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

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Authors: Wei-Hsiang Lo, Jinyoung Lee, Carmen Roberts, Miaomiao Dong, Kimberly D. Martinez, Egbe-Etu Etu, Shashank Mehrotra, Kumar Akash, Kevin Salubre, Teruhisa Misu, Gaojian Huang
Cited by: 1
References: 132

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.

Fields of Study & Subjects

Human-Automation Interaction and Safety Behavioral Health and Interventions Technology Adoption and User Behaviour

Publication details

Journal / source
International Journal of Human-Computer Interaction
Publisher
Informa UK Limited
Volume
42
Issue
16
Pages
13244–13271
Publication date
15 January 2026
Language
EN