After more than a decade of intense focus on automated driving, we are still facing huge challenges for the vision of fully autonomuous driving to become a reality. The same ‘disillusionment’ is true in many other domains, in which autonomuous Cyber-Physical Systems (CPS) could considerably help to overcome societal challenges and be highly beneficial to society and individuals. Taking the automotive domain – i.e., highly automated vehicles (HAV) – as an example, this paper sets out to summarize the major challenges that are still to overcome for achieving safe, secure, reliable and trustworthy highly automated resp. autonomous CPS. We constrain ourself to technical challenges, acknowledging the importance of (legal) regulations, certification, standardization, ethics, and societal acceptance, to name but a few, but not providing any insights as this is beyond the scope of this paper. Four challenges have been identified as being the main obstacles to realizing HAV: Realization of continuous, post-deployment systems improvement, handling of uncertainties and incomplete information, verification of HAV with machine learning components, and prediction. Each of these challenges is described in detail, including sub-challenges and, where appropriate, possible solutions to overcome them. By working together in a common effort between industry and academy and focussing on these challenges, the authors hope to contribute to overcome the ‘disillusionment’ for realizing HAV.