According to Lux Research, by 2030, Lidar will gain nearly $100 million in business opportunities in the field of autonomous driving. In addition, according to the commercialization plan of the car enterprise from ADAS to fully automatic driving, the laser radar has begun to play a special role in the vehicle part. Among the sensors used for autonomous driving, the evaluation of the laser radar by professionals is “essentialâ€. From the earliest Google pod car to the endless test of car companies, laser radar has gradually developed into a standard. It is not difficult to find that the commercialization of automotive laser radar is quietly taking place with the choice and planning of enterprise autopilot solutions. However, different Lidar companies have different strategies for entering the field of automatic driving, and there are differences in product technology. How does lidar and autonomous driving come together as the best CP? As a leader in laser radar, what are the different postures of Velodyne, Ibeo and Quanergy opening up the market? Look at the investigation of car cloud bacteria.
Technical expertise: Impressive automatic driving with high precision
"Sensor + High Precision Map + Cloud Computing" is currently recognized by the industry as "the most reliable autopilot solution". The sensor is the eye of an autonomous car that is used to observe the dynamic changes in the environment while driving. High-precision maps provide a global view of the car, and are especially good at predicting road conditions outside the detection range. Cloud computing guarantees that sensor data is updated and uploaded, so that the high-precision map is always in the latest version and the vehicle is delivered.
To make the autopilot system replace the human driver, the first priority is to "see" the environment at any time and any place. The driving environment is complicated, and the car cannot rely on a single sensor to do all the work. Based on the principle of “Who is going to be onâ€, cameras, laser radars, and millimeter-wave radars have their respective advantages, and the division of labor has completed a full set of perceptions to ensure that lanes, traffic, pedestrians, signs, and brakes are detected within 360 degrees in different time climates. Various real-time information such as lights and roadblocks. Among them, the most good part of lidar is obstacle detection and obstacle tracking.
Similar to the radar principle, the technology used by lidar is TOF (TIme of Flight). In short, the relative distance between the target and himself is calculated based on the return time after the laser encounters the obstacle. However, according to industry insiders, the laser beam is more concentrated than the sound wave, so it can accurately measure the relative distance between the contour edge of the object in the field of view and the device. These contour information form a so-called point cloud and draw a 3D environment map with precision. Centimeter level. Ibeo China Sales Director Beijing Ou Bai Tuo Information Technology Development Co., Ltd. CEO drama Ming Ming made an analogy, using the laser radar to see the world, the effect is better than wearing myopia glasses.
This accuracy is closer to 100% safer for self-driving cars on the road. Wendy, the director of Velodyne Asia, gave a simple case. Millimeter wave radar can find roadside obstacles, but can only "see" the fuzzy shape. The centimeter-level accuracy can clearly distinguish whether the obstacle is a tooth or a slope. After the self-driving car determines that it is a slope, it can make a decision to safely drive the lane. Of course, laser radar is not a panacea. Dr. Ming believes that for the distinction of environmental color information, Lidar is not direct and fast, and this is the strength of the camera. Millimeter wave radar can quickly obtain speed information, and has a low attenuation rate and good penetration in foggy days, which is an advantage compared with laser radar. In the case of a sensorless weather, you need a high-precision map. Weng Yi cited the case of Google's self-driving pod car. When the snow covered the road, the pod car was positioned on the high-precision map to calculate the position of the road lane and determine the driving track.
Industry benchmark: Velodyne 64-line laser radar
If you have a deeper understanding of how Lidar paints the surrounding landscape, line count, point density, horizontal and vertical viewing angle, detection distance, scanning frequency, and accuracy are several main parameters. The combination of autopilot and lidar, the CP, starts from the Velodyne 64 line and enters the public line of sight. In May 2012, the Google modified version of the Toyota Prius autopilot was tested on the road in Nevada. The Velodyne 64 line that turned around at the top of the show quickly became the hallmark of autonomous vehicles. At the same time, Google announced its project research goal - to achieve driverless and mass production.
The Google patents revealed at the time showed that the role of the roof 64-line lidar was to create a dynamic 3D high-precision map of the surrounding environment. A 360-degree mechanical rotation ensures complete detection of the environment around the vehicle. The equipment was retained in the production car and the final prototype was redesigned after considering wind resistance and protection. But in fact, this Velodyne64 line was born for the map industry, and the data obtained is redundant for real-time detection of autonomous vehicles. We may wish to look for a case to explain. It happened that Velodyne employees had released a video of the disassembly of a 64-line product that could help understand.
There are differences in the construction of different lidars, but they are roughly composed of the transmitting system, the receiving system, and the information processing. The disassembled Velodyne64 line is shown below. From the front, the entire laser transceiver can be regarded as the upper and lower parts, each part has three side-by-side lenses, the two sides of the lens is the laser emission, and the middle is the receiving place. Going to the back of the product, you will find that there are 16 sets of diodes on each side of the convex mirror, and the middle lens corresponds to 32 receivers, which can turn the optical signal into an electrical signal.
The laser beam is emitted from the two sides of the lens, and after being caught by the obstacle, it is captured by the intermediate lens, and the receiver processes the analysis to determine the position of the obstacle. All time information, control information, and received signals are transmitted to the top motherboard for information processing. The rotary recorder at the bottom will record the position and rotation information when rotating. All raw data can be transferred to the computer via the bottom data line. To keep the machine balanced while rotating, the 64-line laser has a heavy base. When working, this product has 64 beams in the vertical direction (line number), which can cover the angle of 26° in the vertical direction (vertical angle of view), reach the distance of 100-120 meters (detection distance), and the error of detecting the position of the obstacle is about About 10cm (accuracy). After power-on, the base motor will drive the laser radar to rotate 10 times per second (frequency), covering the 360° horizontal field of view (horizontal viewing angle), outputting 130,000 information points (dot density) per revolution, forming a so-called “point cloudâ€. .
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