Continuous Engineering for Trustworthy Learning-Enabled Autonomous Systems

Saddek Bensalem, Panagiotis Katsaros, Dejan Ničković, Brian Hsuan Cheng Liao, Ricardo Ruiz Nolasco, Mohamed Abd El Salam Ahmed, Tewodros A. Beyene, Filip Cano, Antoine Delacourt, Hasan Esen, Alexandru Forrai, Weicheng He, Xiaowei Huang, Nikolaos Kekatos, Bettina Könighofer, Michael Paulitsch, Doron Peled, Matthieu Ponchant, Lev Sorokin, Son TongChangshun Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


Learning-enabled autonomous systems (LEAS) use machine learning (ML) components for essential functions of autonomous operation, such as perception and control. LEAS are often safety-critical. The development and integration of trustworthy ML components present new challenges that extend beyond the boundaries of system’s design to the system’s operation in its real environment. This paper introduces the methodology and tools developed within the frame of the FOCETA European project towards the continuous engineering of trustworthy LEAS. Continuous engineering includes iterations between two alternating phases, namely: (i) design and virtual testing, and (ii) deployment and operation. Phase (i) encompasses the design of trustworthy ML components and the system’s validation with respect to formal specifications of its requirements via modeling and simulation. An integral part of both the simulation-based testing and the operation of LEAS is the monitoring and enforcement of safety, security and performance properties and the acquisition of information for the system’s operation in its environment. Finally, we show how the FOCETA approach has been applied to realistic continuous engineering workflowsfor three different LEAS from automotive and medical application domains.

Original languageEnglish
Title of host publicationBridging the Gap Between AI and Reality - 1st International Conference, AISoLA 2023, Proceedings
EditorsBernhard Steffen
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages23
ISBN (Print)9783031460012
StatePublished - 2024
Event1st International Conference on Bridging the Gap between AI and Reality, AISoLA 2023 - Crete, Greece
Duration: 23 Oct 202328 Oct 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14380 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference1st International Conference on Bridging the Gap between AI and Reality, AISoLA 2023

Bibliographical note

Publisher Copyright:
© 2024, The Author(s).


This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 956123.

FundersFunder number
Horizon 2020956123


    • Learning-enabled Autonomous Systems
    • continuous engineering
    • formal analysis
    • machine learning
    • safety
    • security


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