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AutomotiveUI 2016 : Automotive User Interfaces and Interactive Vehicular Applications

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Conference Series : Automotive User Interfaces and Interactive Vehicular Applications
 
Link: http://www.auto-ui.org/16/
 
When Oct 24, 2016 - Oct 26, 2016
Where Ann Arbor, MI, USA
Submission Deadline May 27, 2016
Notification Due Jul 22, 2016
Final Version Due Sep 12, 2016
Categories    computer science   user interfaces   automotive
 

Call For Papers

AutomotiveUI’16 invites you to submit original work in one or more of the following formats: full papers, workshops, work in progress and doctorial colloquia. Submissions that include theoretically-based, quantitative predictions of experimental outcomes as well as validation of those outcomes, are particularly encouraged.

Topics include, but are not limited to:
Devices & Interfaces

Multi modal, speech, audio, gestural, natural input/output
In-car gaming, entertainment and social experiences
Interfaces for navigation
Text input and output while driving
Applications and user-interfaces for inter-vehicle communication
Sensors and context for interactive experiences in the car
Biometrics and physiological sensors as a user-interface component

Automation & Instrumentation

Automated Driving and Interfaces for (semi-) autonomous driving
Head-Up Displays (HUDs) and Augmented Reality (AR) concepts
Co-operative Driving/Connected Vehicles
Assistive technology in the vehicular context
Information access (search, browsing, etc.)
Vehicle-based apps, web/cloud enabled connectivity

Evaluation & Benchmarking

Methods and tools for automotive user-interface research, including simulation
Automotive user-interface frameworks and toolkits
Naturalistic/field studies of automotive user interfaces
Automotive user-interface standards
Modeling techniques for cognitive workload and visual demand estimation

Driver Performance & Behavior

Different user groups and user group characteristics
Subliminal cues, warnings, and feedback to augment driving behavior
Emotional state recognition while driving
Detecting/measuring driver distraction
Detecting and estimating user intentions

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