Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles

• DOI: 10.20485/jsaeijae.10.1_73
• Publication Date: 2020-02-28T22:11:04Z
• Authors: Morgan Price; John Lee; Azadeh Dinparastd...; Heishiro Toyoda; Joshua Domeyer
• Keywords: Driving simulator

Increasingly vehicle automation may convey greater capability than it actually possesses. The emergence of highly capable (e.g., SAE Level 4) and the promise driverless vehicles in near future can lead drivers to inappropriately cede responsibility for driving with less 2). This inappropriate reliance on compromise safety, so we investigated how algorithms instructions might mitigate overreliance. Seventy-two drivers, balanced by gender, between ages 25 55, participated this study using a fixed-base simulator. Drivers were exposed one three steering algorithms: lane centering, keeping, or an adaptive combination. A gaze tracker was used track eye glance behavior. While engaged, participants told they could interact email sorting task tablet positioned center stack. Changes roadway demand—traffic approaching adjacent lane—varied across drive. Instructions indicating driver responsible, combination algorithm, led be particularly attentive road as traffic approached them. These results also have implications evaluating more (SAE Levels 4 5), where need not attend road: unnecessary attention demands indicate lack trust acceptance control that guide vehicles.