Technology aimed at improving the performance of autonomous cars in visually challenging conditions has been developed by scientists at the Massachusetts Institute of Technology (MIT). The new system uses a combination of sensors and computer vision to detect objects that are not visible from outside the car, such as pedestrians, cyclists or other vehicles. This would allow the vehicle to detect sub-THz waves rebounded from an object and to use those signals to recreate an image of that object. To achieve the optimal sensitivity, scientists implemented heterodyne detectors, a scheme of independent signal-mixing pixels. Unlike traditional infrared-based LIDAR imaging systems, sub-THz waves are detectable even in adverse visual conditions, such as fog.
Technology aimed at improving the performance of autonomous cars in visually challenging conditions has been developed by scientists at the Massachusetts Institute of Technology (MIT). The new system uses a combination of sensors and computer vision to detect objects that are not visible from outside the car, such as pedestrians, cyclists or other vehicles. This would allow the vehicle to detect sub-THz waves rebounded from an object and to use those signals to recreate an image of that object. Unlike traditional infrared-based LIDAR imaging systems, sub-THz waves are detectable even in adverse visual conditions, such as fog.