Designing With Motion: Exploring Vestibular Cues as a Subtle Awareness Nudge Modality in Automated Vehicles
Authors
Automated driving systems, particularly at SAE Level 3, present new challenges in managing driver attention to ensure smooth transitions from automated to manual control. This paper reports on a qualitative investigation of vestibular cues—implemented via subtle deceleration events—as a form of a dynamic Human-Machine Interface (dHMI) that subtly "nudges" a user's attention away from a non-driving related task (NDRT) and towards the driving environment. Conducted as a test-track study (N=25), we explore awareness, acceptance, and design considerations related to these cues. Findings reveal that while participants showed positive attitudes toward vestibular nudges as safety features, they were unable to differentiate nudges from necessary vehicle deceleration during automated driving. The study reveals how drivers interpret the implicit interaction with the dHMI during realistic NDRT and potential limitations. The study highlights the need for multimodality HMI approaches and customisation to optimise user experience in conditional automated vehicles.
Research Questions / Practical Problems
Question signals indexed for this paper.
- 100%
Evaluating In-Car Tasks’ Distraction Effects with Drive-In Lab
CHI '25· Automated Driving Interface & Takeover Design +1
- 100%
Understanding User Requirements for Creating Sensor-Powered Smart Car Cabins Through Retrofitting
CHI '26· Automated Driving Interface & Takeover Design +1
- 100%
A Review on the Development of the In-Vehicle Human-Machine Interfaces in Driving Automation: A Design Perspective
AutoUI '24· Automated Driving Interface & Takeover Design +1
- 80%
In UX We Trust: Investigation of Aesthetics and Usability of Driver-Vehicle Interfaces and Their Impact on the Perception of Automated Driving
CHI '19· Automated Driving Interface & Takeover Design +2
- 80%
Matching Explanation Detail to Scene Complexity: Studying Situational Awareness-Specific AI Feedback in Pedestrian Encounter Driving Scenarios
CHI '26· Automated Driving Interface & Takeover Design +2
- 80%
A Framework for Adapting In-Car Touchscreen Interfaces to Driver Behaviors, Perception, and Cognition
CHI '26· Automated Driving Interface & Takeover Design +2
- 80%
From Awareness to Intent: Mitigating Silent Driving System Failures through Prospective Situation Awareness Enhancing Interfaces
CHI '26· Automated Driving Interface & Takeover Design +2
- 80%
MUST: Smartwatch-based Multimodal Framework for Predicting Driver State and Takeover Performance
CHI '26· Automated Driving Interface & Takeover Design +2
- 80%
MIRAGE: Enabling Real-Time Automotive Mediated Reality
CHI '26· Automated Driving Interface & Takeover Design +2
- 80%
A Social Approach for Autonomous Vehicles: A Robotic Object to Enhance Passengers’ Sense of Safety and Trust
HRI '24· Automated Driving Interface & Takeover Design +2
Based on Jaccard similarity of research subtopics & professions (≥60%)