Data-driven Modeling of Transportation Systems and Traffic Data Analysis During a Major Power Outage in the Netherlands

Abstract

Efficient methods and tools for road network planning and traffic management are critically important in the ever more urbanized world. The goal of our research is the development of a data-driven multiscale modeling approach for accurate simulation of road traffic in real-life transportation networks, with applications in real-time decision support systems and urban planning. This paper reviews the multiscale traffic models, describes the traffic sensor data collected from 25000 sensors along the arterial roads in the Netherlands, and discusses the applicability of sensor data to model calibration and validation on each modeling scale. We also present a road network graph model and the reconstructed Dutch road network. Finally, we show the results of traffic data analysis during the major power outage in North Holland on 27 March 2015, paying special attention to one of the most affected locations around the A9/E19 interchange near Amsterdam airport Schiphol.