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Tytuł:
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Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles.
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Autorzy:
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Lian Y; School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan, People's Republic of China.
Zhang G; School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan, People's Republic of China.
Lee J; School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan, People's Republic of China. Electronic address: .
Huang H; School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan, People's Republic of China.
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Źródło:
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Accident; analysis and prevention [Accid Anal Prev] 2020 Oct; Vol. 146, pp. 105711. Date of Electronic Publication: 2020 Sep 04.
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Typ publikacji:
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Journal Article; Systematic Review
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Język:
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English
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Imprint Name(s):
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Publication: Oxford : Pergamon Press
Original Publication: [New York, Pergamon Press]
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MeSH Terms:
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Accidents, Traffic*
Artificial Intelligence*
Automation*
Automobile Driving*
Big Data*
Research Design*
Safety*
Humans ; Transportation
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Contributed Indexing:
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Keywords: Big Data; Connected and automated vehicles; Data mining; Intelligent transportation systems; Machine learning; Traffic safety
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Entry Date(s):
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Date Created: 20200908 Date Completed: 20210104 Latest Revision: 20210104
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Update Code:
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20240105
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DOI:
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10.1016/j.aap.2020.105711
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PMID:
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32896748
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The era of Big Data has arrived. Recently, under the environment of intelligent transportation systems (ITS) and connected/automated vehicles (CAV), Big Data has been applied in various fields in transportation including traffic safety. In this study, we review recent research studies that employed Big Data to analyze traffic safety under the environment of ITS and CAV. The particular topics include crash detection or prediction, discovery of contributing factors to crashes, driving behavior analysis, crash hotspot identification, etc. From the reviewed studies, employing advanced analytics for Big Data has a great potential for understanding and enhancing traffic safety. Big Data application in traffic safety integrates and processes massive multi-source data, breaks through the limitations of the traditional data analytics, and discovers and solves the problems, which cannot be solved by the traditional safety analytics. Lastly, suggestions are provided for future Big Data safety analytics under the environment of ITS and CAV.
(Copyright © 2020 Elsevier Ltd. All rights reserved.)