Risk Assessment of Human Errors in Interaction Design Using Fuzzy Fault Tree Analysis

User experience constitutes an essential element of effective interaction design. To enhance the user experience, it is necessary to identify the primary root causes related to human errors and then initiate actionable interventions for the high-priority root causes. Risk assessment of human errors in interaction design is characterized by subjective uncertainties and a lack of precise numerical values. However, very little attention has been given to these issues when assessing human errors. In this paper, a fuzzy fault tree analysis approach is proposed to execute risk assessment of human errors in interaction design. First, the system is analyzed, and a fault tree diagram is constructed. Subsequently, probabilities for each basic event are derived through the combination of fuzzy set theory and the similarity aggregation method. Then, the minimal cut sets (MCSs) are identified. Following this, the failure probability of the top event is determined, and the MCSs are ranked in accordance with their respective importance values. Finally, the results are evaluated, and the recommendations for corrective actions are provided for the high-priority MCSs. A practical case study of the in-vehicle information system in heavy trucks was conducted to demonstrate the feasibility and effectiveness of the proposed approach. The findings suggest that this approach can effectively address the subjective and even subconscious aspects of risk assessment related to human errors in interaction design, providing accurate results for risk evaluation. Furthermore, it can effectively address the situations where the probabilities related to human errors are imprecise, inadequate, and ambiguous. The proposed approach can be universally applied to enhance the user experience in interaction design.