Streamlining Drowsiness Assessment: An In-Depth Review of ORD and PERCLOS Methods

Every year, drowsy and fatigued driving contributes to thousands of crashes and their resulting injuries and fatalities. Naturalistic driving data allows researchers an opportunity to better understand drowsy driving through review of driver-facing video capturing the driver’s behavior and eyes. Two drowsiness measures that have been successfully used in naturalistic driving data are Observer Rating of Drowsiness (ORD) (Wiegand, McClafferty, McDonald, & Hanowski, 2009) and manual percentage of eye closure (PERCLOS) (Wierwille & Ellsworth, 1994). The current study explored how different drowsiness measures impact fatigue determination for an event and study estimates of fatigue prevalence, risk, and secondary task association for truck and motorcoach drivers. Analyses investigated PERCLOS scores using 1 minute of data (PERCLOS 1) versus 3 minutes of data (PERCLOS 3). The study found the sample size of events with PERCLOS data increased by 8.94% when PERCLOS 1 criteria were used. Overall, matching fatigue determination (whether fatigue was observed) in PERCLOS 3 and PERCLOS 1 scores was found for between 95.89% and 99.48% of truck and motorcoach baselines (BLs) and safety-critical events (SCEs). The risk of SCE involvement when driving while fatigued was consistent for truck drivers when using PERCLOS 1 or PERCLOS 3 to determine fatigue. However, for motorcoach drivers, the risk of SCE involvement when driving while fatigued depended on the PERCLOS measure used. The study also aimed to determine how to potentially lessen the effort of fatigue data reduction in future studies and obtain the most valuable dataset at the lowest cost to time and budget. The single fatigue reduction approach with the lowest time and cost budget was PERCLOS 1 for all events. However, a targeted fatigue reduction approach that includes ORD for all events and targeted PERCLOS 3 or PERCLOS 1 reduction for events that meet or exceed an ORD threshold can reduce the cost of fatigue reduction while maintaining the advantage of ORD reduction.