Joint Optimization of Zone Area and Headway for Demand Responsive Transit Service under Heterogeneous Environment

This paper presents a mathematical model to optimize zonal demand responsive transit (DRT) considering heterogeneous environment (i.e., community boundary, land use, demand distribution, line-haul travel time, etc.) under the advent of Mobility-as-a-Service (MaaS). Since most previous models over-simplified conditions of the DRT service area, we propose a new modeling approach to formulate the operator and user costs. Passengers with varied expectations of vehicle arrival time at a drop-off location are considered. The average cost is minimized through optimizing service zone areas and associated headways subject to practical constraints (i.e., policy headway and vehicle capacity). A real-world region in the City of Calgary, Canada, is applied to demonstrate the applicability of the model. The impact of real-time vehicle arrival information to the optimal solution is assessed. The relationship between system parameters (i.e., line-haul travel time, demand density, vehicle capacity, and passenger composition, etc.) and the optimized solutions (i.e., zone area, headway, and costs) is explored through the sensitivity analysis.