🎤 Talk: “Critical scenario identification for testing
       autonomous driving systems”

Autonomous driving systems have to be tested thoroughly and rigorously to validate their functionalities and safety, particularly in hazardous situations known as critical scenarios. However, identifying these critical scenarios for testing remains a significant challenge. In this presentation, I will introduce an integrated toolchain that we have developed for identifying critical scenarios and its application for testing realistic autonomous driving systems in collaboration with Volvo Cars. Additionally, I will present contemporary practices in using critical scenarios for testing autonomous driving systems, synthesized from interviews with 13 domain experts from 7 autonomous driving companies in Sweden. Current industrial practices suggest that critical scenario identification, as an essential aspect of testing autonomous driving systems, is still in its early stages and requires improvement. Progress in this area relies on combining available approaches and fostering increased collaboration among various stakeholders from both industry and academia.

📝 Qunying Song

Qunying Song is a PhD student in Computer Science at Lund University, Sweden. His research focuses on identifying critical scenarios for testing autonomous driving systems using simulation and optimization techniques.

Qunying received his bachelor’s and master’s degrees in Computer Software Development from Kristianstad University in 2012 and 2013, respectively. Before starting his PhD studies, he worked in the industry as a software developer for six years.

When, where?

📅 Thursday 25th of April 2024

⏰ 8:30 Workshops,   13:00 Talks,   18:00 Afterparty

📍 IHM Business School – Fabriksgatan 25, Gothenburg

💸 Free of charge

🅿️ Closest parking lot: P-hus Tomtegatan