Exploring Naturalistic Driving Study (NDS) Data and Roadway Information Database (RID) for Emerging Applications in Traffic Safety

016279172016Final ReportPDFTech ReportNCITEC Project No. 2016-11Geographic information systemsAutomatic data collection systemsTraffic safetyHuman factorsData linkageData mappingHighwaysSafety and Human FactorsUnited StatesMississippiMississippi State University. National Center for Intermodal Transportation for Economic CompetitivenessIshak, SherifOsman, Osama A.Ashly, GraceTheriot, MatthewYe, MengqiuBakhit, PeterLouisiana State University (Baton Rouge, La.). Dept. of Civil and Environmental EngineeringMississippi State University. National Center for Intermodal Transportation for Economic CompetitivenessUnited States. Dept. of Transportation. Research and Innovative Technology AdministrationUniversity Transportation Centers Program (U.S.)US Transportation CollectionRecently, several transportation-related databases were introduced and archived in order to analyze the behavior of the different components of the transportation system. The Naturalistic Driving Study (NDS), which provides data on drivers\u2019 behavior during their typical commutes, and the Roadway Information Database (RID), which includes information about the geometric characteristics of the roads where the NDS participants drove, are two of the main data sources that have recently grabbed researchers\u2019 attention. These two databases provide ample amount of data that have the potential for transportation research in the area of traffic safety and human factors. While many researchers studied drivers\u2019 behavior using the NDS data, few studies were performed on the link between drivers\u2019 behavior and the characteristics of roadways. Thus, in this study, the research team thoroughly explored the RID dataset and identified its ability to link to NDS. Specifically, analysis was conducted to map RID and NDS data using ArcGIS. In addition, researchers provided several potential research topics integrating the combined RID and NDS database. A short list of potential applications includes quantifying the effect of warning and regulatory signs on driver compliance, measuring the effectiveness of safety campaigns with driver compliance, examining statistically significant clusters of crash and near crash events taking into account roadway conditions, and others.75