未来のモビリティにおけるウェルビーイング：相互作用を通じて幸福度を高める自動運転車政策設計に向けて
Wellbeing in Future Mobility: Toward AV Policy Design to Increase Wellbeing through Interactions
自動運転車と他道路利用者とのやり取りが人の幸福度に与える影響を、動画ベースのユーザー研究と機械学習モデルで分析し、幸福度を高める最適な譲り行動政策を提案した。
著者: Shashank Mehrotra, Zahra Zahedi, Teruhisa Misu, Kumar Akash
分類: cs.HC, cs.RO
原文アブストラクト
Recent advances in Automated vehicle (AV) technology and micromobility devices promise a transformational change in the future of mobility usage. These advances also pose challenges concerning human-AV interactions. To ensure the smooth adoption of these new mobilities, it is essential to assess how past experiences and perceptions of social interactions by people may impact the interactions with AV mobility. This research identifies and estimates an individual's wellbeing based on their actions, prior experiences, social interaction perceptions, and dyadic interactions with other road users. An online video-based user study was designed, and responses from 300 participants were collected and analyzed to investigate the impact on individual wellbeing. A machine learning model was designed to predict the change in wellbeing. An optimal policy based on the model allows informed AV actions toward its yielding behavior with other road users to enhance users' wellbeing. The findings from this study have broader implications for creating human-aware systems by creating policies that align with the individual state and contribute toward designing systems that align with an individual's state of wellbeing.
