Perceived safety of AI technology and trust in AI-enabled e-scooters are the strongest self-reported predictors of willingness to use them, based on a 405-person US survey.
Impact of Road Infrastructure and Traffic Scenarios on E-scooterists' Riding and Gaze Behavior
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abstract
The growing adoption of e-scooters has raised significant safety concerns, particularly due to a surge in injuries and fatalities. This study explores the relationship between road infrastructure, traffic scenarios, and e-scooterists' riding and gaze behaviors to improve road safety and user experience. A naturalistic study was conducted using instrumented e-scooters, capturing gaze patterns, fixation metrics, and head movement data across various road layouts and traffic scenarios. Key findings reveal that bike lanes offer a stable environment with reduced horizontal head movement and focused attention on the road, while shared roads and sidewalks lead to more dispersed gaze and increased head movement, indicating higher uncertainty and complexity. Interactions with other road users, such as navigating intersections, passing buses, riding near cars, and descending on downhill paths, demand greater cognitive load. Intersections require heightened visual focus and spatial awareness, reflected in increased horizontal eye and head movements. Interactions with vehicles prioritize visual scanning over head movement to maintain stability and avoid collisions, while high-speed and downhill riding demand focused attention on obstacles and the road surface. The results provide insights into e-scooter riders' behavior and physiological response analysis, paving the way for safer riding experiences and improved understanding of their needs.
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Adoption of AI-Assisted E-Scooters: The Role of Perceived Trust, Safety, and Demographic Drivers
Perceived safety of AI technology and trust in AI-enabled e-scooters are the strongest self-reported predictors of willingness to use them, based on a 405-person US survey.