Unmanned driving technology is actually very mature now. Judging from the current technical level, if the complex traffic situation in a big city is changed into a laboratory-specific pattern, there are vehicles with unified standards and pedestrians who meet the rules in the scene. Then there is no need for a steering wheel, and a car that drives all the way automatically can be available now.

Unmanned driving technology is actually very mature now. Judging from the current technical level, if the complex traffic situation in a big city is changed into a laboratory-specific pattern, there are vehicles with unified standards and pedestrians who meet the rules in the scene. Then there is no need for a steering wheel, and a car that drives all the way automatically can be available now.

The problem lies in how the car can understand the complex traffic situation in reality, and how can it be as flexible as the human eye and brain. The key lies in the cooperation of various sensors, which eventually transmit the monitored data to a high-precision processor, identify roads, signs and pedestrians, and make decisions such as acceleration, steering, and braking.

In the part of intelligent perception and recognition, the on-board optical system and on-board radar system are the most important to ensure driving safety. At present, the mainstream sensors used for surrounding environment sensing include LiDAR, millimeter wave radar, vision Three types of sensors.

Lidar (LiDAR), which determines the distance of an object by scanning the laser light reflected from an object, can form a 3D environment map with an accuracy of up to centimeters, so it plays a role in ADAS (advanced driver assistance system) and unmanned systems. important role. From the current vehicle lidar, mechanical multi-beam lidar is the mainstream solution, but it has not yet become popular due to the high price.

On the body of Baidu’s self-driving car, which was successfully tested on December 10 last year, in addition to deploying sensors such as millimeter-wave radar and video, a large 64-bit laser with a value of more than 700,000 yuan was placed on the roof of the car. Radar (VelodyneHDL64-E), Google also uses the same high-end configuration lidar. The pros and cons of vehicle-mounted lidar systems mainly depend on the performance of 2D laser scanners. The more beams of laser emitters, the more cloud points are collected per second. However, the more wiring harnesses, the more expensive the lidar is.

Taking Velodyne’s products as an example, the price of a 64-wire LiDAR is 10 times that of a 16-wire beam. In addition to the high cost of lidar, the performance of lidar in smoky medium and in rain and snow weather will hinder its performance.

However, as the core sensor, low-cost solutions will accelerate the arrival of unmanned driving. At present, the manufacturers of high-precision automotive lidar products are mainly concentrated in foreign countries, including Velodyne and Quanegy in the United States and IBEO in Germany. Domestic lidar products are relatively backward at present. Zhou Shining, senior executive of China Aviation Automotive Systems Holdings Co., Ltd., once said that foreign parts and components companies such as Bosch, Continental, Valeo, Infineon, and Delphi have already seized the commanding heights of ADAS technology, especially in ADAS technology. In the market layout of sensors, my country’s auto parts companies have already lost at the starting line.

Analysis of Three Mainstream Sensors for Intelligent Vehicle Environment Sensing

Millimeter wave radar (millimeter wave), millimeter wave refers to the electromagnetic wave in the frequency range of 30 to 300 GHz (wavelength is 1 to 10 mm). The wavelength of the millimeter wave is between the centimeter wave and the light wave, so the millimeter wave has both microwave guidance and photoelectric guidance. The advantages. Compared with the centimeter-wave seeker, the millimeter-wave seeker has the characteristics of small size, light weight and high spatial resolution. Compared with optical seekers such as infrared, laser, and television, the millimeter-wave seeker has a strong ability to penetrate fog, smoke, and dust, and has the characteristics of all-weather (except heavy rain) all-weather days, which can be combined with the effect of lidar. Complementary. In addition, the anti-jamming and anti-stealth capabilities of the millimeter-wave seeker are also superior to other microwave seekers.

The disadvantage is that the millimeter-wave radar has a very limited detection distance due to its wavelength, and cannot sense pedestrians, while lidar can accurately model all surrounding obstacles. In order to overcome the different shortcomings and shortcomings, car companies will inevitably combine these sensors.

At present, millimeter-wave radar is also a standard sensor for smart car ADAS systems. According to the current mainstream classification, millimeter-wave radar can be divided into 24GHz radar and 77GHz radar. Referring to its characteristics, 24Ghz is usually used for vehicle detection around the vehicle, and 77GHz is used for vehicle detection in front. Judging from China’s actual national conditions and industry characteristics such as the progress of chip research and development, there will still be market space for 24GHz millimeter-wave radar in China in the next three years. Looking around the world, the large-scale application of my country’s 77GHz millimeter-wave radar will be delayed slightly.

Because the functions of ADAS are often bundled and sold in the form of sensors + processors, the chips and algorithms of domestic automotive millimeter-wave radar systems are still mainly imported, and the cost is very high. Accelerating the development of domestic 77GHZ millimeter-wave radar chips and applying them to vehicles as soon as possible will be an opportunity for my country’s automotive millimeter-wave radar industry. Professor Bai Jie from the School of Automotive Engineering of Tongji University believes that compared with the fierce competition in cameras, millimeter-wave radar is more innovative, with a larger potential market space and more opportunities.

Vision sensor, ADAS uses the camera as the main sensor because the resolution of the camera is higher than that of other sensors, and it can obtain enough environmental details to help the vehicle to understand the environment. The vehicle camera can describe the appearance and shape of objects, read signs, etc., These functions cannot be achieved by other sensors. From the perspective of cost reduction, the camera is one of the strong candidates for identification sensors. Of course, the camera is the best choice when everything is clear, but it is greatly affected by environmental factors and external factors, such as insufficient light in the tunnel, weather factors resulting in reduced vision, etc.

An important tool for collecting image information, some functions such as road sign recognition and lane line sensing are intelligently implemented by cameras. At present, the main applications of cameras are: monocular camera, rear-view camera, stereo camera or binocular camera, surround-view camera. According to the demand for 6-8 cameras in more than 80 million new vehicles and bicycles in the world in 2015, the overall demand in the future is expected to be Over 600 million pieces, corresponding to 100 billion market space.

Vision algorithms are indispensable in the ADAS technical route. Active sensors such as millimeter-wave radars are less dependent on algorithms, and the algorithms are relatively simple. Passive sensors such as cameras are highly dependent on algorithms, and are generally provided by third-party companies alone. For example, the vision algorithm company Mobileye.

Previously, there was a lot of buzz about the termination of cooperation between Tesla and Mobileye. Mobileye provided a standard sensor installation method + map data cloud service + software system platform construction, but Tesla wanted to optimize the autonomous driving experience through the crowdsourcing model of online data collection, and the EyeQ3 chip limited the Tesla builds its own maps, so Tesla will develop its own image algorithms and image processing chips in the future.

However, Mobileye still occupies 90% of the market share with several products. This Israeli company’s status in the local arena is equivalent to BAT. Algorithms and hardware are the core of ADAS systems and Mobileye’s core competitiveness. Mobileye stands at the top of ADAS, throwing several streets away from its competitors. ADAS and traditional in-vehicle vision products have different requirements for software technology and hardware. It is not easy for traditional in-vehicle electronics companies to enter the ADAS market. If the domestic team starts from scratch, it will take at least 3 or 4 years to complete the initial technical accumulation.

Of course, in order to improve the accuracy of environmental perception, a combination of multiple sensors is usually required, and finally a stable and durable solution is provided. At present, the typical ones are millimeter-wave radar, lidar and vehicle cameras. Other ultrasonic and infrared technologies and the algorithm fusion of these technologies will bring a huge market to the sensor industry. But there is no doubt that the sensor industry chain should be the first to gain benefits in the past few years when cars are fully intelligent.

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