Park-and-Ride (P&R) scheme is an effective means for managing traffic demand in urban areas. This paper proposes a network equilibrium formulation for modeling the P&R services in a stochastic transportation network with capacity constraints. In the propose model, it is assumed that travelers can complete their journeys by three options: using auto mode, walk-metro mode or the auto-metro mode (referred to as the P&R mode). The proposed model simultaneously considers travelers' travel choices on travel mode, route/path and transfer point, as well as their parking choice behavior nearby the destination. The proposed model can be formulated as a fixed-point problem. An augmented Lagrangian dual algorithm embedded by the method of successive averages (MSA) is developed to solve the proposed model. Numerical results show that as compared to the stochastic network model, the deterministic network model will overestimate the car demand split and underestimate the P&R demand and the total network cost. Numerical results also show that adding a P&R facility into the network might lead to a paradoxical phenomenon, i.e., total network travel costs after adding a new P&R facility become larger than before instead. This study will provide a powerful tool for the authority to design a rational and efficient P&R system.


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    Titel :

    Modeling Park-and-Ride Behavior in a Stochastic Transportation Network with Capacity Constraints


    Beteiligte:
    Fan, Wenbo (Autor:in) / Yang, Deming (Autor:in)

    Kongress:

    Second International Conference on Transportation Engineering ; 2009 ; Southwest Jiaotong University, Chengdu, China



    Erscheinungsdatum :

    2009-07-29




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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