Choose The Right Sensors For Autonomous Vehicles
When the world’s first “motorwagen” was introduced in 1885, the notion that a car would one day drive itself was laughable. Today, assisted and autonomous vehicles are the reality of an age where digital sensors can outperform human ability to perceive motion, distance, and speed.
When used together, sensor technologies including camera, lidar, radar, and ultrasonic give vehicles one complete understanding of the world to navigate safely with little or no human intervention.
But as engineers and designers, identifying the right combination of these sensors to satisfy the end user’s needs — including safety, functional performance, and price — requires thoughtful consideration of each sensor type’s roles, capabilities, and limitations.
Examples of sensor applications in vehicles include:
Automatic emergency braking
Lane departure warning
Adaptive cruise control
Traffic jam chauffeur
Driverless taxis and delivery
What are the four types of autonomous sensors?
High-resolution digital cameras help a vehicle “see” its environment and interpret the world around it. When multiple cameras are installed around the vehicle, a 360° view allows the vehicle to detect objects in its proximity, like other cars, pedestrians, road markings, and traffic signs.
There are several types of cameras to consider for meeting different design needs, including NIR cameras, VIS cameras, thermal cameras, and time of flight cameras. As with most sensors, cameras work best when used to complement each other.
NIR camera: near-infrared cameras rely on light outside the visible range and are often combined with NIR emitters, such as LEDs
VIS camera: identifies objects based on the reflection of visible light
Thermal camera: detects objects from the infrared energy they emit
Time of flight camera: measures distance between the camera and subject
Cameras are ideal for situations such as maneuvering and parking, lane departure, and recognizing driver distraction.
Lidar stands for “light detection and ranging,” and is a remote sensor technology that uses light pulses to scan an environment and produce a three-dimensional copy. It’s the same principle as sonar, except lidar uses light instead of sound waves. In autonomous vehicles, lidar scans surroundings in real-time, allowing cars to avoid collisions.
Components of lidar:
Emitter: emits pulsed light waves into the environment and scans to measure how long it takes light to reflect back from objects to judge distance and depth
Receiver: captures reflected light waves to understand form, size, speed, and distance to a certain object
Signal Processing: compiles and interprets the data
Lidar is very accurate with depth perception and determining the presence of an object. It can see at long distances and through poor environmental conditions, like nighttime or rain and fog. Because it recognizes and categorizes what it sees, it can tell the difference between objects like a squirrel and a stone and predict behavior accordingly.
Radar stands for “radio detection and ranging.” This sensor emits short pulses in the form of electromagnetic waves to detect objects in the environment. As soon as the waves hit an object, they are reflected and bounce back to the sensor. In autonomous vehicles, radar is used to identify other vehicles and large obstacles.
Components of radar:
Transmitter: directs radio signals in identified directions
Receiver: captures radio waves as they reflect off of objects
Interface: translates radio data into driver-friendly information
Because it does not rely on light, radar performs well regardless of weather conditions and is most commonly used to enable cruise control and collision avoidance systems.
While radar uses radio waves and lidar uses light pulses, ultrasonic sensors evaluate the objects in an environment by sending out short, ultrasonic impulses that are reflected back to the sensor. They are very cost effective, excellent at detecting solid hazards, and are typically used on car bumpers to alert drivers of obstacles while parking. For best results in assisted driving applications, ultrasonic sensors are commonly combined with cameras.