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首页> 外文期刊>Mechatronics, IEEE/ASME Transactions on >MPC-Based Haptic Shared Steering System: A Driver Modeling Approach for Symbiotic Driving
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MPC-Based Haptic Shared Steering System: A Driver Modeling Approach for Symbiotic Driving

机译：基于MPC的触觉共享转向系统：共生驾驶的驾驶员建模方法

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摘要

Advanced driver assistance systems (ADAS) aim to increase safety and reduce mental workload. However, the gap in the understanding of the closed-loop driver-vehicle interaction often leads to reduced user acceptance. In this article, an optimal torque control law is calculated online in the model predictive control (MPC) framework to guarantee continuous guidance during the steering task. The research contribution is in the integration of an extensive prediction model covering cognitive behavior, neuromuscular dynamics, and the vehicle-steering dynamics, within the MPC-based haptic controller to enhance collaboration. The driver model is composed of a preview cognitive strategy based on a linear-quadratic-gaussian, sensory organs, and neuromuscular dynamics, including muscle coactivation and reflex action. Moreover, an adaptive cost-function algorithm enables dynamic allocation of the control authority. Experiments were performed in a fixed-base driving simulator at Toyota Motor Europe involving 19 participants to evaluate the proposed controller with two different cost functions against a commercial lane keeping assist system as an industry benchmark. The results demonstrate the proposed controller fosters symbiotic driving and reduces driver-vehicle conflicts with respect to a state-of-the-art commercial system, both subjectively and objectively, while still improving the path-tracking performance. Summarising, this article tackles the need to blend human and ADAS control, demonstrating the validity of the proposed strategy.
机译：先进的驾驶辅助系统（ADA）旨在提高安全性并减少心理工作量。然而，理解闭环驱动器 - 车辆交互的间隙通常导致用户接受减少。在本文中，在模型预测控制（MPC）框架中在线计算最佳扭矩控制法，以保证在转向任务期间的连续引导。研究贡献在基于MPC的触觉控制器内覆盖了认知行为，神经肌肉动力学和车辆转向动力学的广泛预测模型中的集成，以增强协作。驱动模型由基于线性 - 二次高斯，感觉器器官和神经肌肉动力学的预览认知策略组成，包括肌肉共存和反射作用。此外，自适应成本函数算法能够动态分配控制权限。实验在丰田电机欧洲的固定基地驾驶模拟器中进行了涉及19名参与者，以评估具有两种不同成本函数的建议控制器，以防止商业车道保持辅助系统作为行业基准。结果展示了建议的控制器促进了共生驾驶，并减少了主观和客观的最先进的商业系统的驾驶员冲突，同时仍在提高路径跟踪性能。总结，本文解决了混合人类和ADAS控制的必要性，展示了拟议策略的有效性。

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