Loughborough University
Browse

Development of a measurement instrument for pedestrians’ initial trust in automated vehicles

Download (1.96 MB)
journal contribution
posted on 2025-02-26, 14:27 authored by Siyuan Zhou, Xu Sun, Qingfeng Wang, Bingjian Liu, Gary BurnettGary Burnett

Considering that a significant portion of the current pedestrian population has limited exposure to automated vehicles (AVs), it is crucial to have a reliable instrument for assessing pedestrians’ initial trust in AVs. Using a survey of 436 pedestrians, this study developed and validated a PITQA (Pedestrians’ Initial Trust Questionnaire for AVs) scale using partial least squares structural equation modeling (PLS-SEM). The proposed scale will be valuable in monitoring the progression of trust over time and considering trust-related factors during the design process. The results revealed that seven key constructs significantly contribute to predicting initial trust between pedestrians and AVs. These constructs include propensity to trust, perceived statistical reliability, dependability and competence, perceived predictability, familiarity, authority/subversion, care/harm, and sanctity/degradation. These shed light on how the trust propensity of individuals, different trust/trustworthiness attributes might constitute different aspects of initial trust in the pedestrian-AV context. The developed scale can be a potentially useful tool for future research endeavors concerning trust calibration and the design of AVs specifically tailored for vulnerable road users.

Funding

Supported by the Chinese Ergonomics Society Fund of the Chinese Ministry of Education [grant number 202101042006]

2025 Key Technological Innovation Program of Ningbo City [grant number 2022Z080]

History

School

  • Design and Creative Arts

Published in

International Journal of Human-Computer Studies

Volume

191

Publisher

Elsevier Ltd

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Acceptance date

2024-07-25

Publication date

2024-07-26

Copyright date

2024

ISSN

1071-5819

Language

  • en

Depositor

Prof Gary Burnett. Deposit date: 9 August 2024

Article number

103344

Usage metrics

    Loughborough Publications

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC