A Stepwise Approach of Generating Agent-based Simulation Model for Brussels Using Ubiquitous Big Data

Abstract

Synthetic travel demands are essential for agent-based traffic models which explicitly define the entire population of the study area's respective personal attributes and travel behaviours on disaggregated levels. Several papers specifically concentrate on synthetic population or travel demand generation, but they are seldom integrated into one pipeline. As such, this paper presents a pipeline for generating ABM using big data such as cell phone OD matrices. A case study of our pipeline is carried out for Brussels, Belgium, using the currently most popular ABM simulator MATSim, which results in the first ABM considering reality-based mobility behaviours for the "capital of the European Union". Notably, all data inputs of our pipeline are ubiquitous, which means our approach is transferable to modellers who would like to generate representative ABMs for their study areas in the future.