01590026

Component

The SHRP 2 NDS project was the largest naturalistic driving study ever conducted with three years’ worth of data collected. The data obtained was released to the researching public in 2014 through the project’s InSight webpage. The objectives of this study were to first explore the massive dataset and determine if it were possible to develop a prediction model from several performance measures that could be used to study driver distraction. Time series data on driver GPS speed, lateral and longitudinal acceleration, throttle position and yaw rate were discovered as five appropriate performance measures available from the NDS that could be used for the purpose of this research. Using this data the objective was to develop three models that could predict whether a driver was engaged in any of three specific groups of distracting tasks or no secondary task at all. The specific distracting tasks that were examined included talking or listening on a hand-held phone, texting or dialing on a hand-held phone, and driver interacting with an adjacent passenger. Multiple logistic regression was the statistical method used to determine the odds of a driver being engaged in one of the secondary tasks given their corresponding driving performance data. Results indicated none of the three models were a good fit of the data and all had little predictive power. However, a change in lateral acceleration seemed to be an indicator of a driver engaged in texting or dialing, but more research is needed to confirm this conclusion.

This paper was sponsored by TRB committee AND10 Standing Committee on Vehicle User Characteristics. Alternative title: Exploration of SHRP 2 Naturalistic Driving Study: Development of Distracted Driving Prediction Model

01584066

16-2922

English

15p

2016

Transportation Research Board 95th Annual Meeting

Web

Figures; References (21) ; Tables

Automatic data collection systems; Behavior; Cellular telephones; Data analysis; Data mining; Distraction; Performance measurement; Speed; Text messaging

Data and Information Technology; Highways; Safety and Human Factors; I83: Accidents and the Human Factor

Transportation Research Board Annual Meeting 2016 Paper #16-2922

TRIS, TRB, ATRI

Jan 12 2016 5:18PM