Privacy Protection of Automated and Self-Driving Vehicles

Automated and autonomous vehicles (AVs) may be the greatest disruptive innovation to travel that we have experienced in a century. Their development coincides with the appearance of connected vehicles. To achieve their goals, connected and automated vehicles require extensive data and machine learning algorithms processing data from local sensors and received from other cars and road-side infrastructure for their decision-making. Specifically, we are seeing the emergence of vehicles that feature an impressive array of sensors and on-board decision-making units capable of coping with an unprecedented amount of data.

While privacy for connected vehicles has been considered for many years, AV technology is still in its infancy and the privacy and data protection aspects for AV are not well addressed. The capabilities of AVs pose new challenges to privacy protection, given the large sensor arrays of AVs that collect data in public spaces. The massive introduction of sensors and AI technology into automated and autonomous vehicles opens substantial new privacy and data protection problems, both from the technology research perspective as well as the ethical, legal and policy perspective, which still need to be phrased clearly, elaborated on and resolved. We discussed a variety of challenges in a first – and just virtual – seminar in early 2022 (Dagstuhl Seminar 22042) and will now take the next step.

The objective of this Dagstuhl Seminar is to produce a research roadmap to address the major road-blocks that the experts see in making progress on the way to deployment of privacy protection in Automated and Self-Driving Vehicles. 

ASSURED is invited to give a presentation on security and privacy in connected cars and how trust enablers as the ones designed in ASSURED can help towards enabling the dynamic trust assessment of future CCAM services.