Overview
Sensor fusion combines information from multiple sensors so a vehicle can build a more reliable picture of its surroundings.
A camera may recognise lane markings, signs and object types. Radar may measure distance and relative speed. Ultrasonic sensors may detect nearby objects during low-speed manoeuvres.
Each sensor has strengths and limitations. Sensor fusion allows the vehicle to compare and combine their information.
Why sensor fusion is needed
No single sensor works perfectly in every condition.
Cameras can identify shapes and colours but may struggle with glare, darkness, fog or dirty glass. Radar can measure distance and relative speed well but may not identify exactly what an object is.
By combining data from several sensors, the system can make a more informed decision.
A simple example
A forward-facing camera detects the shape of a vehicle ahead.
At the same time, the radar measures how far away that vehicle is and whether the distance is closing.
The control system combines both sets of information before deciding whether to warn the driver or request braking.
Why calibration matters
Sensor fusion depends on each sensor describing the same physical scene accurately.
If a camera or radar is misaligned, the sensors may disagree about the position of an object. This can reduce system accuracy or prevent a function from operating as intended.
Australian context
Australian workshops should follow current vehicle manufacturer procedures whenever inspection, diagnosis or calibration is required.
Calibration methods, environmental conditions and prerequisites vary between vehicles. A successful scan-tool message alone does not replace the full manufacturer procedure.
Key point
Sensor fusion does not make an ADAS system infallible.
It improves confidence by combining different sources of information, but the system still depends on correct sensor operation, accurate calibration and suitable driving conditions.