Scalable Autonomous Vehicle Safety Tools Developed By Researchers

As the speed of autonomous vehicle manufacturing and deployment increases, the safety of autonomous vehicles becomes even more important. For that reason, researchers are investing in the creation of metrics and tools to track the safety of autonomous vehicles. As reported by ScienceDaily, a research team from the University of Illinois at Urbana-Champaign have used machine learning algorithms to create a scalable autonomous vehicle safety analysis platform, utilizing both hardware and software improvements to do so. Improving the safety of autonomous vehicles has remained one of the more difficult tasks in AI, because of the many variables involved in the task. Not only are the sensors and algorithms involved in the vehicle extremely complex, but there are many external conditions that are constantly in flux, such as road conditions, topography, weather, lighting and traffic.