Simulation of Demand Responsive Transport using a dynamic scheduling tool with SUMO

Abstract

Demand responsive transport (DRT) has been increasingly tested and applied in recent years as a new form of transportation that seeks to address mobility problems in cities and rural areas. The planning of DRT systems is a challenging task for transport planners since the performance of the service depends significantly on the demand, how the scheduling is made, and how the routes are computed. Transport simulations are a useful option to evaluate these systems. The paper presents a Python tool, which aims to simulate diverse DRT services using the software package for microscopic simulations Eclipse SUMO (Simulation of Urban MObility) as a framework. The fleet and requests of the DRT are handled dynamically by the scheduling module of the tool. This module is also responsible for calling a solver algorithm for the Dial-a-Ride-Problem (DARP), processing its results, and dispatching the DRT vehicles according to them. The tool also enables easier implementation of other methods to solve the DARP. To demonstrate the use of the tool, a DRT service operating in two central neighborhoods of the city of Brunswick (Germany) is presented. The tool is called drtOnline.py and is included in SUMO since version 1.9.0.