Mapping mental models of parents’ risk perceptions of autonomous public transport use by young children: a social representations theory approach

Abstract

Numerous countries are integrating autonomous vehicles into their public transport systems. Among the expected benefits of autonomous public transport, increased mobility for families with young children is foregrounded. Yet, the potential risks associated with autonomous public transport may impede parents’ acceptance of the technology for use by their children. As risk communication is an effective strategy for mitigating the influence of risk perception on acceptance, this study sought to proactively identify risk perceptions that parents hold toward autonomous public transport. Against the backdrop of Singapore’s imminent deployment of autonomous public transport and informed by the social representations theory, we elicited a mental model of parents’ risk perceptions toward autonomous public transport that was sensitive to the diversity of opinion among parents and their preferences for risk communication messages about autonomous public transport. To that end, we conducted three online focus group discussions consisting of 21 Singaporean parents who had children aged 2 wk to 12 years old. Theoretically, this study addresses research gaps in the mental models literature and offers theoretical implications for scholars seeking to employ the mental models approach to understand lay risk perceptions. Practically, this study informs the design of relevant and targeted risk communication messages about autonomous public transport.

Keywords:

• Autonomous public transport
• risk perceptions
• parents
• young children
• mental models
• social representations theory
• artificial intelligence
• risk communication

Acknowledgements

This work was supported by the Artificial Intelligence Research Institute and NTU Institute of Science and Technology for Humanity at Nanyang Technological University [Grant Number: #021175-00001]. We thank Niels de Boer, Chief Operating Officer of the Energy Research Institute at Nanyang Technological University, for his help with developing the definition of autonomous public transport in this study. We also thank him for reviewing the moderator’s guide and supplementary material used in the focus group discussions.

Disclosure statement

The authors have no known conflicts of interest to disclose.

Geolocation information

This study was conducted in Singapore.

Data availability statement

Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.

Notes

1 1. “SA,” “SB,” and “SC” indicate the FGD session that a participant participated in while “Pn” differentiates participants within a session. For example, “SAP1” is the first participant among seven in FGD Session A.