详情

Automatic Safety Diagnosis in Connected Vehicle Environment (Project F4)

项目名称：	Automatic Safety Diagnosis in Connected Vehicle Environment (Project F4)
摘要：	Traditionally highway safety studies rely on historical crash data. Yet because crashes are rare events, crash-data possess deficiency in availability and quality. As an alternative, the non-crash-data approach which measures conflict and near-crash based on Traffic Conflict Technology (TCT) has been increasingly widely used. Connected vehicle (CV) is a major research initiative of the US Department of Transportation to capture vehicle position, motion and instantaneous driving for information connectivity. In the CV environment, massive Basic Safety Messages (BSMs) are being generated and exchanged between vehicles and infrastructures. Driving behavior differs considerably among individuals and each driver has her/his own driving patterns, among which the most important feature for safety diagnosing is threshold segmenting normal and abnormal/aggressive driving status. Due to the tremendous volume and complexity, it is not realistic to store all the BSMs generated in CV into the data center. Extensive researches have been dedicated to the big data of BSMs but not yet on individual level for near-crash detection. This research is motivated to explore what information imbedded in BSMs need to be stored, how to extract it and how to process it for real-time traffic safety diagnosis combining the TCT technology. The goal of this research is to construct a computational pipeline of Near-crash Diagnoses System to process the BSMs generated in the CV environment to identify near-crash events on the individual level.
状态：	Active
资金：	57500
资助组织：	Southeastern Transportation Research, Innovation, Development and Education Center (STRIDE)<==>Office of the Assistant Secretary for Research and Technology
项目负责人：	Tucker-Thomas, Dawn
执行机构：	Jackson State University, Jackson
开始时间：	20200801
预计完成日期：	20210731
主题领域：	Data and Information Technology；Highways；Operations and Traffic Management；Safety and Human Factors