With the development of artificial intelligence and new energy technologies, the development from smart driving to driverless technology, car networking, and automotive big data will subvert the traditional automotive industry. The "electricization, intelligence, networking, and sharing" of automobiles is bringing about revolutionary changes, not only the automobile industry, but also the way cars travel. The change in the way of travel will lead to tremendous changes in the overall social form, which is a technological revolution. It is understood that the primary autonomous driving technology will be popular around 2020, and high-level intelligent driving technology will appear in 2030. With the changes in the entire industry ecology and competition model, the competitors of new energy vehicles are no longer companies like BMW and Toyota, but companies like Apple and Google.
On March 13, 2018, China Automotive Engineering Research Institute and Munich Exhibition Group of Germany held the 2018 New Energy and Intelligent Networking International Innovation and Development Forum at the Sheraton Shanghai Pudong Hotel on March 13~14, 2018. This forum focuses on the new ecology, new kinetic energy and new pattern brought about by the development of new energy and intelligent networked vehicles. The two main lines/breakthroughs of the industry from large to strong are based on industrial technology discussion and sharing. The latest developments in the industry chain and related industries. The "International Electronic Business" reporter participated in this forum, and will bring you the latest car industry's interpretation and thinking on the new energy smart car.
How does autonomous driving drive the automotive industry revolution?
Professor Yang Diange, the head of the Department of Automotive Engineering at Tsinghua University, first introduced the current state of technological development and technological breakthroughs in autonomous driving. Professor Yang Diange said that the car is “electricized, intelligent, networked and sharedâ€. This is the newization of the car, which is bringing revolutionary changes, not only the automobile industry, but also the way of car travel. . The change in the way of travel will lead to dramatic changes in the overall social form, which is a technological revolution. Speaking of this, our national leaders are very concerned. People in the industry know that in December last year, the National Development and Reform Commission released the “Smart Vehicle Innovation Development Strategyâ€, which means that the development of smart cars will become a national strategy in China in the future. The Ministry of Industry and Information Technology is also promoting the standards related to intelligent networked vehicles. Baidu unmanned vehicles are driving on the bridge during the Spring Festival evening. At this year's CES exhibition, Toyota also announced that it will make an important transformation. The competitors will be companies such as Google and Apple. From car manufacturers to transportation service operators.
Different levels of intelligent driving cars, L4`5 is seen as an advanced stage of autonomous driving
A quick look at the classification of smart cars, the current automatic driving is roughly divided into 5 levels. A system similar to an emergency collision avoidance belongs to L1~2, ​​L3 is a human-machine driving, and L4~5 is a relatively advanced automatic driving. From control to monitoring to failure response, it is unmanned. This is a relatively advanced automatic driving. .
Development status and goals of Japanese self-driving cars
Japanese auto companies are focusing on first- and second-level autonomous driving technologies, mainly driving assistance technology, to improve the safety of automobiles through assistive technology. Japan hopes to control the number of traffic deaths to 2,500 in 2018 through the promotion of first- and second-level intelligent driving assistance technologies. The Winter Olympics Japan will carry out demonstrations of high-level automatic driving. The promotion node of high-level automatic driving is mainly in 2021-2030. As a component company, the promotion of autonomous driving technology should be ahead of the whole vehicle company. This is a mainland company. Before 2020, the important goal of the mainland should be driving assistance. In 2025, automatic driving will be introduced into the industrialization promotion. On the right is the EU's technology roadmap. Before 2025, the focus is on driving assistance. The 2030 high-level autopilot operation will enter the promotion stage. High-level automatic driving will enter industrialization after 2025.
What applications can an intelligent network car achieve?
From this table, we can see more clearly. At the 2020 node, all new cars equipped with first- and second-level driver assistance technologies account for about 50% of the new cars. By 2025, the proportion will reach 80%, and the 3-4 level smart cars may be 10-20%. In 2030, 100% vehicles have 1-2 level intelligent functions, and 5 levels are around 10%. Everyone will be looking forward to it, but for most people, by 2030, 10% of the vehicles are professional vehicles, not the cars we usually drive. For example, logistics vehicles for buses and ports, including some special vehicles, may achieve the latest high-level automatic driving on these vehicles.
Cars are now highly saturated with hardware and software, and the software layers between them are not compatible. Yang Diange believes that the reason why mobile phones and PCs are highly developed is because of the separation of software and hardware. The development of smart cars needs to support the separation of software and hardware.
Speaking of the intelligent computing platform for advanced autonomous driving, Yang Diange believes that there is a need for powerful computing power and artificial intelligence technology to meet the needs of advanced autonomous driving, so the super computing platform is needed in the future.
The other is the perceptual technology. To achieve intelligent driving at 4 or 5 levels, it is necessary to perceive the distance between the super-horizon and the super-field of view. It is necessary to compensate for the driver's decision-making speed through the perceptual ability and exceed the human's perception ability. For smart cars, it is necessary to solve the problems that cannot be seen through the Internet of Vehicles.
Speaking of the technological breakthroughs faced by advanced autonomous driving, Yang Diange said that the technology required from L1 to L5 is different. When it comes to L4 or L5, the automatic driving map is a must. With a map, you can combine perception and map, and the driver can know how far it is from the surrounding driving environment.
This is based on the decision to drive the map automatically, based on the control logic to drive. This method is relatively simple for making a car, which requires more precise control of the entire vehicle. Google and Baidu did not work in the development of the car itself, through a large number of data collection and artificial intelligence deep learning to drive decision and control. The training of intelligent driving through deep learning can also drive the car up.
However, there is a problem with the car that has been made. If the cause of the accident is not known, safety is the most important thing for the car, even if there is a problem. Therefore, for the future high-level intelligent driving must combine deep learning and driving decisions. Finally, the safety of the car, the safety of the car is much more important than the safety of mobile phones and PCs. In-vehicle information security involves the national strategic security level and needs to be considered at the national level.
Yang Diange also introduced the current progress of Tsinghua University. Tsinghua University has set up an intelligent network of automobile and transportation research center. At present, L2\2 driving assistance technology developed by Tsinghua is one kilogram in SAIC, Changan, Guangzhou Automobile, Yutong, Nissan and Toyota. The company carries out batch preloading. At the same time, Tsinghua University's intelligent team also hatched entrepreneurs such as Zhixing Technology.
How do governments and companies use big energy vehicle big data?
Professor Wang Zhenpo, secretary-general of the National Big Data Alliance of the New Energy Vehicles and deputy director of the State Key Laboratory of Electric Vehicles, said that for enterprises, the data of vehicle fault, safety, driving and operation monitoring will have a great deal for enterprises to provide more car services. the value of. In the future, the entire industry will meet customer needs, as well as battery management in the entire industry chain. In the future, this automotive big data will play a more important role in the development of China's new energy vehicle industry.
Speaking of big data for new energy vehicles, President Xi proposed the National Big Data Strategy on December 8, 2017. The so-called big data is essentially reflected in the depth and breadth of data mining, that is, the breadth of cross-border integration. For big data and new energy vehicles, the volume has also been achieved in government work reports. In the key research areas of China's manufacturing 2025, we use low-carbon, information and intelligence as the core technology.
What is the construction of the new energy vehicle big data platform? Wang Zhenpo said that at the end of 2016, the supervision system for enterprise, local and national level three inspection platforms was completed, and data monitoring of enterprise-level platforms was realized.
Through this system, the standardization of data projects has been completed, including various data of needle cars, batteries and motors. Through these data lists, for national platforms, supervision and inspection and data analysis of new energy vehicles in the country can be carried out. For local platforms, you can safely monitor new energy vehicles in the public service sector. The enterprise platform can achieve 100% real-time monitoring of the product. With the construction of the platform system, in 2017, based on the data monitoring of the whole sample industry, it is also possible to upload the privacy number in addition to the removal of the privacy data.
From a technical analysis point of view, this platform has unique advantages at Beijing Institute of Technology. This technology develops a remote fault diagnosis system for electric vehicles based on big data mining. In addition to the basic security threshold warning, through the historical application analysis of big data, the commercial value change based on typical data can provide early warning information. How to test and logically judge the authenticity and validity of big data? The data has an invalidity rate to ensure the reliability and security of the data. In 2017, there is still a job. In the past, the technical parameters of the vehicles came out of the laboratory. Nowadays, there are a large number of vehicle application technologies, which can be calculated by various models of the enterprise through the standards of economy, environmental applicability, reliability and safety index.
With the driving information of the new energy vehicle itself, when it comes to the cross-border integration of data, it can also achieve multi-integration of data. For the government sector, with the integration of multiple data, it provides a series of data support for traffic management, vehicle tracking, national security, and industrial policy formulation. With relevant data, companies can provide a variety of public and business service information. For example, time-sharing, the current data between companies is separate, if you can do multi-enterprise data communication, when you use an APP to meet all service needs. There are a few specific things in our platform right now.
In addition to determining the course through the data returned by the vehicle, the operating rules can also be obtained. It can also be seen whether the vehicle is running through changes in the energy consumption of the vehicle. For example, the energy consumption data of the logistics vehicle can calculate whether the operation is normal. Through the health of the battery, the safety of the battery can be determined, and the abnormality point and fault diagnosis can be picked out by the voltage variation law of the power battery. Similarly, these data can also serve operational companies, optimize vehicle driving behavior and reduce operating costs through vehicle application models, energy consumption and driving behavior.
For the driver's data, behavior and energy analysis can be performed, and the driver can be personalized to guide the development of low-energy driving. We have a national new energy vehicle testing platform, and we have decided to establish a new energy vehicle national monitoring and power battery recycling and traceability management platform.
FTTx Accessories Clamps & Hooks
Galvanized Steel Pole Clamp,Steel Drop Wire Clamp,Galvanized Steel Hoop Fastening Retractor
Sijee Optical Communication Technology Co.,Ltd , https://www.sijee-optical.com