Data-driven modeling of transportation systems and traffic data analysis during a major power outage in the Netherlands

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 calibr... Mehr ...

Verfasser: Melnikov, Valentin R.
Krzhizhanovskaya, Valeria V.
Boukhanovsky, Alexander V.
Sloot, Peter M. A.
Dokumenttyp: Journal article
Erscheinungsdatum: 2018
Schlagwörter: DRNTU::Engineering::Computer science and engineering / Transportation Systems / Data-driven Modeling
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26810541
Datenquelle: BASE; Originalkatalog
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Link(s) : https://hdl.handle.net/10356/88992