Sensor-Actuator Supported Implicit Interaction in Driver Assistance Systems

• Κύριος συγγραφέας: Riener, Andreas (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Wiesbaden : Vieweg+Teubner, 2010.
• Θέματα: Engineering.; Computer science.; User interfaces (Computer systems).; Automotive engineering.; Automotive Engineering.; Computer Science, general.; User Interfaces and Human Computer Interaction.

 The research trend in the automotive domain is clearly moving from mechanically controlled to computer assisted systems for both vehicle handling and comfort functions. Driver Assistance Systems (DAS), originally integrated to decrease the cognitive load and to increase the comfort for the driver, cause additional workload and stress for the driver, and as a consequence may distract from the main activity of driving and lead to traffic accidents. Andreas Riener studies the influence of implicit interaction using vibro-tactile actuators, invisibly and unobtrusively embedded into the car seat, as additional sensory channels for car-driver feedback, and pressure sensor mats, integrated into the seat for implicit information transmission from the driver toward the vehicle. The results of the experiments, e.g. implicit driver identification or activity recognition, vibro-tactile activity notification, motivate to use both vibro-tactile notifications and pressure sensor images to improve vehicle handling performance and to decrease the driver’s cognitive workload. 

 Research Hypotheses -- Perception -- Driver Expression -- Perception and Articulation -- Hypotheses and Research Questions -- Driver-Vehicle Interaction -- Vibro-Tactile Articulation and Presentation -- Information Needs of Drivers -- The Driver as the Weak Point in Interaction -- Driver Activity and Notification Demands -- Advanced Driver Assistance Systems (ADAS) -- Vibro-Tactile Interfaces -- Methodology -- Analytical Methods -- Experiments -- Discussion and Conclusion -- Predeterminations for Investigation -- Reflecting on the Hypotheses -- Experiments: Lessons Learned -- Conclusion -- Future Prospects.