Relationship Between Driver Eyes-Off-Road Interval and Hazard Detection Performance Under Automated Driving 2016-01-1424
Partially automated driving involves the relinquishment of longitudinal and/or latitudinal control to the vehicle. Partially automated systems, however, are fallible and require driver oversight to avoid all road hazards. Researchers have expressed concern that automation promotes extended eyes-off-road (EOR) behavior that may lead to a loss of situational awareness (SA), degrading a driver’s ability to detect hazards and make necessary overrides. A potential countermeasure to visual inattention is the orientation of the driver’s glances towards potential hazards via cuing. This method is based on the assumption that drivers are able to rapidly identify hazards once their attention is drawn to the area of interest regardless of preceding EOR duration. This work examined this assumption in a simulated automated driving context by projecting hazardous and nonhazardous road scenes to a participant while sitting in a stationary vehicle. Participants engaged in visual-based secondary tasks of various lengths before being exposed to either a hazardous or nonhazardous road scene. Drivers were asked to press a hand-held button as soon as a hazard was detected. Results showed that EOR duration did not influence detection rates or reaction time to imminent hazards. These findings suggest that imminent forward hazards in drivers’ field of view automatically capture drivers’ attention in a manner that does not involve “higher-level” SA processes. Effectiveness of forward cuing in avoiding imminent hazards in a partially automated driving context is not moderated by prior EOR duration.
Citation: Glaser, Y., Llaneras, R., Glaser, D., and Green, C., "Relationship Between Driver Eyes-Off-Road Interval and Hazard Detection Performance Under Automated Driving," SAE Technical Paper 2016-01-1424, 2016, https://doi.org/10.4271/2016-01-1424. Download Citation
Yi G. Glaser, Robert E. Llaneras, Daniel S. Glaser, Charles A. Green
General Motors Co., Virginia Polytechnic Institute & State Univ.