Global and China Software-Defined Vehicle Industry Report 2022: 40 Arenas, Hundreds of Suppliers, and Rapidly-Improved Software Autonomy - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "Global and China Software-Defined Vehicle Research Report 2022- Architecture Trends and Industry Panorama" report has been added to ResearchAndMarkets.com's offering.

Software-defined vehicle research: 40 arenas, hundreds of suppliers, and rapidly-improved software autonomy.

The overall architecture of software-defined vehicles can be divided into four layers:

(1) The hardware platform, heterogeneous distributed hardware architecture

(2) The system software layer, including hypervisor, system kernels, POSIX, AUTOSAR, etc.

(3) The application middleware and development framework, including functional software, SOA, etc.

(4) The application software layer, including smart cockpit HMI, ADAS/AD algorithms, connectivity algorithms, cloud platforms, etc.

In a broad sense, an operating system refers to the middleware based on kernel OS, including system software layer (kernel, hypervisor, middleware), functional software layer (common functional modules and related middleware) and APIs. In a narrow sense, an operating system mainly means the vehicle control OS and automotive OS at the bottom of the system kernel.

The operating system in the narrow sense is the cornerstone of building intelligent connected vehicles, while the operating system in the broad sense is the bridge for application development.

Microkernel, only to achieve basic task management, memory management, process communication, etc., and other drivers are defined in the user side to achieve, the current commonly used intelligent driving operating systems are mainly Linux, QNX and Other RTOS (such as free RTOS, VxWorks, etc.). The open-source microkernel seL4 based on the third-generation microkernel technology has attracted more and more attention from domestic automakers and technology companies. Li Auto, NIO, Lotus Cars, Horizon Robotics, Xiaomi and other technology companies have joined the seL4 Foundation to promote the development of seL4 microkernel.

The development of smart cars still faces the dilemma - 'lack of chips' and 'absence of automotive operating systems'. The former has received enough attention, while the latter still needs to be broken through. At present, foreign vendors QNX (Blackberry), Linux (open source), and Android (Google) are the core players of the narrowly defined automotive operating systems.

For example, in terms of smart cockpit systems, the combination of QNX+Android is the mainstream solution chosen by domestic vendors. China-based Huawei HarmonyOS and Powered by AliOS have made certain breakthroughs, but their self-sufficiency rates are still low. In the field of intelligent driving systems, QNX occupies an absolute monopoly position.

Under the background of autonomous controllability, real-time automotive operating systems signalize an important development direction for filling the gap in automotive operating systems. Many domestic technology companies, including Huawei, ZTE, Baidu Apollo and Banma SmartDrive, are seeking breakthroughs in the field of real-time microkernel operating systems.

In a broad sense, an operating system is a bridge for developers to facilitate the development of application algorithms, and it is a development platform including an operating system in the narrow sense, and middleware, etc.

Key Topics Covered:

1 Vehicle Basic Software

1.1 Automotive Operating System in Narrow Sense

1.2 Autonomous Driving OS in Broad Sense

1.3 Intelligent Cockpit General Operating System (OS)

1.4 Vehicle-cloud Integrated General Operating System (SOA Platform)

1.5 Communication Middleware (DDS, SOME/IP, MQTT)

1.6 Automotive Middleware (AUTOSAR, ROS2, CyberRT)

1.7 Hypervisor

2 Vehicle Tool Software

2.1 Automotive Electronics Software Development Tool Chain

2.2 AI Deep Learning Software

2.3 Data Training Dataset

2.4 Data Collection & Annotation Tool Software

2.5 Data Closed Loop Tools

2.6 Data Desensitization Software SDK

2.7 Simulation & Testing Software

2.8 Autonomous Driving Typical Scenario Library

2.9 Chip Development Tool Chain

2.10 ADAS Performance Evaluation Software

2.11 ADAS Data Logging Software

2.12 Automotive Software Test System Software

3 Application and Algorithm Software - Autonomous Driving

3.1 Development Trends of Autonomous Driving Algorithms

3.2 Passenger Car Autonomous Driving Algorithm Software

3.3 Commercial Vehicle Autonomous Driving Algorithm Software

3.4 HD Map

4 Application and Algorithm Software - Vehicle Control

4.1 Automotive Energy Management Software

4.2 Vehicle Body and Vehicle Control Software

4.3 Power and Drive Management Software

5 Application and Algorithm Software - Telematics and Cybersecurity

5.1 Roadside Operating System

5.2 Vehicle-Infrastructure-Cloud Cooperation Service

Companies Mentioned

• Green Hills
• ZTE
• UnTouch Technology
• HoloMatic
• BYD
• Li Auto
• Thundersoft
• Banma Zhixing
• Megatronix
• ECARX
• SAIC Z-ONE
• Geely
• VolvoCars.OS
• Bosch ETAS
• iSoft Infrastructure Software
• Shanghai HingeTech
• ZlingSmart
• ETAS
• dSPACE
• Wind River
• NI
• Haitian Ruisheng
• Xpeng
• Waymo
• Momenta
• Haomo.ai
• Horizon
• Black Sesame Technologies
• SemiDrive
• NVIDIA
• Tesla
• Vector
• Valeo
• Huawei
• AICC
• PIX Moving
• Eatron Technologies
• Tencent
• EXCEEDDATA
• Luxoft

For more information about this report visit https://www.researchandmarkets.com/r/vrgf0w

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