Challenges facing LiDAR technology

What is LiDAR?

Light detection and ranging, more commonly known as LiDAR, is a technology used to detect and range objects in a space. A LiDAR system creates a three-dimensional model of any environment using reflectance LASER to measure the distance of objects. In this way, it is very similar to radar technology, the only difference being the use of lasers instead of radio waves.

LiDAR is used in various applications where accurate object detection or ranking is required. It can have a resolution of a few centimeters at a distance of 100 m, which is significantly better than several meters of radar. LiDAR’s accuracy makes it the preferred choice in altimetry, contour mapping, scanning for AR experiences like the new iPhone, and various other applications.

Today, the main application of LiDAR is in vehicles for ADAS and autonomous driving features. The race to create a low-cost LiDAR system that provides safe autonomous driving capabilities is underway as you read this. However, the technology has some issues to deal with and a competing technology to beat before it emerges as the winner. Let’s look at the main challenges ahead of LiDAR.

1. Range

LiDAR manufacturers claim the technology has a range of 100m and even 200m in some cases. These claims can be misleading as the range can be defined in different ways. A LiDAR system may not be as accurate in detecting objects at a greater distance in real-life situations even if it can detect a presence.

For example, let’s say an autonomous car with a LiDAR is driving down a road. A dark object at 100 m may not be fully detected due to reflection, and LiDAR may not be able to create an accurate 3D map from point clouds of reflected laser beams. The same applies to the case when a bright object is very close to the vehicle and a dark object is further away. Such cases call into question the claimed range of LiDAR devices.

The range issue should be checked through tests under real life conditions. The range question is less about specific situations and more about the limitations of LiDAR in different cases. Manufacturers and researchers should find a general solution to this issue to ensure the accuracy of the system.

2. Security concerns in edge cases

As mentioned above, the issue of LiDAR accuracy under certain conditions can be significant if it affects safety. In conditions such as fog, rain, snow and bright sun behind a white object, autonomous vehicles of all types face detection problems. This can be dangerous and even fatal in the worst case scenario.

Weather conditions can interfere with LiDAR laser beams to cause similar problems. Fog and rain are known to limit the use of LiDAR due to limited penetration and reflection of laser beams in such conditions. Whether it’s the weather or an object being transported by the wind, the environment mapped by LiDAR becomes inaccurate and the information can be misleading.

The inability to distinguish between a weather phenomenon or everyday objects and a vehicle on the road could be a hindrance to the autonomous car industry. However, this issue is already being worked on using high power lasers and better algorithms that can use the available data in such conditions to get the best results.

3. Cost

Another major issue with LiDAR is its higher cost. While costs have come down rapidly over the years, a LiDAR system is still significantly more expensive than the alternative camera vision system. LiDAR still costs about $500 per while eight cameras in a Tesla cost less than $100. In a competitive market with low margins, it can make a big difference.

The cost of a LiDAR will continue to decrease based on what we’ve seen over the years. In 2015 alone, a LiDAR unit cost $75,000. While the reduction in costs becomes slower after a certain point, with its higher accuracy LiDAR may soon enter a competitive range against cameras.

4. Credibility

Common LiDAR devices are electromechanical systems with many moving parts. Such systems tend to be less reliable and may see more failures and breakdowns. Add to that the working conditions of the vehicles where they go through dirt, water, vibration and all kinds of real world conditions and you have an important system that may not last long before it fails.

Creating reliable LiDAR is possible by reducing moving parts. Since this is an engineering problem, it can be solved with better designs. Several solid-state LiDAR systems have been developed, which may also become the ultimate solution to this issue in the long run.

LiDAR is a promising technology for autonomous vehicles. With resources being invested in research and development by automotive and laser manufacturers, it has great potential to find solutions to all challenges. The accuracy of LiDAR can make self-driving cars safer and bring the future closer to all fans of autonomous technology. If you’re one of them, keep an eye on the LIDAR space as it’s only going to get better.

The editors and editorial staff of the Daily Californian were not involved in the production of this advertisement. For advertising and sponsorship opportunities or more information about paid content, get in touch [email protected]

Leave a Comment

Your email address will not be published.