The second half of the ＂marathon＂ of intelligent driving starts, and the cost of commercialization still needs to be reduced
Movies can be watched on the car window, and the windshield automatically recognizes street store information… Scenes from science fiction movies may be coming to life.
In the 2022 China International Trade in Services Fair (hereinafter referred to as the "Service Trade Fair"), the 2022 Automotive Capital Forum "Double Carbon Future, Intelligent Vehicle Acceleration" was officially held.
At present, the global automotive industry is experiencing a scientific and technological revolution unseen in a century. China’s new energy vehicles have seized the opportunity to achieve "lane change and overtake", but they still face multiple challenges when integrating with technologies such as the Internet and artificial intelligence.
Beijing News Shell Financial reporter interviewed Wu Gansha, founder of Uisi Technology, Zhang Dezhao, CEO of Smart Walker, Xu Junfeng, CEO of Future Black Technology, and other "leaders" of intelligent driving industry chain enterprises on September 1 to understand the development trend of intelligent driving and where the road to commercialization is.
"Black Technology" Revitalizes the Smart Electric Vehicle Industry Chain, Trillions of Blue Oceans Are Coming
When talking about the development of intelligent driving, the above mentioned several people introduced the "black technology" in the automotive industry chain today.
In terms of display screens, Xu Junfeng gave an example to reporters that in real life, people can enter the virtual world by wearing a pair of 3D glasses, while cars hope to turn the windshield into a screen that connects the digital world and the real world. In Xu Junfeng’s vision, the future dashboard, video conferencing, watching movies and other functions can be realized through display systems, such as the windshield in front of the driver and the window of the rear passenger.
However, according to his understanding, the above-mentioned products have been developed and mass-produced in Germany, but the effect has not yet reached the level that people expect to enter the "virtual world". He said that there are still a lot of technical problems in the virtual world that have not been solved, such as how the picture of the car is relatively still in the bumps, and whether the lidar can support the vehicle to clearly integrate the destination 100 meters away with the screen.
According to Xu Junfeng’s prediction, by 2030, people may be able to see augmented reality based on digital twins.
For example, in the future, everyone will have a digital twin of the street, and the vehicle will accurately calculate the information that the driver needs to know according to the algorithm, and project this information on the windshield, "such as the coffee shop you are used to consuming, the screen will identify the store and project the coffee price."
In terms of intelligent driving cruise systems, Zhang Dezhao introduced that today’s intelligent driving solutions mostly rely on high-precision maps, which is equivalent to superimposing human experience and intelligence into the map, marking left-turn lanes, right-turn lanes, and impassable areas.
Behind these black technologies, smart electric vehicles have actually reconstructed the automotive industry chain. The ** chain companies that are deeply tied to car companies are expected to benefit from the wave of intelligence and the rise of local technology car companies.
With the rise of smart electric vehicles, there is a strong demand for electronic accessories. From lidar, cameras, millimeter waves, and high-precision maps in induction systems, to AI chips and software in decision-making systems, to electric braking in the execution stage, and finally to intelligent cockpits, screens, and voice control in human-machine interaction needs, a large number of local enterprises have benefited from it.
The reporter combed and found that now class A shares a number of smart car industry chain companies, such as chips such as Junsheng Electronics and Zhaoyi Innovation; lidar such as Juguang Technology, Changguang Huaxin, etc.; vehicle software such as Guangting Information.
According to the analysis of the research report of Yiou Think Tank, by 2030, the scale of China’s smart transportation market will reach 10.60 trillion yuan. With the continuous improvement of the intelligent layout of the vehicle end, the road end and the cloud end, the demand for the C end will be gradually released. At the same time, with the formation of the autonomous driving market mechanism, the industrial chain has become more mature, and the smart transportation market has shown a stable growth trend.
Autonomous driving commercialization marathon, cost and technology are two major hurdles
"After people have computers and mobile phones, intelligent cars will become the third end point," Zhang Dezhao told reporters. Intelligent cars bring huge social value and have broad commercial prospects.
Zhang Dezhao further said that the intelligent driving track is a marathon track, and it is not the most important who runs the fastest, but who has the most technical reserves and can persevere until the end.
However, it will not be easy to win this marathon, as the commercialization of autonomous taxis is still being explored today.
Wu Gansha calculated an account for the reporter: if the hardware of the vehicle can be reduced to less than $10,000, the operating cost is about $5,000 per year, and the profit of the vehicle can reach 20 cents per mile, then the profit of each vehicle can be 30,000 dollars per year 150,000 miles, which is a good prospect for sustainable development of driverless taxis.
Wu Gansha founded Uisi Technology in 2016, an autonomous driving solution provider that has deployed passenger vehicles, unmanned public transportation, unmanned logistics, and smart city services, and implemented autonomous driving technology in industrial parks and other fields.
But in Wu Gansha’s opinion, what he just described is only a profitable ideal model, and the reality is still far from the above model.
Looking back on the development of new energy vehicles over the past ten years, Wu Gansha still remembers that high-resolution lidar used to cost 800,000 yuan, but now it is less than 100,000 yuan, while the cost of relatively low-resolution lidar can reach several thousand yuan. The development of the industrial chain has brought more business possibilities for enterprises, but there is still a long way to go in the future.
"The implementation of autonomous driving is a gradual process," Zhang Dezhao said. Now many autonomous driving companies have to do a lot of technical investment and research and development, and it is difficult to achieve profitability so far, and they need to consider business risks.
In addition to cost, technology is also a major challenge.
In the keynote speech of the forum, Zhang Xiaoyu, vice president of Changan Automobile, said that smart electric vehicles will become the birthplace of the next trillion-yuan market value enterprises.
From the demand point of view, the continuous advancement of users request to transform the car from a mobile machine to a model robot, which will enable the car to have a powerful sensing system, energy system and drive execution system, as well as a computing platform. Cars have eyes, ears, hearts, hands and feet, bringing similar cameras, lidar, millimeter wave radar, power battery and other industrial aggregates.
"It can be said that the core team that masters the vertical technology supply chain capability in the next ten years will have the opportunity to overtake," Zhang Xiaoyu said.
In Wu Gansha’s opinion, there are currently two main paths to the commercialization of autonomous driving. One is the gradual development of L2 autonomous driving technology based on passenger cars. In the case of a driver, L2-assisted driving technology has been given a certain fault tolerance rate and can be widely promoted.
The other is the L4 autonomous driving technology for commercial vehicles and special vehicles. In limited paths and scenarios, the road does not have too much information to process, and the speed requirements are not high, allowing for commercial operation.
In fact, these two routes also complement each other. L2-assisted driving in passenger vehicles requires continuous improvement of technology, and the operational experience accumulated in commercial vehicle L4 autonomous driving can provide reference.
Referring to the autonomous driving timetable, Wu Gansha recalled that when the company started its business in 2016, the whole industry was envisioning the implementation of L4-level autonomous driving in 2021, but this idea was too radical, and in fact it has not been fully realized now. According to his judgment, 2030 is the year when large-scale autonomous driving commercialization can be seen on public roads.
However, in recent years, our country’s autonomous driving support policies have been frequent. Recently, Chongqing and Wuhan have issued intelligent driving road test management measures, and Beijing has also disclosed that the autonomous driving demonstration zone will promote the construction of the 3.0 stage within the year, and the construction area will be expanded to 500 square kilometers in the city. The trillion-dollar blue ocean of autonomous driving is coming.
Beijing News Shell Financial Reporter, Lin Zi, Editor, Wang Jinyu, Proofreader, Liu Jun
