Optimal Design of Demand-Responsive Feeder Transit Services

The general public considers Fixed-Route Transit (FRT) to be inconvenientwhile Demand-Responsive Transit (DRT) provides much of the desired flexibility with adoor-to-door type of service. However, FRT is typically more cost efficient than DRT todeploy. Therefore, there is an increased interest in flexible transit services including alltypes of hybrid services that combine FRT and pure DRT. The demand-responsivefeeder transit, also known as Demand-Responsive Connector (DRC), is a flexible transitservice because it operates in a demand-responsive fashion within a service area andmoves customers to/from a transfer point that connects to a FRT network. In thisresearch we develop analytical models, validated by simulation, to design the DRCsystem.Feeder transit services are generally operated with a DRC policy which might beconverted to a traditional FRT policy for higher demand. By using continuousapproximations, we provide an analytical modeling framework to help planners andoperators in their choice of the two policies. We compare utility functions of the two policies to derive rigorous analytical and approximate closed-form expressions of criticaldemand densities. They represent the switching conditions, that are functions of theparameters of each considered scenario, such as the geometry of the service area, thevehicle speed and also the weights assigned to each term contributing to the utilityfunction: walking time, waiting time and riding time.We address the problem faced by planners in determining the optimal number ofzones for dividing a service area. We develop analytical models representing the totalcost functions balancing customer service quality and vehicle operating cost. We obtainclose-form expressions for the FRT and approximation formulas for the DRC todetermine the optimal number of zones.Finally we develop a real-case application with collected customer demand dataand road network data of El Cenizo, Texas. With our analytical formulas, we obtain theoptimal number of zones, and the times for switching FRT and DRC policies during aday. Simulation results considering the road network of El Cenizo demonstrate that ouranalytical formulas provide good estimates for practical use.