Journal of Cognitive Engineering and Decision Making · 2017 · 282 citations · 20 references
EngineeringAutomotive EngineeringAutonomous SystemsAutomationAutonomous VehiclesVehicle TestingDriving AssessmentSituation AwarenessVehicle ControlVehicle Control SystemsDiscrete ControlDriver BehaviorDriver DistractionDriver Interface DesignDriver-vehicle InteractionHuman Factors In DrivingMental Model DevelopmentSituation Awareness In Driving
Autonomous and semiautonomous vehicles are being developed by many companies, offering potential safety and convenience benefits but also posing new challenges for drivers, especially regarding situation awareness and interaction with autonomy. The study aims to provide preliminary insights into driver challenges with new autonomous cars in realistic conditions, extending prior human‑autonomy research to driving. The authors performed a six‑month naturalistic driving study of Tesla Model S autonomy features, recording experiences and assessing situation awareness and autonomy problems. The study identified multiple challenges—including driver training gaps, mental model deficits, mode confusion, unexpected interactions, reduced situation awareness, distraction susceptibility, variability in SA, a shift from continuous to serial control, and the need for complex decisions—and proposes guidelines and recommendations to improve driver situation awareness when interacting with autonomous vehicles.
Autonomous and semiautonomous vehicles are currently being developed by over14 companies. These vehicles may improve driving safety and convenience, or they may create new challenges for drivers, particularly with regard to situation awareness (SA) and autonomy interaction. I conducted a naturalistic driving study on the autonomy features in the Tesla Model S, recording my experiences over a 6-month period, including assessments of SA and problems with the autonomy. This preliminary analysis provides insights into the challenges that drivers may face in dealing with new autonomous automobiles in realistic driving conditions, and it extends previous research on human-autonomy interaction to the driving domain. Issues were found with driver training, mental model development, mode confusion, unexpected mode interactions, SA, and susceptibility to distraction. New insights into challenges with semiautonomous driving systems include increased variability in SA, the replacement of continuous control with serial discrete control, and the need for more complex decisions. Issues that deserve consideration in future research and a set of guidelines for driver interfaces of autonomous systems are presented and used to create recommendations for improving driver SA when interacting with autonomous vehicles.
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Sebastian Hergeth, Lutz Lorenz, Roman Vilimek et al. · Human Factors The Journal of the Human Factors and Ergonomics Society · 2016 · 344 citations