Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2014 · 149 citations · 7 references
EngineeringAutonomous Vehicle NavigationAdvanced Driver-assistance SystemIntelligent SystemsPerceptionSocial SciencesAugmented Reality ConceptsVisual InspectionVisual CognitionDriver BehaviorAutonomous VehiclesSystems EngineeringAutomated VehiclesCognitive ScienceDesignAugmented Reality InformationAutonomous DrivingDriver PerformanceAugmented RealityAutomationExtended RealityHuman-computer InteractionAutomated Driving
Highly automated driving lets drivers disengage from monitoring, creating a challenge to re‑engage them when the system reaches a boundary. The study examines whether augmented reality cues can improve the driver takeover process. Two AR concepts were tested: AR red shows a corridor to avoid, while AR green indicates a safe corridor to steer through during takeover. AR type did not affect takeover times but did influence reaction type, with AR green yielding more consistent driving trajectories than AR red.
Highly automated driving allows the driver to temporarily turn away from the driving task, meaning he or she does not have to monitor the system. This leads to the challenge of getting the driver back into the loop, if the automation reaches a system boundary. This study investigates, whether augmented reality information can positively influence the take over process. Therefore we evaluated two augmented reality concepts. The concept “AR red” displays a corridor on the road to be avoided by the driver in a take over scenario. The concept “AR green” suggests a corridor the driver can safely steer through. Results indicate that the type of augmented reality information does not influence take over times, but considerably affects reaction type. Visual inspection revealed higher consistency in driving trajectories for participants following the proposed corridor of “AR green” concept as compared to trajectories of drivers confronted with the restricted zone of “AR red”.
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