# In-Vehicle Interface Adaptation to Environment-Induced Cognitive Workload

arXiv: https://arxiv.org/abs/2210.11271 · HTML: https://mlsanity.com/paper/2210.11271/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 20 references that are in the map.
- First posted on arXiv 20 Oct 2022.

## Builds on (most cited first, 1 of 1)

- [What's on your mind? A Mental and Perceptual Load Estimation Framework towards Adaptive In-vehicle Interaction while Driving](https://mlsanity.com/paper/2208.05564/) (2022)

## Built on by (most cited first, 1 of 1)

- [Adaptive User-centered Neuro-symbolic Learning for Multimodal Interaction with Autonomous Systems](https://mlsanity.com/paper/2309.05787/) (2023)

## Abstract (arXiv)

Many car accidents are caused by human distractions, including cognitive distractions. In-vehicle human-machine interfaces (HMIs) have evolved throughout the years, providing more and more functions. Interaction with the HMIs can, however, also lead to further distractions and, as a consequence, accidents. To tackle this problem, we propose using adaptive HMIs that change according to the mental workload of the driver. In this work, we present the current status as well as preliminary results of a user study using naturalistic secondary tasks while driving (i.e., the primary task) that attempt to understand the effects of one such interface.