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Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles

Lian, Yanqi ; Zhang, Guoqing ; Lee, Jaeyoung ; Huang, Helai

Accident analysis and prevention, 2020-10, Vol.146, p.105711-105711, Article 105711 [Periódico revisado por pares]

England: Elsevier Ltd

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  • Título:
    Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles
  • Autor: Lian, Yanqi ; Zhang, Guoqing ; Lee, Jaeyoung ; Huang, Helai
  • Assuntos: Accidents, Traffic ; Artificial Intelligence ; Automation ; Automobile Driving ; Big Data ; Connected and automated vehicles ; Data mining ; Humans ; Intelligent transportation systems ; Machine learning ; Research Design ; Safety ; Traffic safety ; Transportation
  • É parte de: Accident analysis and prevention, 2020-10, Vol.146, p.105711-105711, Article 105711
  • Notas: ObjectType-Article-2
    SourceType-Scholarly Journals-1
    ObjectType-Undefined-1
    ObjectType-Feature-3
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  • Descrição: •This paper reviews Big Data safety analytics for intelligent transportation systems and connected/automated vehicles.•The data, models, techniques and applications of 57 safety studies are discussed.•Types of analytics including descriptive, predictive, and perspective analysis are summarized.•Challenges and future research suggestions are offered based on the above analysis. 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.
  • Editor: England: Elsevier Ltd
  • Idioma: Inglês
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