The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.D uring recent years, the percentage of crashes involving some type of driver error or impairment before the crash was thought to be as high as 94% (1). Factors such as vehicle failures, roadway design or condition, or environment composed lower crash percentages. Naturalistic driving studies (NDSs) offer a unique opportunity to study driver performance and behavior experienced in the real world with actual consequences and risks (2-4). The NDS research method developed at the Virginia Tech Transportation Institute (VTTI) involves equipping volunteer participants' vehicles with advanced, unobtrusive instrumentation (e.g., cameras, sensors, radar) that automatically and continuously collects driving parameters-including speed, time to collision, global positioning system (GPS) location, acceleration, and eye glance behavior-from key-on to key-off (2, 5). The recently completed Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS), sponsored by the Transportation Research Board (TRB) of the National Academy of Sciences (NAS), is the largest NDS of its kind, capturing more than 35 million miles of continuous naturalistic driving data and 2 petabytes (PB) of video, kinematic, and audio data from more than 3,500 participants (5).NDSs provide insight into the factors that cause crashes, giving researchers the opportunity to observe actual driver behavior and to accurately understand drivers' performance during the minutes or seconds leading up to a crash (6, 7). However, previous NDSs captured a relatively small number of crashes (2,8). To obtain a statistically valid sample of crash factors in earlier NDSs, surrogate measures (e.g., near-crash events) were integrated into analyses. Near-crashes are operationally defined as having the observable factors that could lead to a crash, with one difference present: the performance of a successful evasive maneuver. Although previous studies used near-crashes as a surrogate for estimating crash risk, the accuracy and validity of combining crashes and near-crashes to estimate driver risk are just beginning to be understood (9). With the com...

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Teenaged, young adult drivers and senior drivers are more adversely impacted by secondary-task engagement than middle-aged drivers. Visual-manual distractions impact drivers of all ages, whereas cognitive distraction may have a larger impact on young drivers.

IMPORTANCE Government motor vehicle crash reports used in the study of driver safety can be biased and incomplete. Naturalistic driving methods using in-vehicle instrumentation have been developed in recent years to objectively measure crashes and near crashes as they occur on the road using video and vehicle kinematic data.OBJECTIVE To examine visual risk factors associated with at-fault crashes and near crashes among older drivers, most of whom have age-related eye conditions associated with vision impairment. DESIGN, SETTING, AND PARTICIPANTSThis prospective cohort study was conducted at an academic ophthalmology clinic from January 1, 2015, to November 10, 2018, among 154 adults 70 years of age or older who were legally licensed in Alabama and who reported currently driving at least 4 days per week; 137 of 151 participants (90.7%) had an age-related eye condition in at least 1 eye. Drivers participated in a baseline visual function assessment followed by installation of a data acquisition system recording multichannel synchronized video and vehicle kinematics in their personal vehicle. Drivers were instructed to drive for 6 months as they normally would during everyday life. Statistical analysis was performed from June 15 to September 15, 2020. MAIN OUTCOMES AND MEASURESThe rate of combined incident at-fault crashes and near crashes, defined by the number of events and the number of miles driven. RESULTSThe sample consisted of 154 drivers (85 men [55.2%]; mean [SD] age, 79.3 [5.1] years). Visual functions associated with crash and near-crash involvement included impaired contrast sensitivity (rate ratio [RR], 2.7; 95% CI, 1.3-5.5), moderate (RR, 2.3; 95% CI, 1.1-4.9) and severe (RR, 5.0; 95% CI, 2.2-11.7) slowing in visual processing speed, and elevated motion perception thresholds for a drifting grating (RR, 1.9; 95% CI, 1.1-3.5). Those with impaired peripheral visual field sensitivity had increased rates of crashes and near crashes (RR, 1.8; 95% CI, 1.0-3.3); however, this finding was not statistically significant (P = .07). CONCLUSIONS AND RELEVANCEWith the use of naturalistic driving methods in which crashes and near crashes involving older drivers are objectively measured as they occur on the road, associations have been identified between impaired contrast sensitivity, slowed visual processing speed, and impaired motion perception and an increased rate of a combined total of at-fault crashes and near crashes.