Demo
Driver Gaze-Aware Adaptive LiDAR Sensing for Advanced Driver Assistance Systems
Federico Scari (TU Delft - Mechanical Engineering)
Arkady Zgonnikov (TU Delft - Mechanical Engineering)
Chen Quan (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Nitin Jonathan Myers (TU Delft - Mechanical Engineering)
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Abstract
Light detection and ranging (LiDAR) plays a crucial role in machine perception for advanced driver assistance systems. Existing LiDARs, however, do not adapt their sensing strategy to complement driver's perception. We demonstrate a novel LiDAR prototype that dynamically adapts its range and resolution over the field of view, according to real-time driver gaze. Our gaze-aware LiDAR emphasizes scanning peripheral zones the driver may overlook, i.e., critical areas during driving. Our demonstration showcases enhanced perception, highlighting the potential of hybrid human-machine sensing for safer driving.