• Medientyp: E-Artikel
  • Titel: Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles
  • Beteiligte: Hruboš, Marián; Nemec, Dušan; Bubeníková, Emília; Holečko, Peter; Spalek, Juraj; Mihálik, Michal; Bujňák, Marek; Andel, Ján; Tichý, Tomáš
  • Erschienen: Hindawi Limited, 2021
  • Erschienen in: Journal of Advanced Transportation
  • Sprache: Englisch
  • DOI: 10.1155/2021/6634944
  • ISSN: 2042-3195; 0197-6729
  • Schlagwörter: Strategy and Management ; Computer Science Applications ; Mechanical Engineering ; Economics and Econometrics ; Automotive Engineering
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  • Beschreibung: <jats:p>The paper proposes a method for detection of a fire inside the road tunnel without direct view on the fire, using on-board vehicle technologies. The system is based on comparing the measured development of temperature and smoke with model scenarios precomputed for a given road tunnel. The fire scenarios are computed by HW/SW tool TuSim regarding the parameters of the real road tunnel and then the results are presented to the vehicles via car-to-infrastructure communication link. The proper detection of the fire allows early evacuation of the vehicle passengers, which will significantly increase chance of their survival. The computed scenarios also provide supporting information for the rescue teams.</jats:p>
  • Zugangsstatus: Freier Zugang