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市場調查報告書
商品編碼
2045770

汽車智慧駕駛座平台市場：市場機會、成長要素、產業趨勢分析及2026-2035年預測

Automotive Intelligent Cockpit Platform Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2026 - 2035
出版日期: | 出版商: Global Market Insights Inc. | 英文 280 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球汽車智慧駕駛座平台市場預計到 2025 年將達到 270 億美元，並以 11.6% 的複合年成長率成長，到 2035 年將達到 800 億美元。

汽車智慧座艙平台市場-IMG1

由於互聯出行技術的快速普及和向軟體定義車輛（SDV）的轉型，汽車產業正獲得顯著發展動力。汽車製造商正日益將資訊娛樂系統、導航平台、高級駕駛輔助系統（ADAS）、連網工具和車輛控制操作整合到統一的駕駛座生態系統中，為駕駛和乘客提供無縫的數位化體驗。消費者對智慧、互動和個人化車內環境日益成長的期望進一步加速了市場擴張。此外，人工智慧、雲端運算、機器學習和即時數據處理技術的不斷進步，正將車內轉變為一個高度適應性強的數位化平台。這些創新正在提升語音控制、預測性客製化、多螢幕管理以及整體系統反應速度。有關網路安全、駕駛員安全和拖車管理的監管要求也促使製造商開發更安全、更可靠的駕駛座架構。因此，汽車智慧駕駛座平台市場正在演變為一個高度整合、人工智慧主導、以軟體為中心的生態系統，能夠為整個現代車輛提供增強的互聯性、便利性和用戶參與度。

市場範圍
開始年份 2025
預測期 2026-2035
上市時的市場規模 270億美元
預計金額 800億美元
複合年成長率 11.6%

隨著汽車製造商將先進的數位體驗和增強的軟體功能列為優先事項，汽車智慧駕駛座平台產業正經歷著快速的技術變革。汽車製造商正在增加對集中式運算架構的投資，以使多個車輛系統能夠透過統一的軟體平台運作。這種轉變使製造商能夠提高營運效率、降低硬體複雜性並縮短功能部署週期。隨著數位顯示器、智慧感測器、語音控制系統和互聯服務的日益整合，用戶互動和車內便利性也在不斷提升。此外，對空中下載 (OTA) 軟體更新和即時系統診斷日益成長的需求，正在推動乘用車和商用車採用智慧駕駛座技術。汽車製造商與科技公司之間日益密切的合作，進一步加速了市場的創新。

預計到2025年，乘用車市佔率將達到68%。這一細分市場持續引領市場成長，主要得益於消費者對先進資訊娛樂系統、聯網汽車技術和互動式數位介面的日益成長的需求。智慧駕駛座平台是現代乘用車設計的核心，它能夠將數位儀錶叢集、資訊娛樂系統、導航工具、車輛監控功能以及駕駛輔助資訊的視覺化整合到一個統一的操作環境中。汽車製造商越來越注重提供沉浸式且方便用戶使用的車內體驗，並藉助即時運算能力和增強的圖形性能來實現這一目標。對個人化駕駛體驗、智慧互聯和整合式出行解決方案日益成長的需求，也進一步推動了全球汽車市場乘用車細分市場的強勁成長。

截至2025年，高級整合市場將佔據49.5%的市場。由於汽車行業越來越傾向於採用能夠將多種駕駛座功能整合到集中式管理系統中的整合運算架構，該細分市場正在快速擴張。高級整合平台使聯網汽車。汽車製造商正在加強對這些平台的採用力度，以加快產品開發週期並滿足對功能豐富的數位化座艙環境日益成長的需求。半導體技術的持續進步和軟體最佳化正在進一步推動該細分市場的成長。

中國汽車智慧駕駛座平台市場佔54%的全球佔有率，預計2025年市場規模將達到43億美元。中國汽車的快速數位化、消費者對先進汽車技術的強勁需求以及互聯出行解決方案的日益普及，持續推動區域市場的成長。不斷加快的都市化和消費者對智慧車載體驗日益成長的偏好，促使汽車製造商將先進的駕駛座系統整合到各種車型中。國內汽車製造商和技術主導汽車相關企業正大力投資於數位化汽車生態系統，旨在提升資訊娛樂功能、乘員監控、互聯性和駕駛輔助系統的可視性。此外，中國強大的製造業實力、蓬勃發展的電動車產業以及智慧運輸技術的快速普及，正鞏固其作為亞太地區智慧駕駛座平台研發領先創新中心的地位。

目錄

第1章：調查方法

第2章執行摘要

第3章：行業洞察

  • 工業生態系分析
    • 供應商情況
    • 利潤率分析
    • 成本結構
    • 每個階段增加的價值
    • 影響價值鏈的因素
    • 中斷
  • 影響產業的因素
    • 促進因素
      • 擴大5G網路部署
      • 消費者對互聯體驗的需求日益成長
      • 人們越來越關注個人化和改善用戶體驗
      • 電動汽車的普及和安全通訊的需求
    • 產業潛在風險與挑戰
      • 硬體限制
      • 軟體更新的挑戰
    • 市場機遇
      • 軟體定義車輛（SDV）的普及
      • 人工智慧汽車助理整合
      • 自動駕駛和半自動駕駛介面的成長
  • 成長潛力分析
  • 技術與創新展望
    • 最新科技趨勢
    • 新技術
  • 價格分析
    • 對過去價格趨勢的分析
    • 定價策略：按業務類型分類
  • 監理情勢
    • 北美洲
      • 汽車資料隱私與網路安全法規（CCPA/CPRA）
      • 美國國家公路交通安全管理局 (NHTSA) 車輛網路安全指南
      • FCC 和聯網汽車通訊標準
      • 加拿大數位憲章實施法案（CPPA）
    • 歐洲
      • 歐盟一般資料保護規則（GDPR）
      • 歐盟網路安全法和聯合國歐洲經濟委員會WP.29條例
      • 歐洲資料法（存取聯網汽車資料）
      • 德國道路交通法（自動駕駛框架）
    • 亞太地區
      • 中國網路安全法（CSL）
      • 中國個人資料保護法（PIPL）
      • 日本個人資訊保護法（APPI）
      • 韓國個人資訊保護法（PIPA）
      • 印度數位個人資料保護法（DPDP 法案）
    • 拉丁美洲
      • 巴西通用資料保護法（LGPD）
      • 墨西哥聯邦個人資料保護法
      • 阿根廷個人資料保護法（第25.326號法律）
      • 區域間流動性和數據整合計劃
    • 中東和非洲
      • 阿拉伯聯合大公國聯邦資料保護法（PDPL）
      • 沙烏地阿拉伯個人資料保護法（PDPL-SDAIA框架）
      • 南非個人資料保護法（POPIA）
  • 波特的分析
  • PESTLE分析
  • 專利分析
  • 成本細分分析
  • 人工智慧和生成式人工智慧對市場的影響
    • 利用人工智慧改造現有經營模式
    • 基於細分市場的生成式人工智慧的應用案例和部署藍圖
    • 風險、限制和監管考量
  • 永續性和環境方面
    • 永續發展計劃
    • 減少廢棄物策略
    • 生產中的能源效率
    • 環保舉措
    • 考慮碳足跡
  • 預測假設和情境分析
    • 基本案例：驅動複合年成長率的關鍵宏觀經濟與產業變量
    • 樂觀情境：宏觀經濟與產業的利多因素
    • 悲觀情景：宏觀經濟放緩或產業逆風

第4章 競爭情勢

  • 介紹
  • 企業市佔率分析
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東和非洲
  • 主要市場公司的競爭分析
  • 競爭定位矩陣
    • 併購
    • 夥伴關係和聯盟
    • 新產品發布
    • 業務拓展計劃及資金籌措
  • 按公司規模進行基準測試
    • 排名分類標準與遴選標準
    • 按銷售額、地區和創新能力分類的層級定位矩陣。

第5章 市場估價與預測：依車輛類型分類，2022-2035年

  • 搭乘用車
  • 商用車輛

第6章 市場估計與預測：依組件分類，2022-2035年

  • 硬體
    • 顯示系統
    • 感應器
    • ECU
    • 其他
  • 軟體
  • 服務

第7章 市場估計與預測：依平台分類，2022-2035年

  • 基於SoC的
  • 高階整合
  • 個人化

第8章 市場估計與預測：依應用領域分類，2022-2035年

  • 資訊娛樂
  • 導航
  • 駕駛輔助
  • 連接與通訊
  • 空調
  • 其他

第9章 市場估計與預測：依地區分類，2022-2035年

  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 挪威
    • 荷蘭
    • 瑞典
  • 亞太地區
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 韓國
    • 新加坡
    • 泰國
    • 印尼
    • 越南
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • 中東和非洲
    • 南非
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 土耳其

第10章：公司簡介

  • 世界公司
    • Advanced Micro Devices
    • Aptiv
    • Continental
    • Denso
    • DXC Technology Company
    • Elektrobit
    • Forvia Hella
    • Infineon Technologies
    • Intel
    • LG Electronics
    • MediaTek
    • NVIDIA
    • NXP Semiconductors
    • Panasonic Automotive Systems
    • Qualcomm Technologies
    • Robert Bosch
    • Visteon
  • 當地公司
    • Baidu
    • Desay SV Automotive
    • HiRain Technologies
    • Horizon Robotics
    • Huawei Technologies
    • Joyson Electronics
    • NavInfo
    • Neusoft
    • ThunderSoft
簡介目錄
Product Code: 11754

The Global Automotive Intelligent Cockpit Platform Market was valued at USD 27 billion in 2025 and is estimated to grow at a CAGR of 11.6% to reach USD 80 billion by 2035.

Automotive Intelligent Cockpit Platform Market - IMG1

The industry is gaining significant momentum due to the rapid adoption of connected mobility technologies and the growing transition toward software-defined vehicles. Automakers are increasingly integrating infotainment systems, navigation platforms, advanced driver assistance functions, connectivity tools, and vehicle control operations into centralized cockpit ecosystems to deliver seamless digital experiences for drivers and passengers. Rising consumer expectations for intelligent, interactive, and personalized in-vehicle environments are further accelerating market expansion. In addition, continuous advancements in artificial intelligence, cloud computing, machine learning, and real-time data processing technologies are transforming vehicle interiors into highly adaptive digital platforms. These innovations are improving voice interaction, predictive customization, multi-screen management, and overall system responsiveness. Regulatory requirements related to cybersecurity, driver safety, and distraction management are also encouraging manufacturers to develop more secure and reliable cockpit architectures. As a result, the automotive intelligent cockpit platform market is evolving toward highly integrated, AI-driven, and software-centric ecosystems capable of delivering enhanced connectivity, convenience, and user engagement across modern vehicles.

Market Scope
Start Year2025
Forecast Year2026-2035
Start Value$27 Billion
Forecast Value$80 Billion
CAGR11.6%

The automotive intelligent cockpit platform industry is witnessing rapid technological transformation as vehicle manufacturers prioritize advanced digital experiences and enhanced software functionality. Automakers are increasingly investing in centralized computing architectures that allow multiple in-vehicle systems to operate through unified software platforms. This transition is helping manufacturers improve operational efficiency, simplify hardware complexity, and accelerate feature deployment timelines. The growing integration of digital displays, smart sensors, voice-controlled systems, and connected services is also improving user interaction and in-vehicle convenience. Furthermore, rising demand for over-the-air software updates and real-time system diagnostics is supporting the expansion of intelligent cockpit technologies across passenger and commercial vehicles. Increasing collaboration between automotive manufacturers and technology companies is further accelerating innovation within the market.

The passenger vehicles segment accounted for 68% share in 2025. The segment continues to dominate due to rising consumer demand for advanced infotainment systems, connected vehicle technologies, and interactive digital interfaces. Intelligent cockpit platforms have become central to modern passenger vehicle design by enabling the integration of digital instrument clusters, infotainment systems, navigation tools, vehicle monitoring functions, and driver assistance visualization within a unified operating environment. Automakers are increasingly focusing on delivering immersive and user-friendly cabin experiences supported by real-time computing capabilities and enhanced graphical performance. Rising demand for personalized driving experiences, smart connectivity, and integrated mobility solutions is further contributing to the strong growth of the passenger vehicle segment across global automotive markets.

The high-level integration segment held a 49.5% share in 2025. The segment is expanding rapidly due to increasing industry preference for integrated computing architectures capable of combining multiple cockpit functions into a centralized system. High-level integration platforms enable automakers to unify infotainment systems, digital displays, connectivity tools, and vehicle control operations within a single framework, improving operational efficiency and reducing hardware complexity. This approach also supports faster software deployment, improved data synchronization, and enhanced system performance across connected vehicle ecosystems. Automakers are increasingly adopting these platforms to accelerate product development cycles and support the growing demand for feature-rich digital cabin environments. Continuous advancements in semiconductor technologies and software optimization are further strengthening segment growth.

China Automotive Intelligent Cockpit Platform Market held a 54% share, generating USD 4.3 billion in 2025. The country continues to lead regional market growth due to rapid automotive digitalization, strong consumer demand for advanced in-vehicle technologies, and expanding adoption of connected mobility solutions. Rising urbanization and increasing preference for intelligent cabin experiences are encouraging automotive manufacturers to integrate advanced cockpit systems across a wide range of vehicle categories. Domestic automakers and technology-focused automotive companies are heavily investing in digital vehicle ecosystems designed to improve infotainment functionality, occupant monitoring, connectivity, and driver assistance visualization. In addition, China's strong manufacturing capabilities, expanding electric vehicle industry, and rapid adoption of smart mobility technologies continue to position the country as a major innovation hub for intelligent cockpit platform development across the Asia Pacific region.

Major companies operating in the Global Automotive Intelligent Cockpit Platform Market include Robert Bosch, Continental, Panasonic, Harman International, Aptiv, EcarX, NVIDIA, Advanced Micro Devices, Denso, and Qualcomm Technologies. Companies operating in the automotive intelligent cockpit platform market are implementing multiple strategic initiatives to strengthen their market position and expand technological capabilities. Leading players are investing heavily in artificial intelligence, cloud-enabled computing systems, and software-defined vehicle platforms to improve cockpit functionality and user experience. Strategic partnerships between automotive manufacturers, semiconductor companies, and software developers are becoming increasingly important for accelerating innovation and reducing product development timelines. Many companies are also focusing on advanced display technologies, voice recognition systems, and real-time connectivity solutions to enhance digital cabin experiences. Expansion of research and development centers, increased investments in cybersecurity infrastructure, and adoption of over-the-air update technologies are further supporting competitive growth strategies.

Table of Contents

Chapter 1 Methodology

  • 1.1 Research approach
  • 1.2 Quality Commitments
    • 1.2.1 GMI AI policy & data integrity commitment
      • 1.2.1.1 Source consistency protocol
  • 1.3 Research Trail & Confidence Scoring
    • 1.3.1 Research Trail Components
    • 1.3.2 Scoring Components
  • 1.4 Data Collection
    • 1.4.1 Partial list of primary sources
  • 1.5 Data mining sources
    • 1.5.1 Paid sources
      • 1.5.1.1 Sources, by region
  • 1.6 Base estimates and calculations
    • 1.6.1 Base year calculation for any one approach
  • 1.7 Forecast model
    • 1.7.1 Quantified market impact analysis
      • 1.7.1.1 Mathematical impact of growth parameters on forecast
  • 1.8 Research transparency addendum
    • 1.8.1 Source attribution framework
    • 1.8.2 Quality assurance metrics
    • 1.8.3 Our commitment to trust

Chapter 2 Executive Summary

  • 2.1 Industry 360° synopsis, 2022 - 2035
  • 2.2 Key market trends
    • 2.2.1 Regional
    • 2.2.2 Vehicle
    • 2.2.3 Component
    • 2.2.4 Platform
    • 2.2.5 Application
  • 2.3 TAM Analysis, 2026-2035
  • 2.4 CXO perspectives: Strategic imperatives

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
    • 3.1.1 Supplier landscape
    • 3.1.2 Profit margin analysis
    • 3.1.3 Cost structure
    • 3.1.4 Value addition at each stage
    • 3.1.5 Factor affecting the value chain
    • 3.1.6 Disruptions
  • 3.2 Industry impact forces
    • 3.2.1 Growth drivers
      • 3.2.1.1 Increasing rollout of 5G networks
      • 3.2.1.2 Rising consumer demand for connected experiences
      • 3.2.1.3 Increasing emphasis on personalization and enhanced user experience
      • 3.2.1.4 Proliferation of electric vehicles g demand for secure messaging
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 Hardware limitations
      • 3.2.2.2 Software update challenges
    • 3.2.3 Market opportunities
      • 3.2.3.1 Expansion of Software-Defined Vehicles (SDVs)
      • 3.2.3.2 Integration of AI-powered In-Vehicle Assistants
      • 3.2.3.3 Growth of Autonomous and Semi-Autonomous Driving Interfaces
  • 3.3 Growth potential analysis
  • 3.4 Technology and innovation landscape
    • 3.4.1 Current technological trends
    • 3.4.2 Emerging technologies
  • 3.5 Pricing Analysis (Driven by primary research)
    • 3.5.1 Historical Price Trend Analysis
    • 3.5.2 Pricing Strategy by Player Type
  • 3.6 Regulatory landscape
    • 3.6.1 North America
      • 3.6.1.1 Vehicle Data Privacy and Cybersecurity Regulations (CCPA / CPRA)
      • 3.6.1.2 NHTSA Vehicle Cybersecurity Guidelines
      • 3.6.1.3 FCC and Connected Vehicle Communication Standards
      • 3.6.1.4 Canada Digital Charter Implementation Act (CPPA)
    • 3.6.2 Europe
      • 3.6.2.1 EU General Data Protection Regulation (GDPR)
      • 3.6.2.2 EU Cybersecurity Act & UNECE WP.29 Regulations
      • 3.6.2.3 European Data Act (Connected Vehicle Data Access)
      • 3.6.2.4 Germany Road Traffic Act (Automated Driving Framework)
    • 3.6.3 Asia Pacific
      • 3.6.3.1 China Cybersecurity Law (CSL)
      • 3.6.3.2 China Personal Information Protection Law (PIPL)
      • 3.6.3.3 Japan Act on Protection of Personal Information (APPI)
      • 3.6.3.4 South Korea Personal Information Protection Act (PIPA)
      • 3.6.3.5 India Digital Personal Data Protection Act (DPDP Act)
    • 3.6.4 Latin America
      • 3.6.4.1 Brazil General Data Protection Law (LGPD)
      • 3.6.4.2 Mexico Federal Law on Protection of Personal Data
      • 3.6.4.3 Argentina Personal Data Protection Law (Law 25.326)
      • 3.6.4.4 Regional Mobility and Data Integration Initiatives
    • 3.6.5 Middle East & Africa
      • 3.6.5.1 UAE Federal Data Protection Law (PDPL)
      • 3.6.5.2 Saudi Arabia Personal Data Protection Law (PDPL - SDAIA Framework)
      • 3.6.5.3 South Africa Protection of Personal Information Act (POPIA)
  • 3.7 Porter's analysis
  • 3.8 PESTEL analysis
  • 3.9 Patent analysis (Driven by primary research)
  • 3.10 Cost breakdown analysis
  • 3.11 Impact of AI and Generative AI on the Market
    • 3.11.1 AI Driven Disruption of Existing Business Models
    • 3.11.2 GenAI Use Cases and Adoption Roadmap by Segment
    • 3.11.3 Risks Limitations and Regulatory Considerations
  • 3.12 Sustainability and environmental aspects
    • 3.12.1 Sustainable practices
    • 3.12.2 Waste reduction strategies
    • 3.12.3 Energy efficiency in production
    • 3.12.4 Eco-friendly Initiatives
    • 3.12.5 Carbon footprint considerations
  • 3.13 Forecast assumptions & scenario analysis (Driven by Primary Research)
    • 3.13.1 Base Case- Key Macro & Industry Variables Driving CAGR
    • 3.13.2 Optimistic Scenarios- Favorable macro and industry tailwinds
    • 3.13.3 Pessimistic Scenario - Macroeconomic slowdown or industry headwinds

Chapter 4 Competitive Landscape, 2025

  • 4.1 Introduction
  • 4.2 Company market share analysis
    • 4.2.1 North America
    • 4.2.2 Europe
    • 4.2.3 Asia Pacific
    • 4.2.4 LATAM
    • 4.2.5 MEA
  • 4.3 Competitive analysis of major market players
  • 4.4 Competitive positioning matrix
  • 4.5 Key developments
    • 4.5.1 Mergers & acquisitions
    • 4.5.2 Partnerships & collaborations
    • 4.5.3 New Product Launches
    • 4.5.4 Expansion Plans and funding
  • 4.6 Company tier benchmarking
    • 4.6.1 Tier classification criteria & qualifying thresholds
    • 4.6.2 Tier positioning matrix by revenue, geography & innovation

Chapter 5 Market Estimates & Forecast, By Vehicle, 2022 - 2035 (USD Mn)

  • 5.1 Key trends
  • 5.2 Passenger vehicle
  • 5.3 Commercial vehicle

Chapter 6 Market Estimates & Forecast, By Component, 2022 - 2035 (USD Mn)

  • 6.1 Key trends
  • 6.2 Hardware
    • 6.2.1 Display systems
    • 6.2.2 Sensors
    • 6.2.3 ECUs
    • 6.2.4 Others
  • 6.3 Software
  • 6.4 Services

Chapter 7 Market Estimates & Forecast, By Platform, 2022 - 2035 (USD Mn)

  • 7.1 Key trends
  • 7.2 SoC-based
  • 7.3 High-level Integration
  • 7.4 Personalized

Chapter 8 Market Estimates & Forecast, By Application, 2022 - 2035 (USD Mn)

  • 8.1 Key trends
  • 8.2 Infotainment
  • 8.3 Navigation
  • 8.4 Driver assistance
  • 8.5 Connectivity & communication
  • 8.6 Climate control
  • 8.7 Others

Chapter 9 Market Estimates & Forecast, By Region, 2022 - 2035 (USD Mn)

  • 9.1 Key trends
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 France
    • 9.3.4 Italy
    • 9.3.5 Spain
    • 9.3.6 Russia
    • 9.3.7 Norway
    • 9.3.8 Netherlands
    • 9.3.9 Sweden
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 India
    • 9.4.3 Japan
    • 9.4.4 Australia
    • 9.4.5 South Korea
    • 9.4.6 Singapore
    • 9.4.7 Thailand
    • 9.4.8 Indonesia
    • 9.4.9 Vietnam
  • 9.5 Latin America
    • 9.5.1 Brazil
    • 9.5.2 Mexico
    • 9.5.3 Argentina
  • 9.6 MEA
    • 9.6.1 South Africa
    • 9.6.2 Saudi Arabia
    • 9.6.3 UAE
    • 9.6.4 Turkey

Chapter 10 Company Profiles

  • 10.1 Global Players
    • 10.1.1 Advanced Micro Devices
    • 10.1.2 Aptiv
    • 10.1.3 Continental
    • 10.1.4 Denso
    • 10.1.5 DXC Technology Company
    • 10.1.6 Elektrobit
    • 10.1.7 Forvia Hella
    • 10.1.8 Infineon Technologies
    • 10.1.9 Intel
    • 10.1.10 LG Electronics
    • 10.1.11 MediaTek
    • 10.1.12 NVIDIA
    • 10.1.13 NXP Semiconductors
    • 10.1.14 Panasonic Automotive Systems
    • 10.1.15 Qualcomm Technologies
    • 10.1.16 Robert Bosch
    • 10.1.17 Visteon
  • 10.2 Regional Players
    • 10.2.1 Baidu
    • 10.2.2 Desay SV Automotive
    • 10.2.3 HiRain Technologies
    • 10.2.4 Horizon Robotics
    • 10.2.5 Huawei Technologies
    • 10.2.6 Joyson Electronics
    • 10.2.7 NavInfo
    • 10.2.8 Neusoft
    • 10.2.9 ThunderSoft