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市場調查報告書
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2071296

軟體定義汽車（SDV）市場：市場機會、成長促進因素、產業趨勢分析及未來預測（2026-2035）

Software-Defined Vehicle Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2026 - 2035
出版日期: | 出版商: Global Market Insights Inc. | 英文 285 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球軟體定義汽車（SDV）市場預計到 2025 年將達到 1,985 億美元，年複合成長率為 25.6%，到 ​​2035 年將達到 18,641 億美元。

軟體定義汽車市場-IMG1

汽車產業的快速數字轉型和以軟體為中心的車輛架構的日益普及是推動市場成長的主要因素。監管趨勢和不斷發展的行業標準正促使汽車製造商提升網路安全、軟體生命週期管理和車輛互聯能力。在關鍵汽車市場，政府和產業相關人員正積極支持智慧型運輸系統(ITS)、互聯出行平台、先進安全技術和下一代汽車軟體框架的部署。隨著車輛對數位化能力的依賴性日益增強，製造商正投資於擴充性的軟體生態系統，以支援持續更新、提升使用者體驗和增強車輛智慧。向集中式運算架構的轉變也使得車輛功能的管理更加高效，同時為新的數位服務和收入來源創造了機會。對聯網汽車、高級駕駛輔助技術、基於雲端的車輛管理和軟體驅動的出行解決方案日益成長的需求，持續增強著已開發市場和新興市場軟體定義汽車市場的長期前景。

市場範圍
開始年份 2025
預測期 2026-2035
初始市場規模 1985億美元
市場規模預測 1.8641兆美元
複合年成長率 25.6%

隨著汽車製造商擴大採用集中式軟體架構來提升車輛性能和功能，軟體定義車輛（SDV）技術的實用化在全球汽車產業中持續加速。汽車製造商正致力於建立支援持續改進、遠端軟體交付、即時車輛數據處理、高級分析和智慧系統管理的整合軟體平台。這種轉變正在重新思考車輛開發策略，並使製造商能夠在車輛的整個生命週期中提供更具適應性、數位互聯的駕駛體驗。

預計到2025年，硬體市佔率將達到47%，並在2026年至2035年間以26.3%的複合年成長率成長。硬體仍然是軟體定義車輛生態系統的關鍵組成部分，它提供支援運算、感測、通訊和控制功能所需的基礎設施。該領域涵蓋了實現感知、處理、連接和車輛智慧所需的技術。隨著汽車架構的演進，硬體的設計越來越傾向於支援集中式運算環境和軟體主導的操作，而非作為獨立的機械系統運作。這種轉變正在推動對能夠支援日益複雜的數位化功能的高級車輛硬體的需求。

預計到2025年，內燃機（ICE）汽車市佔率將達到37.6%，並在2035年之前以17.9%的複合年成長率成長。雖然這些車輛傳統上以硬體為中心進行設計，但製造商正擴大融入軟體驅動功能，以提升性能、連接性、診斷能力和用戶體驗。將數位技術整合到現有汽車平臺中，正在加速軟體主導功能的應用，同時也使製造商能夠應對不斷變化的消費者期望和監管要求。因此，軟體整合到內燃機汽車中仍然是推動整體市場成長的關鍵因素。

中國軟體定義汽車（SDV）市場佔57%的全球佔有率，預計到2025年市場規模將達到414億美元。中國市場的擴張得益於其強大的汽車製造生態系統、聯網汽車技術的日益普及以及智慧出行解決方案的不斷部署。汽車製造商正在加速採用以軟體為中心的架構，以支援遠端功能、高級安全系統、自動駕駛能力和即時營運智慧。這一趨勢推動了對可擴展的軟體開發、部署和生命週期管理平台的需求，這些平台能夠支援大規模聯網汽車網路和日益複雜的汽車軟體環境。

目錄

第1章：分析方法和範圍

第2章執行摘要

第3章業界考察

  • 產業生態系分析
    • 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
      • 電動車的日益普及正在加速對「軟體優先」車輛架構的需求。
      • OTA軟體更新的廣泛應用降低了召回成本，並實現了功能的持續性。
      • 網路安全監管要求（UN R155/R156）和自動駕駛安全標準
      • 消費者對連網和個人化車載數位體驗的需求日益成長
    • 產業潛在風險與挑戰
      • 從傳統的基於 ECU 的架構過渡到集中式平台涉及高度複雜性和成本。
      • 隨著車輛軟體整合度的提高，網路安全攻擊面也不斷擴大。
      • 汽車軟體工程師和跨學科技術人才嚴重短缺。
    • 市場機遇
      • 基於訂閱的功能變現和車載應用商店生態系統作為新的收入來源
      • 將 GenAI 整合到數位駕駛座和 ADAS 中，可以創建一個新的、高利潤的軟體層。
      • 商用車和車隊管理領域的 SDV 細分市場滲透率較低，是一個具有高成長潛力的前沿領域。
  • 成長潛力分析
  • 技術與創新展望
    • 最新科技趨勢
    • 新興技術
  • 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
      • 美國國家公路交通安全管理局（NHTSA）
      • 美國聯邦通訊委員會（FCC）
      • 美國運輸部（USDOT）
      • 美國聯邦貿易委員會（FTC）資料隱私框架
      • ISO/SAE 21434 網路安全標準
    • 歐洲
      • 聯合國歐洲經濟委員會工作小組29（R155和R156）
      • 一般資料保護規則（GDPR）
      • 歐盟資料法
      • 歐盟通用安全法規（GSR）
      • ISO 26262 功能安全標準
    • 亞太地區
      • 中國的網路安全法
      • 中國的資料安全法
      • 個人資訊保護法（PIPL）
      • 日本有關汽車安全和自動駕駛的法規
      • 印度汽車產業發展計畫（AMP）
    • 拉丁美洲
      • 巴西通用資料保護法（LGPD）
      • 墨西哥關於汽車、數位旅行和旅行的法規
      • 南方共同市場數位一體化框架
      • 智慧運輸政策框架
    • 中東和非洲
      • 阿拉伯聯合大公國人工智慧戰略和數據法規
      • 沙烏地阿拉伯資料與人工智慧管理局（SDAIA）規章
      • 海灣合作理事會的智慧運輸與數位經濟框架
      • 非洲聯盟數位轉型策略
      • 非洲自由貿易區（AfCFTA）數位協議
  • 波特五力分析
  • PESTLE分析
  • 專利分析
  • 貿易數據分析
    • 進出口量及進口額趨勢
    • 主要貿易路線及關稅的影響
  • 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
    • 按細分市場分類的生成式人工智慧用例和部署藍圖
    • 風險、限制和監管考量
  • 生產能力和生產情況
    • 設備產能：按地區和主要生產商分類
    • 運轉率和擴張計劃
  • 永續性和環境方面
    • 永續計劃
    • 減少廢棄物策略
    • 生產中的能源效率
    • 具有環保意識的舉措
    • 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：宏觀經濟與產業的順風
    • 悲觀情景：宏觀經濟放緩或產業逆風

第4章 競爭情勢

  • 介紹
  • 公司市佔率分析
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東和非洲
  • 主要公司的競爭分析
  • 競爭定位矩陣
  • 主要趨勢
    • 企業合併（M&A）
    • 商業夥伴關係與合作
    • 新產品發布
    • 擴張計劃和資金籌措
  • 按公司規模進行基準測試
    • 排名分類標準與遴選標準
    • 層級定位矩陣：依收入、地區和創新能力分類

第5章 市場估算與預測：依總結類別分類（2022-2035 年）

  • 軟體
    • 資訊娛樂和遠端資訊處理軟體
    • ADAS（進階駕駛輔助系統）軟體
    • 自動駕駛軟體
    • 空中下載 (OTA) 軟體更新平台
    • 網路安全軟體
    • 連接解決方案
    • 其他
  • 硬體
    • 感應器
    • 計算硬體
    • 連接模組
    • 其他
  • 服務
    • 專業服務
    • 託管服務

第6章 市場估算與預測：依電子/電氣架構分類（2022-2035 年）

  • 分散式架構
  • 領域中心架構
  • 區域建築
  • 混合架構

第7章 市場估計與預測：依成熟度分類的SDV（2022-2035年）

  • 半SDV
  • 完整版 SDV

第8章 市場估算與預測：依應用領域分類（2022-2035 年）

  • 高級駕駛輔助系統（ADAS）/自動駕駛
  • 資訊娛樂系統/數位駕駛座
  • 遠端資訊處理連接
  • 動力傳動系統管理
  • 車輛控制和舒適系統
  • 車隊管理
  • 其他

第9章 市場估計與預測：依實施方法分類（2022-2035 年）

  • 內燃機車
  • 電動車（EV）
  • 混合動力汽車

第10章 市場估價與預測：依車輛類型分類（2022-2035 年）

  • 搭乘用車
    • 掀背車
    • 轎車
    • SUV
  • 商用車輛
    • 輕型商用車
    • MCV（中型商用車）
    • 重型商用車 (HCV)

第11章 市場估計與預測：按地區分類（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
    • UAE
    • 土耳其

第12章：公司簡介

  • 世界公司
    • Tesla
    • NVIDIA
    • Qualcomm
    • Mercedes-Benz
    • BMW
    • Volkswagen
    • General Motors
    • Robert Bosch
    • Aptiv
    • Continental
  • 當地公司
    • XPeng
    • NIO
    • Li Auto
    • Zeekr
    • BYD
    • Huawei（Intelligent Automotive BU）
    • Baidu
    • SAIC Motor
    • Hyundai Motor Company
    • Changan Automobile
簡介目錄
Product Code: 6887

The Global Software-Defined Vehicle Market was valued at USD 198.5 billion in 2025 and is estimated to grow at a CAGR of 25.6% to reach USD 1,864.1 billion by 2035.

Software-Defined Vehicle Market - IMG1

Market growth is being driven by the rapid digital transformation of the automotive industry and increasing adoption of software-centric vehicle architectures. Regulatory developments and evolving industry standards are encouraging automakers to enhance cybersecurity, software lifecycle management, and vehicle connectivity capabilities. Across major automotive markets, governments and industry stakeholders are supporting initiatives that accelerate the deployment of intelligent transportation systems, connected mobility platforms, advanced safety technologies, and next-generation automotive software frameworks. As vehicles become increasingly dependent on digital functionality, manufacturers are investing in scalable software ecosystems capable of supporting continuous updates, enhanced user experiences, and advanced vehicle intelligence. The shift toward centralized computing architectures is also enabling more efficient management of vehicle functions while creating opportunities for new digital services and revenue streams. Growing demand for connected vehicles, advanced driver assistance technologies, cloud-based vehicle management, and software-enabled mobility solutions continues to strengthen the long-term outlook for the software-defined vehicle market across both developed and emerging economies.

Market Scope
Start Year2025
Forecast Year2026-2035
Start Value$198.5 Billion
Forecast Value$1,864.1 Billion
CAGR25.6%

The practical implementation of software-defined vehicle technologies continues to accelerate across the global automotive sector as manufacturers increasingly adopt centralized software architectures to improve vehicle performance and functionality. Automotive companies are focusing on integrated software platforms that support continuous feature enhancements, remote software delivery, real-time vehicle data processing, advanced analytics, and intelligent system management. This transition is reshaping vehicle development strategies and enabling manufacturers to deliver more adaptable and digitally connected driving experiences throughout a vehicle's lifecycle.

The hardware segment accounted for 47% share in 2025 and is anticipated to grow at a CAGR of 26.3% from 2026 to 2035. Hardware remains a critical component of software-defined vehicle ecosystems by providing the infrastructure required to support computing, sensing, communication, and control functions. The segment encompasses technologies that enable perception, processing, connectivity, and vehicle intelligence. As automotive architectures evolve, hardware is increasingly designed to support centralized computing environments and software-driven operations rather than functioning as isolated mechanical systems. This transition is reinforcing demand for advanced vehicle hardware capable of supporting increasingly sophisticated digital capabilities.

The internal combustion engine (ICE) vehicles segment held a 37.6% share in 2025 and is projected to grow at a CAGR of 17.9% through 2035. Although these vehicles are traditionally associated with hardware-focused designs, manufacturers are increasingly incorporating software-enabled functionalities to enhance performance, connectivity, diagnostics, and user experience. The integration of digital technologies into existing vehicle platforms is enabling broader adoption of software-driven capabilities while helping manufacturers address evolving consumer expectations and regulatory requirements. As a result, software integration within ICE vehicles continues to represent an important component of overall market growth.

China Software-Defined Vehicle Market accounted for 57% share, generating USD 41.4 billion in 2025. Market expansion in the country is supported by its strong automotive manufacturing ecosystem, increasing adoption of connected vehicle technologies, and growing deployment of intelligent mobility solutions. Vehicle manufacturers are accelerating the implementation of software-centric architectures that support remote functionality, advanced safety systems, autonomous features, and real-time operational intelligence. This trend is driving demand for scalable software development, deployment, and lifecycle management platforms capable of supporting large networks of connected vehicles and increasingly complex automotive software environments.

Key participants operating in the global software-defined vehicle market include Mercedes-Benz, Li Auto, Hyundai Motor Company, Tesla, NIO, Volkswagen, Baidu, XPeng, BYD, and Zeekr. Companies operating in the software-defined vehicle market are pursuing a variety of strategies to strengthen their competitive position and expand market share. Investments in software development capabilities, cloud-based automotive platforms, and artificial intelligence technologies remain key priorities across the industry. Market participants are focusing on building centralized vehicle architectures that support continuous software updates, enhanced cybersecurity, and advanced digital services. Strategic collaborations with technology providers, semiconductor companies, and software developers are helping manufacturers accelerate innovation and reduce development timelines. Companies are also expanding research and development activities to improve autonomous driving functions, vehicle connectivity, and intelligent mobility solutions.

Table of Contents

Chapter 1 Research 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 Offering
    • 2.2.3 E/E Architecture
    • 2.2.4 SDV Maturity Level
    • 2.2.5 Application
    • 2.2.6 Propulsion
    • 2.2.7 Vehicle
  • 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 Surging EV Adoption Accelerating Demand for Software-First Vehicle Architectures
      • 3.2.1.2 Proliferation of OTA Software Updates Reducing Recall Costs & Enabling Continuous Feature Delivery
      • 3.2.1.3 Regulatory Mandates for Cybersecurity (UN R155/R156) & Autonomous Driving Safety Standards
      • 3.2.1.4 Rising Consumer Demand for Connected, Personalized In-Vehicle Digital Experiences
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 High Complexity & Cost of Transitioning Legacy ECU-Based Architectures to Centralized Platforms
      • 3.2.2.2 Expanding Cybersecurity Attack Surface as Vehicles Become Increasingly Software-Connected
      • 3.2.2.3 Critical Shortage of Automotive Software Engineers & Cross-Domain Technical Talent
    • 3.2.3 Market opportunities
      • 3.2.3.1 Subscription-Based Feature Monetization & In-Vehicle App Store Ecosystems as New Revenue Streams
      • 3.2.3.2 GenAI Integration in Digital Cockpit & ADAS Creating New High-Margin Software Layers
      • 3.2.3.3 Underpenetrated Commercial Vehicle & Fleet Management SDV Segment as a High-Growth Frontier
  • 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 National Highway Traffic Safety Administration (NHTSA)
      • 3.6.1.2 Federal Communications Commission (FCC)
      • 3.6.1.3 U.S. Department of Transportation (USDOT)
      • 3.6.1.4 Federal Trade Commission (FTC) Data Privacy Framework
      • 3.6.1.5 ISO/SAE 21434 Cybersecurity Standard
    • 3.6.2 Europe
      • 3.6.2.1 UNECE WP.29 (R155 & R156)
      • 3.6.2.2 General Data Protection Regulation (GDPR)
      • 3.6.2.3 EU Data Act
      • 3.6.2.4 EU General Safety Regulation (GSR)
      • 3.6.2.5 ISO 26262 Functional Safety Standard
    • 3.6.3 Asia Pacific
      • 3.6.3.1 China Cybersecurity Law
      • 3.6.3.2 China Data Security Law
      • 3.6.3.3 Personal Information Protection Law (PIPL)
      • 3.6.3.4 Japan Automotive Safety & Autonomous Driving Regulations
      • 3.6.3.5 India Automotive Mission Plan (AMP)
    • 3.6.4 Latin America
      • 3.6.4.1 Brazil General Data Protection Law (LGPD)
      • 3.6.4.2 Mexico Automotive Digital & Mobility Regulations
      • 3.6.4.3 MERCOSUR Digital Integration Framework
      • 3.6.4.4 Chile Smart Mobility Policy Framework
    • 3.6.5 Middle East & Africa
      • 3.6.5.1 UAE Artificial Intelligence Strategy & Data Regulations
      • 3.6.5.2 Saudi Data & Artificial Intelligence Authority (SDAIA) Regulations
      • 3.6.5.3 GCC Smart Mobility & Digital Economy Framework
      • 3.6.5.4 African Union Digital Transformation Strategy
      • 3.6.5.5 African Continental Free Trade Area (AfCFTA) Digital Protocol
  • 3.7 Porter's analysis
  • 3.8 PESTEL analysis
  • 3.9 Patent analysis (Driven by primary research)
  • 3.10 Trade Data Analysis (Driven by paid database)
    • 3.10.1 Import/export volume & value trends
    • 3.10.2 Key trade corridors & tariff impact
  • 3.11 Cost breakdown analysis
  • 3.12 Impact of AI and Generative AI on the Market
    • 3.12.1 AI Driven Disruption of Existing Business Models
    • 3.12.2 GenAI Use Cases and Adoption Roadmap by Segment
    • 3.12.3 Risks Limitations and Regulatory Considerations
  • 3.13 Capacity & Production Landscape (Driven by Primary Research)
    • 3.13.1 Installed Capacity by Region & Key Producer
    • 3.13.2 Capacity Utilization Rates & Expansion Pipelines
  • 3.14 Sustainability and environmental aspects
    • 3.14.1 Sustainable practices
    • 3.14.2 Waste reduction strategies
    • 3.14.3 Energy efficiency in production
    • 3.14.4 Eco-friendly Initiatives
    • 3.14.5 Carbon footprint considerations
  • 3.15 Forecast assumptions & scenario analysis (Driven by Primary Research)
    • 3.15.1 Base Case- Key Macro & Industry Variables Driving CAGR
    • 3.15.2 Optimistic Scenarios- Favorable macro and industry tailwinds
    • 3.15.3 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 Offering, 2022 - 2035 (USD Bn)

  • 5.1 Key trends
  • 5.2 Software
    • 5.2.1 Infotainment & telematics software
    • 5.2.2 Advanced Driver Assistance Systems (ADAS) software
    • 5.2.3 Autonomous driving software
    • 5.2.4 Over-the-Air (OTA) software update platforms
    • 5.2.5 Cybersecurity software
    • 5.2.6 Connectivity solutions
    • 5.2.7 Others
  • 5.3 Hardware
    • 5.3.1 Sensors
    • 5.3.2 Computing hardware
    • 5.3.3 Connectivity modules
    • 5.3.4 Others
  • 5.4 Services
    • 5.4.1 Professional Services
    • 5.4.2 Managed Services

Chapter 6 Market Estimates & Forecast, By E/E Architecture, 2022 - 2035 (USD Bn, Units)

  • 6.1 Key trends
  • 6.2 Distributed Architecture
  • 6.3 Domain Centralized Architecture
  • 6.4 Zonal Architecture
  • 6.5 Hybrid Architecture

Chapter 7 Market Estimates & Forecast, By SDV Maturity Level, 2022 - 2035 (USD Bn, Units)

  • 7.1 Key trends
  • 7.2 Semi-SDV
  • 7.3 Full SDV

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

  • 8.1 Key trends
  • 8.2 Advanced Driver Assistance Systems (ADAS) & Autonomous Driving
  • 8.3 Infotainment Systems / Digital Cockpit
  • 8.4 Telematics & Connectivity
  • 8.5 Powertrain Management
  • 8.6 Body Control & Comfort Systems
  • 8.7 Fleet Management
  • 8.8 Others

Chapter 9 Market Estimates & Forecast, By Propulsion, 2022 - 2035 (USD Bn, Units)

  • 9.1 Internal Combustion Engine (ICE) Vehicles
  • 9.2 Electric Vehicles (EVs)
  • 9.3 Hybrid Vehicles

Chapter 10 Market Estimates & Forecast, By Vehicle, 2022 - 2035 (USD Bn, Units)

  • 10.1 Key trends
  • 10.2 Passenger Vehicles
    • 10.2.1 Hatchback
    • 10.2.2 Sedan
    • 10.2.3 SUV
  • 10.3 Commercial Vehicles
    • 10.3.1 LCV (Light Commercial Vehicles)
    • 10.3.2 MCV (Medium Commercial Vehicles)
    • 10.3.3 HCV (Heavy Commercial Vehicles)

Chapter 11 Market Estimates & Forecast, By Region, 2022 - 2035 (USD Bn, Units)

  • 11.1 Key trends
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 France
    • 11.3.4 Italy
    • 11.3.5 Spain
    • 11.3.6 Russia
    • 11.3.7 Norway
    • 11.3.8 Netherlands
    • 11.3.9 Sweden
  • 11.4 Asia Pacific
    • 11.4.1 China
    • 11.4.2 India
    • 11.4.3 Japan
    • 11.4.4 Australia
    • 11.4.5 South Korea
    • 11.4.6 Singapore
    • 11.4.7 Thailand
    • 11.4.8 Indonesia
    • 11.4.9 Vietnam
  • 11.5 Latin America
    • 11.5.1 Brazil
    • 11.5.2 Mexico
    • 11.5.3 Argentina
  • 11.6 MEA
    • 11.6.1 South Africa
    • 11.6.2 Saudi Arabia
    • 11.6.3 UAE
    • 11.6.4 Turkey

Chapter 12 Company Profiles

  • 12.1 Global Players
    • 12.1.1 Tesla
    • 12.1.2 NVIDIA
    • 12.1.3 Qualcomm
    • 12.1.4 Mercedes-Benz
    • 12.1.5 BMW
    • 12.1.6 Volkswagen
    • 12.1.7 General Motors
    • 12.1.8 Robert Bosch
    • 12.1.9 Aptiv
    • 12.1.10 Continental
  • 12.2 Regional Players
    • 12.2.1 XPeng
    • 12.2.2 NIO
    • 12.2.3 Li Auto
    • 12.2.4 Zeekr
    • 12.2.5 BYD
    • 12.2.6 Huawei (Intelligent Automotive BU)
    • 12.2.7 Baidu
    • 12.2.8 SAIC Motor
    • 12.2.9 Hyundai Motor Company
    • 12.2.10 Changan Automobile