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Seamless human-machine interaction via intention recognition based on triboelectric-pressure signals and fault-tolerant control with switchable torque-angle targets

delete2026-08-03
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PRE
AI
X
Xiang Chen
Y
Yongyao Yuan
Y
Yicai Liu *
X
Xiangyu Wang
Y
Yushu Li
李亮 cover
李亮 (Liang Li)
W
Wanzhong Zhao
DOI:10.1007/s11431-025-3316-6delete
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Abstract

Abstract

En 中文
Human-machine interaction (HMI) is a key component of conditional autonomous driving. However, the HMI system based on the steering wheel module often suffers from delayed recognition of takeover signals, potential actuator faults, and jerkiness during the takeover process. To address these challenges, this paper proposes a seamless HMI architecture combined with intention recognition and fault-tolerant control. First, a composite sensor capable of simultaneously acquiring triboelectric and pressure signals is designed, adopting a shared structural layer to minimize thickness, and an associated takeover intention recognition scheme is developed. Then, a four-dimensional hand wheel model that captures the transient characteristics of the steering wheel is proposed, based on which a switchable tube-model predictive control (MPC) controller combined with an auxiliary sliding-mode control law is constructed. Finally, an adaptive weight adjustment function is integrated into the tube-MPC framework to ensure a smooth takeover process. Experimental results demonstrate that the proposed architecture enables seamless HMI, including accurate driver intention recognition and promising tracking accuracy under both healthy and faulty conditions.
Keywords:
intelligent vehicles
human-machine interaction
fault-tolerant control
steer-by-wire system

Journal

Science China-Technological Sciences cover
Science China-Technological Sciences
IF:
4.9
Papers:
4.9K
Citations:
9.9K

Organization

S
School of Vehicle and Mobility
Scholars:
53
Papers: 20
Citations: 0
C
College of Energy and Power Engineering
Scholars:
98
Papers: 29
Citations: 0
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