Cover Story AV Simulation Testing Faces a Long and Winding Road by Sebastian Blanco There are many divergent-but-related ideas about how best to leverage simulation to 'teach' and test automated vehicles. Global AV simulation experts continue to attack the technology's persistent obstacles. Right now, millions of virtual vehicles are driving millions of virtual miles. Their long-term digital mission is to make high-level vehicle automation a reality. Settling on the best methods to test all of these AVs is part of a healthy debate throughout the industry, as engineers can't agree on ways to explore different simulation and sensor models. AV startups around the world are busy writing the code that defines the rules of these virtual test beds. Even when there's agreement on some aspects - everyone knows AVs need to be safe - there are legitimate questions about how to get there. Imagry: a focus on real-world miles Even companies that are happy to explore the mysterious world of AV neural networks have found there are real limits to the tests that can be accomplished in a server box. Imagery is one such entity. Imagry's mapless Level 3 and Level 4 automated-driving software was built on the idea that neural networks and AI are the only way to truly solve selfdriving vehicles. " We believe strongly in the singularity of AI, " Imagry CEO Eran Ofir told SAE Media at the IAA Mobility 2023 exposition in Munich, Germany. To better discover edge cases, dRISK built a hyper-dimensional dataset of vehicle crashes and near-crashes around the world that tracks 500 different points. " Basically, that AI would be better than humans in [driving] tasks. " Imagry was founded in 2015 and is headquartered 8 November 2023 ADAS & AUTONOMOUS VEHICLE ENGINEERING 8 November 2023 ADAS & AUTONOMOUS VEHICLE ENGINEERING Sebastian Blanco