Autonomous driving systems use a variety of sensors, each with its own advantages and disadvantages. Here’s a breakdown of the three major types of sensors—cameras, radar, and LiDAR—and examples of car brands that use them:
- Cameras:
Cameras provide high-resolution images and can capture details like texture, color, and contrast. They are widely used in features such as lane-keeping assistance, traffic sign recognition, and adaptive cruise control (ACC). However, cameras struggle in poor lighting or adverse weather conditions.
- Tesla is a notable brand that has relied heavily on camera-based systems through its “Tesla Vision” technology, moving away from radar in some models.
- Radar:
Radar is great at detecting objects and their speed in various weather conditions. It works well in fog, rain, or snow but lacks the high-resolution detail that cameras provide. Radar is often combined with cameras to overcome the limitations of each.
- Audi and BMW use radar in their adaptive cruise control and emergency braking systems.
- LiDAR:
LiDAR offers precise 3D mapping of the environment by measuring the distance to objects using laser pulses. It provides a 360-degree view and is excellent for obstacle detection. However, LiDAR is expensive and less effective in bright sunlight or extreme weather.
- Waymo and Volvo are known for integrating LiDAR systems into their autonomous vehicles.
Most modern autonomous vehicles use a combination of these sensors to ensure redundancy and compensate for the weaknesses of each technology. For example, Tesla is reintroducing radar to complement its vision-based system, while brands like Waymo integrate LiDAR, radar, and cameras for a comprehensive autonomous driving solution. The trend is moving towards sensor fusion, where these technologies work together for safer driving.
The combination of these systems varies by brand and model, with Tesla, Audi, BMW, and Waymo leading the way in deploying such technologies.