NMPC in Haptic Shared Control Steering:Optimizing Vehicle Motion

Q3 Engineering

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI:10.1016/j.ifacol.2024.09.059

Richard Gao , Tomohiro Nakade , Robert Fuchs , Jürg Schiffmann

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引用次数: 0

Abstract

As vehicles become more automated in the pursuit of comfort and safety, the human-machine interface must adapt to accommodate the intent of both driver and automation. The concept of haptic shared control steering allows lateral control of the vehicle to be continuously shared between driver and automation via the steering wheel. The automation imparts a torque on the steering wheel which serves to both guide the vehicle and inform the driver of the automation's intent without impairing the driver's ability to steer the vehicle. The combination of haptic feedback and seamless transition of vehicle control makes the use of automation more intuitive. This paper describes a Nonlinear Model Predictive Control (NMPC) approach for controlling the strength of the automation torque with the aim of optimizing vehicle motion. NMPC allows for intuitive tuning and customization of the vehicle steering performance through the NMPC parameterization. Results on a vehicle in real driving scenarios show that the proposed control is able to decrease the lateral jerk, a common measure of passenger comfort, compared to the current state of the art by up to 50% while maintaining the same or similar levels of path tracking performance.

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触觉共享控制转向中的 NMPC：优化车辆运动

随着车辆的自动化程度越来越高，为了追求舒适性和安全性，人机界面必须适应驾驶员和自动化系统的意图。触觉共享控制转向的概念允许驾驶员和自动驾驶系统通过方向盘持续共享对车辆的横向控制。自动驾驶系统在方向盘上施加扭矩，既能引导车辆，又能将自动驾驶系统的意图告知驾驶员，而不会影响驾驶员操纵车辆的能力。触觉反馈与车辆控制无缝过渡的结合使自动驾驶的使用更加直观。本文介绍了一种用于控制自动化扭矩强度的非线性模型预测控制（NMPC）方法，旨在优化车辆运动。通过 NMPC 参数设置，可以直观地调整和定制车辆转向性能。在实际驾驶场景中对车辆进行测试的结果表明，与目前的技术水平相比，所提出的控制方法能够在保持相同或类似水平的路径跟踪性能的同时，将横向颠簸（衡量乘客舒适度的常用指标）降低多达 50%。

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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来源期刊

IFAC-PapersOnLine Engineering-Control and Systems Engineering

CiteScore

1.70

自引率

0.00%

发文量

1122

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