When the Environment Becomes the Interface: Multisensory Environmental Interfaces for Human-AI Interaction in Autonomous Vehicles

2026-09-26

AI Summary

This study addresses how users establish trust with intelligent systems when explicit interfaces are relinquished following AI takeover. It proposes the concept of "ambient interfaces," establishing the environment as an independent interaction modality. In an autonomous driving context, a within-subjects experiment combined with simulated driving was conducted to facilitate implicit interaction through multisensory stimuli, including lighting and scent modulation. The findings reveal a hierarchical multisensory processing architecture that challenges the prevailing vision-dominant paradigm by demonstrating olfaction's superior influence on affective responses. Perceived ambiance accounts for 66.5% of the variance in user experience, while ambient quality and sensory congruence significantly enhance user trust in autonomous driving systems.

Abstract

As AI increasingly assumes operational control, human-computer interaction is shifting from operating systems through explicit interfaces to inhabiting intelligent environments. This raises a fundamental question: when users no longer directly manipulate a system, what mediates their relationship with intelligent technologies? We introduce environmental interfaces: designed environmental conditions that shape human-AI relationships through ambient, holistic, and evaluative pathways rather than explicit functional interaction. Using autonomous vehicle cabins as a revealing context, we conducted a within-subject experiment with 24 participants (216 observations), manipulating lighting and scent in a simulated autonomous driving environment. Three findings emerged. First, perceived atmosphere accounted for 66.5% of the variance in overall journey experience, showing that environmental conditions can function as an interface rather than merely a supporting design element. Second, multisensory processing followed a hierarchical architecture: individual sensory appraisals were initially independent, while cross-modal integration emerged during higher-order environmental evaluation. Third, olfactory stimuli influenced affective responses and experience evaluation more strongly than visual stimuli, challenging the visual dominance of automotive interaction design. Environmental quality and sensory congruency also predicted trust in the autonomous system, suggesting that passengers may use environmental cues as proxy signals when direct assessment of AI competence is difficult. These findings establish environmental interfaces as a distinct interaction modality and point to a broader transition from designing interfaces for operating intelligent systems to designing environments for inhabiting them.

Problem

• Human-AI Interaction
• Autonomous Vehicles
• Environmental Interfaces
• Multisensory Perception
• Trust

Innovation

• Environmental Interfaces
• Multisensory Integration
• Autonomous Vehicles
• Olfactory Stimuli
• Human-AI Trust