Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F21%3A00349222" target="_blank" >RIV/68407700:21260/21:00349222 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1155/2021/6634944" target="_blank" >https://doi.org/10.1155/2021/6634944</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1155/2021/6634944" target="_blank" >10.1155/2021/6634944</a>
Alternative languages
Result language
angličtina
Original language name
Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
21100 - Other engineering and technologies
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Advanced Transportation
ISSN
0197-6729
e-ISSN
2042-3195
Volume of the periodical
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Issue of the periodical within the volume
02
Country of publishing house
GB - UNITED KINGDOM
Number of pages
14
Pages from-to
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UT code for WoS article
000621827200002
EID of the result in the Scopus database
2-s2.0-85101517216