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JRM Vol.37 No.5 pp. 1172-1185
doi: 10.20965/jrm.2025.p1172
(2025)

Paper:

Input-Constrained Human Assist Control for Automobiles Using Control Barrier Functions

Issei Tezuka* ORCID Icon, Hisakazu Nakamura** ORCID Icon, Takashi Hatano*** ORCID Icon, Kenji Kamijo***, and Shota Sato*** ORCID Icon

*Graduate School of Frontier Sciences, The University of Tokyo
5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan

**Department of Electrical Engineering, Faculty of Science and Technology, Tokyo University of Science
2641 Yamazaki, Noda, Chiba 278-8510, Japan

***Integrated Control System Development Division, Mazda Motor Corporation
3-1 Shinchi, Fuchu-cho, Aki-gun, Hiroshima 730-8670, Japan

Received:
March 26, 2025
Accepted:
May 26, 2025
Published:
October 20, 2025
Keywords:
nonlinear control, control barrier function, human assist control
Abstract

Control barrier functions with the notion of viability kernels solve state-constrained problems under input constraints. However, it is not clear that how viability kernels are obtained for general systems and whether an optimal safety assist controller satisfying both state and input constraints is continuous. In this paper, we consider a four-wheeled vehicle model and demonstrate how to obtain its viability kernel. Then, by explicitly solving an optimization problem, we design a human assist controller that ensures the safety of the system with minimal intervention. Moreover, we show that the proposed explicit controller is continuous. Lastly, we confirm the effectiveness of the proposed method by computer simulation.

CBF for viability kernel

CBF for viability kernel

Cite this article as:
I. Tezuka, H. Nakamura, T. Hatano, K. Kamijo, and S. Sato, “Input-Constrained Human Assist Control for Automobiles Using Control Barrier Functions,” J. Robot. Mechatron., Vol.37 No.5, pp. 1172-1185, 2025.
Data files:
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Last updated on Oct. 19, 2025