Software-defined Vehicle Research Report, 2023-2024 - Industry Panorama and Strategy

Table of Contents

1. How to Build Intelligent Driving Software System?

• 1.1. Overall Software and Hardware Architecture of Intelligent Cockpit
• 1.2. Basic Software: Real-time Vehicle Control Operating System (OS in Narrow Sense)
  • 1.2.1. Intelligent Vehicle software architecture includes hypervisor, system cores, middleware, functional software, and application programs
  • 1.2.2. Narrowly Defined OS (Kernel) for Intelligent Driving
  • 1.2.3. CATARC's Automotive OS Standard System
  • 1.2.4. Intelligent Driving Real-time Vehicle Control OS Reference Architecture
  • 1.2.5. Intelligent Driving Operating System Kernel Development Path (1): Inheriting Linux's rich open source ecosystem
  • 1.2.6. Intelligent Driving Operating System Kernel Development Path (2): Implementation of Microkernel RTOS Based on POSIX Standard
  • 1.2.7. Intelligent Driving Underlying OS: Status Quo of Chinese Market Development
  • 1.2.8. Intelligent Driving Underlying OS: Software OS Providers Bind with Hardware Chip Vendors for Deep Cooperation
  • 1.2.9. Intelligent Driving Underlying OS: Key to Localization Breakthrough lies in Collaboration of Chinese Chips and Microkernel OS
  • 1.2.10. Intelligent Driving Underlying OS: Chinese Real-Time Vehicle Control OS Vendors Launch Open Source Programs
  • 1.2.11. Localization of Real-time Operating System:"CETC iSOFT Infrastructure Software" EasyAda Microkernel (1)
  • 1.2.12. Localization of Real-time Vehicle Control OS: "CETC iSOFT Infrastructure Software" EasyAda Microkernel (2)
  • 1.2.13. Localization of Real-time Operating System:ZTE's Dual Core Intelligent Driving OS Based on ZTE Microkernel and Safety Linux
  • 1.2.14. Localization of Real-time Vehicle Control OS: ZTE Dual-kernel Intelligent Driving OS based on ZTE microkernel and Safety Linux (2)
  • 1.2.15. Localization of Real time Operating System: ZTE's "Three Step" Strategy for Intelligent Driving OS
  • 1.2.16. Localization of Real-time Vehicle Control OS: ZTE Intelligent Driving OS Adaptation Solution
  • 1.2.17. Localization of Real-time Vehicle Control OS: ZTE Safety Linux Adaptation on Black Sesame Technologies A1000
  • 1.2.18. Localization of Real-time Vehicle Control OS: "ReachAuto +ZTE +SemiDrive" Collaborate on Fully Localized Vehicle Control Platform
  • 1.2.19. Localization of Real time Operating System: RT Thread Open Source Real Time Operating System (RTOS)
  • 1.2.20. Localization of Real time Operating System: Banma AliOS Drive Intelligent Driving System
  • 1.2.21. Localization of Real-time Vehicle Control OS: Banma Zhixing AliOS Drive+Horizon J5+HoloMatic AI Algorithm
  • 1.2.22. Localization of Real time Operating System: ZLingsmart"RAITE Microkernel" and"RAITE Hypervisor"
  • 1.2.23. Localization of Real Time Operating System: Matrix of Kernelsoft Photon Operating System Products Based on Linux
  • 1.2.24. Localization of Real-time Vehicle Control OS: "China Intelligent and Connected Vehicles (CICV)" Baseline 1.0 Automotive OS
  • 1.2.25. Real Time Operating System: Aptiv VxWorks Microkernel
  • 1.2.26. Real Time Operating System: Aptiv VxWorks Microkernel
  • 1.2.27. Real-Time Vehicle Control OS: Aptiv Introduces Wind River Studio "Cloud Native" to Automotive Industry
  • 1.2.29. Real Time Operating System: QNX OS for Safety
  • 1.2.30. Real Time Operating System: Xpeng X-EEA 2.0/3.0 Intelligent Driving Adopts QNX OS at the Bottom Layer
  • 1.2.31. Real Time Operating System: Tesla OS Bottom Layer Self-developed on Linux
  • 1.2.32. Real Time Operating System: Li OS Bottom Layer Self-developed on Linux
  • 1.2.33. Real Time Operating System: Changan SDA RTDriveOS Intelligent Driving Operating System (1)
  • 1.2.33. Real Time Operating System: Changan SDA RTDriveOS Intelligent Driving Operating System (2)
  • 1.2.34. Real Time Operating System: Toyota Open Vehicle Operating System - Arene
  • 1.2.35. RTOS (in Narrow Sense) Suppliers and Product List (1)
  • 1.2.36. RTOS (in Narrow Sense) Suppliers and Product List (2)
  • 1.2.37. RTOS (in Narrow Sense) Suppliers and Product List (3)
  • 1.2.38. RTOS (in Narrow Sense) Suppliers and Product List (4)
  • 1.2.39. Summary: Real Time Operating System (in Narrow Sense)
• 1.3. Basic Software: Intelligent Driving Middleware (ROS, CyberRT, DDS, AutoSAR)
  • 1.3.1. Key Technology for Mass Production and Implementation of Intelligent Driving: Middleware
  • 1.3.2. Intelligent Driving Vehicle Middleware: Communication Middleware (1)
  • 1.3.3. Intelligent Driving Vehicle Middleware: Communication Middleware (2)
  • 1.3.4. Development Prospects of SOME/IP & DDS
  • 1.3.5. Intelligent Driving Communication Middleware Solutions (1): Greenstone "Swift" Communication Middleware SWIFT DDS (1)
  • 1.3.6. Intelligent Driving Communication Middleware Solutions (1): Greenstone "Swift" Communication Middleware SWIFT DDS (2)
  • 1.3.7. Intelligent Driving Communication Middleware Solution (2): RTI Connext Drive 3.0
  • 1.3.8. Mainstream Communication Middleware Suppliers and Their Product Lists (1)
  • 1.3.9. Mainstream Communication Middleware Suppliers and Their Product Lists (2)
  • 1.3.10. Intelligent Driving Middleware: Autosar, ROS2, CyberRT
  • 1.3.11. Intelligent Driving Middleware Solution Options for OEMs and Tier1 Suppliers (1)
  • 1.3.12. Intelligent Driving Middleware Solution Options for OEMs and Tier1 Suppliers (2)
  • 1.3.13. Intelligent Driving Automotive Middleware (1): AP AUTOSAR
  • 1.3.14. Intelligent Driving Middleware: AUTOSAR CP+AP Hybrid Software Architecture (1)
  • 1.3.15. Intelligent Driving Middleware: AUTOSAR CP+AP Hybrid Software Architecture (2)
  • 1.3.16. Intelligent Driving Middleware: ROS
  • 1.3.17. Differences between ROS 2 and AUTOSAR AP
  • 1.3.18. Autonomous Driving Middleware Solution (1): Baidu CyberRT
  • 1.3.19. Autonomous Driving Middleware Solution (2): Bosch EDMS AD Middleware (1)
  • 1.3.20. Autonomous Driving Middleware Solution (2): Bosch EDMS AD Middleware (2)
  • 1.3.21. Autonomous Driving Middleware Solution (3): HoloMatic HoloSAR
  • 1.3.22. Autonomous Driving Middleware Solution (3): HoloSAR Autonomous Driving Middleware of HoloMatic Technology (2)
  • 1.3.23. Autonomous Driving Middleware Solution (4): Technomous Domain Control Middleware - RazorWareX1.0
  • 1.3.24. Autonomous Driving Middleware Solution (5): Photon Middleware Adaptive Software Platform
  • 1.3.25. Autonomous Driving Middleware Solution (6): iSOFT ORIENTAIS AP Intelligent Driving Basic Software Platform
  • 1.3.26. Is It Necessary for OEMs to Self-develop Middleware? (1): Suppliers' Perspective
  • 1.3.27. It Necessary for OEMs to Self-develop Middleware? (2): OEMs' Perspective
  • 1.3.28. Is It Necessary for OEMs to Self-develop Middleware? (3): Summary
  • 1.3.29. Global Autonomous Driving Middleware AUTOSAR Suppliers and Product Lists(1)
  • 1.3.30. Global Autonomous Driving Middleware AUTOSAR Suppliers and Product Lists(2)
  • 1.3.31. Global Autonomous Driving Middleware AUTOSAR Suppliers and Product Lists(3)
  • 1.3.32. Chinese Autonomous Driving Middleware AUTOSAR Suppliers and Product Lists(1)
  • 1.3.33. Chinese Autonomous Driving Middleware AUTOSAR Suppliers and Product Lists(2)
  • 1.3.34. Chinese Autonomous Driving Middleware AUTOSAR Suppliers and Product Lists(3)
  • 1.3.35. Autonomous Driving Middleware ROS 2 Players and Product Lists
  • 1.3.36. Independent R&D Suppliers of Autonomous Driving Middleware and Product Lists(1)
  • 1.3.37. Independent R&D Suppliers of Autonomous Driving Middleware and Product Lists(2)
  • 1.3.38. Independent R&D Suppliers of Autonomous Driving Middleware and Product Lists(3)
  • 1.3.39. Independent R&D Suppliers of Autonomous Driving Middleware and Product Lists(4)
• 1.4. Basic Software: How to Systematically Build a Generalized OS for Autonomous Driving?
  • 1.4.1. Generalized OS Definition for Autonomous Driving
  • 1.4.2. Evolution of Vehicle EEA Drives Changes in Underlying OS of Vehicles
  • 1.4.3. Development Trend of Generalized OS for Autonomous Driving: Evolution towards Unified and Integrated Smart Car Operating System
  • 1.4.4. Market Size of China Autonomous Driving Operating System in Broad Sense(Middleware OS)
  • 1.4.5. Intelligent Driving Generalized OS Software Platform: Neusoft ReachNeuSAR 4.0 (1)
  • 1.4.6. Intelligent Driving Generalized OS Software Platform: Neusoft Reach NeuSAR 4.0 (2)
  • 1.4.7. Intelligent Driving Generalized OS Software Platform: ISOFT Infrastructure Software's AUTOSAR CP+AP Integrated Solution
  • 1.4.8. Intelligent Driving Generalized OS Software Platform: ZTE Communications Layered Decoupling Three-Dimensional Ecology
  • 1.4.9. Generalized Intelligent Driving OS Software Platform: Vehicle OS of Jingwei Hirain Technologies
• 1.5. Construction of Universal Algorithms for Intelligent Driving: from Small Models to Large Models
  • 1.5.1. Intelligent Driving 3.0 Era, from Small Models to Large Models
  • 1.5.2. How to Build an End-to-end Neural Network Foundation Model of Autonomous Driving?
  • 1.5.3. Core Autonomous Driving Algorithm Modules
  • 1.5.4. Iteration Process of Autonomous Driving Algorithm module (2016-2023)
  • 1.5.5. Autonomous Driving Algorithm Module: Bev+Transformer Intelligent Driving Algorithm
  • 1.5.6. Autonomous Driving Algorithm Module: BEV Is Further Upgraded to Occupancy Network
  • 1.5.7. Autonomous Driving Algorithm Module: "End-to-end" Intelligent Driving Algorithm, 2023 Best Paper Autonomous Driving General Algorithm Framework UniAD
  • 1.5.8. Autonomous Driving Algorithm Module: "End-to-end" UniAD Large Model (1)
  • 1.5.9. Autonomous Driving Algorithm Module: "End-to-end" UniAD Large Model (2)
  • 1.5.10. Automated Driving Algorithm Module: The Official Version of Tesla V12 will Introduce an "End-to-End" Algorithm
  • 1.5.11. Summary of OEM Self-Developed Intelligent Driving Algorithm (1)
  • 1.5.12. Summary of OEM Self-Developed Intelligent Driving Algorithm (2)
  • 1.5.13. Summary of Tier 1 Supplier Intelligent Driving Algorithm
  • 1.5.14. Tesla's Autopilot solution Is Called the "IOS" in Autonomous Driving World
  • 1.5.15. Third-Party Giants Expected to Build "Android" in the Automated Driving Field with Tool Chains
  • 1.5.16. Baidu Is Committed to Enhancing the Perception Model of Autonomous Driving and Mining Long Tail Data by Using Large Model ERNIE
  • 1.5.17. SenseTime Uses Foundation Models to Empower Autonomous Driving Perception Closed Loop and Decision-making Closed Loop, Etc.
  • 1.5.18. Horizon Robotics Believes that Future Autonomous Driving will Eventually Move toward End-to-End Algorithms
  • 1.5.19. Tesla Transformer Neural Network Enables Multi-Camera Data Fusion
  • 1.5.20. Tesla FSD Deep Learning Code Ratio Increases
  • 1.5.21. HAOMO.AI MANA System Adopts Transformer Neural Network
  • 1.5.22. Deployment of XPeng G9 Transformer Network
  • 1.5.23. "Xnet"-the New Generation Perception Architecture Released by Xpeng G9
  • 1.5.24. Xpeng Self-develops Automatic Annotation System
  • 1.5.25. End-to-end Autonomous Driving Algorithms May Replace Traditional Open Source Frameworks for Autonomous Driving Software
  • 1.5.26. Open Source Software Platform Autonomous Driving OS Suppliers and Product List (1)
  • 1.5.27. Open Source Software Platform Autonomous Driving OS Suppliers and Product List (2)
• 1.6. Intelligent Driving General Algorithm Architecture: AI Deep Learning Software Platform
  • 1.6.1. AI Deep Learning Software Suppliers and Product Lists (1)
  • 1.6.2. AI Deep Learning Software Suppliers and Product Lists(2)
  • 1.6.3. Major Foundation Model Vendors at Home and Abroad
  • 1.6.4. Emergence of Large Models Brings Great Challenges to Model Training
  • 1.6.5. Featured Distributed Training Technology of Baidu PaddlePaddle in the Field of Foundation Model Training
  • 1.6.6. Baidu and Geely Released the Industry's First Knowledge-enhanced Automotive Foundation Model - Geely-Baidu*ERNIE
  • 1.6.7. Huawei Open Dource Delf-developed AI Framework MindSpore Transformer Large Model Training Library
  • 1.6.8. Colossal-AI Large Model Training System of Luchen Tech
  • 1.6.9. NVIDIA CV-CUDA Open Source Library, General High-performance Image Processing Acceleration Library
• 1.7. Intelligent Driving General Algorithm Construction : Intelligent Driving Data Training Set
  • 1.7.1. Why to Build Dataset? (1)
  • 1.7.2. Why to Build Dataset? (2)
  • 1.7.3. Why to Build Dataset? (3)
  • 1.7.4. How does the autonomous driving training data acquisition vehicle collect data ?
  • 1.7.5. Dataset Development Direction (1): Evolve from Single Vehicle Intelligence to Vehicle-City Fusion
  • 1.7.6. Dataset Development Direction (2): Data Set Tasks Extend from Perception to Prediction and Planning
  • 1.7.7. Dataset Development Direction (3): large model era, the new generation data set development direction of autonomous driving
  • 1.7.8. Next-generation data set product : the world 's first language + self-driving full-stack open source data set-DriveLM(1)
  • 1.7.9. Next-generation data set product : the world 's first language + self-driving full-stack open source data set-DriveLM(2)
  • 1.7.10. Autonomous Driving Dataset Product Comparison (1)
  • 1.7.10. Autonomous Driving Dataset Product Comparison (1)
  • 1.7.11. Autonomous Driving Dataset Product Comparison (2)
  • 1.7.12. Autonomous Driving Dataset Product Comparison (3)
  • 1.7.12. Autonomous Driving Dataset Product Comparison (3)
  • 1.7.13. Autonomous Driving Dataset Product Comparison (4)
  • 1.7.14. Autonomous Driving Dataset Product Comparison (5)
  • 1.7.15. Autonomous Driving Dataset Product Comparison (6)
  • 1.7.16. Data Training Dataset Suppliers and Product List (1)
  • 1.7.17. Data Training Dataset Suppliers and Product List(2)
  • 1.7.18. Data Training Dataset Suppliers and Product List(3)
  • 1.7.19. Data Training Dataset Suppliers and Product List(4)
  • 1.7.20. Data Training Dataset Suppliers and Product List(5)
• 1.8. Construction of Intelligent Driving General Algorithm : Autonomous Driving System Integration and Engineering Strategy
  • 1.8.1. Autonomous Driving Algorithm Classification
  • 1.8.2. Autonomous Driving Perception Algorithm - Visual Perception
  • 1.8.3. LiDAR Perception (1)
  • 1.8.3. LiDAR Perception (2)
  • 1.8.4. Radar Perception
  • 1.8.5. Autonomous Driving Perception Algorithm-Multi-sensor Fusion Perception
  • 1.8.6. Advantages and Disadvantages Comparison of Pre/ Middle/ Post Fusion
  • 1.8.7. Autonomous Driving Perception Route-BEV Perception System
  • 1.8.8. Autonomous Driving Perception Technology(1): BEV Transformer Large Model (1)
  • 1.8.9. Autonomous Driving Perception Technology(1): BEV Transformer Large Model(2)
  • 1.8.10. Autonomous Driving Perception Technology(2): Occupancy Network
  • 1.8.11. Domestic Intelligent Driving Perception System Market Trends: BEV + Transformer Accelerate Boarding to Assist "Heavy Perception, Light Map"
  • 1.8.12. OEM's Perception Algorithm: Full Fusion Algorithm of RISING AUTO
  • 1.8.13. OEM's Perception Algorithm: Xpeng XNet Deep Visual Neural Network(BEV + Transformer)
  • 1.8.14. OEM's Perception Algorithm: Xpeng XNet Deep Visual Neural Network(BEV + Transformer)
  • 1.8.15. OEMs' Application of Autonomous Driving Perception Model
  • 1.8.16. Tier1s' Application of Autonomous Driving Perception Model
• 1.9. Intelligent Driving Terminal-cloud Integration: Data Closed-loop
  • 1.9.1. The Development Process of High-level Autonomous Driving Evolves from the V-model-based to the Data-driven
  • 1.9.2. Importance of Closed-loop Data for L3/L4 Autonomous Driving
  • 1.9.3. Data Closed-loop is Key to Mass Implmentation of City NOA
  • 1.9.4. Process of Baidu Full-link Data Closed Loop Technology
  • 1.9.5. Baidu Full-link Data Closed Loop Solution: Autonomous Driving Toolchain
  • 1.9.6. Momenta Flywheel Model
  • 1.9.7. iMotion's Data Closed Loop and Cloud Platform Network
  • 1.9.8. Data Closed Loop Solution of Black Sesame Technologies
  • 1.9.9. Data Closed Loop Platform of PhiGent Robotics
  • 1.9.10. List of Autonomous Driving Data Closed-loop Providers and Products (1)
  • 1.9.11. List of Autonomous Driving Data Closed-loop Providers and Products (2)
  • 1.9.12. List of Autonomous Driving Data Closed-loop Providers and Products (3)
• 1.10. Intelligent Driving Terminal-Cloud Integration: Data Collection & Annotation
  • 1.10.1. Development Trends of Autonomous Driving Data Collection and Labeling Market
  • 1.10.2. Data Collection and Annotation Industry Chain: Upstream and Downstream Structure and Role
  • 1.10.3. Data Collection & Annotation Platform: Architecture Design
  • 1.10.4. Data Collection & Annotation Platform: Difficulties of Data Collection
  • 1.10.5. Data Collection & Annotation Platform: Data Collection Process and Method
  • 1.10.6. Data Collection & Annotation Platform: Data Collection & Annotation Process
  • 1.10.7. Data Collection & Annotation Platform: Backend Simulation of Data Collection
  • 1.10.8. Five Stages of Intelligent Driving Data Annotation Development
  • 1.10.9. L0/L1 Stage of Intelligent Driving Data Annotation: Data Crowdsourcing
  • 1.10.10. L0/L1 Stage of Intelligent Driving Data Annotation: Data Crowdsourcing
  • 1.10.11. L2/L3 Stage of Intelligent Driving Data Annotation: ChatGPT and Other Large Models Introduced to Intelligent and Semi-Automated Annotation
  • 1.10.12. L2/L3 Stage of Intelligent Driving Data Annotation: Automakers Become Mainstay in Intelligent and Semi-Automated Annotation
  • 1.10.13. New Trend of Intelligent Driving Data Annotation: BEV & 4D Annotation
  • 1.10.14. New Trend of Intelligent Driving Data Annotation: Data Simulation Synthesis for Corner Case Pain Points
  • 1.10.15. New Trend of Intelligent Driving Data Annotation: End-Cloud Integrated Intelligent Driving Solution with End-to-End Large Model
  • 1.10.16. AI Data Annotation Company Ranks in China
  • 1.10.17. Xpeng Self-develops Automatic Annotation System
  • 1.10.18. Appen MatrixGo Platform Data Loopback
  • 1.10.19. Appen MatrixGo Invests in Mindtech to Expand Corner Case Applications Based on Synthetic Data
  • 1.10.20. Example of 4D Data Annotation for Appen MatrixGo Platform
  • 1.10.21. Haomo.ai DriveGPT Dramatically Reduces Annotation Costs
  • 1.10.22. Huawei Octopus Data Automatic Annotation Service
  • 1.10.23. Haitian Ruisheng Autonomous Driving Data Collection & Annotation Business (1)
  • 1.10.24. Haitian Ruisheng Autonomous Driving Data Collection & Annotation Business (2)
  • 1.10.25. EXCEEDDATA Vehicle-side Data Acquisition Architecture
  • 1.10.26. EXCEEDDATA Vehicle-Cloud Link Empowering Data Acquisition and Storage
  • 1.10.27. EXCEEDDATA Corner Cases Solution Mechanisms
  • 1.10.28. CATARC "Automotive Big Data Algorithm Service Platform"
  • 1.10.29. Autonomous Driving Data Collection & Annotation Tool Software Suppliers and Product List (1)
  • 1.10.30. Autonomous Driving Data Collection & Annotation Tool Software Suppliers and Product List (2)
  • 1.10.31. Autonomous Driving Data Collection & Annotation Tool Software Suppliers and Product List (3)
  • 1.10.32. Autonomous Driving Data Collection & Annotation Tool Software Suppliers and Product List (4)
  • 1.10.33. Autonomous Driving Data Collection & Annotation Tool Software Suppliers and Product List (5)
• 1.11. Intelligent Driving Terminal-Cloud Integration: Simulation Testing: Scenario Library
  • 1.11.1. Data Sources for Autonomous Driving Scenario Library
  • 1.11.2. Automatic Generation of Autonomous Driving Scene Library
  • 1.11.3. Autonomous Driving Scene Library Format Standard
  • 1.11.4. Building Process of Autonomous Driving Scenario Library
  • 1.11.5. Construction of Autonomous Driving Test and Evaluation System (1)
  • 1.11.6. Construction of Autonomous Driving Test and Evaluation System (2)
  • 1.11.7. Suppliers and Standardization Organizations for Autonomous Driving Scenario Library (1)
  • 1.11.8. Suppliers and Standardization Organizations for Autonomous Driving Scenario Library (2)
• 1.12. Intelligent Driving Terminal-Cloud Integration: Simulation Testing: Simulation Platform
  • 1.12.1. Why Autonomous Driving Simulation Tests?
  • 1.12.2. Intelligent Connected Vehicle Simulation Testing Tools and Platform Market Size
  • 1.12.3. Autonomous Driving Simulation Toolchain
  • 1.12.4. Autonomous Driving Simulation Testing Trend (1)
  • 1.12.5. Autonomous Driving Simulation Testing Trend (2)
  • 1.12.6. Autonomous Driving Simulation Testing Trend (3)
  • 1.12.7. Autonomous Driving Simulation Testing Trend (4)
  • 1.12.8. Autonomous Driving Simulation Testing Trend (5)
  • 1.12.9. Global Mainstream Autonomous Driving Simulation Software Companies
  • 1.12.10. Suppliers and Products of Autonomous Driving Simulation Software: Traffic Flow Simulation
  • 1.12.11. Suppliers and Products of Autonomous Driving Simulation Software: Vehicle Simulation (1)
  • 1.12.12. Suppliers and Products of Autonomous Driving Simulation Software: Vehicle Simulation (2)
  • 1.12.13. Suppliers and Products of Autonomous Driving Simulation Software: Vehicle Simulation (3)
• 1.13. Intelligent Driving Terminal-Cloud Integration: Cloud Native and Storage Platform
  • 1.13.1. Autonomous Driving Storage Platform
  • 1.13.2. ETAS Ladder Platform (1)
  • 1.13.3. ETAS Ladder Platform (2)
  • 1.13.4. Alibaba Cloud ACK@Edge Facilitates DeepRoute.ai's Vehicle-Cloud Integrated Cooperation
  • 1.13.5. Alibaba Cloud ACK Cloud-Native AI Suite Powers Haomo.ai AI's Platform
• 1.14. Intelligent Driving Terminal-Cloud Integration: HD Map
  • 1.14.1. Urban NOA Becomes A New Battlefield in Passenger Car Autonomous Driving
  • 1.14.2. Passenger Car Map Solution 1 with Urban NOA: HD Map
  • 1.14.3. Passenger Car Map Solution 2 with Urban NOA: Light HD Map (1)
  • 1.14.4. Passenger Car Map Solution 2 with Urban NOA: Light HD Map (2)
  • 1.14.5. Passenger Car Map Solution 2 with Urban NOA: Cloud Map
  • 1.14.6. Multi-source Fusion Autonomous Driving Maps can effectively Solve the Problem of Urban NOA
  • 1.14.7. Tier 1 Advanced Assisted Driving Map Solution: Baidu Mapping Technology (1)
  • 1.14.8. Tier 1 Advanced Assisted Driving Map Solution: Baidu Mapping Technology (2)
  • 1.14.9. Tier 1 Advanced Assisted Driving Map Solution: DeepRoute-Driver 3.0 (1)
  • 1.14.10. Tier 1 Advanced Assisted Driving Map Solution: DeepRoute-Driver 3.0 (2)
  • 1.14.11. Tier 1 Advanced Assisted Driving Map Solution: MAXIEYE Hyperspace
  • 1.14.12. Tier 1 Advanced Assisted Driving Map Solution: MAXIEYE automated mapping memory
  • 1.14.13. Tier 1 Advanced Assisted Driving Map Solution: JueFX + Horizon Robotics
  • 1.14.14. Tier 1 Advanced Assisted Driving Map Solution: Huawei
  • 1.14.5. Advanced Assisted Driving Loading Solution for OEMs (1)
  • 1.14.6. Advanced Assisted Driving Loading Solution for OEMs (2)
  • 1.14.7. Advanced Assisted Driving Map Solution: Mainstream Map Providers Build Map in Advance
  • 1.14.8. Advanced Assisted Driving Map Solution: Some Players Build Map Online with Algorithms (1)
  • 1.14.9. Advanced Assisted Driving Map Solution: Some Players Build Map Online with Algorithms (2)
• 1.15. Intelligent Driving Assistance Software: ADAS Performance Evaluation
  • 1.15.1. Vehicle ADAS Power Consumption Evaluation Software Requirements
  • 1.15.2. Vehicle ADAS Performance Evaluation Tool: ViCANdo Extended Tool Set (ICVT)
  • 1.15.3. Polelink Information Intelligent Driving Test Solution
  • 1.15.4. List of ADAS Performance Assessment Software Vendors and Products
• 1.16. Intelligent Driving Assistance Software: ADAS Data Recording
  • 1.16.1. ADAS Data Recording Requirements (Validation Test Link)
  • 1.16.2. ADAS Data Logging Requirements (Post-delivery)
  • 1.16.3. Definition of L3 Autonomous Driving System
  • 1.16.4. What Are The Requirements of L3 System for Data Logging?
  • 1.16.5. NI Completes ADAS Verification by Cooperating with Others
  • 1.16.6. Vector's Solution for ADAS Data Logging System
  • 1.16.7. List of Data Logging Tool Software Providers and Products (1)
  • 1.16.8. List of Data Logging Tool Software Providers and Products (2)
  • 1.16.9. List of Data Logging Tool Software Providers and Products (3)

2. How to Build Intelligent Cockpit Software System?

• 2.1. Overall Software and Hardware Architecture of Intelligent Cockpit
• 2.2. Basic Software: Automotive Non- RTOS (in Narrow Sense)
  • 2.2.1. Intelligent Cockpit Operating System: System Framework
  • 2.2.2. Intelligent Cockpit Operating System : Underlying Core OS
  • 2.2.3. Summary of Intelligent Cockpit Underlying OS for Auto Companies
  • 2.2.4. Market Share of Cockpit Operating Systems for New Vehicles
  • 2.2.5. Non- RTOS (in Narrow Sense) Suppliers and Product List (1)
  • 2.2.6. Non- RTOS (in Narrow Sense) Suppliers and Product List (2)
• 2.3. Basic Software: Intelligent Cockpit Operating System (in Broad Sense)
  • 2.3.1. Intelligent Cockpit Operating System (in Broad Sense): Secondary Development Based on Underlying OS
  • 2.3.2. Intelligent Cockpit Operating System (in Broad Sense): Evolve from Cockpit OS to Vehicle OS
  • 2.3.3. Market Prospect of Intelligent Cockpit Operating System (in Broad Sense)
  • 2.3.4. Tier1 Solution (1): Thundersoft Cockpit Middleware OS Software Architecture
  • 2.3.5. Tier1 Solution (2): Banma Zhixing AliOS Intelligent Cockpit Operating System
  • 2.3.6. Tier1 Solution (3): Huawei Harmony Cockpit Software Platform - HOS-A
  • 2.3.7. Tier1 Solution (4): Megatronix Cockpit Solution
  • 2.3.8. Tier1 Solution (5): ECARX Cross-platform General Operating System Software Framework - EAS Core
  • 2.3.9. Tier1 Solution (6): E Planet Technology Venus Intelligent Vehicle Software Platform
  • 2.3.10. List of Intelligent Cockpit General Operating System Providers and Products (1)
  • 2.3.11. List of Intelligent Cockpit General Operating System Providers and Products (2)
  • 2.3.12. List of Intelligent Cockpit General Operating System Providers and Products (3)
  • 2.3.13. List of Intelligent Cockpit General Operating System Providers and Products (4)
  • 2.3.14. List of Intelligent Cockpit General Operating System Providers and Products (5)
  • 2.3.15. OEM Solution (1): Xpeng Motor X-EEA 3.0 Architecture
  • 2.3.16. OEM Solution (2): SAIC Z-ONE SOA Software Platform
  • 2.3.17. OEM Solution (3): Geely Galaxy NOS
  • 2.3.18. OEM Solution (4): ZEEKR OS Intelligent Cockpit
  • 2.3.19. OEM Solution (5): Great Wall Self-developed Cockpit Operating System - GC-OS
• 2.4. Basic Software: Hypervisor
  • 2.4.1. Current Fused Domains Isolation Solutions for Intelligent Cockpits
  • 2.4.2. Hypervisor Mainly Used in Vehicles
  • 2.4.3. Application of Smart Cockpit Hypervisors in China
  • 2.4.4. Hypervisor Alternative Solution for Intelligent Cockpits: Hard Isolation Solution
  • 2.4.5. Advantages and Disadvantages of Intelligent Cockpit Hardware Isolation Solution
  • 2.4.6. Prospects of Global Automotive Hypervisor Market
  • 2.4.7. Global Hypervisor Suppliers and Their Product Lists (1)
  • 2.4.8. Global Hypervisor Suppliers and Their Product Lists (2)
  • 2.4.9. Global Hypervisor Suppliers and Their Product Lists (3)
  • 2.4.10. Global Hypervisor Suppliers and Their Product Lists (4)
  • 2.4.11. Global Hypervisor Suppliers and Their Product Lists (5)
  • 2.4.12. Global Hypervisor Suppliers and Their Product Lists (6)
  • 2.4.13. Chinese Hypervisor Suppliers and Their Product Lists
• 2.5. Application Algorithm: Application of GPT Model in Intelligent Cockpit
  • 2.5.1. OEMs Actively Promote Chat GPT and Other Large AI Model Platforms to Get on Smart Cockpit
  • 2.5.2. Application Field of Large AI Model in Automotive
  • 2.5.3. GPT Model Layout of Tier 1 Suppliers (1): Generative AI Model
  • 2.5.4. GPT Model Layout of Tier 1 Suppliers (2): Generative AI Model
  • 2.5.5. GPT Model Layout of Tier 1 Suppliers (3): Generative AI Model
  • 2.5.6. Large AI Model Layout Modes of OEMs
  • 2.5.7. Application of Large AI Model in Vehicles (1)
  • 2.5.8. Application of Large AI Model in Vehicles (2)
  • 2.5.9. Application of Large AI Model in Vehicles (3)
  • 2.5.10. Application of Large AI Model in Vehicles (4)
  • 2.5.11. Application of Large AI Model in Vehicles (5)
  • 2.5.12. Application of Large AI Model in Vehicles (6)
• 2.6. Application Algorithm: UI Design Software
  • 2.6.1. Overview of Vehicle Interface Design
  • 2.6.2. Classification of HMI Design
  • 2.6.3. Market Prospects of Cockpit HMI UI/UX Design
  • 2.6.4. Automakers Apply 3D Engines to Intelligent Cockpit
  • 2.6.5. Layout and Business Model of Automotive 3D Engine Application in Intelligent Cockpit
  • 2.6.6. Application of 3D Engine in Vehicles (1)
  • 2.6.7. Application of 3D Engine in Vehicles (1)
  • 2.6.8. Application of 3D Engine in Vehicles (1)
  • 2.6.9. Application of 3D Engine in Vehicles (2)
  • 2.6.10. Application of 3D Engine in Vehicles (3)
  • 2.6.11. Application of 3D Engine in Vehicles (4)
  • 2.6.12. Application of 3D Engine in Vehicles (5)
  • 2.6.13. Application of 3D Engine in Vehicles (6)
  • 2.6.14. Application of 3D Engine in Vehicles (7)
  • 2.6.15. Application of 3D Engine in Vehicles (8)
  • 2.6.16. Application of 3D Engine in Vehicles (9)
  • 2.6.17. HMI Design Software Suppliers (1)
  • 2.6.18. HMI Design Software Suppliers (2)
  • 2.6.19. HMI Design Software Suppliers (3)
  • 2.6.20. HMI Design Software Suppliers (4)
  • 2.6.21. HMI Design Software Suppliers (5)
• 2.7. Application Algorithm: Voice Software
  • 2.7.1. Overview of Human Computer Interaction
  • 2.7.2. Overview of In-vehicle Voice Interaction Technology
  • 2.7.3. Global and Chinese In-vehicle Voice Players
  • 2.7.4. Market Prospects of In-vehicle Voice
  • 2.7.5. Advanced Evolution of HMI Driven by New technologies such as AI Large Model
  • 2.7.6. Multimodal Interactive Software Supply Trend: Shift from Single Module to Integrated Supply
  • 2.7.7. Voice Interaction Development Trends (1): Evolve from Single Interaction Supplier to Multimodal Interaction System Supplier
  • 2.7.8. Voice Interaction Development Trends (1): Evolve from Single Interaction Supplier to Multimodal Interaction System Supplier
  • 2.7.9. Voice Interaction Development Trends (2): Establish A Solid Foothold in Segments and Enhance Competitive Edges
  • 2.7.10. Voice Interaction Development Trends (3): Extend Product Chain and Integrated Layout in Supply Chain
  • 2.7.11. Voice Interaction Development Trends (4): Pre-integration Collaboration
  • 2.7.12. Vehicle Voice Software Suppliers and Products List (1)
  • 2.7.13. Vehicle Voice Software Suppliers and Products List (2)
  • 2.7.14. Vehicle Voice Software Suppliers and Products List (3)
  • 2.7.15. Vehicle Voice Software Suppliers and Products List (4)
  • 2.7.16. Vehicle Voice Software Suppliers and Products List (5)
• 2.8. Application Algorithm: Acoustics Software
  • 2.8.1. Summary of Business Models of Acoustic Software Vendors
  • 2.8.2. Some Automakers Self-develop Tuning Systems for A Say in Acoustics Technology
  • 2.8.3. Exploration of Acoustic Software Business Model
  • 2.8.4. New Requirement of Automotive Acoustics
  • 2.8.5. Typical Case (1)
  • 2.8.6. Typical Case (2)
  • 2.8.7. Typical Case (3)
  • 2.8.8. Typical Case (4)
  • 2.8.9. Typical Case (5)
  • 2.8.10. Acoustic Software Suppliers and Products List (1)
  • 2.8.11. Acoustic Software Suppliers and Products List (2)
• 2.9. Application Algorithm: AR HUD Software
  • 2.9.1. Overview of AR-HUD Products and Technologies
  • 2.9.2. AR-HUD Optical Waveguide Technology
  • 2.9.3. AR Engine Software Technology
  • 2.9.4. AR-HUD Applied Vehicle Models
  • 2.9.5. AR-HUD Ushered in A Period of Fast Adoption in Vehicles
  • 2.9.6. Core Technology of AR HUD Industry: Supporting Software of AR-HUD Is More And more important
  • 2.9.7. Main Direction of AR-HUD Software Upgrade
  • 2.9.8. AR Creator Becomes Core Element of AR-HUD, Software Capability Is Especially Important
  • 2.9.9. AR Creator Integrates into Head Unit System
  • 2.9.10. Typical Case (1)
  • 2.9.11. Typical Case (2)
  • 2.9.12. Typical Case (3)
  • 2.9.13. AR-HUD Software Suppliers and Products List (1)
  • 2.9.14. AR-HUD Software Suppliers and Products List (2)
  • 2.9.15. AR-HUD Software Suppliers and Products List (3)
• 2.10. Application Algorithm: DMS/OMS Software
  • 2.10.1. Overview of DMS (1)
  • 2.10.2. Overview of DMS (2)
  • 2.10.3. DMS Software Technology
  • 2.10.4. Market Prospects of DMS Software Technology
  • 2.10.5. DMS Visual Perception Algorithm Suppliers and Products List (1)
  • 2.10.6. DMS Visual Perception Algorithm Suppliers and Products List (2)
  • 2.10.7. DMS Visual Perception Algorithm Suppliers and Products List (3)
• 2.11. Application Algorithm: Face and Gesture Recognition Software
  • 2.11.1. Overview of Face Recognition Interaction Technology
  • 2.11.2. Major Global and Chinese Face Recognition Players
  • 2.11.3. Market Prospects of Vehicle Face Recognition
  • 2.11.4. Overview of Gesture Recognition and Interaction Technology
  • 2.11.5. Major Global and Chinese Gesture Recognition Players
• 2.12. Intelligent Cockpit Terminal-Cloud Integration: Vehicle Cloud Platform Software
  • 2.12.1. Conventional V2X Technology Platform Architecture
  • 2.12.2. Bottleneck of Conventional V2X Technology Platform
  • 2.12.3. Next Generation Vehicle Cloud Technology Platform
  • 2.12.4. Next Generation Vehicle Cloud Technology Platform: Achieving High-precision and High-quality Data Collection
  • 2.12.5. Four Major Product Modules of EXCEEDDATA
  • 2.12.6. Data Acquisition Platform Architecture of EXCEEDDATA V2X
  • 2.12.7. Application Scenario Prospects of Automotive Cloud Services in Intelligent Connected Vehicles
  • 2.12.8. Building Model of Auto Companies Cloud Services: Self-built Private Cloud, Procurement of Public Cloud (Hybrid Cloud)
  • 2.12.9. Status Quo of Cloud Service Platform Market Development
  • 2.12.10. Cloud Service Platform Suppliers and Products List (1)
  • 2.12.11. Cloud Service Platform Suppliers and Products List (2)
  • 2.12.12. Cloud Service Platform Suppliers and Products List (3)
  • 2.12.13. Development Status of Remote Cloud Diagnosis
  • 2.12.14. Remote Cloud Diagnosis Provider Solutions
  • 2.12.15. EXCEEDDATA "Vehicle Remote Intelligent Diagnosis System Solution"
  • 2.12.16. EXCEEDDATA " Active and Intelligent Diagnosis Solution"
  • 2.12.17. EXCEEDDATA "Intelligent Diagnosis Data Closed Loop"
• 2.13. Intelligent Cockpit Terminal-Cloud Integration: Cloud Native Platform
  • 2.13.1. Cloud Native Development Course
  • 2.13.2. Cloud Native Layout Modes of OEMs
  • 2.13.3. Cloud Native Layout Cases of OEMs (1)
  • 2.13.4. Cloud Native Layout Cases of OEMs (2)
  • 2.13.5. Cloud Native Layout Cases of OEMs (3)
  • 2.13.6. Cloud Native Layout Cases of OEMs (4)
  • 2.13.7. Cloud Native Product Cases