Bofan Yu

BoRui Li, Bofan Yu, Xing-Dong Yang

As car cabins evolve with the integration of diverse sensors, traditional car cabins are transforming into smart environments. This shift raises important questions about how privacy is understood and managed in such spaces. In this work, we investigate privacy perceptions from the perspectives of both vehicle owners (i.e., people who purchase and own cars) and non-owners (i.e., people who temporarily use cars, such as family members, friends, or renters). Through semi-structured interviews with eighteen participants, we identified key factors that influence these groups' views on privacy. Our findings reveal factors that commonly influence privacy preferences for both owners and non-owners, as well as factors that have a stronger impact on one group over the other. Drawing on these insights, we discuss design implications for future designs to better support and balance the diverse privacy needs of multiple stakeholders in smart car cabins.

Bofan Yu, Borui Li, Tingyu Zhang et al.

In this paper, we explore a novel approach that leverages retrofitting to create sensor-powered smart car cabins. We propose that retrofitting offers a promising way to complement and extend the capabilities of built-in smart cabin sensors provided by car manufacturers. To understand how retrofitting solutions should be designed, we conducted a two-phase study. First, through semi-structured interviews with 18 participants, we examined challenges with built-in smart cabin sensors and identified opportunities where retrofitting could address these limitations. Second, through probe-based participatory design sessions with 15 participants, we identified user requirements and expectations for effective retrofit solutions. Based on our findings, we present a set of design recommendations to guide the future development of retrofit methods for smart car cabins.