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

被引:0
|
作者
Lu, Xiao [1 ]
Tan, Haiqiu [2 ]
Zhang, Haodong [3 ]
Wang, Wuhong [2 ]
Xie, Shaorong [1 ,4 ]
Yue, Tao [4 ,5 ,6 ,7 ]
Chen, Facheng [8 ]
机构
[1] Shanghai Univ, Sch Comp Engn & Sci, Shanghai 200444, Peoples R China
[2] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China
[3] Tsinghua Univ, Sch Vehicle & Mobil, Beijing 100084, Peoples R China
[4] Tongji Univ, Shanghai Inst Intelligent Sci & Technol, Shanghai 200092, Peoples R China
[5] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200444, Peoples R China
[6] Shanghai Univ, Sch Future Technol, Shanghai 200444, Peoples R China
[7] Shanghai Univ, Shanghai Key Lab Intelligent Mfg & Robot, Shanghai 200444, Peoples R China
[8] Peoples Publ Secur Univ China, Dept Traff Management Sch, Beijing 100038, Peoples R China
基金
中国国家自然科学基金;
关键词
ACTIVITY RECOGNITION; DRIVERS; SYSTEM;
D O I
10.1038/s41467-025-56169-2
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:13
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