CU-ICAR To Host Symposium On Autonomous VehiclesMay 14, 2018 03:19PM ● By Kathleen Maris
Automotive experts say today’s smart vehicles are generating upwards of one gigabyte of information every second. So the question is: How do you collect all that data and what do you do with it?
This is at the heart of the inaugural SAE Automated and Connected Vehicle Systems Testing Symposium, which will be held at Clemson University’s International Center for Automotive Research (CU-ICAR) on June 20-21. Representatives from some of the most prestigious and cutting-edge automotive companies will come together to try to answer this and many other questions facing the future of autonomous vehicles. With all 33 major auto companies now having some form of an autonomous vehicle program in place, SAE International and Clemson decided it was about time to host an event like this and bring the industry’s smartest minds together.
Over the two-day symposium, technical experts will discuss ideas and methods to bridge the gap between technologies and products to address the top challenges of automated vehicle use in the public transportation system. This event will dive deeper to address the underlying engineering frameworks, showcase the engineering challenges, discuss systematic choices and how they are made, and the comparative analyses needed to create reliable engineered products. Over the two days, there will be six main sessions on topics ranging from what standards should be adopted industrywide to monetizing vehicle connections, as well as two keynote speakers. There will also be an interactive element open to the media.
Barry Smith, director of the National Center for Ontological Research (NCOR) and professor of philosophy, biomedical informatics, computer science and engineering, and neurology at SUNY Buffalo, will share some methods used in the biomedical and military fields that might prove useful to the automotive industry.
Thomas A. Dingus, director of the Virginia Tech Transportation Institute, will share some of his research methods, which involve instrumenting vehicles with unobtrusive video cameras and sophisticated instrumentation to assess crash and near-crash data.