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.

Automated summary

This paper presents a mathematical model to optimize zonal demand responsive transit (DRT) considering heterogeneous environment and the advent of Mobility-as-a-Service (MaaS). The model takes into account various factors such as community boundary, land use, demand distribution, line-haul travel time, etc. Passengers with different expectations of vehicle arrival time are considered, and the average cost is minimized through optimizing service zone areas and associated headways. The model is applied to a real-world region in Calgary, Canada, and the impact of real-time vehicle arrival information is assessed. The sensitivity analysis explores the relationship between system parameters and the optimized solutions.