Exploring naturalistic driving data for distracted driving measures : [research project capsule].

Ishak, Sherif · 2015 · ROSA P / Louisiana Transportation Research Center

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Summary

This document is a research project capsule describing a study titled "Exploring Naturalistic Driving Data for Distracted Driving Measures," initiated in February 2015 by the Louisiana Transportation Research Center (LTRC) and Louisiana State University. The project addresses the significant public health and safety issue of distracted driving, which the National Highway Traffic Safety Administration (NHTSA) estimated caused 3,328 deaths and 421,000 injuries in the United States in 2012. In Louisiana, distracted driving was estimated to contribute to 10% of the 675 motor vehicle crash deaths reported in 2011. While a prior LTRC study identified texting and passenger conversation as performance impairers, it lacked the sample size to draw statistical conclusions regarding driver demographics, vehicle types, or road facility types. This new study aims to leverage the larger dataset from the Strategic Highway Research Program Naturalistic Driving Studies (SHRP NDS) to overcome these limitations. The primary objective of the research is to determine if the SHRP NDS data is sufficient for enhanced statistical analysis of distracted driving crash risks. The methodology involves a multi-step approach: first, conducting a comprehensive review of distracted driving laws across all 50 U.S. states, with a focus on cell phone and texting regulations; second, thoroughly exploring the SHRP NDS database, which contains data from over 3,000 drivers equipped with data acquisition systems; and third, identifying appropriate performance and surrogate measures of distraction. The team will document driver demographics, vehicle descriptions, and road facility types to identify suitable samples for further study. A key deliverable is the outlining of a methodology for developing a "distraction index," a mathematical model designed to quantify the crash risk potential of various distraction activities or combinations thereof. The study is designed as an exploratory effort to compile a summary of the capabilities and limitations of the SHRP NDS data for distracted driving research. By utilizing this large-scale naturalistic driving data, the project seeks to enable valid statistical inferences that can be applied to Louisiana drivers, specifically analyzing the impact of distractions based on gender, age, vehicle description, road facility type, and time of day. The final output will be a report recommending the suitability of the SHRP NDS data for further research on distracted driving in Louisiana. The project was funded through the Technology Transfer Program and was scheduled to conclude in August 2016.

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Topics

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• visual
• distraction detection algorithms
• external distraction
• distraction laws
• mobile phones
• naturalistic crash near crash

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: observational prevalence, crash risk outcomes
• Methodological Resource: dataset resource