Shared Control in Micro-Mobility: Effects of Rider Skill and Automation Levels on Subjective Well-Being in E-Scooter Use

Publication Date

1-15-2026

Document Type

Article

Publication Title

International Journal of Human Computer Interaction

DOI

10.1080/10447318.2025.2601282

Abstract

The rapid growth of shared e-scooters presents an opportunity for integrated AI and automation systems in micro-mobility. However, users’ expectations and satisfaction with cooperative behavior and control-sharing in such automated micro-mobility settings remain uncertain. An online survey was conducted in the U.S., yielding 401 responses. Participants were asked to rate four control-sharing configurations (i.e., Baseline, Human-lead, System-lead, and Balance) using subjective well-being (SWB) measures, including two affective SWB measures (i.e., PANAS, SCAS), one cognitive SWB measure (i.e., SWLS), and one transportation-domain SWB measure (i.e., STS). Results indicated that increasing individual skill could improve the riding experience (i.e., affective SWB) and support travel goals (i.e., cognitive SWB). Increasing the automation level was associated only with support for travel goals (i.e., SWLS). These observations indicate that individual rider capability is a stronger predictor of SWB in micro-mobility than automated system capability. These findings may inform the development of future micro-mobility systems.

Keywords

E-scooter, human-AI interaction, micro-mobility, Shared control, subjective well-being

Department

Industrial and Systems Engineering

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