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Competition between bicycle intelligence and vehicle road coordination From Automatic driving under the new infrastructure

The following is the Competition between bicycle intelligence and vehicle road coordination From Automatic driving under the new infrastructure recommended by recordtrend.com. And this article belongs to the classification: Deloitte Consulting , Smart car, research report.

Since 2020, “new infrastructure”, namely new infrastructure construction, has become a new focus of the public. Among the subdivisions involved in the new infrastructure, 5g, Internet of things, artificial intelligence and intelligent transportation infrastructure are closely related to the automatic driving technology. The new infrastructure will also create an unprecedented strategic window for the development of automatic driving technology in China, and further accelerate the commercialization of automatic driving.

In the future, with the maturity of driverless technology and the deepening of commercialization, the car will no longer be a driving tool subordinate to human beings, but will become a transportation robot with autonomous navigation, which will promote the arrival of the era of truly shared cars. Based on this industry trend, Deloitte automotive industry team released the white paper of intelligent network connection, automatic driving under the new infrastructure: the fight between single car intelligence and vehicle road coordination.

1. Networking is the only way for automatic driving

In March 2020, the Ministry of industry and Commerce issued China’s “auto driving automation classification” recommendation of national standards for approval, and solicited opinions from all sectors of the society, marking that China has its own classification standards for automatic driving.

Intellectualization usually refers to the intellectualization of a single vehicle. At the perception level, multi-sensor fusion is used to collect data from the surrounding environment through radar system and vision system. At the decision-making level, the data is processed through on-board computing platform and appropriate algorithm, and the optimal decision is made. Finally, the execution module converts the decision signal into vehicle behavior.

Networking means vehicle networking and real-time information interaction, through V2V (vehicle to vehicle communication), V2I (vehicle to infrastructure), v2n (vehicle to Internet Communication) and V2P (vehicle to pedestrian communication) to obtain the status and intention of traffic participants beyond visual range or non visual range.

2. Two directions of automatic driving: single car intelligence and vehicle road cooperation

Due to the high cost of single car intelligence, if roadside equipment is used to replace some technologies and make the road “smarter”, many vehicle costs can be reduced. In this way, two directions of automatic driving are derived: single car intelligence and vehicle road cooperation, whose essence is the distribution of technology and cost on vehicle side and roadside.

The premise of vehicle road coordination is the intelligent transformation of highway and infrastructure investment. The distribution and development of vehicle side intelligence and road side intelligence are affected by many factors, such as the government’s support for highway intelligent transformation, road conditions in different regions and so on. These factors jointly determine the level of initial investment, the length of investment return period, and the economy of investment of different schemes, thus affecting the allocation scheme and evolution route of technology and cost on vehicle side and road side.

The evolution of three technical routes

Starting from the allocation of technology and cost on vehicle side and road side, the future development of automatic driving evolves into three technical routes, namely, the “Google style” intelligent bicycle route represented by lidar and high-precision map, the “Tesla style” intelligent bicycle route represented by visual perception and shadow mode, and the vehicle road collaborative route that takes the lead in networking.

The single car intelligent “Google pie” takes lidar as the main sensing device, and adopts the scheme of multi-sensor fusion such as lidar, millimeter wave radar and camera.

The “Tesla school” of bicycle intelligence takes visual recognition as the core. This technical route considers that vision is the most effective method to obtain information. It chooses a cheaper and easier computer vision scheme for mass production vehicles, and uses neural network model training algorithm.

The development path of vehicle road collaboration is expected to take the lead in achieving a breakthrough in the dimension of network connectivity, which puts forward higher requirements for the collaboration of vehicle end, road end and cloud end. The communication platform provides real-time information pipelines for vehicle vehicle, vehicle road and vehicle cloud transmission, so as to realize network connectivity and automatic driving of vehicles.

3. Path choice of different countries

For the choice of the development path of automatic driving, the United States, China, Japan, Germany and other countries from their own national conditions, based on the development situation and core competence of related industries, integrate their respective strategic advantages, will choose their own development path.

For the United States, the field of artificial intelligence is leading in the world, with sufficient talent reserves and strong basic scientific research strength. The number of artificial intelligence enterprises in the United States ranks the first in the world, covering the basic layer, technical layer and application layer. It has a deep technical accumulation in the field of artificial intelligence algorithm in the field of automatic driving, and maintains a certain advantage.

For China, there are many 4G and 5g base stations with wide coverage. At the same time, the Chinese government vigorously promotes the construction of new infrastructure such as 5g network and Internet of things, resolutely implements 5g lte-v2x technical standards in road reconstruction, and supports the smooth evolution of lte-v2x to 5g-v2x. In the future, China is expected to achieve “corner overtaking” in the field of automatic driving through vehicle road cooperation.

4. Change of value distribution pattern of automobile industry chain

In the future, the core parts of the automobile industry will shift from the transmission system reflecting power and driving experience to the intelligent software system (artificial intelligence algorithm) and processor chip reflecting the level of automatic driving technology. With the development of automatic driving technology, the profits of non core parts and vehicle manufacturing will be further compressed, while the profits of design and R & D of automatic driving, travel service and operation service closer to users will be higher.

In addition, a lot of start-up companies have sprung up in the self driving track, focusing on L4 / L5 level self driving solutions around specific scene layout. For travel companies, the arrival of automatic driving means that the traffic barrier and platform mode of head travel companies may be subverted. For the parts suppliers, the long-term and stable cooperation between the traditional parts suppliers and the main engine plants determines that they naturally form an alliance with the main engine plants in the automatic driving campaign.

In the long run, once the Internet technology giant’s autopilot program matures, artificial intelligence algorithms, cloud computing, data, core components and other aspects form technical and scale barriers, which can quickly dilute the cost of software and hardware through scale effect, it is possible to rewrite the rules of the game in the field of autopilot and squeeze the profit space of other companies.

Future value distribution pattern of China’s automobile industry chain

The technical routes of automatic driving in China and the United States are different, with vehicle road coordination as the main mode. The technology giants with abundant funds can establish their own core business ecology through simulation platform products, access different brands of vehicles, and establish core technology standards of software and hardware, so as to grasp the initiative of future research and development and landing of automatic driving.

Communication operators are also one of the important players to promote the overall solution of vehicle road coordination. As the transmission and scheduling channel of road information, they combine cloud computing and AI as the technical support of scheduling platform and participate in the construction of automatic driving vehicle road coordination scheduling system. In addition, the government, vehicle manufacturers and financial institutions need to participate in the investment and construction to jointly promote the implementation of vehicle road coordination.

For China’s parts suppliers, the competition of core parts is more fierce. In addition, vehicle road collaboration also brings opportunities for incremental parts and services.

5. Enlightenment to the main engine factory

Deloitte believes that for the main engine plant, the field of automatic driving should not only make a good global deployment, but also take full account of the differences in the national conditions and development paths of different countries. In other words, in addition to a unified global plan, it should also adapt to local conditions. Specifically, it can be considered from the following three directions.

Foreign car companies should consider “walking on two legs”, global solutions follow the intelligent route of bicycles, and at the same time, local car road coordination solutions should be deployed in China

With the leading 5g level, extensive layout of communication base stations, policy support of “new infrastructure” and broad domestic market, China has embarked on a road vehicle coordination route with Chinese characteristics. Therefore, for the world’s leading engine plants, the global deployment of automatic driving should fully consider the uniqueness of China’s development path, even “walking on two legs”. For foreign-funded car companies, the time to formulate and implement localization programs in China is increasingly urgent, and China’s local brand car manufacturers can seize this window period to develop their own autonomous driving and vehicle road coordination strategies.

Pay close attention to China’s market trends, follow the government’s guidance, and make full use of the new opportunities brought by “new infrastructure”

Deloitte believes that auto companies should closely follow the guidance of the government, actively communicate with the government, and make use of relevant policies and regulations to help the government complete the layout of “new infrastructure” information and integration infrastructure. The local governments have also launched the automatic driving demonstration zone one after another to carry out the test and application of vehicle road cooperation from three aspects of vehicle end, road end and cloud end, so as to accelerate the implementation of automatic driving technology. The main engine plant should seize the opportunity of the times, obtain high-level road test license as soon as possible, accumulate test mileage and lay out for the future.

Grasp the landing and breakthrough period of automatic driving segmentation scenarios in the next 3-5 years, and formulate appropriate business models

2020 is the eve of the commercialization of automatic driving, which will usher in the continuous breakthrough of subdivision application scenarios. In the next 3-5 years, automatic driving solution providers will select 1-2 application scenarios to make breakthroughs and explore possible landing paths and business models. Deloitte believes that the main engine manufacturers should pay full attention to the commercialization process of each segmentation scene of automatic driving, formulate their own business model, and grasp the initiative in the competition.

In the next 3-5 years, there will be a breakthrough in the solution of automatic driving based on application scenarios. Players participating in autopilot need to pay close attention to the landing progress of the scene, make technological breakthroughs according to their own advantages, formulate appropriate business models, and launch differentiated services.

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