The focus of this thesis is to assess how drivers interact with automated driving systems, more specifically: how control transitions from automated driving to manual driving and vice versa are executed and can be improved upon. In doing so, it identifies the key elements in research into control transitions in automated driving and addresses them. Whilst automated driving shows great promise in reducing road accident rates and congestion it is no panacea in driving safety at its current level (SAE Level 2 and Level 3). Until full autonomy (SAE Level 4) can be realised drivers will still have to be prepared to resume control when the automated driving system can no longer handle a situation. Research has shown that when drivers are exposed to automation, their reaction time slows, and the sudden change of task creates a sudden spike in workload. Such events could lead to incidents. To investigate this problem, the thesis utilise a multi-method using driving simulators as well as on road trials. Ultimately, the thesis aims to provide insights into how drivers handle the transition of control and whether this transition can be assisted by different levels of information support. Recommendations regarding the design of control transitions in highly automated driving are valuable for policy makers and vehicle manufacturers alike when designing and deploying automated vehicles of the future.