Automotive Software Business Models and Suppliers´ Layout Research Report, 2024
상품코드:1567948
리서치사:ResearchInChina
발행일:2024년 09월
페이지 정보:영문 450 Pages
라이선스 & 가격 (부가세 별도)
한글목차
OEM의 소프트웨어 개발은 '플랫폼화'를 향해 발전하여 원류 비용 절감을 실현
2024년 OEM 조직 구조는 점점 더 자주 조정되고 치열한 경쟁 자동차 시장을 수용하기 위해 전략을 실시간으로 조정해야 합니다. 한 OEM은 기업의 판매 및 기타 현상을 안정화하기 위해 조직 구조를 조정하고, 일부 OEM은 기업의 소프트웨어와 새로운 비즈니스의 초점을 추진하기 위해 조직 구조, 특히 R&D 비즈니스 팀을 조정합니다.
로컬 OEM은 R&D 조직 구조를 변경하고 소프트웨어 개발 전략을 재구성
최근 XPeng Motors는 대규모 조직 구조를 지속적으로 조정하고 동시에 지능적이고 경쟁이 치열한 자동차 시장과 마주하기 위해 비용 절감과 효율성, 예산 감소 등 많은 조치를 제안하고 있습니다. 2024년 7월, XPeng Motors의 자율주행 부문은 새로운 조직 재편을 시작했습니다. Xpeng의 자율주행 부문은 3개의 새로운 부문을 설립했습니다. AI 모델 개발, AI 애플리케이션 개발, AI 효율 개발입니다. AI 모델 개발 부서는 주로 엔드 투 엔드 모델 개발을 담당하고 AI 엔드 투 엔드의 지능형 운전 기술 레이아웃을 강화합니다.
2024년 8월 SAIC은 IM과 Rising 브랜드의 R&D 사업을 SAIC Group Innovation Research and Development Institute(SAIC R&D Institute)에 통합합니다. 이 중 IM 및 Rising 브랜드 R&D 팀, 전원 배터리, 지능형 드라이브, 섀시 등의 기술 프로젝트는 SAIC R&D Institute로 중앙 집중식으로 전환되고 R&D Institute에서 통합 및 조정됩니다. 전 서브브랜드의 연구개발력을 일원화하고 통일적으로 발전시키는 이 모델은 자동차 제조그룹이 일반적으로 채용하고 있는 '대형 연구개발기관' 모델입니다. 이 모델을 통해 제품의 플랫폼과 표준화된 레이아웃을 실시하고, 연구개발비용의 평등한 분담을 실현하고, 원류에서의 비용 절감에 노력하고 있습니다.
다국적 자동차 제조업체가 중국의 로컬 소프트웨어 공급망과의 협력 강화
현재, 다국적 자동차 제조업체의 중국 현지화 전개는 새로운 단계에 들어가 있습니다. 이것은 이전의 "봉제"보조 장식 및 개발과는 다르지만, 근본적으로 시스템을 재구성하고, 적극적으로 전략을 조정하고, 적극적으로 중국 자동차 시장의 새로운 변화를 해결하기 위해 레이아웃. 그것은 다음과 같이 요약할 수 있습니다.
중국 현지 투자·연구개발센터 레이아웃을 늘립니다. 예를 들어 2022년 3월, Mercedes-Benz는 중국에서 R&D 레이아웃을 더욱 확대하기 위해 상하이에 R&D 센터를 설립할 것이라고 발표했습니다. 상하이 R&D 센터는 지능형 상호 연결, 자율주행, 소프트웨어 및 하드웨어 개발, 빅데이터에 중점을 둡니다. 2023년 4월 Volkswagen Group은 약 10억 유로를 투자하여 지능형 커넥티드 전기자동차에 초점을 맞춘 R&D, 혁신 및 조달 센터를 설립할 것이라고 발표했습니다.
· 중국 현지 팀의 권한을 더욱 개방하고 중국 현지 맞춤형 전략을 강화합니다. 현재 Mercedes-Benz, BMW, Volkswagen과 같은 국외 자동차 제조업체들은 중국 현지 팀의 권한을 더욱 개방하기 위해 중국 현지 맞춤형 개발 모델을 제안하고 있습니다.
· 중국의 현지 공급업체와 적극적으로 협력합니다. 예를 들어, Mercedes-Benz는 Momenta, Tencent, AISpeech 등과 깊게 협력하고 Volkswagen은 ThunderSoft, Horizon, XPeng Motors 등과 깊게 협력하고 있습니다.
이 보고서는 중국 자동차 산업에 대한 조사 분석을 통해 자동차 소프트웨어의 비즈니스 모델과 국내외 공급업체의 레이아웃에 대한 정보를 제공합니다.
목차
제1장 자동차 소프트웨어의 비즈니스 모델과 동향 분석
지능형 차량 소프트웨어의 산업 체인 개요
주요 OEM의 소프트웨어 시스템 공급망 구축 및 조직 구조 조정
지능형 차량 소프트웨어 관련 공급업체의 비즈니스 모델 개요
스마트카 소프트웨어 비즈니스 모델 개발 동향
제2장 OEM의 소프트웨어 혁신 전략에 대한 대응 분석
Mercedes-Benz
BYD
BMW
Volkswagen
Ford
SAIC
Great Wall Motor
Geely
Changan Automobile
Xpeng
Li Auto
FAW
Chery
제3장 자동차 운영 체제의 비즈니스 및 레이아웃 모델
자동차 운영체제 비즈니스 모델의 현상과 동향
차량 OS
주요 자동차 운영 체제
주요 자동차 미들웨어의 비즈니스 모델
AUTOSAR
제4장 지능형 조종석의 비즈니스 및 레이아웃 모델
지능형 조종석 소프트웨어 시스템의 비즈니스 모델과 동향
자동차 HMI 디자인
자동차 음성의 비즈니스 모델과 동향
자동차 지도 네비게이션의 비즈니스 모델과 동향
자동차 음향 시스템
AR-HUD 소프트웨어
인콕핏 비전(DMS/OMS)의 비즈니스 모델과 동향
멀티모달 퓨전 인터랙션
AI 기반 모델의 조종석 용도
제5장 자율주행 비즈니스 및 레이아웃 모델
자율주행 시스템 소프트웨어의 비즈니스 모델의 현상과 동향
중고급 ADAS 솔루션의 비즈니스 모델
L3/L4 자율주행 시스템의 비즈니스 모델
제6장 자동차 클라우드 플랫폼의 비즈니스 및 레이아웃 모델
클라우드 플랫폼 소프트웨어의 비즈니스 모델의 현상과 동향
클라우드 네이티브
OTA
TSP/MNO 차량 인터넷 서비스 제공업체
JHS
영문 목차
영문목차
Software business model research: from "custom development" to "IP/platformization", software enters the cost reduction cycle
According to the vehicle software system architecture, this report classifies smart car software into three categories: basic software layer, application software layer, and cloud software layer, as well as several sub-categories.
The software development of OEMs is developing towards "platformization" to achieve cost reduction at the source
In 2024, the organizational structure of OEMs are adjusted more and more frequently, and strategies need to be adjusted in real time to cope with the fiercely competitive automotive market. Some OEMs adjust their organizational structure in order to stabilize the company's sales and other status quo, and some adjust their organizational structure, especially R & D business team, to promote the company's software and new business focus.
Local OEMs conduct R & D organizational structure change, and restructure software development strategy
In recent years, XPeng Motors has continued to adjust its organizational structure on a large scale, and at the same time proposed a number of measures such as cost reduction and efficiency increase, budget reduction, etc., to face the intelligent and highly competitive automotive market. In July 2024, XPeng Motors' autonomous driving department ushered in another organizational restructuring. Xpeng's autonomous driving department established three new segments: AI model development, AI application development, and AI efficiency development. The AI model development department is mainly responsible for end-to-end model development, which is to strengthen the layout of AI end-to-end intelligent driving technology.
In August 2024, SAIC is unifying R & D business of IM and Rising brands into SAIC Group Innovation Research and Development Institute (referred to as SAIC R & D Institute). Among them, the R & D teams of IM and Rising brands, as well as technical projects such as power batteries, intelligent driving, and chassis, will be centrally migrated to SAIC R & D Institute, and unified and coordinated by R & D Institute. This model of centralizing the R & D power of all its sub-brands and developing them uniformly is the "large R & D institute" model commonly used by automobile manufacturing groups. Through this model, the platform and standardized layout of products are carried out to achieve equal sharing of R & D costs and strive to reduce costs at the source.
Multinational automakers strengthen cooperation with China's local software supply chain
At present, the localization development of multinational automakers in China has entered a new stage. This is different from the previous "sewing" auxiliary decoration and development, but to fundamentally restructure the system, actively adjust the strategy, and actively layout to cope with the new changes in China's auto market. It can be summarized as follows:
Increase China's local investment and R & D center layout. For example, in March 2022, Mercedes-Benz announced the establishment of a R & D center in Shanghai to further expand its R & D layout in China. The Shanghai R & D center will focus on intelligent interconnection, autonomous driving, software and hardware development and big data. In April 2023, Volkswagen Group announced that it will invest about 1 billion euros to establish a R & D, innovation and procurement center focusing on intelligent connected electric vehicles.
Further open up the authority of China's local teams and strengthen China's local customization strategy. At present, Mercedes-Benz, BMW, Volkswagen and other foreign automakers have proposed China's local customized development model to further open up the authority of China's local teams.
Actively cooperate with local Chinese suppliers. For example, Mercedes-Benz has in-depth cooperation with Momenta, Tencent, AISpeech, etc.; Volkswagen has in-depth cooperation with ThunderSoft, Horizon, XPeng Motors, etc.
In recent years, Volkswagen Group has actively promoted the layout of intelligent software. In Chinese market, Volkswagen Group has completely delegated the R & D decision-making power to the team in the Chinese market. From hardware platform of the model to electronic and electrical architecture to intelligent driving, cockpit, and even design, the local team makes independent decisions and makes local solutions. Volkswagen is responding to the challenges of its development in China and reshaping its software business by strengthening partnerships and leveraging external expertise.
In May 2023, Volkswagen Group announced the establishment of the largest R & D center in Hefei besides the German headquarters, investing about 1 billion euros, namely Volkswagen (China) Technology Co., Ltd., to systematically strengthen R & D strength "in China, for China". On April 11, 2024, Volkswagen Group (China) announced that it would invest 2.50 billion euros to further expand production and innovation center in Hefei, Anhui.
At the same time, starting from 2023, Volkswagen will cooperate with Horizon, ThunderSoft, XPeng Motors, SAIC and other local Chinese companies in the fields of E/E architecture, cockpit, intelligent driving, UI/UX and so on.
Software suppliers promote "customized development" to "IP/platformization" layout, the software R&D cycle is greatly compressed, and the cost reduction cycle is started
The IP/platformization layout of the software supplier's products helps OEM reduce costs and increase efficiency
At present, the automotive software business mainly includes customized software development and design, technical services, software IP authorization/licensing, and system integration, and the fees mainly include one-time fee NRE, software authorization/licensing, and royalty paid per piece.
In recent years, software suppliers in China's automotive market have mainly focused on software customized development or technical service business. Especially in the field of intelligent cockpit and intelligent driving. As to customized supply model, suppliers need to improve their company's reputation and expand market demand by developing new technologies and solutions through customized development with OEMs at the early stage.
With the emergence of mass production effect, in order to further improve efficiency and achieve large-scale product production at the same time, the software supplier business has gradually developed from "customization" to "IP/platformization". On the one hand, through IP or platformization product layout, OEMs can reduce costs and increase efficiency at a greater level, shorten the development cycle; on the other hand, it is more conducive to the large-scale replication of supplier business and the polishing and optimization of smart vehicle products, expanding the company's profit margins.
Taking cockpit platform products as an example, many suppliers offer cockpit platform products, which not only ensure high performance, but also achieve performance such as shortening development cycles and reducing costs through platform to meet the needs of highly competitive OEMs.
Cloud-native, AI large models help explore new models of software development and shorten development cycles
With the increasing complexity of automotive system software, especially the birth of new applications such as central computing and autonomous driving, application code has become more and more abundant, resulting in new ways of software development, deployment, and management to quickly meet a variety of changing consumer needs.
Among them, cloud-native software development, as a new development model, means moving to a cloud-based development model for automotive application development, enabling software development in the cloud and deployment directly on the edge of the car. Developers deploy and test automotive software applications anytime, anywhere, greatly shortening the development and deployment cycle of in-vehicle system applications.
In September 2023, AWS and Qualcomm announced a collaboration. One of the core of the collaboration is a power builder and infrastructure based on cloud-native technologies to help automakers develop, test and deploy software in the cloud. The partnership project showcases a cloud-based development environment and virtualized Snapdragon SoC platform for testing and validating automotive software in the cloud. The entire architecture design takes full advantage of the flexibility and scalability of cloud computing, enabling developers to carry out efficient development work anywhere in the world.
Based on the open-source community, ETAS builds SDV. OS cloud-native solutions, provides SDV power builder chains, and provides customers with cloud-native development, deployment, and management and analysis solutions.
In addition, as technologies such as AI large models continue to mature, AI large models will lead a new model of automotive software development. More than 60% of automotive software code work will be replaced by large models, and basic application software and other products will continue to develop on a platform. At that time, the concentration of automotive software industry will further increase, and the industry's leadership will become inevitable. The upstream and downstream will enter the "flywheel acceleration" rally.
Vehicle-level OS platform, OEMs and suppliers coordinate layout
At present, vehicle OS products are mainly composed of standardized middleware such as Hypervisor, underlying OS, AUTOSAR, other core middleware and tool chains, etc., to realize the operating system of the central computing unit software system function.
At present, there are three main paths for OEMs in China to deploy vehicle OS: full-stack self-development, internal incubation of Tier1, and joint development.
At present, except for some OEMs with strong R & D strength, most OEMs tend to implement the layout of the whole vehicle OS through the model of joint development with suppliers. In the face of the customized needs of OEMs, the supplier's software development team is an ideal partner for OEMs, which can cooperate in R & D and help customers quickly develop products, shortening product launch time.
In the face of the vehicle-level OS market, software suppliers have launched platform-based vehicle OS solutions and flexible supply methods to help OEMs quickly create suitable software platform products for central computing. For example, ThunderSoft launched the vehicle AquaDrive OS system, ArcherMind Technology's cross-domain vehicle Fusion OS, Kotei KCar-OS, ETAS's end-to-end vehicle OS solution, Huawei iDVP intelligent digital base, etc.
In addition, under the trend of SOA software frameworks, cooperation models such as OEMs, Tier1, and software developers are no longer chimney-like, but in-depth strategic cooperation models. Through partnerships and ecological integration, the entire OS can be more open and serve the development of the entire industry.
Table of Contents
1 Analysis of Automotive Software Business Model and Trend
1.1 Overview of Intelligent Vehicle Software Industry Chain
1.1.1 Definition and Architecture of Intelligent Vehicle Software
1.1.2 Categories Covered by Intelligent Vehicle Software
1.1.3 Evolution of Intelligent Vehicle Software Architecture:
1.1.4 Changes in Automotive Software Development Methods of OEMs
1.1.5 Categories of Automotive Software Suppliers
1.1.6 Software Empowers OEMs to Realize Value
1.1.7 Development Trends of Intelligent Vehicle Software
1.1.8 Automotive Software Market Size
1.2 Software System Supply Chain Establishment and Organizational Structure Adjustment of Major OEMs
1.2.1 Organizational Structure Adjustment of OEMs in Software R&D
1.2.1.1 Organizational Structure Adjustment Strategies of OEMs (1):
1.2.1.2 Organizational Structure Adjustment Strategies of OEMs (2):
1.2.1.3 Organizational Structure Adjustment Strategies of OEMs (3):
1.2.1.4 Organizational Structure Adjustment Strategies of OEMs (4):
1.2.1.5 R&D Organizations, R&D Investment and Team Size of Major OEMs
1.2.2 Software System Supply Chain Construction Strategies of Major OEMs
1.2.2.1 Software Layout Strategies of OEMs (1):
1.2.2.2 Software Layout Strategies of OEMs (2):
1.2.2.3 Software Layout Strategies of OEMs (3):
1.2.2.4 Software Layout Strategies of OEMs (4):
1.2.2.5 Software Layout Strategies of OEMs (5):
1.2.2.6 Software Layout Strategies of OEMs (6):
1.2.2.7 Software Layout Strategies of OEMs (7):
1.2.2.8 Software System Supply Chain Construction of OEMs: NIO
1.2.2.9 Software System Supply Chain Construction of OEMs: Xpeng
1.2.2.10 Software System Supply Chain Construction of OEMs: Li Auto
1.2.2.11 Software System Supply Chain Construction of OEMs: Leapmotor
1.2.2.12 Software System Supply Chain Construction of OEMs: Neta
1.2.2.13 Software System Supply Chain Construction of OEMs: ZEEKR
1.2.2.14 Software System Supply Chain Construction of OEMs: IM
1.2.2.15 Software System Supply Chain Construction of OEMs: GAC
1.2.2.16 Software System Supply Chain Construction of OEMs: Chery
1.2.2.17 Software System Supply Chain Construction of OEMs: Voyah
1.3 Summary of Business Models of Intelligent Vehicle Software Related Suppliers
1.3.1 Main Business Types of Software Suppliers
1.3.2 Main Charging Models of Software Suppliers
1.3.3 Software Licensing Fees for Some Intelligent Vehicle Software Modules
1.3.4 Automotive Software Sales Models
1.3.5 Summary of Business Models of Major Automotive Software Suppliers by Product (1)
1.3.6 Summary of Business Models of Major Automotive Software Suppliers by Product (2)
1.3.7 Summary of Business Models of Major Automotive Software Suppliers by Product (3)
1.3.8 Summary of Business Models of Major Automotive Software Suppliers by Product (4)
1.3.9 Summary of Business Models of Major Automotive Software Suppliers by Product (5)
1.3.10 Summary of Business Models of Major Automotive Software Suppliers by Product (6)
1.3.11 Summary of Business Models of Major Automotive Software Suppliers by Product (7)
1.3.12 Business models of Major Automotive Software Products
1.3.13 Business Models of Major Automotive Software Suppliers
1.3.14 Evolution Trend of Role of Software Suppliers under SVD Trend
1.3.15 Software Development Strategies of OEMs
1.3.16 Software Value Realization Solution of Suppliers
1.3.17 Evolution Trend of Value Realization Mode of Intelligent Vehicle Software
1.3.18 Proportion of Value Realization Mode of Intelligent Vehicle Software
1.4 Development Trend of Smart Vehicle Software Business Model
1.4.1 Changes in Intelligent Vehicle Software Supply Models
1.4.1.1 Role Transformation of Software Suppliers under SVD Trend (Tier2-Tier1/Tier0.5)
1.4.1.2 Automotive Software Supply Models (1):
1.4.1.3 Automotive Software Supply Models (2):
1.4.1.4 Automotive Software Supply Models (3):
1.4.2 Software Business Exploration Models (1):
1.4.2.1 Charging Strategies of Software Suppliers:
1.4.2.2 Case 1:
1.4.2.3 Case 2:
1.4.3 Software Business Exploration Models (2):
1.4.3.1 Exploration of Software Suppliers in Charging Models:
1.4.3.2 Case:
1.4.4 Development Trends of Business Models by Software Product
1.4.4.1 Future Automotive Software Product Development Trends and Business Model Exploration (1)
1.4.4.2 Future Automotive Software Product Development Trends and Business Model Exploration (2)
1.4.5 New Development Models of Intelligent Vehicle Software (1):
1.4.5.1 Future Central Computing Will Be Oriented Towards Value Development, and Development Methods Will Become More Open
1.4.5.2 The New Cloud Native Development Model Facilitates Simultaneous Development of Software and Hardware and Shortens the Development Cycle
1.4.5.3 Case 1:
1.4.5.4 Case 2:
1.4.5.5 Case 3:
1.4.5.6 Case 4:
1.4.5.7 Case 5:
1.4.5.8 Case 6:
1.4.6 New Development Models of Intelligent Vehicle Software (2):
1.4.6.1 AI Foundation Model Software Development
1.4.6.2 AI Foundation Models are Used for Software Development and Testing
1.4.6.3 Case 1:
2. Analysis on OEMs' Response to Software Innovation Strategy
2.1 Mercedes-Benz
2.1.1 Software Business Layout
2.1.2 Layout Mode of MB.OS
2.1.3 Construction of Software Division
2.1.4 Software Layout Strategy:
2.1.5 Localized Software Business Layout in China
2.1.6 Software Partners
2.2 BYD
2.2.1 Intelligent Layout Planning
2.2.2 Self-developed BYD OS
2.2.3 Intelligent Organizational Adjustment:
2.2.4 Intelligent Driving Business Layout Evolves from Cooperation to Independent R&D (1)
2.2.5 Intelligent Driving Business Layout Evolves from Cooperation to Independent R&D (2)
2.2.6 Intelligent Driving Business Layout Evolves from Cooperation to Independent R&D (3)
2.3 BMW
2.3.1 Software Business Layout: Continuous Evolution of IVI System
2.3.2 Software business layout: In-depth Layout in Intelligent Driving Cooperation
2.3.3 Localized Software Business Layout in China:
2.3.4 Localized Software Business Layout in China:
2.3.5 Localized Software Business Layout in China: Partners
2.4 Volkswagen
2.4.1 Software Platform Planning
2.4.2 Process of Software Team Construction
2.4.3 The Latest Software Organizational Structure in China
2.4.4 Establishment of the Largest R&D Center in China
2.4.5 Software Team Layout in China: Local Solution Layout
2.4.6 Core Business in China
2.4.7 Partners
2.5 Ford
2.5.1 Software Business Layout
2.5.2 Software Business Team (1)
2.5.3 Software Business Team (2):
2.5.4 Software Business Layout Strategy:
2.6 SAIC
2.6.1 Software Business Layout
2.6.2 Software Business Layout Strategy (1):
2.6.3 Software Business Layout Strategy (2):
2.6.4 Software Business Layout Strategy (3):
2.6.5 Software Business Layout Strategy (4):
2.6.6 R&D Team Adjustment:
2.6.7 Personnel Change: A Major Reshuffle of Senior Management
2.6.8 Evolution of Z-One Galaxy Full Stack Solution
2.6.9 Z-One Galaxy Full Stack Solution 3.0
2.6.10 Z-One Galaxy's First-generation Central Brain Software System
2.6.11 Z-One Galaxy's Second-generation Central Brain Software System
2.7 Great Wall Motor
2.7.1 Status Quo of Intelligent Business Layout
2.7.2 Layout of Coffee Intelligence
2.7.3 Forest Ecosystem
2.7.4 Software Layout Strategy (1):
2.7.5 Software Layout Strategy (2):
2.7.6 Software Team Construction:
2.7.7 Organizational Architecture Adjustment
2.7.8 Software Cooperation Ecosystem
2.8 Geely
2.8.1 Software Business Layout
2.8.2 Software Business Layout Strategy:
2.8.3 Software Business Layout Planning
2.8.4 R&D Architecture Adjustment:
2.9 Changan Automobile
2.9.1 Software Business Layout
2.9.2 Software Business Planning
2.9.3 R&D System Reform
2.9.4 Software Business Team Construction:
2.9.5 Software Business Team Construction:
2.10 Xpeng
2.10.1 Software Business Layout
2.10.2 Distribution of R&D Centers
2.10.3 Continuous Adjustment of Organizational Structure
2.10.4 Personnel Reshuffle and AI-oriented Organizational Change
2.10.5 Autonomous Driving Team
2.11 Li Auto
2.11.1 Software Business Layout
2.11.2 Organizational Architecture Adjustment
2.11.3 R&D Center
2.11.4 Intelligent Driving Software Business Layout
2.11.5 Li OS
2.12 FAW
2.12.1 Intelligent Layout
2.12.2 Global R&D Layout
2.12.3 Hongqi Intelligent HIS Software Architecture
2.13 Chery
2.13.1 Intelligent Layout Planning
2.13.2 Software Business Layout
2.13.3 Intelligent Driving Business Layout
2.13.4 Zhuojie Joint Innovation Center
3 Automotive Operating System Business and Layout Models
3.1 Status Quo and Trends of Automotive Operating System Business Models
3.1.1 Types of Automotive Operating Systems
3.1.2 Synergy and Symbiosis between Narrow Operating Systems and Generalized Operating Systems
3.1.3 Automotive Operating System Business Models
3.1.4 Business Models of Automotive Basic Software (Generalized Operating Systems) by Module
3.1.5 Business Models of Major Automotive Operating System Enterprises
3.1.6 Smart Cockpit OS Business Models
3.1.7 Business Models of Autonomous Driving OS Suppliers
3.1.8 Development Trends and Business Model Exploration of Automotive Operating Systems
3.2 Vehicle OS
3.2.1 Definition of Vehicle OS
3.2.2 Framework of Vehicle OS
3.2.3 Purpose of Vehicle OS
3.2.4 Evolution of Vehicle OS Development Models
3.2.5 Market Opportunities for Vehicle OS Suppliers
3.2.6 Role Transformation of Automotive OS Software Suppliers
3.2.7 Evolution of Business Models under the Trend of Vehicle OS
3.2.8 Vehicle OS Layout Modes of OEMs
3.2.9 Business Models (1):
3.2.10 Business Models (2):
3.2.11 Business Models (3):
3.2.12 Vehicle OS Composition and Business Models of Suppliers (1)
3.2.13 Vehicle OS Composition and Business Models of Suppliers (2)
3.2.14 Vehicle OS Composition and Business Models of Suppliers (3)
3.2.15 Vehicle OS Composition and Business Models of Suppliers (4)
3.2.16 Vehicle OS Layout Cases of Suppliers (1):
3.2.17 Vehicle OS Layout Cases of Suppliers (2):
3.2.18 Vehicle OS Layout Cases of Suppliers (3):
3.2.19 Vehicle OS Layout Cases of Suppliers (4):
3.2.20 Vehicle OS Layout Cases of Suppliers (5):
3.2.21 Vehicle OS Layout Cases of Suppliers (6):
3.2.22 Vehicle OS Layout Cases of Suppliers (7):
3.2.23 Vehicle OS Layout Cases of Suppliers (8):
3.2.24 Vehicle OS Layout Cases of Suppliers (9):
3.2.25 Vehicle OS Layout Cases of Suppliers (10):
3.2.26 Vehicle OS Layout Cases of Suppliers (11):
3.3 Main Underlying Automotive Operating Systems
3.3.1 Basic Automotive Operating Systems and Business Models
3.3.2 Automotive RTOS and Business Models (1)
3.3.3 Automotive RTOS and Business Models (2)
3.3.4 Intelligent Driving Operating Systems and Business Models (1)
3.3.5 Intelligent Driving Operating Systems and Business Models (2)
3.3.6 Intelligent Driving Operating Systems and Business Models (3)
3.3.7 Intelligent Driving Operating Systems and Business Models (4)
3.3.8 Intelligent Driving Operating Systems and Business Models (5)
3.3.9 Cockpit Operating Systems and Business Models (1)
3.3.10 Cockpit Operating Systems and Business Models (2)
3.4 Main Automotive Middleware Business Models
3.4.1 Types of Middleware Suppliers
3.4.2 Business Models of Middleware Suppliers
3.4.3 Business Models of Middleware Suppliers
3.4.4 ROS Middleware Products and Business Models
3.4.5 DDS Middleware Products and Business Models (1)
3.4.6 DDS Middleware Products and Business Models (2)
3.4.7 DDS Middleware Products and Business Models (3)
3.4.8 Communication Middleware Products and Business Models
3.4.9 MCAL Middleware Products and Business Models (1)
3.4.10 MCAL Middleware Products and Business Models (2)
3.4.11 Autonomous Driving Middleware Products and Business Models (1)
3.4.12 Autonomous Driving Middleware Products and Business Models (2)
3.4.13 Autonomous Driving Middleware Products and Business Models (3)
3.4.14 Autonomous Driving Middleware Products and Business Models (4)
3.4.15 Autonomous Driving Middleware Products and Business Models (5)
3.4.16 Autonomous Driving Middleware Products and Business Models (6)
3.4.17 Autonomous Driving Middleware Products and Business Models (7)
3.4.18 Autonomous Driving Middleware Products and Business Models (8)
3.4.19 Other Middleware Products and Business Models (1)
3.4.20 Other Middleware Products and Business Models (2)
3.4.21 Other Middleware Products and Business Models (2)
3.5 AUTOSAR
3.5.1 AUTOSAR Industry Chain
3.5.2 Business Models of AUTOSAR Software Tool Suppliers (1)
3.5.3 Business Models of AUTOSAR Software Tool Suppliers (2)
3.5.4 Business Models of AUTOSAR Software Tool Suppliers (3)
3.5.5 Business Models of AUTOSAR Software Tool Suppliers (4)
3.5.6 Business Models of AUTOSAR Software Tool Suppliers (5)
3.5.7 Business Models of AUTOSAR Software Tool Suppliers (6)
3.5.8 Business Models of AUTOSAR Software Tool Suppliers (7)
3.5.9 Business Models of AUTOSAR Software Tool Suppliers (8)
4 Intelligent Cockpit Business and Layout Models
4.1 Intelligent Cockpit Software System Business Models and Trends
4.1.1 Cockpit Application Software Layer Industry Chain
4.1.2 Main Cockpit Application Software Module Business Models
4.1.3 Trends of Main Cockpit Application Software Module Business Models
4.1.4 Evolution Trends of Intelligent Cockpit System Development
4.1.5 Four Supply Models of Intelligent Cockpit Systems
4.1.6 The Cockpit Platform Development Cycle of Major Suppliers Continues to Shorten
4.1.7 Main Intelligent Cockpit Software Platform Suppliers and Business Models (1)
4.1.1 Main Intelligent Cockpit Software Platform Suppliers and Business Models (2)
4.1.9 Main Intelligent Cockpit Software Platform Suppliers and Business Models (3)
4.2 Automotive HMI Design
4.2.1 Automotive HMI Software Business Models
4.2.2 Automotive 3D Engine-equipped Intelligent Cockpit Layout and Business Models
4.2.3 Typical Business Models (1):
4.2.4 Typical Business Models (2):
4.2.5 Typical Business Models (3):
4.2.6 Products and Business Models of Major HMI Designers (1)
4.2.7 Products and Business Models of Major HMI Designers (2)
4.2.8 Products and Business Models of Major HMI Designers (3)
4.2.9 Products and Business Models of Major HMI Designers (4)
4.2.10 Products and Business Models of Major HMI Designers (5)
4.2.11 Latest Products and Business Models of Major HMI Design Software Suppliers (6)
4.2.12 3D HMI Engine Layout and Business Models of Major Suppliers (7)
4.3 Automotive Voice Business Models and Trends
4.3.1 Automotive Voice Industry Chain
4.3.2 Automotive Voice Industry Supply:
4.3.3 Customization of Automotive Voice Functions
4.3.4 Automotive Voice Suppliers Expand Their Monotonous Business to All-in-one Business
4.3.5 AI Foundation Models Support the Development of Automotive Voice
4.3.6 Typical Business Models (1):
4.3.7 Typical Business Models (2):
4.3.8 Typical Business Models (3):
4.3.9 Typical Business Models (4):
4.3.10 Typical Business Models (5):
4.3.11 Typical Business Models (6):
4.3.12 Main Voice Software Suppliers and Business Models (1)
4.3.13 Main Voice Software Suppliers and Business Models (2)
4.3.14 Main Voice Software Suppliers and Business Models (3)
4.3.15 Main Voice Software Suppliers and Business Models (4)
4.3.16 Main Voice Software Suppliers and Business Models (5)
4.3.17 Main Voice Software Suppliers and Business Models (6)
4.4 Automotive Map Navigation Business Models and Trends
4.4.1 HD Map Business Models (1):
4.4.2 HD Map Business Models (2):
4.4.3 Cooperation Mode between HD Map Suppliers and OEMs
4.4.4 Monetization
4.4.5 HD Map Profit Models
4.4.6 Changes in Business Models of Map Suppliers amid the Development of Urban NOA
4.4.7 Cases of Business Models:
4.4.8 Automotive Navigation Map Business Models of Main Suppliers (1)
4.4.9 Automotive Navigation Map Business Models of Main Suppliers (2)
4.4.10 HD Map Business Models of Main Suppliers (1)
4.4.11 HD Map Business Models of Main Suppliers (2)
4.4.12 HD Map Business Models of Main Suppliers (3)
4.4.13 HD Map Business Models of Main Suppliers (4)
4.4.14 Light Intelligent Driving Map Business Models of Major Suppliers (1)
4.4.15 Light Intelligent Driving Map Business Models of Major Suppliers (2)
4.5 Automotive Acoustic System
4.5.1 Status Quo of Acoustic Software Business Models
4.5.2 Summary of Business Models of Acoustic Software Suppliers
4.5.3 Evolution of Acoustic Software Procurement Models of OEMs:
4.5.4 Exploration of Acoustic Software Business Models
4.5.5 Typical Models (1):
4.5.6 Typical Models (2):
4.5.7 Typical Models (3):
4.5.8 Typical Models (4):
4.5.9 Typical Models (5):
4.5.10 Typical Models (6):
4.5.11 Typical Models (7):
4.5.12 Typical Models (8):
4.5.13 Acoustic Software Suppliers and Business Models (1)
4.5.14 Acoustic Software Suppliers and Business Models (2)
4.5.15 Acoustic Software Suppliers and Business Models (3)
4.5.16 Acoustic Software Suppliers and Business Models (4)
4.5.17 Acoustic Software Suppliers and Business Models (5)
4.5.18 Acoustic Software Suppliers and Business Models (6)
4.5.19 Acoustic Software Suppliers and Business Models (7)
4.6 AR-HUD Software
4.6.1 Core AR HUD Technology
4.6.2 Main Directions for AR-HUD Software Upgrade
4.6.3 AR Creator Has Become The Core Element of AR-HUD, and Software Capabilities Are Particularly Important
4.6.4 AR HUD Software Supply Models
4.6.5 AR HUD Software Supply Models
4.6.6 AR HUD Quotation Logic
4.6.7 Typical Models (1):
4.6.8 Typical Models (2):
4.6.9 Typical Models (3):
4.6.10 Typical Models (4):
4.6.11 Typical Models (5):
4.6.12 Typical Models (6):
4.6.13 HUD Software Suppliers and Business Models (1)
4.6.14 HUD Software Suppliers and Business Models (2)
4.6.15 HUD Software Suppliers and Business Models (3)
4.6.16 HUD Software Suppliers and Business Models (4)
4.6.17 HUD Software Suppliers and Business Models (5)
4.7 In-cockpit Vision (DMS/OMS) Business Models and Trends
4.7.1 In-cockpit Vision Industry Chain
4.7.2 Cost Composition of In-cockpit Vision Industry
4.7.3 In-cockpit Vision Quotation Logic
4.7.4 In-cockpit Vision Business Models
4.7.5 Typical Models (1):
4.7.6 Typical Models (2):
4.7.7 Typical Models (3):
4.7.8 DMS Visual Perception Algorithm Suppliers and Business Models (1)
4.7.9 DMS Visual Perception Algorithm Suppliers and Business Models (2)
4.7.10 DMS Visual Perception Algorithm Suppliers and Business Models (3)
4.7.11 DMS Visual Perception Algorithm Suppliers and Business Models (4)
4.7.12 DMS Visual Perception Algorithm Suppliers and Business Models (5)
4.8 Multi-modal Fusion Interaction
4.8.1 Multi-modal Interactive Software Supply Trend: Transition from Single-module Supply to Integrated Supply
4.8.2 Product Model Strategies of HMI Suppliers (1):
4.8.3 Product Model Strategies of HMI Suppliers (2):
4.8.4 Product Model Strategies of HMI Suppliers (3):