Autonomous Vehicle Technology (AVT) annually recognizes the most innovative technologies, products, and services of the year in the following areas: vehicle autonomy, connectivity, electrification, and mobility services (ACES). This year, AVT awarded FLIR for advancing ADAS and AV safety with the Thermal Imaging Regional Dataset program for machine-learning development.
FLIR regional datasets enable developers to start training convolutional neural networks (CNN), empowering the automotive community to create the next generation of safer and more efficient ADAS and driverless vehicle systems. The program builds on a free dataset program FLIR launched in 2018, and includes new variations in weather, including fog and rain, plus additional driving scenes at different hours of the day.
Thermal cameras can detect and classify objects in challenging conditions including total darkness, fog, smoke, inclement weather, and glare, providing a supplemental dataset beyond LiDAR, radar, and visible cameras. Having regional specific datasets enables developers and carmakers to more quickly ramp up and execute thermal imaging testing as part of the ADAS/AV sensor suite. FLIR has so far released a San Francisco dataset and a Santa Barbara dataset, and will release additional regional datasets as they are developed to provide engineers with expanded object classes, weather, and seasonal driving conditions.
Winners of the AVT ACES Awards were determined based on contributor, industry expert, company, and reader inputs. Autonomous Vehicle Technology is the only business-to-business magazine dedicated to the autonomous vehicle industry, and the AVT ACES recognize production and prototype innovations and the work or result of top partnerships, collaborations, and consortia in the industry.