AAA Foundation Study: Assessing Crash Causes Using Naturalistic Data
Researchers know a great deal about the factors that affect whether or not drivers crash in simulators and experimental studies. Actual crashes, however, represent the unique confluence of an almost infinite number of factors, including roadway, weather, driver mental and emotional state, and traffic, to name just a few. There is currently little definitive scientific knowledge about factors - such as drowsiness and distraction - that cause actual crashes.
Over the past ten years, in-vehicle event recorders (IVERs) have become more widely accepted as a way to gather crash data. In this study, the HF Program;s naturalistic driving specialists developed a detailed coding strategy to analyze the sources of real-world crashes using data from the DriveCam IVER system.
Analysts began by coding DriveCam data gathered in previous HF studies of younger drivers. Early results from the coding of 837 vehicle-to-vehicle crashes have produced some interesting findings on crash type (56% were rear-end crashes), prevelance of distraction (present in 67% of crashes), and sleepiness (coded in only 1% of crashes).
Also interesting is the unexpected finding that for each crash it is possible to calculate the magnitude and force of the crash, and therefore produce an accurate reconstruction of the event using the DriveCam data.
This project represents the first-ever comprehensive examination of naturalistic crash data. The knowledge gained will provide significant societal benefit and advance the field of traffic and crash safety. More
specifically, information regarding whether and how drivers actually respond can be used to enhance automotive safety technology and distraction and drowsiness mitigation.