A model for estimating the optimal cycle length of demand responsive feeder transit services

An Analytical Model for the Many-to-One Demand Responsive Transit Systems

“…A great deal of research was conducted to investigate the factors influencing the performance of DRT systems from multiple aspects. Amirgholy and Gonzales [7] pointed out that the modeling approaches can be categorized in terms of the data availability, which are simulations [2,[18][19][20] and mathematical methods [21,22]. The simulation method is applicable when it is difficult to develop closed-form expressions for the system's performance, which needs a large body of data including passenger demand and distribution (both spatially and temporally), fleet size, and vehicle trajectory.…”

“…Dessouky et al [20] conducted a study through simulation and investigated the level of service for specific strategies (e.g., zoning and time-window settings) conducted on the DRT system in Los Angeles, California. Chandra et al [2] explored the optimal operating capacity, fleet size, and cycle length in El Cenizo, Texas, via a simulation study by using the data collected from a survey questionnaire.…”

“…The relationship between the velocity along the primary direction and the demand was analyzed. Chandra and Quadrifoglio [2] developed an analytical model for the approximation of the near-optimal terminal-to-terminal cycle length of the DRT service. The objective function of this model was to maximize the system's level of service with respect to the cycle length.…”

“…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 (e.g., railway or fixed-route bus stations), which is an alternative travel option that is competitive with private automobiles.…”

Optimization of demand-responsive transit systems using zonal strategy

“…To more effectively operate DRT systems, a number of mathematical models have been developed in order to optimize these systems (Daganzo et al 1977, Chang & Schonfeld 1991a, Chang & Lee 1993, Chien et al 2001, Nourbakhsh & Ouyang 2012, Chandra & Quadrifoglio 2013. Most of these models were designed to operate in service areas with a regular shape (rectangular, square and circular).…”