ADAS (Advanced Driver Assistance Systems) mainly rely on the collaborative work of multiple sensors, including millimeter-wave radar, cameras, ultrasonic sensors, and LiDAR. Millimeter-wave radar excels at detecting the speed and distance of long-range objects, making it suitable for adaptive cruise control and collision warning; monocular or multi-camera systems process lane lines, traffic signs, and pedestrians through image recognition, serving as the core for lane keeping and traffic sign recognition; ultrasonic sensors are used in low-speed parking scenarios, detecting nearby obstacles via sound wave reflection; LiDAR enhances environmental modeling capabilities through high-precision 3D point cloud data and is commonly found in high-level autonomous driving systems. These sensors achieve 360-degree environmental perception through data fusion-for example, the complementarity of forward radar and cameras can improve target recognition rates in severe weather, while the combination of ultrasonic sensors and surround-view cameras can optimize automatic parking accuracy. With technological development, 4D imaging radar and solid-state LiDAR are gradually expanding the performance boundaries of ADAS.
