Online driver model parameter identification using the Lyapunov approach based shared control

Mohamed Radjeb Oudainia, C. Sentouh, Anh‐Tu Nguyen, J. Popieul
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Abstract

The work described in this paper proposes a new conflict minimisation strategy in shared driving control for lane keeping systems (LKS) in intelligent vehicles. This strategy takes into account a dynamic driver model, where the driver’s parameters are identified online using the Lyapunov approach. The design of an adaptive shared controller is based on the dynamic parameters of the driver model which changes according to the driver and the situation encountered. Based on Lyapunov stability arguments, the overall asymptotic stability of the closed-loop control system with the adaptive driver model and the variation of the vehicle speed is proved and an LMI optimization is used to formulate the control design. The simulation results, conducted with the SHERPA dynamic car simulator under real-world driving situations, show the importance of integrating a dynamic driver model in the controller design in order to decrease the conflict between the driver and the lane keeping system and to ensure the safety of the vehicle as well as to increase the confidence and acceptability of the driver.
基于共享控制的Lyapunov方法在线驱动模型参数辨识
本文所描述的工作提出了一种新的冲突最小化策略,用于智能车辆车道保持系统(LKS)的共享驾驶控制。该策略考虑了动态驾驶员模型,其中使用李雅普诺夫方法在线识别驾驶员参数。自适应共享控制器的设计基于驾驶员模型的动态参数,该参数根据驾驶员和遇到的情况而变化。基于李雅普诺夫稳定性自变量,证明了具有自适应驾驶员模型和车速变化的闭环控制系统的总体渐近稳定性,并使用LMI优化来制定控制设计。使用SHERPA动态汽车模拟器在真实驾驶情况下进行的仿真结果表明,在控制器设计中集成动态驾驶员模型的重要性,以减少驾驶员与车道保持系统之间的冲突,确保车辆的安全,并提高驾驶员的信心和可接受性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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