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11 Continuous video collected data on four channels at 30 Hz: · Critical incident button; and driver's face, forward roadway, left rear, and right rear. Addi- · Analyst identified. tional data included vehicle network information (speed, brake pedal, throttle, and turn signal), GPS (latitude, longitude, and Events identified from the data reduction included crash, heading), lateral and longitudinal acceleration, forward radar- crash: tire strike, near crash, crash-relevant conflict, uninten- collected data, and sleep quantity (measured by an activity tional lane deviation, and illegal maneuver. After the data wristwatch). reduction, five crashes, 61 near crashes, 1,586 crash-relevant After the data reduction, 16 crashes and 136 near crashes conflicts, 1,215 unintentional lane deviations, and 5,069 base- were identified. Data were reduced to identify events based on lines were identified (11). such information as: Project 9: Naturalistic Driving · Lateral acceleration; Performance During · Longitudinal acceleration; Secondary Tasks · Lane deviation; · Normalized lane position; and The purpose of the study, which was conducted by UMTRI, was · Forward TTC. to determine the frequency and conditions under which driv- ers engage in secondary behaviors and to explore the relation- The following events were identified: baseline driving epoch, ship these behaviors might have to driving performance. Data crash, crash: tire strike (defined as any physical contact of tires from 36 drivers involved in a naturalistic driving study were with other objects on the road), near crash (evasive maneuver), divided into three age-groups and analyzed to determine the crash-relevant conflict (evasive maneuver), crash-relevant frequency and conditions under which drivers engage in sec- conflict (no evasive maneuver), or nonconflict. Other vari- ondary behaviors, such as eating, drinking, and using a cellular ables, such as seat belt usage, date, time, light, weather, work phone. Mean ages for drivers in this study were 25.1, 45.6, and zone, roadway condition, and traffic density, were also coded. 64.2 for the younger, middle, and older age-groups, respec- tively. The data collected were also analyzed to explore the rela- The status of the vehicle and driver before events was coded as tionship these behaviors might have to driving performance. well (10). A video camera was mounted to the inside of the vehicle's A-pillar and captured 5-s images of the driver's face at Project 8: Naturalistic Truck 10 frames/s at 5-min intervals. Researchers examined a repre- Driving Study sentative sample of 18,281 video clips from the FOT. The sample was not associated with any RDCWS alerts, repre- Conducted by VTTI, the Naturalistic Truck Driving Study sented driving at least 25 mph, and included drivers with at (NTDS) attempted to examine the crash risk factors of least 10 qualifying video clips. Researchers coded 1,440 5-s commercial truck drivers. VTTI instrumented eight tractor video clips of the drivers' faces for the occurrence of specific trailers to monitor truck-driving behavior. The data set secondary behaviors and the duration of glances away from includes 735,000 VMT data, which amounts to 6.2 TB and the forward scene. 14,500 h of driving. Almost 3,000 critical events, such as Other performance data from instrumented vehicles were crashes, illegal maneuvers, and unintentional lane deviations, used to calculate the variability of the steering angle, the mean were analyzed. and the variability of lane position, the mean and the variabil- Continuous video data were collected on four channels: ity of throttle position, and the variability of speed (12). driver's face, forward roadway, left rear, and right rear. Addi- tionally, the final data set has vehicle network information (speed, brake pedal, throttle, and turn signal), GPS (latitude, Project 10: Effect of In-Vehicle longitude, and heading), lateral and longitudinal accelera- Video and Performance tion, forward and rear radar-collected data, and sleep quan- Feedback on Teen Driving Behavior tity (measured by an activity wristwatch). Data were reduced based on the following triggers: The study was conducted with 26 participants from a high school in rural Iowa. Study periods consisted of a 9-week base- · Longitudinal acceleration (LA); line period followed by 40 weeks of video collection and feed- · Swerve; back and 9 weeks of video collection without immediate · TTC; feedback. The study found that teen drivers showed a statisti- · Lane deviation; cally significant decrease in triggering behaviors between the