The impact of in-car human-machine interface prompt locations on driver attention resource redistribution: An event-related potential study

• Early ERP components assess attention priority in vehicle HMI during driving. • Lower-left HMI position captures driver attention fastest, with higher P1 amplitude. • P1 component best assesses driver attention allocation in HMI. • Priority: lower-left, lower-right, upper-right, upper-left, defies traditional design. As transportation systems become more intelligent, the allocation of attention within in-vehicle Human-Machine Interfaces (HMIs) has emerged as a key research focus. This study employed a two-phase design. In the preparatory phase, a behavioral dual-task experiment (N = 31) and a questionnaire survey (N = 137) were conducted to identify realistic attentional hotspots and high-priority functions. Building on these findings, an event-related potential (ERP) experiment was carried out with 12 participants (4 males) to examine attention allocation across different cueing spaces. By recording electroencephalogram (EEG) activity in response to varied prompt location, the study evaluated spatial prioritization and explored how drivers distribute attention within interfaces. The results revealed an attentional bias toward the lower-left area, with significantly larger P1 amplitudes (p = 0.005) in the frontal cortex. These findings provides preliminary neurophysiological evidence that spatial prioritization exists in in-vehicle HMIs design and influences cognitive evaluation. Early ERP components were also sensitive to this phenomenon. Collectively, the results enrich understanding of attention and cognition in vehicle interfaces and offer baseline evidence for optimizing spatial information layout to reduce cognitive load and inform safer interface design.

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Publication Details

Journal
Transportation Research Interdisciplinary Perspectives
Published
2025-10-25
DOI
https://doi.org/10.1016/j.trip.2025.101691
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

The impact of in-car human-machine interface prompt locations on driver attention resource redistribution: An event-related potential study

Sihua Wang, Feng Shi, Jingshi Huang, Yoshihiro Shimomura et al.
Transportation Research Interdisciplinary Perspectives
Human-Automation Interaction and Safety
article

The impact of in-car human-machine interface prompt locations on driver attention resource redistribution: An event-related potential study

Sihua Wang, Feng Shi, Jingshi Huang, Yoshihiro Shimomura, Yuanli Li
article en

Abstract

• Early ERP components assess attention priority in vehicle HMI during driving. • Lower-left HMI position captures driver attention fastest, with higher P1 amplitude. • P1 component best assesses driver attention allocation in HMI. • Priority: lower-left, lower-right, upper-right, upper-left, defies traditional design. As transportation systems become more intelligent, the allocation of attention within in-vehicle Human-Machine Interfaces (HMIs) has emerged as a key research focus. This study employed a two-phase design. In the preparatory phase, a behavioral dual-task experiment (N = 31) and a questionnaire survey (N = 137) were conducted to identify realistic attentional hotspots and high-priority functions. Building on these findings, an event-related potential (ERP) experiment was carried out with 12 participants (4 males) to examine attention allocation across different cueing spaces. By recording electroencephalogram (EEG) activity in response to varied prompt location, the study evaluated spatial prioritization and explored how drivers distribute attention within interfaces. The results revealed an attentional bias toward the lower-left area, with significantly larger P1 amplitudes (p = 0.005) in the frontal cortex. These findings provides preliminary neurophysiological evidence that spatial prioritization exists in in-vehicle HMIs design and influences cognitive evaluation. Early ERP components were also sensitive to this phenomenon. Collectively, the results enrich understanding of attention and cognition in vehicle interfaces and offer baseline evidence for optimizing spatial information layout to reduce cognitive load and inform safer interface design.

Transportation Research Interdisciplinary PerspectivesVol. 34
Shanghai International Studies University (CN), Chiba University (JP)
Openalex Percentile: Top 65%
Human-Automation Interaction and Safety
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