Zusammenfassung
Jede Beeinträchtigung des Verkehrsflusses unterliegt konkreten Ursachen. Oft entstehen sie aus vorherrschenden Rahmenbedingungen wie Wetter oder besonderen Ereignissen. Ein vom BMVIT kofinanziertes Forschungsprojekt hat sich zum Ziel gesetzt, die Abhängigkeiten und Zusammenhänge zwischen verkehrsbeeinflussenden Rahmenbedingungen und der potentiellen Staugefahr zu untersuchen. Es werden Ansätze aus dem Visuellen Data Mining und der Künstlichen Intelligenz vorgestellt. Die Auswirkungen von Umgebungsbedingungen auf den Verkehrsfluss sind oftmals durch Bildung charakteristischer Muster vorhersagbar. Mit diesem Hintergrund kann ein neues Niveau der Verkehrsprognose umgesetzt werden.
Summary
Every interference of traffic flow is subject to different causes. The majority of them are related to prevailing circumstances like weather and events. During a research project which was co-financed by the Austrian Ministry of Transport coherences and dependencies between traffic sensitive circumstances and congestion risk were investigated. Approaches of visual data mining and artificial intelligence are introduced. The impact of environment conditions on traffic flow is often predictable through detection of characteristic patterns. On this knowledge a new quality of traffic forecast can be implemented.
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Schneider, W., Toplak, W. Verkehrsprognosen mit Visuellem Data Mining und Künstlicher Intelligenz. Elektrotech. Inftech. 125, 232–237 (2008). https://doi.org/10.1007/s00502-008-0538-8
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DOI: https://doi.org/10.1007/s00502-008-0538-8