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SMILE IV - Safety analysis and verification/validation of MachIne LEarning based systems

Autonomous vehicles heavily rely on deep learning (DL) algorithms to function effectively. Nevertheless, it is still an open research question on how to implement DL methods in safety-critical applications.

SMILE IV is the next research exploration in the roadmap of the SMILE program, leveraging the results of the previous projects SMILE I/II/III to further develop enabling technologies and implement safety assurance framework on the new types of transport services enabled by small autonomous vehicles: transport robots in factory settings and delivery robots in public spaces. 

SMILE IV focuses on optimizing and implementing the safety architecture and safety components for the two distinct use cases of small autonomous vehicles operating in different environments and conditions.

By challenging the approach with diverse use cases and requirements from different domains, the results from SMILE IV will be also of high interest for automotive and other industrial actors that plan to use DL to support autonomous functions in safety critical applications.


Project name





Västra Götaland Region

RISE role in project

Coordination; Project management, R&D

Project start


39 months

Total budget

SEK 14 460 000


Dyno Robotics AB, Halmstad University, Infotiv AB, Volvo Group


Vinnova/Fordonsstrategisk forskning och innovation


Project members

Tor Skoglund

Contact person

Tor Skoglund

+46 72 215 58 42

Read more about Tor

Contact Tor
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