From Research to Practice: An Interactive Rapid Review of Autonomous Driving System Testing in Industry

TL;DR

This paper presents a practitioner-driven review of autonomous driving system testing, identifying key challenges and evaluating research relevance to industry needs to bridge the gap between academic research and practical application.

Contribution

It offers the first collaborative review with industry practitioners, highlighting practical challenges and assessing research applicability for industry-relevant ADS testing solutions.

Findings

Practitioners identified 12 key testing challenges.

Two critical issues prioritized: approach and completeness of E2E testing.

Most research focuses on generating critical testing scenarios.

Abstract

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.