This research aims to enhance paratransit services for vulnerable road users amid Medicaid privatization trends. Addressing challenges in determining dwell time (time spent at a stop without progressing), we present adaptive reinforcement learning for more accurate predictions. Unlike traditional methods, we model the interaction between key factors influencing dwell time uncertainty, creating a reliable service tool. This framework optimizes paratransit routing by accurately estimating service times, contributing to more efficient healthcare access in underserved areas. The framework may lessen dwell time uncertainty and in-vehicle travel times, which could enhance the general quality of paratransit services for the elderly and disabled.


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    Titel :

    Optimizing Paratransit Routing Considering Dwell Time Uncertainty


    Beteiligte:

    Kongress:

    International Conference on Transportation and Development 2024 ; 2024 ; Atlanta, Georgia



    Erscheinungsdatum :

    13.06.2024




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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