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Testing autonomous driving systems for safety and reliability is extremelycomplex. A primary challenge is identifying the relevant test scenarios,especially the critical ones that may expose hazards or risks of harm toautonomous vehicles and other road users. There are several proposed methodsand tools for critical scenario identification, while the industry practices,such as the selection, implementation, and limitations of the approaches, arenot well understood. In this study, we conducted 10 interviews with 13interviewees from 7 companies in autonomous driving in Sweden. We used thematicmodeling to analyse and synthesize the interview data. We found there arelittle joint efforts in the industry to explore different approaches and tools,and every approach has its own limitations and weaknesses. To that end, werecommend combining different approaches available, collaborating amongdifferent stakeholders, and continuously learning the field of criticalscenario identification and testing. The contributions of our study are theexploration and synthesis of the industry practices and related challenges forcritical scenario identification and testing, and the potential increase of theindustry relevance for future studies in related topics.

Industry Practices for Challenging Autonomous Driving Systems with Critical Scenarios