AutomotiveUI, the International Conference on Automotive User Interfaces and Interactive Vehicular Applications, is the premier forum for UI research in the automotive domain. AutomotiveUI brings together researchers and practitioners interested in both the technical and the human aspects of in-vehicle user interfaces and applications. AutomotiveUI'15 will address novel in-vehicle services, models of and concepts for enhancing the driver experience, driver performance and behaviour, development of (semi-) autonomous driving, and the needs of different user groups. Papers that include theoretically-based, quantitative predictions of experimental outcomes as well as validation of those outcomes, are particularly encouraged.
In-car interactive technology is becoming ubiquitous and cars are increasingly connected to the outside world. Drivers and passengers use this technology because it provides valuable services. Some technology, such as collision warning systems, assists drivers in performing their primary in-vehicle task (driving). Other technology provides information on myriad subjects or offers entertainment to the driver and passengers.
The design of in-car devices has historically been the responsibility of car manufacturers and their parts suppliers. However, the responsibility is now shifting toward larger and more fluctuating groups including car OEMs, Tier 1 and Tier 2 suppliers of factory-installed electronics, and the manufacturers of hardware and software brought into the vehicle (e.g., personal navigation devices, smartphones, and tablets).
The challenge that arises from the proliferation of in-car devices is that they may distract drivers from the primary task of driving, with possibly disastrous results. Thus, one of the major goals of this conference is to explore ways in which in-car user interfaces can be designed so as to lessen driver distraction while still enabling valuable services.
Consider driving safety, our focus in designing in-car user interfaces should not be purely on eliminating distractions. In-car user interfaces also offer the opportunity to improve the driver's performance (e.g, increasing awareness of upcoming hazards).
In-car interfaces can also enhance the experience of all occupants in the car. To this end, a further goal of AutomotiveU'15 is the exploration of in-car interfaces that address the varying needs of different users (including disabled drivers, elderly drivers, passengers, and the users of rear-seat entertainment systems). The conference goal is to showcase ways to advance the state of the art in vehicular user experiences, for enhanced safety, comfort, and enjoyment.
AutomotiveUI‚ 2015 invites you to submit original work in one or more of the following formats: full and short papers, workshops, work in progress and doctorial colloquium. 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 behaviour
- Emotional state recognition while driving
- Detecting/measuring driver distraction
- Detecting and estimating user intentions