In-Vehicle Interface Adaptation to Environment-Induced Cognitive Workload

TL;DR

This paper explores adaptive in-vehicle interfaces that adjust based on the driver's cognitive workload to reduce distractions and improve safety, supported by preliminary user study results.

Contribution

It introduces a novel adaptive HMI approach that responds to mental workload, with initial findings demonstrating its potential benefits.

Findings

Preliminary results suggest adaptive HMIs can reduce driver distraction.

User study indicates improved cognitive load management.

Adaptive interfaces show promise for enhancing driving safety.

Abstract

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.