The DevSafeOps dilemma: A systematic literature review on rapidity in safe autonomous driving development and operation
Journal article, 2025

Developing autonomous driving (AD) systems is challenging due to the complexity of the systems and the need to assure their safe and reliable operation. The widely adopted approach of DevOps seems promising to support the continuous technological progress in AI and the demand for fast reaction to incidents, which necessitate continuous development, deployment, and monitoring. We present a systematic literature review meant to identify, analyse, and synthesise a broad range of existing literature related to usage of DevOps in autonomous driving development. Our results provide a structured overview of challenges and solutions, arising from applying DevOps to safety-related AI-enabled functions. Our results indicate that there are still several open topics to be addressed to enable safe DevOps for the development of safe AD.

DevSafeOps

Autonomous driving

Safety-related function

Safety of the intended function (SOTIF)

DevOps

Continuous development

Author

Ali Nouri

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

Volvo Group

Beatriz Cabrero-Daniel

University of Gothenburg

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

Fredrik Törner

Volvo Group

Christian Berger

University of Gothenburg

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

Journal of Systems and Software

0164-1212 (ISSN)

Vol. 230 112555

Subject Categories (SSIF 2025)

Software Engineering

Computer Systems

DOI

10.1016/j.jss.2025.112555

More information

Latest update

7/30/2025