Challenges in Front of LiDAR Technology

What is LiDAR?

Light detection and ranging, more popularly 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 surroundings using reflected lasers to measure the distance of objects. In this way, it’s a lot like radar technology, the only difference being the use of lasers instead of radio waves.

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

Today, the major 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 taking place as you read this. However, the technology has some issues to deal with and a competing tech to beat before coming out as the winner. Let’s look at the major challenges in front of LiDAR.

1. The Range

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

For example, let’s say an autonomous car with a LiDAR is moving on a road. A dark object at 100m might not be detected in its entirety because of the reflectivity and the LiDAR might be unable to create an accurate 3D map from the point clouds of reflected laser beams. The same hold for the case when a bright object is too close to the vehicle and a dark object is further away. Such cases bring the claimed ranges of LiDAR devices into question.

The range issue has to be checked through tests in real-life conditions. The question over range is less about specific situations and more about the limitations of LiDAR in various cases. The manufacturers and researchers have to come up with a general solution for this issue to ensure accuracy of the system.

2. Safety Concerns in Edge Cases

As mentioned above, the issue of LiDAR accuracy in certain conditions can be a major one if it affects the safety. In conditions like fog, rain, snow, and bright sun behind a white object, autonomous vehicles of all kinds face detection issues. This can be dangerous and even fatal in the worst-case scenario.

The weather conditions can obstruct the laser beams of LiDAR to cause similar issues. Fog and rain are known to limit the use of LiDAR because of the limited penetration and reflection of laser beams in such conditions. Whether it’s weather or some object being carried around by the wind, the surroundings mapped by LiDAR become erroneous and the information can be misleading.

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

3. The Cost

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

The cost of a LiDAR will continue to go down based on what we’ve seen over the years. Just back in 2015, a LiDAR unit used to cost $75,000. While the reduction in costs gets slower after a certain point, with its higher accuracy LiDAR might enter a competitive range against cameras soon.

4. Reliability

The common LiDAR devices are electromechanical systems with multiple moving parts. Such systems tend to be less reliable and might see more failures and breakdowns. Add to that the working conditions of vehicles where they go through dirt, water, vibration and all kinds of conditions of the real world and you have an important system which might not last for a long time before failure.

Creating reliable LiDAR is possible by reducing moving parts. This being an engineering problem, it can be solved with better designs. Some solid-state LiDAR systems have been created which as well might become the final solution to this issue in the long run.

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

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