Abstract
The demand-responsive transit (DRT) service is an emerging and flexible transit mode to enhance the mobility of the urban transit system by providing personalized services. Passengers can make advanced appointments through smartphone applications. In this paper, an analytical model is proposed for the many-to-one DRT system. The agency and user costs are approximated by closed-form expressions. The agency cost, which is also the operation cost, is approximated by the continuum approximation technique. A nearest-neighbor routing strategy is applied, whereby the vehicle always collects the nearest passenger waiting in the system. The Vickrey queueing theory is adopted as the basis for approximating each component of the user cost, which is composed of the out-of-vehicle and in-vehicle waiting times and schedule deviations, which also depend on the service quality of the DRT system. The results of the numerical experiment show that (1) the agency and user costs are influenced significantly by the demand density, and (2) the DRT operator cannot further decrease the operating cost by solely deploying larger vehicles.
Highlights
The construction of the on-demand transit system was widely recognized in the last decade as an effective policy that can solve the first/last mile connectivity between residential areas and public transit stations
Compared with traditional fixed-route transit, demand-responsive transit (DRT) provides flexible services owing to the on-demand schedules and dynamic deviations [1,2,3,4]
As an essential component of the multimodal transit system, the DRT usually acts as a conjunction by collecting passengers and carrying them to other transit stations, which is an alternative travel option that is competitive with private automobiles
Summary
The construction of the on-demand transit system was widely recognized in the last decade as an effective policy that can solve the first/last mile connectivity between residential areas and public transit stations. Passengers would tolerate higher delay in the system awaiting pickup services, longer in-vehicle travel time, and earliness/lateness resulting from the lack of punctuality if the passenger demand exceeds the existing operating capacity. In this regard, when transporting passengers, improving service quality must be balanced against minimizing operating costs by optimizing operation and management strategies in the DRT system, while the total costs of agency and passengers are minimized. The major motivation of this study is to investigate how these critical parameters affect the system cost and the passenger’s travel behavior in such a transit system To facilitate such a design, an analytical model is formulated to approximate the operating cost of the collection phase. It is still possible to reduce the total system cost by optimizing the decisions variables (e.g., vehicle capacity, occupancy, feet size) during the DRT operation
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