As cities promote sustainable and flexible transport options, micromobility vehicles—such as mopeds and pedal cycles—are becoming increasingly integrated into urban mobility systems. Leveraging a comprehensive dataset spanning from 2013 to 2023, the analysis focuses on the 2023 subset of the data, which includes key variables such as transport mode, user demographics (age and gender), accident characteristics (weather, light conditions, number of vehicles involved), and geographical context (urban versus rural areas). The micromobility model achieved 63.3% accuracy, 0.67 precision, 0.63 recall, and an F1-score of 0.64. The model for other vehicle types yielded marginally better results with 64.7% accuracy, 0.72 precision, 0.65 recall, and an F1-score of 0.67. These results indicate moderate but useful predictive performance, supporting downstream interpretability analysis. These results reveal distinct injury risk profiles between micromobility users and traditional vehicle occupants. The elevated serious and slight injury rates among micromobility users—despite lower fatality rates—highlight the increased vulnerability associated with limited physical protection. The strong influence of age for micromobility users suggests a need for targeted interventions aimed at age-specific risks, such as training programs for young riders and adaptive infrastructure for older adults. Meanwhile, the dominant role of urban context and gender among other vehicle users underscores the importance of location-sensitive planning and gender-informed policy design.
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