Planning public transport services for areas of low population density is important to enable travel by those without convenient travel options. In such areas, transit vehicles frequently travel with few passengers or even no passengers on board and thereby incur more cost to the transport providers. Demand-responsive transportation (DRT) services are potentially an efficient mobility solution to this problem. The choice of a DRT scheme is important because different types of schemes may produce different performances in the same area with the same demand. Although many DRT schemes have some constraints (for example, a fixed route or fixed time), these impose additional constraints on users who are already constrained, for example, by a lack of access to a car or limited times to undertake activities. Removing the fixed constraint on time leads to evaluating the performance of an ad hoc system. This paper investigates the change in performance of two DRT schemes—a fixed-time but flexible route scheme and a completely ad hoc scheme—by using the multiagent simulation tool, MATSIM, a large-scale agent-based transport simulation, and real data from an existing fixed-time DRT service in rural Victoria, Australia. Experimentation showed that the schemes produced different outcomes for the operator and passengers; however, the optimization algorithm was less important in areas of low demand. Higher levels of demand led to extensive vehicle travel for an ad hoc service, but altering the headways between fixed-time services could achieve a middle ground for operators and passengers. This work is a first step toward developing a decision support tool to evaluate DRT schemes, in particular for those integrated with other modes of transport.


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    Title :

    Comparison of Constrained and Ad Hoc Demand-Responsive Transportation Systems


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2019-04-04




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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