Work

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

Year: 2025

Type: review

Abstract: 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. • Applying DevOps to autonomous driving presents several open topics to be addressed. • DevSafeOps is introduced, adding safety-related activities into DevOps iterative loops. • Our systematic literature review led to 11 challenges in the DevSafeOps loop. • Potential solutions are identified and mapped to challenges in DevSafeOps.

Source: Journal of Systems and Software

DOI: 10.1016/j.jss.2025.112555

Authors: Ali Nouri, Beatriz Cabrero-Daniel, Fredrik Törner, Christian Berger

Institutions: Volvo (Sweden), Volvo Cars (Sweden), Chalmers University of Technology, University of Gothenburg

Language: English

Topic: Safety Systems Engineering in Autonomy

Subfield: Safety, Risk, Reliability and Quality

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,820