User Experience Data-Based Quality Evaluation for Micro Electric Vehicle Mobility Services

Purpose: This study aimed to develop a tailored Quality of Service (QoS) evaluation and prediction model specifically for mobility services using micro electric vehicles (MEVs). The purpose of this work was to enhance prediction accuracy and provide a more refined evaluation metric by analyzing user experience data, considering unique characteristics of MEVs.Methods: A weighted evaluation model was developed to capture the interactions and significance of variables derived from user experience. Specifically, this study proposed a weighting method based on usage records, user driving patterns, and travel distances. A weighted regression analysis was then performed to objectively evaluate QoS, aiming to improve predictive power and interpretability.Results: The findings highlighted that user experience history significantly influenced QoS, demonstrating the importance of tailored assessments for MEV-based mobility services using empirical data. The proposed weighted model has an advantage over traditional models in terms of prediction accuracy and interpretability.Conclusion: To ensure the sustainability of MEV-based mobility services, it is essential to move beyond conventional survey-based QoS evaluations. Data-driven models incorporating user-specific factors provide more accurate and comprehensive assessment results. The application of the proposed model to real-world operational data demonstrated its effectiveness in improving the precision of QoS evaluations.