School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan, People's Republic of China.
School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan, People's Republic of China.
Accid Anal Prev. 2020 Oct;146:105711. doi: 10.1016/j.aap.2020.105711. Epub 2020 Sep 4.
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.
大数据时代已经到来。最近，在智能交通系统（ITS）和联网/自动驾驶车辆（CAV）的环境下，大数据已经被应用于交通运输的各个领域，包括交通安全。在本研究中，我们回顾了最近利用大数据分析 ITS 和 CAV 环境下交通安全的研究。特别的主题包括事故检测或预测、发现事故的促成因素、驾驶行为分析、事故热点识别等。从回顾的研究中可以看出，利用高级分析技术进行大数据分析在理解和提高交通安全方面具有巨大的潜力。交通安全中的大数据应用整合和处理大量多源数据，突破了传统数据分析的局限性，并发现和解决了传统安全分析无法解决的问题。最后，为未来 ITS 和 CAV 环境下的大数据安全分析提供了建议。
