Near Crashes as Crash Surrogate for Naturalistic Driving Studies

Abstract

Naturalistic driving is an innovative method for investigating driver behavior and traffic safety. However, as the number of crashes observed in naturalistic driving studies is typically small, crash surrogates are needed. A study evaluated the use of near crashes as a surrogate measure for assessment of the safety impact of driver behaviors and other risk factors. Two metrics, the precision and bias of risk estimation, were used to assess whether near crashes could be combined with crashes. The principles and exact conditions for improved precision and unbiased estimation were proposed and applied to data from the 100-Car Naturalistic Driving Study. The analyses indicated that a positive relationship exists between the frequencies of contributing factors for crashes and for near crashes. The study also indicated that analyses based on combined crash and near-crash data consistently underestimate the risk of contributing factors compared to use of crash data alone. At the same time, the precision of the estimation will increase. This consistent pattern allows investigators to identify true high-risk behaviors while qualitatively assessing potential bias. In summary, the study concluded that the use of near crashes as a crash surrogate provides definite benefit when naturalistic studies are not large enough to generate sufficient numbers of crashes for statistical analysis.