Transit is the backbone of the transportation sector that not only reduces traffic congestion and environmental impact but also provides equity as an affordable mobility service. Bus electrification has an utmost importance to achieve global net-zero economy goals since buses are the main source of emissions in the transit sector. In this study, we revisit the single depot vehicle scheduling problem (SDVSP) to address the operational constraints electrification brings in. To this end, we follow a two-stage modeling approach: We solve an SDVSP model to form vehicle blocks in the first stage, and chain these blocks considering spatio-temporal and state-of-charge conditions in the second stage. A greedy algorithm heuristic is developed to address the complexity of the block chaining problem. Since transit agencies readily use SDVSP models to form blocks, incorporating a straightforward block chaining heuristic makes the solution approach easy to implement. An analysis conducted using this solution framework found that the electric vehicle range plays a key role in determining the fleet size. A 150-mile vehicle range allows for 98% electrification where each diesel vehicle is replaced by 1.6 electric vehicles. This also means a 25% increase in non-revenue time.


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    Titel :

    Solving the Electric Vehicle Scheduling Problem at Large-Scale


    Beteiligte:


    Erscheinungsdatum :

    2023-09-24


    Format / Umfang :

    5556964 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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