Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles
| Autor: | Marek Bujňák, Marián Hruboš, Juraj Spalek, Peter Holečko, Tomáš Tichý, Ján Andel, Dušan Nemec, Michal Mihálik, Emilia Bubenikova |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Smoke
0209 industrial biotechnology Economics and Econometrics TA1001-1280 Article Subject Computer science Strategy and Management Mechanical Engineering Detector 0211 other engineering and technologies Communication link 02 engineering and technology Automotive engineering Computer Science Applications Transportation engineering 020901 industrial engineering & automation Automotive Engineering Transportation and communications HE1-9990 021101 geological & geomatics engineering |
| Zdroj: | Journal of Advanced Transportation, Vol 2021 (2021) |
| ISSN: | 0197-6729 |
| DOI: | 10.1155/2021/6634944 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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