The human-machine interfaces (HMIs) in passenger cars have become more complex over the years, with touch screens replacing physical buttons and more options becoming available. This can result in multiple layers of menus that have to be navigated to perform simple tasks and therefore increase distraction. In addition to this, there is no standardisation for passenger car HMIs. To face these problems, new standards will have to be created. However, knowledge regarding the prevalence of different internal HMI tasks is missing. This complicates efforts to create new standards since it is unclear which internal HMI tasks are most important to assess. It also complicates efforts to create an assessment methodology to rate the safety of different internal HMI interfaces, as tasks that are used more often could be seen as more important. This thesis fills the knowledge gap by identifying the most used internal HMI tasks and the factors that influence their frequencies based on real-world driving observations in a naturalistic setting. In particular, this study especially looks at the influence of car familiarity. Multiple data analysis methods, including Poisson regressions, ANOVA’s, paired t-tests and factor analysis are used to obtain the required knowledge. In general, people seem to perform around 12 tasks per hour in familiar cars versus 9 tasks per hour in unfamiliar cars, but significant differences between tasks exist. The results indicate that the most performed is using the indicator light. Other frequently performed tasks fall into the windshield, radio and media and climate control categories. The factors that influenced the task frequencies included car familiarity, gender, age and weather conditions. The type of car also seems to impact the task frequencies, but more research on this is needed.