For Authors
Welcome to AutomotiveUI 2025
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 2025 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.
AutomotiveUI 2025 conference invites you to submit original work in different formats. Details will be published soon.
Important Dates
- Full Papers Abstract: April 3, 2025
- Full Papers: April 10, 2025
- Work in Progress: June 19, 2025
- Videos: June 26, 2025
- Interactive Demos: July 10, 2025
- Workshops: June 19, 2025
- Doctoral Colloquium: July 3, 2025
- Student Research Track: July 3, 2025
Submissions are accepted until 11:59 pm AoE (Anywhere on Earth) on the dates shown below. The Full Paper dates are fixed; there will be no extensions. Other dates may be subject to change.
Submission Types
Paper
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 in-person conference event.
WORKSHOPS
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.
DOCTORAL COLLOQUIUM
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.
WORK IN PROGRESS
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.
VIDEO DEMOS
Video Demo submissions are short motion presentations that showcase examples best communicated in this format or provide supplementary content to another submission (e.g. a paper). Video demos 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.
Conference Topics
The following provides a non-exhaustive list of conference topics.
- 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
We explicitly invite and encourage submissions targeting a wide scope of automated mobility solutions. Papers discussing relevant challenges and proposing solutions for low automation levels (SAE levels 1 and 2) are just as welcome as papers discussing control transitions for SAE level 3 systems, or aspects of uncrewed drone operations, remote management, or any other relevant higher-automation challenge.
Proposals for mobility solutions outside the “standard” spectrum of interaction solution for powered individual mobility means (automated or non-automated). This category includes both environmental and social aspects subtopics such as:
- User interaction with or user interfaces for green cars and car sharing
- User interaction with or user interfaces for (automated) public transport
- User perception, acceptance and trust in technologies related to sustainability, environmental impact
- Interaction solutions for low-/non-powered and micro mobility means (e.g., bikes/e-bikes, scooters/e-scooters)
- User interfaces for behavior change towards sustainable mobility
- Environmental impact of technologies related to AutomotiveUI
- Prosocial traffic behavior
- 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.
- 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