Integrating Adaptive Lighting Database with SHRP 2 Naturalistic Driving Study Data

Abstract

The limited information in traditional safety data makes exploration of the complex interaction between characteristics of roadway lighting and crash risks and driver behavior difficult, yet this knowledge is needed by transportation agencies that want to reduce energy consumption while maintaining safety. Data from the SHRP 2 Naturalistic Driving Study (NDS) have provided researchers a powerful tool for safety analysis. In addition, the availability of a massive adaptive lighting database (ALD) has made it possible to evaluate and improve the use of roadway lighting as a safety countermeasure. This paper integrates ALD and NDS data and provides insight into how other spatially related data can be integrated with the NDS data to cater to the needs of safety studies. The ALD includes detailed in situ roadway lighting measurements for more than 2,000 mi of major roads in seven states. This paper fills a gap in NDS-related documentation by detailing the NDS database structure and elements. An efficient spatial approach for integrating NDS data with ALD or other large roadway-related data sets in a similar format is presented. The approach uses a combination of existing and custom geographic information system tools, including a hybrid tool that uses attributes to perform the ArcGIS Near function.