Triboelectric sensor gloves for real-time behavior identification and takeover time adjustment in conditionally automated vehicles

The takeover issue, especially the setting of the takeover time budget, is a critical factor restricting the implementation and development of conditionally automated vehicles. The general fixed takeover time budget has certain limitations, as it does not take into account the driver's non-driving behaviors. Here, we propose an intelligent takeover assistance system consisting of all-round sensing gloves, a non-driving behavior identification module, and a takeover time budget determination module. All-round sensing gloves based on triboelectric sensors seamlessly detect delicate motions of hands and interactions between hands and other objects, and then transfer the electrical signals to the non-driving behavior identification module, which achieves an accuracy of 94.72% for six non-driving behaviors. Finally, combining the identification result and its corresponding minimum takeover time budget obtained through the takeover time budget determination module, our system dynamically adjusts the takeover time budget based on the driver's current non-driving behavior, significantly improving takeover performance in terms of safety and stability. Our work presents a potential value in the application and implementation of conditionally automated vehicles.

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Publication Details

Journal
Nature Communications
Published
2025-01-27
DOI
https://doi.org/10.1038/s41467-025-56169-2
Citations
19
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
12.81

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article

Triboelectric sensor gloves for real-time behavior identification and takeover time adjustment in conditionally automated vehicles

Wuhong Wang, Haiqiu Tan, Facheng Chen, Tao Yue et al.
19 citations
Nature Communications
Advanced Sensor and Energy Harvesting Materials
12.81
article

Triboelectric sensor gloves for real-time behavior identification and takeover time adjustment in conditionally automated vehicles

Wuhong Wang, Haiqiu Tan, Facheng Chen, Tao Yue, Shaorong Xie, Haodong Zhang, Xiao Lu
article en
19 citations

Abstract

The takeover issue, especially the setting of the takeover time budget, is a critical factor restricting the implementation and development of conditionally automated vehicles. The general fixed takeover time budget has certain limitations, as it does not take into account the driver's non-driving behaviors. Here, we propose an intelligent takeover assistance system consisting of all-round sensing gloves, a non-driving behavior identification module, and a takeover time budget determination module. All-round sensing gloves based on triboelectric sensors seamlessly detect delicate motions of hands and interactions between hands and other objects, and then transfer the electrical signals to the non-driving behavior identification module, which achieves an accuracy of 94.72% for six non-driving behaviors. Finally, combining the identification result and its corresponding minimum takeover time budget obtained through the takeover time budget determination module, our system dynamically adjusts the takeover time budget based on the driver's current non-driving behavior, significantly improving takeover performance in terms of safety and stability. Our work presents a potential value in the application and implementation of conditionally automated vehicles.

Nature CommunicationsVol. 16(1)
Shanghai University (CN), Tongji University (CN), Beijing Institute of Technology (CN), Shanghai University of Engineering Science (CN), China People's Public Security University (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, National Postdoctoral Program for Innovative Talents, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 1%
Advanced Sensor and Energy Harvesting Materials
12.81
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