Seeing the whole process: How cooperative process transparency in AR-HMI affects driver cognition in V2V lane changes

Vehicle-to-Vehicle (V2V) cooperative driving can improve traffic safety and efficiency, but it also introduces information asymmetry between drivers and automated systems, which may lead to human-machine conflict. This study introduces V2V cooperative process transparency, defined as the level of detail with which the interface reveals the Awareness-Negotiation-Execution process of V2V communication to the driver. Using an augmented reality HMI in a driving simulator, we examined how different levels of V2V cooperative process transparency affect driver cognition during cooperative lane changes. Three interface conditions were compared: a baseline condition with no V2V cooperation information, a limited-transparency condition presenting only the final cooperation outcome, and a high-transparency condition presenting the full cooperation process. Twenty-five participants completed the experiment, and subjective, performance, and qualitative data were collected. The results showed that V2V cooperative process transparency significantly affected drivers’ subjective responses. Compared with the baseline condition, both the limited- and high-transparency conditions significantly improved overall situation awareness and reduced workload. The limited-transparency condition also significantly increased trust and system usability, whereas the differences in trust and system usability between the high-transparency and baseline conditions were not significant. Compared with the limited-transparency condition, the high-transparency condition significantly improved overall situation awareness, whereas overall workload, trust, and system usability did not differ significantly; at the workload-dimension level, however, Temporal Demand was significantly lower under high transparency. No significant differences were found in task performance across conditions. Qualitative interviews indicated that most participants considered the richer interface understandable and acceptable, although some reported possible information overload. These findings highlight V2V cooperative process transparency as an important design variable for cooperative driving HMI design.

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Publication Details

Journal
Transportation Research Part F Traffic Psychology and Behaviour
Published
2026-09-28
DOI
https://doi.org/10.1016/j.trf.2026.103830
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Seeing the whole process: How cooperative process transparency in AR-HMI affects driver cognition in V2V lane changes

Xu Yan, Qianwen Fu, Zhaodong Wang, Fang You
Transportation Research Part F Traffic Psychology and Behaviour
Human-Automation Interaction and Safety
article

Seeing the whole process: How cooperative process transparency in AR-HMI affects driver cognition in V2V lane changes

Xu Yan, Qianwen Fu, Zhaodong Wang, Fang You
article en

Abstract

Vehicle-to-Vehicle (V2V) cooperative driving can improve traffic safety and efficiency, but it also introduces information asymmetry between drivers and automated systems, which may lead to human-machine conflict. This study introduces V2V cooperative process transparency, defined as the level of detail with which the interface reveals the Awareness-Negotiation-Execution process of V2V communication to the driver. Using an augmented reality HMI in a driving simulator, we examined how different levels of V2V cooperative process transparency affect driver cognition during cooperative lane changes. Three interface conditions were compared: a baseline condition with no V2V cooperation information, a limited-transparency condition presenting only the final cooperation outcome, and a high-transparency condition presenting the full cooperation process. Twenty-five participants completed the experiment, and subjective, performance, and qualitative data were collected. The results showed that V2V cooperative process transparency significantly affected drivers’ subjective responses. Compared with the baseline condition, both the limited- and high-transparency conditions significantly improved overall situation awareness and reduced workload. The limited-transparency condition also significantly increased trust and system usability, whereas the differences in trust and system usability between the high-transparency and baseline conditions were not significant. Compared with the limited-transparency condition, the high-transparency condition significantly improved overall situation awareness, whereas overall workload, trust, and system usability did not differ significantly; at the workload-dimension level, however, Temporal Demand was significantly lower under high transparency. No significant differences were found in task performance across conditions. Qualitative interviews indicated that most participants considered the richer interface understandable and acceptable, although some reported possible information overload. These findings highlight V2V cooperative process transparency as an important design variable for cooperative driving HMI design.

Transportation Research Part F Traffic Psychology and BehaviourVol. 123
Tongji University (CN), Hong Kong Polytechnic University (HK)
Openalex Percentile: Top 7%
Human-Automation Interaction and Safety
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