Evidence of automated vehicle safety's influence on people's acceptance of the automated driving technology.

Acceptance Automated vehicles Conflict severity Safety Traffic conflicts

Journal

Accident; analysis and prevention
ISSN: 1879-2057
Titre abrégé: Accid Anal Prev
Pays: England
ID NLM: 1254476

Informations de publication

Date de publication:
17 Nov 2023
Historique:
received: 11 11 2022
revised: 31 01 2023
accepted: 12 11 2023
medline: 20 11 2023
pubmed: 20 11 2023
entrez: 19 11 2023
Statut: aheadofprint

Résumé

Existing studies identified targeted audiences showing increases in Automated Vehicles (AV) acceptance after experiencing automated driving. However, there is still uncertainty regarding the reasons. Although some studies cited safety as the primary reason, there is no objective evidence from safety performance in verifying its impact on AV acceptance. This study contributes to the literature by quantitatively revealing why AV acceptance is changed after experiencing automated driving via a Structural Equation Modeling (SEM) method and objectively validating that safety is the primary factor in determining AV acceptance. Sixty drivers completed driving tasks on a driving simulator under Levels 0, 4, 3, and 2 and survey questions in between. As a result, the safety-related perceptions of AV were identified as reasons for affecting AV acceptance. Particularly, the evaluation of traffic conflicts and conflict severity validates the results from SEM, proving that safety is the primary and significant reason for influencing AV acceptance.

Identifiants

pubmed: 37980839
pii: S0001-4575(23)00428-1
doi: 10.1016/j.aap.2023.107381
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

107381

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Song Wang (S)

School of Traffic and Transportation Engineering, Chongqing Jiaotong University, Chongqing 400074, China.

Zhixia Li (Z)

Department of Civil and Architectural Engineering and Construction Management, University of Cincinnati, Cincinnati, OH 40221, USA. Electronic address: lizx@ucmail.uc.edu.

Yi Wang (Y)

Department of Communication, University of Louisville, Louisville, KY 40292, USA.

Wenjing Zhao (W)

Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China.

Tangzhi Liu (T)

School of Traffic and Transportation Engineering, Chongqing Jiaotong University, Chongqing 400074, China.

Classifications MeSH