  Testing autonomous driving systems for safety and reliability is extremely
complex. A primary challenge is identifying the relevant test scenarios,
especially the critical ones that may expose hazards or risks of harm to
autonomous vehicles and other road users. There are several proposed methods
and tools for critical scenario identification, while the industry practices,
such as the selection, implementation, and limitations of the approaches, are
not well understood. In this study, we conducted 10 interviews with 13
interviewees from 7 companies in autonomous driving in Sweden. We used thematic
modeling to analyse and synthesize the interview data. We found there are
little joint efforts in the industry to explore different approaches and tools,
and every approach has its own limitations and weaknesses. To that end, we
recommend combining different approaches available, collaborating among
different stakeholders, and continuously learning the field of critical
scenario identification and testing. The contributions of our study are the
exploration and synthesis of the industry practices and related challenges for
critical scenario identification and testing, and the potential increase of the
industry relevance for future studies in related topics.
