Global Automotive Cloud Service Platform Industry Report, 2023 – Autonomous Driving 2.0: AWS and Alibaba Cloud Lead the Way with Data Lake Cloud Native Architecture

DUBLIN, Dec. 20, 2023 /PRNewswire/ — The “Automotive Cloud Service Platform Industry Report, 2023” report has been added to ResearchAndMarkets.com’s offering.

As dedicated automotive cloud platforms are launched, the market enters a phase of differentiated competition. In the evolving landscape of automotive technology, the migration of automakers to cloud platforms holds paramount significance, serving as the foundation for their digital transformation. This shift underscores the integral role cloud services play in the digitization of the automotive industry. As cloud adoption gains momentum, the demand for cloud services exhibits notable trends, with China showcasing a distinctive development path for these services.

Cloud capabilities required by Original Equipment Manufacturers (OEMs) become a focal point, driving changes in demand for cloud services. Automotive cloud applications and business models emerge as critical components, with OEMs leveraging cloud platforms for innovative applications and shaping new business paradigms. Simultaneously, cloud computing architecture undergoes a transformative shift towards software and hardware integration, particularly in the realm of Electric/Electronic (E/E) architecture for vehicle cloud computing.

The convergence of Data Lake and Cloud Native technologies emerges as a hotspot for exploration by cloud platform companies. This synergy builds a novel storage and computing system, with Data Lake Cloud Native architecture gaining prominence. Real-world applications of autonomous driving data lakes, such as those by AWS and Alibaba Cloud, exemplify the industry’s commitment to leveraging cloud-native solutions for enhanced functionality and security.

Beyond these core trends, the industry is witnessing a shift from single cloud adoption to a multi-cloud approach, emphasizing versatility and resilience. The expansion of distributed edge cloud applications amplifies the role of telematics cloud control platforms, signifying a broader integration of cloud intelligence into automotive systems. In this dynamic landscape, cloud-native security undergoes evolution, ensuring robust protection for the burgeoning ecosystem of connected vehicles.

The exponentially increasing amount of vehicle data makes cloud migration an inevitable choice

From the perspective of companies, the goals of digital transformation are to digitize all elements of the whole process throughout the full life cycle of vehicles, including R&D, production, sale, operation, and after-sales service; upload the data in the local servers and computer rooms of automakers to the cloud; connect the data channels of each link to gradually realize the integrated management of data in the whole industry chain, and the cloud-pipe-terminal integrated real-time interconnection; and build service operation models that span the full life cycle of users to enhance the connections between upstream and downstream partners in the industry and create greater value.

In terms of products, vehicle intelligence and connectivity are booming. For example, starting from L2, every time the autonomous driving functions evolve to a higher level, the consumption of cloud infrastructure platforms, applications, and services will rise by an order of magnitude. As high-level autonomous driving comes into mass production, the number of vehicle sensors and the amount of data multiply, making it difficult for local processing to meet the requirements. Cloud migration thus will be the best choice.

Automakers spend tens of millions of yuan every year building cloud services, which gives a big boost to the market. In 2022, China’s automotive cloud service market was valued at over RMB15 billion, and it is expected to sustain the growth rate of 30-40% in the next five years.

As dedicated automotive cloud platforms are launched, differentiated competition becomes crucial

In 2021, ByteDance announced the ‘ByteDance Auto Cloud’, which will provide cloud services in four segments: Digital Marketing, Intelligent Cockpit, Autonomous Driving, and Vehicle Services. In 2022, Tencent Intelligent Cloud Cloud, Baidu Auto Cloud, and Alibaba Auto Cloud became available. All the five giants (BATHD), i.e., Baidu, Alibaba, Tencent, Huawei and Douyin have stepped in the market, and the competition in automotive cloud services built on exclusive automotive cloud has become fiercer.

The service scope of each automotive cloud is much of a muchness, generally covering R&D, manufacture, marketing, and supply chain. The support for R&D is concentrated in the fields of autonomous driving, intelligent cockpit, telematics, and “three electrics” (battery, motor and ECU). How to gain differentiated competitive edges in the competition therefore has become the key to success for companies.

The differentiated competitive edges in cloud services are mainly built from two aspects: basic resource layer services and upper-layer R&D tool chains

In terms of basic resource layer, supercomputing centers are an important indicator for assessing service capabilities, and Alibaba and Baidu are the first to deploy.

In August 2022, Alibaba Cloud launched the two intelligent supercomputing centers located in Zhangbei County and Ulanqab, with total compute of 15 EFLOPS (15 exascale floating-point operations per second). At the same time, Alibaba Cloud also introduced the ‘Apsara Intelligent Computing Platform’, an intelligent computing solution which opens up intelligent computing capabilities by way of ‘platform + intelligent computing center’.

Following the five intelligent computing centers in Yangquan, Jinan, Fuzhou, Yancheng, and Tianjin, Baidu Cloud started construction of the Baidu AI Cloud-Shenyang Intelligent Computing Center in May 2023, a project with a land area of about 2.4 hectares, floor areas of 42,000 square meters, and the total planned computing power of 500P, 200P for Phase I. In the future, Baidu Shenyang Intelligent Computing Center will not only involve physical data center construction capabilities and intelligent computing infrastructure capabilities, but also comprehensive solutions for AI software and hardware ecosystem capabilities such as foundation models, supporting the computing tasks of companies in different business scenarios and meeting the industrial application requirements of foundation models in the era of intelligent computing.

With regard to R&D tool chains, cloud service providers are committed to creating ‘fully furnished’ service experiences for users by offering ‘full-process’ and ‘fully closed-loop’ services.

In Tencent’s autonomous driving cloud platform, virtual simulation has become a key link

Huawei’s autonomous driving cloud platform ‘Octopus’ has built in a dataset with 20 million frame annotations, a library with 200,000 simulation scenes, a complete tool chain, and annotation algorithms, covering the full life cycle businesses such as autonomous driving data, models, training, simulation, and annotation, and helping automakers to build autonomous driving development capabilities on a ‘zero’ basis.

Baidu makes a full-stack layout and enables a data closed loop by virtue of from chip (Kunlunxin), deep learning (PaddlePaddle) and training foundation model (ERNIE) to search (Baidu Search), cloud platform (Baidu AI Cloud), autonomous driving (Apollo) and intelligent connection (Xiaodu).

Under the multi-cloud strategy, the need of OEMs has changed from the pursuit of resources to efficiency

With the in-depth migration to the cloud, the resource needs of OEMs for cloud migration have been overall met, and thus the underlying logic of the cloud strategy of companies has changed from the pursuit of resources to efficiency to finally improve their overall digitization capabilities in production and operation. In this process, OEMs are no longer tightly bound with some cloud platform, but implement a multi-cloud strategy where different business types are put on different cloud platforms. Examples include:

• Based on the ‘1+6+N’ Geely Hybrid Cloud Platform co-built with Baidu, Geely works with Alibaba to build the Xingrui Intelligent Computing Center, and teams up with Tencent on telematics and security solutions.
• FAW Group uses Huawei Cloud Stack to build hybrid cloud architecture, and also cooperates with Alibaba Cloud on intelligent manufacturing, digital marketing and other businesses.

Without a doubt, the multi-cloud strategy offers benefits. It can integrate the advantages of various cloud platforms, enable refined business deployment, and reduce costs for companies, and also helps automakers to gain the core initiative in building cloud platforms and avoid being puzzled by the “soul” dispute. Yet the challenges of the multi-cloud strategy are also unavoidable. How to allocate storage/computing power among multiple clouds, cross-cloud data synchronization’s dependency on bandwidth, and whether costs and network delays will have an impact are all urgent problems to be solved. Hence how to formulate a multi-cloud strategy is a problem for OEMs.

Key Topics Covered

1 Overview of Automotive Cloud Service
1.1 Overview of Automotive Cloud Service Industry
1.2 Main Types of Automotive Cloud Services
1.3 Competitive Landscape of Automotive Cloud Services
1.4 Automotive Cloud Business Models in China
1.5 Development Opportunities for Automotive Cloud
1.6 Application Scenarios of Automotive Cloud

2 Automotive Cloud Solutions
2.1 Autonomous Driving Cloud
2.2 Telematics Cloud
2.3 V2X Cloud
2.4 Digital Transformation
2.5 Cloud Data Closed Loop
2.6 Cloud Information Security

3 Cloud Platform Infrastructure
3.1 Automotive Cloud Industry Chain
3.2 Data Centers
3.3 Cloud Servers
3.4 Server Chips
3.5 Progress of Cloud Providers in Self-development of Chips

4 Automotive Public Cloud Platforms
4.1 Amazon Cloud – AWS
4.2 Microsoft Cloud – Azure
4.3 Google Cloud
4.4 Huawei Auto Cloud
4.5 Baidu Auto Cloud
4.6 Alibaba Auto Cloud
4.7 Tencent Auto Cloud
4.8 ByteDance Auto Cloud

5 Cloud Platform Layout of OEMs
5.1 Geely
5.2 Xpeng
5.3 Li Auto
5.4 NIO
5.5 FAW
5.6 Changan
5.7 Great Wall Motor
5.8 SAIC

6 Summary and Trends
6.1 Significance of Automakers’ Migration to Cloud
6.2 Cloud Service Demand Trends
6.3 Automotive Cloud Application and Business Model
6.4 Cloud Computing Architecture Trends
6.5 Data Lake and Cloud Native
6.6 Other Trends

Companies Mentioned

• Amazon Cloud – AWS
• Microsoft Cloud – Azure
• Google Cloud
• Huawei Auto Cloud
• Baidu Auto Cloud
• Alibaba Auto Cloud
• Tencent Auto Cloud
• ByteDance Auto Cloud
• Geely
• Xpeng
• Li Auto
• NIO
• FAW
• Changan
• Great Wall Motor
• SAIC

For more information about this report visit https://www.researchandmarkets.com/r/dvtuh6

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