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

Journal: Accident; analysis and prevention
PMID:

Abstract

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.

Authors

  • Yanqi Lian
    School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan, People's Republic of China.
  • Guoqing Zhang
    Department of Anesthesiology, Zhumadian Central Hospital, Zhumadian, Henan Province, China. Electronic address: hubywk@163.com.
  • Jaeyoung Lee
    School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan, People's Republic of China. Electronic address: jaeyoung@knights.ucf.edu.
  • Helai Huang
    Urban Transport Research Center, School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, 410075 PR China. Electronic address: huanghelai@csu.edu.cn.