  After more than a decade of intense focus on automated vehicles, we are still
facing huge challenges for the vision of fully autonomous driving to become a
reality. The same "disillusionment" is true in many other domains, in which
autonomous 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 ourselves to technical challenges,
acknowledging the importance of (legal) regulations, certification,
standardization, ethics, and societal acceptance, to name but a few, without
delving deeper into them 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 approaches to
overcome them. By working together in a common effort between industry and
academy and focusing on these challenges, the authors hope to contribute to
overcome the "disillusionment" for realizing HAV.
