The impact of perceived cyber-risks on automated vehicle acceptance: Insights from a survey of participants from the United States, the United Kingdom, New Zealand, and Australia

No study has systematically investigated the public's perceptions of cyber risks and their relationship with the acceptance of fully Connected and Automated Vehicles (CAVs). To address this knowledge gap, the authors developed a conceptual model and investigated the impact of the cyber-emulated risks (cyberattack, safety risk, connectivity risk, privacy risk, and performance risk) that may influence the adoption of CAVs. They tested the proposed model using structural equation modelling with a nationally representative sample of 2062 adults from the US, UK, New Zealand, and Australia.The results indicate that perceived cyberattacks had a significant but marginally neutral effect on usage intent, illustrating the acceptance of technical risk with CAVs. This finding challenges the commonly held belief that cyberattacks negatively influence the adoption of products and technology in other product development fields, such as information technology. CAV cyberattacks elevate concerns about safety, connectivity, privacy, and performance risks. Interestingly, connectivity risk had no significant impact on CAV's behaviour intention, but mediation analysis showed it indirectly affects CAV's acceptance through privacy and performance risks. Regarding socio-demographic and technological attributes, participants of older age, middle income, low-middle education, high cybersecurity knowledge and AV understanding exhibit high anxiety about CAV cyberattacks. The results hold significant policy implications, suggesting the need for tailored strategies in enhancing the cybersecurity of CAVs to ensure their successful adoption and deployment. The findings of this study aim to enhance the quality of transport policy and bridge the gap between theory and practice in addressing cyber risks in the transport sector.

Language

  • English

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  • Accession Number: 01919796
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 28 2024 10:44AM