Optimal Design for Demand Responsive Connector Service Considering Elastic Demand

Differing from the conventional fixed-route transit, Demand Responsive Connector (DRC) is scheduled to pick up passengers based on requests, and delivers them to a common destination (e.g., a metro station). The demand for DRC is affected by not only the fare and travel time, but also time reliability. The latter' impact is non-negligible because of the uncertainty nature of DRC on collecting the temporally and spatially distributed passengers. This paper explicitly introduces an elastic demand function embedded with a time deviation penalty model. Based on that, one-vehicle and two-vehicle DRC models are formulated to maximize the social welfare. The decision variables include fare, service area, and operating cycle time. Augmented Lagrange Multiplier Method is applied to solve the optimization problem. Simulation is performed to verify the validity of the models. In numerical studies, sensitivity analysis unveils the influences of several key parameters, e.g., potential demand density, vehicle capacity, line-haul distance and elasticity factors. By comparison, threshold values of demand density are revealed for the applicability of the one-vehicle and two-vehicle schemes. The proposed model provides a decision-making tool for DRC operators considering local conditions.

Automated summary

Demand Responsive Connector (DRC) operates by picking up passengers based on requests and delivering them to a common destination, with demand influenced by fare, travel time, and time reliability. This paper introduces an elastic demand function and time deviation penalty model to formulate one-vehicle and two-vehicle DRC models, optimizing social welfare through decision variables such as fare, service area, and operating cycle time. Simulation and sensitivity analysis reveal key parameters affecting the models' validity and the threshold values for the applicability of one-vehicle and two-vehicle schemes.