22 Mar 2018

ICES director comments on the recent automated vehicle driving accident


Automated vehicles represent a very interesting class of Cyber-Physical Systems, and a domain that is right now pushing the limits of CPS technology. I am writing this posting the evening after the presumably first accident where a pedestrian was killed by an automated test vehicle (despite a supervising person being present).
Most of the topics I have touched upon, such as the challenges, opportunities and complexity facets of CPS, can be very well illustrated with automated driving. An automated vehicle (at high levels of automation, corresponding to roughly SAE levels 3 and above), will need to be able to carry out tasks such as:
* Understanding complex and varying driving environments (roads, signs, debris, people, other vehicles, etc.)
 * Understanding where the ego-vehicle is positioned within such environments
* Taking decisions on what to do in the short and longer term

The complex environments have to be mirrored by correspondingly sophisticated and complex perception, mapping, planning and control systems.
Key challenges in developing such automated systems include the following:
* Dealing with unexpected driving scenarios. While industry will likely do their best, it will   not be possible to provide exhaustive coverage of driving scenarios. There will be limitations in the training of machine learning systems and sometimes also overtraining. AI (machine learning) systems of today lack the generalization power of humans, and it is hard to reason about the robustness of today’s machine learning systems.
* Dealing with uncertainty in perception and world understanding – for example in terms of the intent of pedestrians and other vehicles on the road,
* Dealing with faults in the ego vehicle (sensors, computation, software and hardware),

Read more on Martin Törrngrens blogg