BACKGROUND
Statistical and analytical models have been used widely to predict the counts and probabilities of crashes on roadway locations using historical crash data. Unbiased model estimation is critical in accurately predicting crashes and allocating funds for improving traffic safety. However, underreporting or overreporting of certain behaviors in crash data, specifically alcohol and/or drug-impaired driving and distracted driving, may result in problematic model estimation results. Under/over reporting of impaired and distracted driving also has the potential to impact other areas that rely on reported crash data, such as drug recognition expert (DRE) training, high-visibility enforcement, where to employ saturation patrols, existing laws on cell phone use, and marijuana legislation. Although previous studies have been developed to investigate the effects of crash data misreporting on crash prediction models, most of the existing studies relied on simulated data, which might be difficult to validate in real-world situations. With the growth of multidisciplinary datasets, research is needed to investigate the extent impaired and distracted driving have been under or over reported in crash data, and the potential negative impacts of such misreporting on driver behavior related crash analysis. Additional sources of data that can be used to investigate this issue include hospital injury data, toxicology data, and citation data. Research also is needed to propose what solutions can be used to reduce or eliminate impacts of under/over reporting of these two issues in crash data.
OBJECTIVES
The objectives of this research are to develop procedures to assess the existence and extent of under/over reporting of impaired and distracted driving in crash data, and to propose a methodology to improve the reporting of impaired and distracted driving in motor vehicle crashes.
The research will examine and document the current state of knowledge and practice; develop a method to assess the extent of under/over reporting of impaired and distracted driving in crash data; quantify the impacts of under/over reporting of impaired and distracted driving on crash analysis; and develop guidelines to help reduce or eliminate under/over reporting of impaired and distracted driving in crash data systems.
A series of workshops will be planned to demonstrate the application of the methodology, how it was developed, and assist states with facilitating this effort on their own.
STATUS: Research underway.
