Traffic Simulations with Empirical Data: How to Replace Missing Traffic Flows?

Lars Habel (), Alejandro Molina (), Thomas Zaksek (), Kristian Kersting () and Michael Schreckenberg ()
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Lars Habel: Universität Duisburg-Essen, Physik von Transport und Verkehr
Alejandro Molina: Technische Universität Dortmund, Fakultät für Informatik
Thomas Zaksek: Universität Duisburg-Essen, Physik von Transport und Verkehr
Kristian Kersting: Technische Universität Dortmund, Fakultät für Informatik
Michael Schreckenberg: Universität Duisburg-Essen, Physik von Transport und Verkehr

A chapter in Traffic and Granular Flow '15, 2016, pp 491-498 from Springer

Abstract: Abstract ForHabel, Lars the real-timeMolina, Alejandro microscopic simulationZaksek, Thomas of traffic onKersting, Kristian a real-worldSchreckenberg, Michael road network, a continuous input stream of empirical data from different locations is usually needed to achieve good results. Traffic flows for example are needed to properly simulate the influence of slip roads and motorway exits. However, quality and reliability of empirical traffic data is sometimes a problem for example because of damaged detectors, transmission errors or simply lane diversions at road works. In this contribution, we attempt to close those data gaps of missing traffic flows with processed historical traffic data. Therefore, we compare a temporal approach based on exponential smoothing with a data-driven approach based on Poisson Dependency Networks.

Keywords: Empirical Traffic Data; Traffic Flow Time Series; Exponential Prediction; Real-world Topologies; Road Cross-section (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-33482-0_62

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DOI: 10.1007/978-3-319-33482-0_62

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