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

James E. Pickering; Jisun Kim; Joshua D’Souza; Keith Burnham

doi:10.1007/s42979-025-03714-x

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

James E. Pickering^*, Jisun Kim, Joshua D’Souza, Keith Burnham

^*Corresponding author for this work

Aston University

Research output: Contribution to journal › Article › peer-review

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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.

Original language	English
Article number	278
Number of pages	14
Journal	SN Computer Science
Volume	6
Issue number	3
DOIs	https://doi.org/10.1007/s42979-025-03714-x
Publication status	Published - 13 Mar 2025

Bibliographical note

Copyright © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.

Funding

This work was supported by the EPSRC Doctoral Training Program funding (Grant number is EP/W524566/1).

Keywords

Autonomous vehicles (AVs)
Control engineering
Model-predictive control (MPC)
Navigation algorithms
Variable trust control setting (TCS)
Vehicle safety

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10.1007/s42979-025-03714-xLicence: CC BY 4.0

Variable trust control setting for autonomous vehicle highway navigation
Copyright © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.
Final published version, 2.11 MBLicence: CC BY 4.0

Cite this

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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.",

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note = "Copyright {\textcopyright} The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.",

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AB - 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.

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ER -

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

Abstract

Bibliographical note

Funding

Keywords

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