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Cross-country differences in willingness to use conditionally automated driving systems: Impact of technology affinity, driving skills, and perceived traffic climate

  • University of Leeds

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The importance of public acceptance of automated driving systems (ADS) has grown as these systems have advanced. Previous research has acknowledged the existence of individual and cross-cultural differences in drivers’ willingness to use these systems. This study aimed to further investigate cross-country differences in willingness to use conditionally automated driving systems, and the factors that influence it, such as technology affinity, driving skills, and traffic climate, across eight countries with varying road safety profiles. A large-scale survey was conducted as part of the Hi-Drive project, involving 7896 participants from eight countries (UK, USA, Germany, Sweden, Poland, Greece, China, and Japan). The findings revealed significant cross-country differences in willingness to use ADS, with China having the highest and the United Kingdom having the lowest scores. A mixed-effects model showed that willingness to use ADS was positively associated with technology affinity, driving skills, and external affective demands, and functionality dimensions of Traffic Climate Scale, and negatively associated with internal requirements factor of traffic climate. The results indicate that technology affinity plays a crucial role in influencing willingness to use ADS across countries, while perceptions of driving skills and traffic climate may provide insights into some country and individual-level differences in acceptance of these systems. These findings contribute to our understanding of the acceptance of ADS and the role of individual differences and transport-specific factors.

Original languageEnglish
Article number102903
JournalTechnology in Society
Volume82
DOIs
Publication statusPublished - Sept 2025
MoE publication typeA1 Journal article-refereed

Funding

The authors would like to thank all partners within the Hi-Drive project (https://hi-drive.eu/) for their cooperation and valuable contribution. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101006664.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Acceptance
  • Automated vehicles
  • Technology affinity
  • Traffic climate
  • Willingness to use

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