Domestically, Huawei has released a 96 line LiDAR with an annual output of 100000 sets per line, and the industry is celebrating the spring of autonomous driving. Looking at the world, as many as 5 LiDAR companies have gone public this year! After Velodyne, Luminar, Aeva, and Innoviz announced their launch, recently, Ouster， It is also about to go public through a merger with special purpose acquisition company (SPAC) Colonnade, with a valuation of approximately $1.9 billion.
After these 5 LiDAR companies successfully go public, with the strengthening of capital power, it will intensify the competition and reshuffle of the entire industry. Over the past decade, Lidar technology has made significant progress and has become a showcase of technological innovation vitality.
Now that the show has begun, who will take the top spot in automotive LiDAR?
Lidar and its various forms
Lidar is a remote detection and ranging method that works very similarly to radar. It emits infrared light pulses instead of radio waves, measuring the time it takes for light to return after hitting nearby objects. The time between the output laser pulse and the reflected pulse enables Lidar to accurately calculate the distance to each object based on the speed of light. Lidar captures millions of such precise distance measurement points per second to generate a 3D matrix of the environment. Information about the location, shape, and behavior of objects can be obtained from this comprehensive map of the environment.
Lidar working principle
As a sensor technology, LiDAR can directly measure distance with high resolution and form a grid, where each grid cell has a specific distance associated with it. Due to its high operating frequency and much shorter wavelength than traditional radar, it can provide higher angular resolution than radar, thereby more accurately identifying the edges of objects. Therefore, LiDAR helps autonomous vehicles to see the world, make decisions, and navigate.
In the combination of sensor technology used in semi-automatic and fully automatic vehicles, radar provides constant distance and speed measurements, as well as excellent all-weather performance, but lacks resolution, making it difficult to draw more accurate details at longer distances. The cameras commonly used in cars can provide high-resolution 2D information, but they must rely on powerful artificial intelligence (AI) and corresponding software to convert the captured data into 3D interpretation; Environmental and lighting conditions can have a significant impact on camera technology.
In contrast, Lidar can provide accurate 3D measurement data from short to long distances, even in harsh weather and lighting conditions. This technology can be combined with other perceptual data to provide more reliable representations of static and moving objects in the vehicle environment. Therefore, Lidar technology has become a highly available solution that helps with obstacle detection, collision avoidance, and safe navigation. Nowadays, Lidar has been used in many critical automotive applications, including advanced driver assistance systems (ADAS) and autonomous driving.