Driverless cars can struggle to distinguish between a pedestrian and a cardboard cutout of a person when it is dark or particularly rainy. A system that uses AI to identify objects based on their heat emission patterns could help autonomous vehicles to operate more safely in all outdoor conditions.
Zubin Jacob at Purdue University in Indiana and his colleagues developed a heat-assisted detection and ranging (HADAR) system by training an AI to determine the temperature, energy signature and physical texture of such objects for each pixel in the thermal images.
To train the AI, the researchers captured data outdoors at night using sophisticated thermal-imaging cameras and imaging sensors capable of showing energy emissions across the electromagnetic spectrum. They also created a computer simulation of outdoor environments to allow for additional AI training.