Key Components: The Three Senses of Autonomous Cars
Autonomous cars don't rely on a single type of sensor, but rather a combination of different sensing technologies, each with its own advantages and limitations, to provide a complete 360-degree view of their surroundings.
1. Cameras 📸
- Operational Principle: These passive sensors capture light and create a 2D image, similar to the human eye. They utilize AI and machine learning technologies for processing.
Key Features:
- Object Classification: They can accurately identify colors, traffic signs, traffic lights, lane lines, and distinguish object types (people, cars, bicycles).
- Low Cost: They are the cheapest and easy to install.
- Limitations: They perform poorly in low-light conditions (nighttime), bright light, or inclement weather (heavy rain, fog), and have lower depth perception accuracy.
2. Radar 📡
- Operational Principle: These are active sensors that emit radio waves and measure the time they reflect back to calculate the distance, speed, and direction of an object.
Highlights:
- Weather Resistance: Performs well in conditions where cameras and LiDARs struggle, such as heavy rain, fog, and snow.
- Velocity: Highly accurate in measuring the relative speed of moving objects.
- Long Range: Ideal for detecting objects at a distance (e.g., adaptive cruise control).
- Limitations: Low resolution and poor 3D image generation, making it difficult for the system to clearly identify the shape of objects (e.g., distinguishing a motorcycle from a small car).
3. LiDAR (Light Detection and Ranging) 💡
- Operating Principle: An active sensor that emits thousands or hundreds of thousands of laser pulses per second and measures the time it takes for the light to reflect back to create a "point cloud," or high-resolution 3D map of the environment.
Highlights:
- High Accuracy: Centimeter-level accuracy in measuring distance and shape.
- 3D Mapping: Generates a detailed 3D model of the vehicle's surroundings, allowing the vehicle to clearly understand the height and shape of objects.
- Limitations: Highest cost, and the laser beam may be affected by some inclement weather conditions, such as heavy rain or deep snow (although it is better than cameras in low-light conditions).
Interoperability: Sensor Fusion is the Key
The heart of autonomous vehicles is a process called Sensor Fusion, which fuses data from multiple sensors to address weaknesses in each and create the most complete and reliable picture of the environment.
1. Data Collection: All sensors collect real-time data (2D images, 3D maps, and speed/distance data).
2. Processing: AI software and on-board computers overlay this data to verify redundancy.
- LiDAR accurately identifies the location and shape of the truck ahead (a 3D model).
- Radar confirms how fast the truck is moving and how many meters away it is.
- Cameras determine the color of the truck and what signs are on it.
3. Decision Making: When data from multiple sources matches, the system can make highly confident decisions (such as braking, accelerating, or changing lanes), which is crucial for advanced autonomous driving (Level 3 and above).
Example: In heavy fog:
- Cameras may not see anything (data becomes unusable).
- LiDAR may experience reduced performance. (Due to laser reflection from water droplets)
- Radar still accurately detects the distance and speed of the vehicle in front, allowing the vehicle to maintain a safe distance and continue moving.
Relying on multiple sensors is essential to ensure the system can continue to operate safely even if one sensor fails or is obscured in adverse conditions.
Key Technologies:
- Autonomous Driving, Autonomous Driving, SAELevel, AI Technology
Classification:
- DC Fast Charge, AC Charger, Home Charging, EV Charging System
Practical Applications:
- Level 3, Partial Automation, Full Automation, ADAS
Broad Topics:
- Future Vehicles, EV Technology, Automotive Innovation
Autonomous Driving, Autonomous Driving, SAELevel, Level 3, Future Vehicles, Partial Automation
This image is: Car with Surround Sensors (Concept Overview). This image shows an autonomous car with icons of different sensor types (LiDAR, Radar, Camera) installed all around the car, along with lines connecting the data flowing into the central processing unit to convey 360-degree awareness of the surrounding environment.
