The COVID-19 pandemic has imposed several adverse impacts on the public transit sector. Significant decline in public transit ridership has been observed in many cities around the world. Public transit agencies are facing with increasing financial burden in providing viable transit service. To survive in this difficult COVID-19 period, public transit agencies are working hard on developing innovative and cost-effective transit services. Customized bus (CB) service is such a kind of smart transit services that provides personalized, comfortable, and safe travel service by collecting passenger travel requests via smartphone apps. This work proposes a three-stage optimization framework for optimizing the operations-planning process of CB service considering COVID-19 imposed social distancing constraints. At the first stage, based on traveler's requests, stops are determined, and feasible CB routes are generated following the shortest-path principles. The second stage generates an initial feasible vehicle schedule complying with the COVID-19 imposed constraints. The schedule is further optimized by using a deficit function-based graphical vehicle scheduling technique at the third stage. Results of a numerical example demonstrated the effectiveness of the three-stage optimization framework.


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    Titel :

    A Three-Stage Framework for Optimizing Customized Bus Operations Considering COVID-19 Social Distancing Measures


    Beteiligte:
    Peng, Yiyang (Autor:in) / Liu, Tao (Autor:in)


    Erscheinungsdatum :

    08.10.2022


    Format / Umfang :

    661775 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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