Summary:
Driver-assistance features like adaptive cruise control, automated emergency braking, and lane-keeping rely on a combination of sensors to help vehicles “see” their surroundings. These sensors—radar, sonar, cameras, and lidar—each play a unique role in making autonomous and semi-autonomous systems functional and safe.
Radar:
Radar uses electromagnetic waves to detect objects and measure their speed. Found on a vehicle’s front bumper or behind the rear quarter-panel, radar supports features like adaptive cruise control, emergency braking, and blind-spot monitoring.
Sonar:
Sonar, or ultrasonic sensors, use sound waves to measure distance by calculating the time it takes for the waves to return after bouncing off an object. Manufacturers place these sensors on bumpers to assist with parking and proximity detection but are limited to short-range detection.
Cameras:
Cameras offer a 2D video feed, allowing systems to identify lane markings, traffic signs, pedestrians, and cyclists. Multiple cars use cameras for depth perception. Some systems, like Subaru’s EyeSight, rely on a pair of cameras instead of radar. Cameras can also be used for driver monitoring and even night vision, though they can be affected by sunlight and may require recalibration if the windshield is replaced.
Lidar:
Lidar (Light Detection and Ranging) sends out light pulses to map a vehicle’s surroundings in 3D. It’s used in advanced systems like Level 4 autonomous vehicles, with more affordable static lidar appearing in production vehicles. Lidar is also essential for creating high-definition maps for navigation.
Sensor Fusion:
Sensor Fusion integrates data from multiple sensors to complement each other’s strengths and compensate for weaknesses. This redundancy enhances the system’s overall reliability. While some automakers, like Tesla, rely primarily on cameras, others use sensor fusion to improve safety and performance.
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