LiDAR car sensors are a critical technology used in many vehicles today that are equipped with ADAS and autonomous driving features. These sensors emit laser pulses that will bounce off surrounding objects. The system will measure how long it takes for the pulses to return, allowing LiDAR systems to calculate precise distances.
While most cars offering autonomous driving or advanced safety features use LiDAR sensors, they’re just one of five ADAS sensor types. In this post, we’re going to discuss why LiDAR is important, the pros and cons of LiDAR sensors compared to other ADAS sensors, common ADAS calibrations that may be needed, and the future of LiDAR sensors in automotive technology.
Pros and cons of ADAS LiDAR sensors
LiDAR sensor technology is incredibly advanced, offering strong potential in supporting ADAS and autonomous driving features.
The strongest advantages of LiDAR sensors include high resolution even at far range, which can result in more accurate object detection and modeling. It has a far superior range compared to other ADAS sensors, and can create exceptional 3D maps of a vehicle’s surrounding area.
However, LiDAR sensors do not have the same resolution quality as some other sensors, and they may not function as efficiently in poor or inclement weather. Falling snow or rain, for example, can cause inaccurate readings. They also are more expensive than some other solutions, which may impact its development.
As a result, it’s important to consider not only the pros and cons of LiDAR sensors along, but to understand how they compare to other ADAS sensors that can be used together to benefit from the strengths and counteract the vulnerabilities of each.
LiDAR sensors compared to radar sensors
LiDAR sensors offer higher resolution than radar ADAS sensors, which use radio waves and can result in more accurate object modeling and detection at further ranges.
However, radar sensors’ performance is not impacted by poor weather or light conditions, making it effectively an all-weather and all-hour solution.
LiDAR sensors compared to camera sensors
Camera sensors use video and image to identify objects and provide drivers with assistance on tasks like parking, lane detection, or even blind spot monitoring. They deliver the highest resolution images compared to all sensors, including LiDAR sensors, and can accurately detect colors and 2D shapes.
However, camera sensors may not be as accurate at detecting an object’s distance compared to LiDAR systems. They also are most susceptible to being blinded by sunlight, and performance may struggle in low-visibility weather.
LiDAR sensors compared to sonar sensors
Sonar sensors use sound waves for object detection. Compared to other sensor types, they’re relatively low cost to install and are particularly adept at accurately detecting close objects nearby, even in tight spaces.
However, sonar sensors have short detection ranges, which makes them a strong complementary partner to LiDAR sensors. It’s also important to note that sonar may not accurately detect small or soft objects, and that their performance can be impacted by external surrounding noise.
Common calibrations needed for ADAS LiDAR sensors
LiDAR sensors play a vital role in object detection, lane departure warnings (LDW), localization, adaptive cruise control, and obstacle avoidance. As a result, it’s essential that the sensors are calibrated correctly. If not, they could result in inaccurate warnings, delayed actions, or too-early interventions.
Calibrations may be needed for ADAS LiDAR sensors following:
- Vehicle repairs when sensors may be removed, replaced, or disturbed.
- A motor vehicle collision, even a minor one.
- Significant software changes.
- Alterations to a vehicle’s alignment or suspension.
There are two main types of LiDAR calibration:
- Intrinsic calibration: Adjusts internal parameters of the sensors, including time offset, intensity, and laser beam angles.
- Extrinsic calibration: Adjusts the LiDAR sensors to align with either the robot frame or other sensors, including cameras or IMUs.
Repair shops can upload a single PCD file for each LiDAR sensor, map the uploaded frames by picking four points of each frame, and detecting the ground plane. Run the calibration and visualize the results.
The future of LiDAR sensors
LiDAR sensors’ exceptional potential for long-range detection and accurate 3D mapping make it a key technology for advancing autonomous driving capabilities. However, these sensors do have limitations, and many trends will focus on improving the systems to reduce vulnerabilities and improve or expand functionality.
LiDAR improvements
LiDAR technology is evolving rapidly, with current improvements focusing on the following:
- Reducing costs. Traditional LiDAR systems are both bulky and expensive, and improvements are seeking to reduce costs alongside the size of the sensors.
- Improving integrations: LiDAR systems don’t have advanced integrations with other ADAS sensors, which can reduce the system’s overall potential. Improvements seek to increase integration potential across different ADAS sensor types.
- Machine learning: Machine learning algorithms can deliver more accurate responses in real-world scenarios based on data captured by LiDAR sensors.
LiDAR trends
These are the trends we expect to see in LiDAR advancement and development in the coming years:
- Increased range and resolution. Longer-range detection without sacrificing the sensors’ high-resolution mapping capabilities will be a priority as technology advances, allowing vehicles to detect objects more accurately even at further distances.
- Multiple sensor integration: To compensate for each sensor types’ vulnerabilities— and to take advantage of the unique strengths of each—, most ADAS systems use multiple sensors, though they may operate largely independently. We’ll likely see increased integration from the data of multiple sensors, allowing ADAS systems to make more informed decisions and actions.
- Advancements towards autonomous driving: Right now, most cars offer ADAS features like collision mitigation (CM) or autonomous emergency braking (AEB). In future years, we expect that autonomous driving will become more prevalent, and LiDAR’s extended-range 3D mapping will be developed further to support this.
- Decreased LiDAR unit size: Traditional car LiDAR sensors are bulky, and current developments are focusing on creating smaller, solid-state sensors that won’t impact a car’s aerodynamic function… or its aesthetic, while also potentially reducing costs.
- Improved perception through machine learning: As ADAS technology is expanded upon further, expect to see more advanced features using machine learning algorithms that can more accurately interpret sensor data for better real-world outcomes.
LiDAR sensor calibration with Revv
LiDAR sensor calibration— and overall ADAS calibration— requires detailed information for each unique VIN, making it complicated for many repair shops and mechanics to offer recalibration services at scale.
Revv, however, offers AI-powered calibration reporting for ADAS features, including LiDAR sensors. You can look up individual VINs to assess both optional and equipped ADAS features for each vehicle, while also getting detailed information on mandated OEM calibrations, procedures, and requirements.
Revv has helped our clients drastically increase profits by automatically identifying and supporting ADAS recalibrations for their existing customers, with reducing calibration times by an average of two hours.
Ready to offer custom ADAS calibration services? We have recalibration information for an extensive number of makes and models, dating all the way back to the year 2000.
Book your free live demo to see how we can help boost your profit today.
