摘要：Empirical validation and verification procedures require the sophisticated development of research methodology. Therefore, researchers and practitioners in human–machine interaction and the automotive domain have developed standardized test protocols for user studies. These protocols are used to evaluate human–machine interfaces (HMI) for driver distraction or automated driving. A system or HMI is validated in regard to certain criteria that it can either pass or fail. One important aspect is the number of participants to include in the study and the respective number of potential failures concerning the pass/fail criteria of the test protocol. By applying binomial tests, the present work provides recommendations on how many participants should be included in a user study. It sheds light on the degree to which inferences from a sample with specific pass/fail ratios to a population is permitted. The calculations take into account different sample sizes and different numbers of observations within a sample that fail the criterion of interest. The analyses show that required sample sizes increase to high numbers with a rising degree of controllability that is assumed for a population. The required sample sizes for a specific controllability verification (e.g., 85%) also increase if there are observed cases of fails in regard to the safety criteria. In conclusion, the present work outlines potential sample sizes and valid inferences about populations and the number of observed failures in a user study.
