Modeling Bus Traffic for the Berlin SUMO Traffic Scenario

Abstract

The digital transformation of the transport sector in our cities will be led by the deployment of large-scale digital twins, interacting with their real world counterpart to model, predict, and improve movements and reoccurring patterns. Traffic simulation is an essential tool in this area. While both macroscopic and microscopic simulations are possible, only the latter provide enough detail to realize sophisticated Intelligent Traffic Systems (ITS).
One of the biggest challenges is accurately modeling road traffic on a large scale due to limitations in both reliable data sources, as well as the quickly increasing complexity of size. Only a handful of city-scale traffic scenarios exist, and only a few of them include public transport modalities. With this paper, our aim is to extend this list by integrating bus traffic within the Berlin SUMO Traffic scenario (BeST). We provide an overview of potential data sources and a detailed description of the applied methodology. As the scenario was initially calibrated with only individual private traffic, we conduct an evaluation on how the added traffic volume affects the stability of the scenario.