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Title
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When vehicular networks meet Artificial Intelligence
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Author
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Abstract
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| In Vehicular Networks, some applications require a fast and reliable warning data transmission to the Emergency Services and Traffic Authorities. Nevertheless, communication is not always possible in vehicular environments due to the lack of connectivity. To overcome these issues (i.e., signal propagation problem and delayed warning notification time), an effective, smart, cost-effective, and all-purpose RSU deployment policy should be put into place. In this paper, we propose GARSUD, a system which uses a genetic algorithm that is capable to automatically provide a Roadside Unit deployment suitable for any given road map layout. Simulation results show that our proposal is able to reduce the warning notification time -the time required to inform emergency authorities in traffic danger situations- and to improve vehicular communication capabilities in different flows of traffic at different times during the day. |
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Language
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English
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Source (journal)
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International Conference on Tools with Artificial Intelligence : [proceedings]. - [Los Alamitos, Calif.]
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Source (book)
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Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence
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Publication
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New york
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Ieee
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2017
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ISSN
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1082-3409
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ISBN
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978-1-5386-3876-7
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978-1-5386-3876-7
978-1-5386-3876-7
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DOI
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10.1109/ICTAI.2017.00196
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Volume/pages
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(2017)
, p. 1304-1311
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ISI
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000435294700184
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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