor:in) / Hardt, Cornelius (Autor:in) / Bogenberger, Klaus (Autor:in)


    Erscheinungsdatum :

    08.10.2022


    Format / Umfang :

    2004295 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch