Five questions about the commercialization of autonomous driving heavy trucks: is the turning point coming?

Source | Yunlian Think Tank (ID: tucmedia), author | Jia Yichao, Editor | Small L

2022 has just begun, and the rapid rise in crude oil prices will push logistics companies into the vortex of cost pressure. Under this momentum, some analysts believe that after a new round of price adjustment on March 17 a week later, domestic oil prices may meet the ceiling price.

It should be known that in the cost structure of the logistics fleet "33211", fuel consumption accounts for 30% of the cost of logistics enterprises. The high level of oil prices will undoubtedly amplify the pain points of fleet companies.

Not only fuel consumption, drivers, maintenance and other costs continue to rise, superimposed on the current logistics industry price war under the internal volume, logistics companies need to carry out structural changes in order to achieve cost reduction and efficiency.

Technology, on the other hand, is seen as a "potential stock" that effectively improves this situation.

Since the beginning of this year, players such as Hongjing Intelligent Driving, Mainline Technology, and Yingche Technology in the field of automatic driving have received hundreds of millions of yuan of financing. In the case of the overall weak capital environment, does this segment get a large amount of investment from the capital, which means that the turning point in the commercial application of autonomous driving technology has come?

(Financing inventory in the field of autonomous commercial vehicles since 2022)

Scene side: head competition, trunk line power?

According to the complexity of the logistics scenario, in general, the application scenarios of automatic driving can be divided into three categories: closed low-speed hubs, semi-closed high-speed trunk lines, and full-speed open roads. At present, there are two types of scenarios in which automatic driving can be smoothly laid out, one is to close mines and docks in low-speed scenarios, and the other is the highway trunk line.

The core of autonomous driving companies lies in solving the pain points of cost reduction and efficiency increase in logistics scenarios; therefore, the core point of these technology companies' large-scale commercial landing lies in how many logistics scenarios they can run.

At present, different subdivision scenarios have relatively mature players. Of course, there are also enterprises that infiltrate around the complexity ladder of the scene, such as mainline technology. From 2017 to 2019, mainline technology did closed low-speed scenes, and after 2020, it did semi-open high-speed scenes.

According to Zhang Tianlei, CEO of Mainline Technology, "In the closed low-speed scenario, Mainline Technology is the first company to operate unmanned security officers. At present, the company's fleet size is close to 200 units, which belongs to the head force nationwide. ”

After achieving the technological breakthrough of "safety officer" in Tianjin Port in 2020, mainline technology has begun to replicate on a large scale in Ningbo Zhoushan Port and the intelligent container terminal in Section C of Tianjin Port North Xinjiang Port Area. Its operating efficiency is as high as 33 natural boxes/hour, the energy consumption of the box is reduced by 20%, and the comprehensive operating cost is reduced by 10%.

(Photo: Mainline Technology Port Unmanned)

However, according to Zhang Tianlei's analysis, the closed low-speed scene may be a market scale of tens of billions, and in the entire 6 trillion-yuan market-scale road freight market, the large-scale application of high-speed trunk line scenarios has a broader imagination.

In this trillion-dollar market, it is generally believed that the high-speed trunk line scenario is a subdivision scenario that can land autonomous driving technology earlier and generate value. Therefore, in addition to the early focus on high-speed trunk line scenes of Zhijia Technology, Yingche Technology, in recent years, the power from passenger car automatic driving is also slowly penetrating into this market, such as Baidu, Hongjing Intelligent Driving and so on.

However, industry insiders believe that commercial vehicles have a series of specification requirements such as control and perception, and the cross-border of passenger car players will be difficult, especially in the current commercial vehicle autonomous driving players such as Wincher Technology, Zhijia Technology, Mainline Technology, etc. have entered the stage of commercial mass production, and new players want to catch up and cross the threshold of technology, operation and circle of friends.

Mass production side: Has the goal of "the first year of mass production" been achieved?

As we all know, the head players of commercial vehicle autonomous driving basically regard 2021 as the first year of large-scale mass production. So the past year has also been one in which everyone is keeping up with the timetable. So now, have everyone's goals been achieved?

Relatively speaking, the application of mainline technology in closed low-speed scenarios is relatively mature, and the landing of its mass-produced products is first delivered in batches at the hub. Zhang Tianlei revealed that the joint research and development of electric trucks and electric flatbed trucks by Mainline Technology, Heavy Duty Truck and XCMG Machinery has been delivered in batches in multiple hubs; in the high-speed trunk line scene, its cooperation model with Jiefang will be delivered in large quantities at the end of this year, and the model already has the function of L4.

The relevant person in charge of Yincher Technology said that at the end of 2021, Yincher Technology has taken the lead in realizing the front-loading mass production of L3-level smart trucks in conjunction with its OEMs partners, and can be upgraded to L4 through OTA in the future. Wincher Technology will further increase investment in its truck automatic driving system "Xuanyuan" and jointly launch more mass production models with industry partners.

(Photo: Yingche Technology self-driving truck)

Zhijia Technology's self-developed PlusDrive autonomous driving system based on L4 level has now achieved mass production and delivered in China and the United States. Among them, zhijia technology and zhitu technology, to help FAW Jiefang to build a mass production of self-driving J7 super truck, has completed offline delivery in 2021.

According to Rong Li, general manager of Zhijia Technology China and senior vice president of group engineering, Zhijia has begun to deliver 1,000 orders for 1,000 autonomous driving heavy trucks equipped with the PlusDrive system for Amazon; in addition, Zhijia has also received 8,000 reservation orders from other Sino-US logistics companies and began to deliver.

On the whole, the process of large-scale mass production of automatic driving relies only on technology to "slap a slap". In the past few years, we can clearly see that autonomous driving players have introduced ecological partners to supplement the resources of the industrial chain. Some of these industrial partners have even begun to enter the ranks of shareholders of autonomous driving companies, and gradually explored a set of "technology + scene + main engine factory" "iron triangle" play.

In the process of achieving the mass production goal, everyone is building their own industrial chain.

Profitability of scale: Is autonomous driving a net?

In the commercialization of autonomous driving head enterprises, we are increasingly seeing the addition of network enterprises, such as Amazon, Debon, Yimi Tick, Rongqing Logistics and so on. It can be seen that the transformation of automatic driving to the logistics industry is by no means a point-like breakthrough, and this ability to reduce costs and increase efficiency should be mesh-like.

As a technology company that has grown out of the logistics soil, Yingche Technology may be more representative in this regard. Since its inception, it has adhered to the "technology + operation" business model, promoted technology research and development and commercial operations, and launched commercial operations in early 2019 to build a smart truck capacity network.

According to the relevant person in charge, Yinche Technology pioneered the standardized intercity intelligent driving truck capacity service of "pay-per-kilometer" for logistics customers, and built an intelligent, standardized and economy-of-scale autonomous truck network. At present, Yinche Technology has formed a nationwide, based on commercial contracts, pay-per-kilometer capacity network, and with many of the industry's leading logistics customers and cargo owners to carry out business cooperation, the business scope radiates China's five core economic circles (East China, South China, Central China, North China, Northeast China).

At the same time, Rongli also believes that the large-scale deployment of driverless technology is the ultimate goal of Zhijia, relying on the big data brought by mass production operations to drive software and hardware iteration. At present, the test scope of Zhijia Technology has covered 30 of China's 34 provincial-level administrative regions and all 48 mainland states in the United States, with an overall coverage rate of 95%.

In the process of landing the front-loading mass production truck, Zhijia has also been connected to the network, jointly with Xinzhihong, Rongqing Logistics, CR Vanguard and other partners to carry out commercial operations, and completed the development of operation lines from East China to Central China, North China and South China, covering the most prosperous areas in China such as the Yangtze River Delta, pearl river delta, Beijing-Tianjin-Hebei and the middle reaches of the Yangtze River Economic Circle.

(Photo: Zhijia Technology self-driving truck)

If commercial vehicle autonomous driving companies want to achieve large-scale profitability, they must find opportunities in this network. It is also based on this logic that it is generally believed that the automatic driving of commercial vehicles is not only a chain, but also a network.

So, how much room is there for this opportunity? According to the experience of mainline technology in the closed scene to achieve large-scale landing, Zhang Tianlei believes: "From the product point of view, we are an integrated automatic driving logistics solution with end (vehicle) side (vehicle-road collaboration) cloud (operation cloud). In this process, the autonomous driving company can provide a cloud that can support you to do operations and data analysis, can provide an intelligent car, and can also provide a series of vehicle-road coordination solutions such as field stations and intelligent transformation. ”

Return on assets: How to digest the return on investment cycle of logistics companies?

From an asset perspective, autonomous commercial vehicles, whether hardware or software, mean that the cost of vehicle acquisition is rising. How can this cost be digested for cost-sensitive logistics companies? How fast is the digestion cycle?

According to the communication between the main line technology and the closed hub and high-speed trunk line customers, the network starting cycle of port customers is about 3 years, and it can eventually be used for more than 5 years; trunk line companies hope to return the cost in about 2 years and can be used for more than 4 years.

That is to say, how to play the same abacus with users from the perspective of logistics companies when autonomous commercial vehicles face users has become extremely important. And this imagination space comes from three aspects:

First, the price of hardware after large-scale mass production is reduced. With the maturity of mass production scale and technology, hardware costs have declined.

Second, assisted driving, double driving becomes single driving. As a larger component of the operating cost structure of the fleet, labor cost is a major breakthrough. This can not only effectively solve the problem of high loss of truck drivers in the logistics industry and the low willingness of the younger generation to work, but also bring about greater optimization of the cost structure.

Third, technology optimization to reduce accident rate and fuel consumption. Rongli believes that the profitability of autonomous commercial vehicles has obvious and sustainable phased profit characteristics. At this stage, it is the supervised operation stage of autonomous driving heavy trucks, which will generate profits by reducing the safety accident rate, improving logistics efficiency and fuel efficiency.

At present, the automatic driving system of the head enterprise can basically achieve 6-10% savings in fuel consumption and greatly reduce the driver's driving fatigue.

In addition, in the final game of the freight robot network described by Yinche Technology, in terms of car use, logistics companies have a variety of flexible ways to choose, and can use social resources to do business at a lower cost, such as the pay-per-kilometer model; when a sufficiently large-scale autonomous driving freight network is formed, the waste of resources such as return empty driving will be further reduced, and the overall operational efficiency of the industry will also be improved.

According to data, according to estimates, the large-scale application of automatic driving will bring about an overall cost saving of 30% for logistics enterprises; at the same time, it will also bring huge economic and social value such as cost reduction and efficiency increase, improve driver work comfort, and enhance road safety to the industry.

Energy Substitution: Is New Energy the Future of Autonomous Driving?

In the context of the entire "double carbon", energy substitution is the trend. In particular, the logistics industry, as a basic, strategic and leading industry for the development of the national economy, also bears a large proportion of carbon reduction indicators. At the same time, the current continuous high price fluctuation of oil prices has also catalyzed the demand of logistics companies to adjust the proportion of energy use.

The first is in the system design stage, each autonomous driving system is a vehicle that can adapt to different power systems, including electric trucks. However, at present, there are clean energy sources with diversified patterns such as electricity, natural gas, and hydrogen energy, and traditional car companies and new car-making forces are still in the exploratory stage.

In fact, based on the consideration of the operating cost structure of the logistics fleet, Wincher Technology began to launch natural gas heavy trucks very early, but due to seasonal fluctuations in natural gas supply and demand, the layout of the basic network of gas filling stations and other factors, the business development in recent years has regional and seasonal characteristics. It said that in the future, it will accelerate the layout in the field of electrification.

Zhijia Technology has also signed a memorandum of understanding with Iveco to cooperate in the development and deployment of autonomous driving heavy trucks, including natural gas models, for Europe, China and other markets. In addition, Zhijia Technology has also cooperated with Cummins, the world's leading engine manufacturer, to jointly develop the world's first supervised autonomous gas heavy truck.

Mainline Technology is the first enterprise to do electric unmanned attempts, and it currently has more than 100 applications in closed scenes. In Zhang Tianlei's view, the main line technology is more inclined to electric trucks, because the current basic network of gas stations and hydrogen stations is not perfect; at the same time, automatic refueling and hydrogenation have certain operational difficulties, and in the future, to truly achieve unmanned operation, electric vehicles are still more ideal.

Overall, after mass production, autonomous driving companies have new multiple choices for industries, customers, and trends. To what extent can technology change the operating model of the industry, and what do you think? Welcome to leave a message at the end of the article to share your views, or scan the QR code below to communicate with me!