Apple wants an ‘Apple Car’ to detect ‘hidden’ objects to avoid collisions — Apple World Today

Apple notes that, however, conventional sensor systems often fail in adverse light conditions, including nighttime, low visibility weather (e.g., fog, snow, rain, etc.), glare, and/or the like that obscure or diminish the visibility of such objects. For example, monochromatic sensors generally require active illumination to detect objects in low light conditions and are prone to saturation during glare. As such, objects remain hidden from detection by monochromatic sensors in low light conditions and in the presence of glare, for example, due to external light sources, such as the headlights of other vehicles. 

Other conventional sensor systems eliminate the need for active illumination by using passive sensors, such as long wavelength infrared sensors. However, such sensor systems typically fail to identify objects in adverse light conditions due to low resolution. 

Many other conventional sensor systems are cost, weight, and/or size prohibitive for deployment into a vehicle for object detection. Accordingly, objects remain hidden from conventional sensor systems in adverse light conditions, thereby exacerbating the challenge of avoiding such objects. Apple says that it’s “with these observations in mind, among others, that various aspects of the present disclosure were conceived and developed” for an object detection system.

Here’s the summary of the patent filing: “Implementations described and claimed herein provide systems and methods for object detection. In one implementation, thermal energy data in a long wavelength infrared band for a wide field of view is obtained. The thermal energy data is captured using at least one long wavelength infrared sensor of a sensor suite mounted to a vehicle. A foveated long wavelength infrared image is generated from the thermal energy data. 

“The foveated long wavelength infrared image has a higher resolution concentrated in a designated region of the wide field of view and a lower resolution in a remaining region of the wide field of view. Emissivity and temperature data for the designated region is obtained by processing the foveated long wavelength infrared image. One or more features in the designated region are resolved using the emissivity and temperature data.”