From Research to Practice: An Interactive Rapid Review of Autonomous Driving System Testing in Industry
For practitioners in the autonomous driving industry, this paper provides the first practitioner-driven review of ADS testing research, revealing practical challenges and the disconnect between research and real-world application.
This study identifies 12 key challenges in autonomous driving system testing through collaboration with 21 industry practitioners, prioritizing two critical issues: approaches to and completeness of testing for End-to-End ADS. Analyzing 17 relevant research studies, most focusing on generating critical scenarios, the review finds a gap between academic advances and industrial applicability, highlighting the need for context-aware solutions.
Autonomous driving systems (ADS) are increasingly deployed in real traffic, yet testing remains fundamentally challenging due to open environments, complex scenarios, and the lack of established processes and metrics. Despite extensive research, a gap persists between academic advances and their applicability in industrial practice. To address this, we conduct an interactive rapid review in collaboration with 21 practitioners from a leading automotive company. Practitioners identified 12 key challenges in ADS testing, and prioritised two as the most critical issues, namely approaches to and completeness of testing for End-to-End (E2E) ADS. We analyzed 17 research studies relevant to these two challenges, most of which focus on generating critical testing scenarios, and subsequently assessed their relevance and applicability in practice. Our study provides the first practitioner-driven review and evaluation of current ADS testing research, reveals practical challenges in ADS testing, offers rapid insights for practitioners, and highlights the need for more context-aware, industry-relevant solutions to bridge the gap between research and practice.