Variable Trust Control Setting for Autonomous Vehicle Highway Navigation and Improved User Experience.

SN computer science Pub Date : 2025-01-01 Epub Date: 2025-03-13 DOI:10.1007/s42979-025-03714-x
James E Pickering, Jisun Kim, Joshua D'Souza, Keith J Burnham
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引用次数: 0

Abstract

This paper addresses the development of a model-based design approach to enhance the acceptance of safe manoeuvrability of autonomous vehicles (AVs) on highways. A variable trust control setting (TCS) is introduced that empowers users to 'feel in control' of the AV, potentially increasing confidence in, and acceptance of, the technology. This setting is grounded in deontological ethics and utilises virtual boundaries (VBs) to guide driving decisions, i.e., the distance between two AVs interacting with one another. The approach is simulated using a dynamic bicycle model that represents each AV, controlled through an adaptive model-predictive control (MPC) algorithm. The paper outlines the MPC approach, the dynamic bicycle model, and the associated velocity control algorithm. Metrics are introduced to quantify safety of specific AV manoeuvres during interactions with other AVs, enabling the examination of various scenarios. A novel simulation package has been developed to investigate the impact of the proposed variable TCS, focusing on how VBs and steering limitations influence the safety and comfort of AVs during overtaking manoeuvres. The findings demonstrate the effectiveness of this approach, showing that it could potentially allow users to actively manage the safety and comfort aspects of AV operation.

本文探讨了如何开发一种基于模型的设计方法,以提高人们对自动驾驶汽车(AV)在高速公路上安全机动性的接受度。本文引入了一种可变的信任控制设置(TCS),使用户能够 "感受到 "对自动驾驶汽车的 "控制",从而增强对该技术的信心和接受度。这种设置以义务伦理为基础,利用虚拟边界(VBs)来指导驾驶决策,即两个相互影响的自动驾驶汽车之间的距离。该方法使用代表每辆自动驾驶汽车的动态自行车模型进行模拟,并通过自适应模型预测控制(MPC)算法进行控制。本文概述了 MPC 方法、动态自行车模型以及相关的速度控制算法。文中介绍了在与其他自动驾驶汽车交互过程中量化特定自动驾驶汽车操纵安全性的指标,以便对各种情况进行检查。还开发了一个新颖的模拟软件包,用于研究拟议的可变 TCS 的影响,重点关注 VB 和转向限制如何影响超车机动过程中自动驾驶汽车的安全性和舒适性。研究结果证明了这种方法的有效性,表明它有可能让用户主动管理自动驾驶汽车运行的安全性和舒适性。
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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来源期刊
CiteScore
5.60
自引率
0.00%
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