For Authors

Welcome to AutomotiveUI 2023

AutomotiveUI (AutoUI), the International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, is the premier forum for UI research in the automotive domain. The conference brings together over 200 researchers and practitioners interested in both the technical and the human aspects of in-vehicle user interfaces and applications. Consistent with prior conferences, AutomotiveUI 2023 will address novel in-vehicle services, models of and concepts for enhancing the driver experience, driver performance and behavior, development of (semi-) autonomous driving, and the needs of different user groups.

AutomotiveUI 2023 conference invites you to submit original work in different formats. Details will be published soon.

Important Dates

Submission Deadlines
Full Papers Abstract: April 12, 2023
Full Papers: April 19, 2023
Workshops & Tutorials: June 14, 2023
Videos: June 14, 2023
Interactive demos: June 14, 2023
Work in Progress: June 14, 2023
Doctoral Colloquium: July 5, 2023

Submissions are accepted until 11:59 pm AoE (Anywhere on Earth). These dates are fixed; there will be no extensions.

Submission Types


AutomotiveUI Papers are archival publications of original research. Authors are invited to submit papers formatted in accordance with the new single-column ACM SIGCHI format. All accepted papers will be included in the conference proceedings which will be archived in the ACM digital library. Authors of accepted papers will present their contribution at the virtual event. 


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Video submissions are short motion presentations that showcase examples best communicated in this format or provide supplementary content to another submission (e.g. a paper). Videos can, but are not restricted to present your  study design, data collection design, progress over time, study results, research projects, design concepts and visions of the future. 

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A Work in Progress (WiP) is a concise report of late-breaking findings or other types of innovative or thought-provoking work relevant for the AutomotiveUI community. It represents work that either has not reached a level of completion expected of a conference paper or for which a conference paper is not the most effective communication method. That said, appropriate submissions should make a contribution to the body of AutomotiveUI knowledge, whether realized or promised. 

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A workshop is a meeting to address a topic or method of common interest to a selective group of AutomotiveUI attendees. Typically, there is a focus on contemporary challenges. For example, previous workshops have addressed natural user interfaces, situational awareness, trust in automated driving, and the use of virtual and augmented reality in vehicle studies.

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Interactive Demos

Interactive Demo submissions must consist of a thorough description of the technology / interactive prototype/ interface or methodology being presented, images or video links to the demo, and a description of the demo requirements (space, power and connectivity).

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The DC brings together PhD students working on topics related to automotive user interfaces and interactive vehicular applications, providing them with an opportunity to present and discuss their research with their peers and senior faculty. It will further provide opportunities for PhD students to network and facilitate professional development by sharing research interests.

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Conference Topics
The following provides a non-exhaustive list of conference topics.


Proposals for sustainable mobility that are relevant for AutomotiveUI. Sustainable development can be interpreted as development that meets the needs of the present without compromising the ability of future generations to meet their own needs. This category includes both environmental and social aspects such as:

  • (User interaction with or user interfaces for) green cars
  • (User interaction with or user interfaces for) car sharing
  • User perception, acceptance and trust in technologies related to sustainability, environmental impact
  • User interfaces for behavior change towards sustainable mobility
  • The “second life” of a car: what happens to car after the first owner sells it to another owner (potentially: from another country, context)
  • Environmental impact of technologies related to AutomotiveUI
  • Prosocial traffic behavior
  • The effect of driving automation on employment


  • Accessibility of AutomotiveUI-related technology, settings, and contexts
  • Under-represented groups and their experiences
  • Technologies that accommodate more than “the average” user
  • Experience in and perspective on AutomotiveUI for the Global South


AutomotiveUI technologies and interventions, and automated technology can change experience in various ways. This broad category captures aspects such as the relationship between AutomotiveUI and:

  • Ethics (related to AutomotiveUI)
  • Human and humane experiences (related to AutomotiveUI)
  • Trust (related to AutomotiveUI)
  • Ethical and social dilemma’s (related to AutomotiveUI)
  • Philosophical perspectives (related to AutomotiveUI)


  • Design and validation of novel interfaces and artifacts
  • Novel methods, insights from engaging in or with the design of interactive systems and artefacts.


  • Areas where the field of “computational interaction” (see subcommittee description for CHI) intersects with AutomotiveUI
  • For example: use of signal detection theory, statistics, control theory, natural language processing, machine learning, deep learning, cognitive architectures, simulation to gain insight into AutomotiveUI
  • Computational cognitive or social models to predict human behavior for future interfaces
  • Models or simulations to integrate insights about driving (e.g. in cognitive architectures) 


We encourage submissions that take a radically different (“out of the box”) perspective compared to previous AutomotiveUI publications, provided that this perspective is relevant for the AutomotiveUI community and shows scientific rigour and clarity. For example, papers that apply different methods, or that test an idea that goes against popular opinion. This category is not meant to cover what CHI calls “Alt-CHI” (as in: work that is hard to get into CHI). Rather, it encourages different perspectives that are scientifically valid and grounded, but that are in a substantial way different from the “typical” AutomotiveUI paper.


  • Different input modalities, such as multi-modal, speech, audio, gestural, thermal, touch, natural input/output
  • Different output modalities, such as multi-modal, audio, gestural, thermal, touch, 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
  • Electric vehicle interfaces
  • Affective intelligent interfaces
  • Future interfaces and technology for the automotive domain


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


  • 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


  • Human cognition and behavior in automotive settings
  • Different user groups and user group characteristics
  • Subliminal cues, warnings and feedback to augment driving behavior
  • Emotional or cognitive state recognition while driving
  • Detecting / measuring driver distraction and workload
  • Detecting and estimating user intentions
  • (Cognitive or social) Modeling of driver though, behavior, and experience