Qualitative Research of the Multimodal In-Vehicle Interaction Systems Latency Perception

As the automotive industry evolves towards greater technological intelligence, multimodal in-vehicle interaction systems introduce new challenges, particularly in managing system latency-the delay between user input and system response. This study aims to explore how various factors influence latency perception in in-vehicle multimodal interactions, offering a comprehensive framework to guide future design improvements. Our research, conducted in three phases, began with mapping key input and output modalities through literature reviews and expert evaluations. We then examined real-world user experiences to identify specific latency-related issues in common interaction scenarios. Finally, focus groups refined a framework that categorizes tasks based on interaction complexity, sensitivity, and tolerance to latency. The framework highlights how different modalities impact user sensitivity to delays and their tolerance levels, providing valuable insights for designers. It emphasizes that tasks requiring higher cognitive engagement and quicker responses demand more attention to latency. Although focused on intelligent vehicles, the framework is applicable to traditional vehicles with similar systems and aligns with upcoming safety regulations. This research contributes to creating safer, more intuitive in-vehicle systems that enhance user experience and meet regulatory standards.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-01-10
DOI
https://doi.org/10.1145/3701204
Citations
3
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
7.32
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article

Qualitative Research of the Multimodal In-Vehicle Interaction Systems Latency Perception

Zhengyu Tan, Ruifo Zhang, Ningyi Dai, Wang Jing
3 citations
Proceedings of the ACM on Human-Computer Interaction
Human-Automation Interaction and Safety
7.32
article

Qualitative Research of the Multimodal In-Vehicle Interaction Systems Latency Perception

Zhengyu Tan, Ruifo Zhang, Ningyi Dai, Wang Jing
article en
3 citations

Abstract

As the automotive industry evolves towards greater technological intelligence, multimodal in-vehicle interaction systems introduce new challenges, particularly in managing system latency-the delay between user input and system response. This study aims to explore how various factors influence latency perception in in-vehicle multimodal interactions, offering a comprehensive framework to guide future design improvements. Our research, conducted in three phases, began with mapping key input and output modalities through literature reviews and expert evaluations. We then examined real-world user experiences to identify specific latency-related issues in common interaction scenarios. Finally, focus groups refined a framework that categorizes tasks based on interaction complexity, sensitivity, and tolerance to latency. The framework highlights how different modalities impact user sensitivity to delays and their tolerance levels, providing valuable insights for designers. It emphasizes that tasks requiring higher cognitive engagement and quicker responses demand more attention to latency. Although focused on intelligent vehicles, the framework is applicable to traditional vehicles with similar systems and aligns with upcoming safety regulations. This research contributes to creating safer, more intuitive in-vehicle systems that enhance user experience and meet regulatory standards.

Proceedings of the ACM on Human-Computer InteractionVol. 9(1)
Hunan University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Human-Automation Interaction and Safety
7.32
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Qualitative Research of the Multimodal In-Vehicle Interaction Systems Latency Perception — Zhengyu Tan, Ruifo Zhang, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS