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作者

Moayad Shammut;Muhammad Imran;Syed Faraz Hasan

来源

CITIES,Vol.133,Issue1,Article 104110

语言

英文

关键字

Autonomous vehicles;Mobilities paradigm;Social practices;Trust;Facebook;New Zealand

作者单位

School of People, Environment and Planning, Massey University, Palmerston North, New Zealand;Directorate of Research Services, University of New England, Armidale, Australia;School of People, Environment and Planning, Massey University, Palmerston North, New Zealand;Directorate of Research Services, University of New England, Armidale, Australia

摘要

Social perception and acceptance are crucial for the large-scale adoption of autonomous vehicles (AVs). Using the theoretical lens of the mobilities paradigm, this study explored the social meanings, cultural practices, and structure of feelings that could influence adoption and use of AVs in New Zealand (NZ) cities. The data were collected from public NZ Facebook pages during the period 2015–2020 when the AV debate gained momentum. Qualitative content analysis was conducted for a dataset drawn from 57 Facebook posts with over 4200 comments. The findings show that AVs are associated with meanings of safety, (un)employment, freedom, and control. The findings show how a society's car culture influences the adoption and ownership of AVs. They also show how AVs may increase productivity by introducing new practices while on the move such as eating, applying makeup, reading, or working, suggesting that travel time in AVs is not ‘dead’ time. The findings also uncover new aspects of how and why the public could develop trust in AVs. Overall, NZ society tends to be inclined towards accepting AVs with lower automation levels to maintain the pleasure of driving and allow the exploration of unplanned destinations. This study contributes to the mobilities paradigm by enriching our understanding of the diversified meanings and competencies associated with the adoption of AVs and draws attention to ways in which social meanings could be incorporated in AV policy interventions to better inform urban planning and infrastructure decisions that would shape the smart cities of the future.