Empowering Drivers as Collaborative Social Agents: Enhancing Pedestrian Interaction through Cooperative Interfaces in Autonomous Vehicle Systems
Abstract
While autonomous driving technology reduces the operational burden on drivers, it may also diminish their sense of engagement, for example, by interrupting social interactions between drivers and other road users such as pedestrians. To address this, this article proposes a “Social Cooperation” driving mode from a cooperative driving perspective, aiming to activate drivers’ social capabilities to compensate for the limitations of autonomous systems in social interaction and to enhance drivers’ engagement in pedestrian-yielding scenarios. Through a driving simulator prototype experiment, we found that the proposed approach significantly improved drivers’ psychological need satisfaction, enhancing their autonomy, competence, and relatedness needs, while also showing positive trends in empathy, benevolence, and overall satisfaction. The results provide new insights into social interactions in autonomous driving contexts and offer practical and theoretical guidance for the design of human-machine cooperative driving interfaces.
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Authors: Jun Zhang, Weiqi Mei, Yuchen Wang, Fang You, Yan Luximon
Institutions: Hong Kong Polytechnic University, Tongji University, Wuhan University of Technology, Guangdong University of Technology, Hubei Institute of Fine Arts