As cars become more intelligent, ensuring better vision has been the priority, especially at night. US-based Owl Autonomous Imaging integrates thermal images with artificial intelligence to do object detection, classification and ranging for a vehicle. The company launched its first commercial product in early January.
According to Wade Appelman, Owl AI’s chief marketing officer, thermal cameras use passive energy – radiation from all objects in the form of heat – while RGB cameras use visible light.
He said thermal cameras can see in all light conditions, including in complete darkness. The sensors were created primarily for high-cost industrial applications like avionics and the military. But Owl AI has been developing cost-effective thermal cameras and AI software suitable for the automotive industry.
Appelman explained that real-time images shot by Owl AI’s thermal cameras are run through the convolutional neural network the company has been training. The system will help a car detect an object, and then classify and check how far it is away. The information is essential for vehicles to react safely to ever-changing road situations.
The first version of Owl AI’s solution can classify cars, children and adult-sized people, evaluating their distance from a vehicle precisely, Appelman said. The startup will continue to enhance the technology to classify deer, stop signs, traffic cones and many more objects.
Detecting unexpected objects at night has been a real problem for drivers. There is also room for improvement in the related car safety features. The US Insurance Institute for Highway Safety did a nighttime test of pedestrian automatic emergency braking (AEB) systems in 2022. Results showed eight of the 23 tested models earned basic scores. In addition, four vehicles did not perform well enough in the dark to get any score.
Appelman said vehicles that failed to stop in time in the test were mostly equipped with RGB cameras or radars.
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