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市場調查報告書
商品編碼
2141545

自動駕駛汽車市場機會、成長要素、產業趨勢分析及2026-2035年預測

Self-driving Cars Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2026 - 2035

出版日期: | 出版商: Global Market Insights Inc. | 英文 225 Pages | 商品交期: 2-3個工作天內

價格
簡介目錄

全球自動駕駛汽車市場預計到 2025 年將達到 2,024 億美元,年複合成長率為 5.4%,到 2035 年將達到 3,546 億美元。

市場範圍
開始年份 2025
預測期 2026-2035
初始市場規模 2024億美元
預測金額 3546億美元
複合年成長率 5.4%

人們日益關注如何最大限度地降低交通風險並提高出行效率,這持續加速了自動駕駛技術的應用。支援受控測試和早期部署的法律規範為自動駕駛技術的商業化創造了新的機會。人工智慧、感測器系統和高效能運算的進步正在提升系統的可靠性和實際性能。自動駕駛車輛與智慧城市基礎設施的整合,透過互聯交通平台、車路通訊和自適應路徑規劃功能,正在推動市場發展。這些技術有助於改善交通流量、緩解擁塞並降低能耗。自動駕駛出行平台的擴展進一步推動了這一成長。這些平台正在重塑城市交通的經濟結構,提高車隊效率,同時實現可擴展的自動駕駛交通模式。隨著車輛營運商報告稱,在實施以自動化為中心的系統後,營運成本至少降低了30%,自動駕駛出行即服務(AMaaS)平台市場持續擴張。這些平台已展現出商業性可行性和擴充性,增強了人們對自動駕駛交通服務的長期信心。

預計到2025年,L3級自動駕駛市佔率將達到46%,並在2026年至2035年間以5.2%的複合年成長率成長。 L3級自動駕駛車輛正被廣泛應用於多個車型類別,因為它們能夠讓駕駛員在保持駕駛人準備的同時,部分地減輕駕駛任務的負擔。大多數自動駕駛研發專案仍專注於L3級功能,從而支撐著持續成長的市場需求。

預計到2025年,內燃機汽車市佔率將達到72%,並在2035年之前以4.8%的複合年成長率成長。這些車輛受益於成熟的製造平台,簡化了自動化整合。電動自動駕駛汽車憑藉其軟體驅動架構、先進的感測器陣列以及與集中式運算系統的兼容性,佔據了第二大市場佔有率。同時,內燃機平台也越來越依賴機械性能特性。

預計2025年,美國自動駕駛汽車市佔率將達到83%,市場規模將達336億美元。憑藉強勁的投資活動、有利的政策措施和加速的商業部署,美國正不斷鞏固其作為自動駕駛汽車發展和長期市場成長中心的地位。

目錄

第1章:調查方法

第2章執行摘要

第3章 行業洞察

  • 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
      • 交通安全和事故減少
      • 人工智慧和感測器技術的進步
      • 政府對測試的批准和監管
      • 自動駕駛出行服務的成長
    • 產業潛在風險與挑戰
      • 高昂的開發和檢驗成本
      • 區域監管不確定性
    • 市場機遇
      • 擴大機器人計程車和自動駕駛汽車服務
      • 自主物流與貨運
      • 與智慧城市基礎建設的融合
  • 成長潛力分析
  • 監理情勢
    • 北美洲
      • 美國國家公路交通安全管理局 (NHTSA) 對自動駕駛車輛的聯邦機動車輛安全標準 (FMVSS) 進行了更新
      • 美國運輸部(DOT)的自動駕駛汽車綜合計劃(AVCP)
      • 州級自動駕駛考試許可證(加州車輛管理局和內華達州車輛管理局指南)
      • 加拿大運輸部關於測試自動駕駛系統(ADS)的指導方針
    • 歐洲
      • 聯合國歐洲經濟委員會第157號法規,關於汽車車道維持系統(ALKS)
      • 歐盟通用安全法規 (GSR) 與 ADS 的型式認可有關
      • 德國聯邦汽車運輸管理局 (KBA) 頒發的 4 級營運許可證
      • 英國自動駕駛汽車法律與責任框架
    • 亞太地區
      • 中國工業和資訊化部(工信部)ICV市場准入指南
      • 日本國土交通省(MLIT)第4類許可證
      • 韓國國土交通部(MOLIT)制定的自動駕駛汽車商業化安全標準
      • 新加坡關於自動駕駛車輛的第68號技術參考文件(TR 68)
      • 印度公路運輸和公路部 (MoRTH) 發布了關於高級駕駛輔助系統 (ADAS) 的新指南
    • 拉丁美洲
      • 巴西國家交通委員會 (CONTRAN) 關於駕駛員輔助的決議
      • 墨西哥《交通與道路安全總法》(LGMSV)對自動駕駛的影響
      • 智利運輸部發布的關於自動駕駛測試的規定
      • 與聯合國世界機動車法規協調論壇(WP.29)的區域協調一致
    • 中東和非洲
      • 阿拉伯聯合大公國道路運輸管理局 (RTA) 關於自動駕駛的法規
      • 沙烏地阿拉伯電動和自動駕駛汽車技術標準(SASO)
      • 以色列運輸部關於自動駕駛車輛測試的指導方針
      • 南非智慧型運輸系統(ITS)實施標準
  • 波特的分析
  • PESTEL 分析
  • 技術與創新展望
    • 最新科技趨勢
    • 新技術
  • 價格趨勢
    • 按地區
    • 依產品
  • 生產統計
    • 生產基地
    • 消費中心
    • 出口和進口
  • 成本細分分析
    • 採購自動駕駛感測器套件(LiDAR、雷達、攝影機)
    • 高效能運算 (HPC) 和人工智慧用半導體的成本
    • 與軟體開發、檢驗和高精度測繪相關的成本。
    • 遠端操作和車輛管理基礎設施的成本
    • 監管機構類型認證和安全認證費用
    • 保險費和責任險承保範圍結構
  • 專利分析
  • 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
    • 環保舉措
    • 考慮碳足跡
  • 打入市場策略
    • 機器人計程車(旅遊即服務)與私人商業模式
    • 策略聯盟:OEM硬體與科技巨頭的軟體堆疊合作
    • 基於訂閱的收入模式(FSD/軟體即服務)
  • 主要製造商的研發投入
    • 固態LiDAR與4D成像雷達等新技術
    • 自動駕駛汽車開發中的智慧財產權和專利糾紛

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
  • 戰略展望矩陣
  • 主要進展
    • 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

第5章 市場估價與預測:依自動駕駛等級分類,2022-2035年

  • L1
  • L2
  • L3
  • L4
  • L5

第6章 市場估計/預測:推進法,2022-2035年

  • ICE
  • 電
  • 混合

第7章 市場估計與預測:依技術分類,2022-2035年

  • 基於攝影機的系統
  • 基於雷達的系統
  • 基於LiDAR的系統
  • 感測器融合系統

第8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
    • MPV
  • 商用車輛
    • 輕型商用車(LCV)
    • 中型商用車(MCV)
    • 重型商用車(HCV)

第9章 市場估計與預測:依應用領域分類,2022-2035年

  • 個人使用
  • 共享出行
  • 物流/配送
  • 大眾運輸
  • 其他

第10章 市場估價與預測: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
    • 北歐的
    • 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11章:公司簡介

  • 世界公司
    • BMW
    • Daimler AG(Mercedes-Benz)
    • Ford Motor Company
    • General Motors(GM)
    • Honda Motor
    • Hyundai Motor
    • Stellantis NV
    • Tesla
    • Toyota Motor
    • Volkswagen Group
  • 本地公司
    • BYD
    • Geely Holding Group
    • Renault-Nissan-Mitsubishi Alliance
    • SAIC Motor
    • Tata Motors
  • 新興企業/顛覆者
    • Aurora Innovation
    • Baidu
    • NIO Inc.
    • Waymo
    • XPeng Motors
簡介目錄
Product Code: 13160

The Global Self-driving Cars Market was valued at USD 202.4 billion in 2025 and is estimated to grow at a CAGR of 5.4% to reach USD 354.6 billion by 2035.

Market Scope
Start Year2025
Forecast Year2026-2035
Start Value$202.4 Billion
Forecast Value$354.6 Billion
CAGR5.4%

Increased focus on minimizing traffic-related risks and improving travel efficiency continues to accelerate adoption. Regulatory frameworks that support controlled testing and early deployment are opening new commercialization opportunities for autonomous technologies. Advancements in artificial intelligence, sensing systems, and high-performance computing are improving system reliability and real-world performance. Integration of autonomous vehicles with intelligent urban infrastructure is strengthening market momentum through connected traffic platforms, vehicle-to-infrastructure communication, and adaptive routing capabilities. These technologies are improving traffic flow, lowering congestion levels, and supporting reduced energy consumption. Growth is further supported by the expansion of autonomous mobility platforms, which are reshaping urban transportation economics and improving fleet efficiency while enabling scalable automated transport models. The autonomous mobility as a service platform market continues to expand as fleet operators report operational cost reductions of at least 30% following the adoption of automation-focused systems. These platforms are proving commercially viable and scalable, reinforcing long-term confidence in automated transportation services.

The Level 3 automation segment held a 46% share in 2025 and is forecast to grow at a CAGR of 5.2% from 2026 to 2035. Level 3 vehicles allow partial disengagement from driving tasks while ensuring driver readiness, making them widely adopted across multiple vehicle categories. A significant portion of autonomous development programs continues to focus on Level 3 functionality, supporting sustained demand.

The internal combustion engine vehicles segment accounted for 72% share in 2025 and is expected to grow at a CAGR of 4.8% through 2035. These vehicles benefit from established manufacturing platforms that simplify automation integration. Electric autonomous vehicles represent the second-largest segment due to their compatibility with software-driven architectures, advanced sensor arrays, and centralized computing systems, while ICE platforms rely more heavily on mechanical performance characteristics.

United States Self-driving Cars Market held an 83% share and generated USD 33.6 billion in 2025. Strong investment activity, favorable policy initiatives, and accelerating commercial deployment continue to position the country as a central hub for autonomous vehicle development and long-term market growth.

Key companies active in the Global Self-driving Cars Market include Tesla, Toyota Motor, Hyundai Motor, Volkswagen, General Motors, BMW, Ford Motor Company, Daimler (Mercedes-Benz), Honda Motor, and BYD. Companies in the Global Self-driving Cars Market are strengthening their market position through aggressive investment in artificial intelligence, advanced driver assistance software, and proprietary autonomous platforms. Strategic partnerships with technology providers are enabling faster innovation cycles and improved system integration. Automakers are prioritizing scalable architectures that support multiple autonomy levels across vehicle portfolios. Continuous real-world testing and data-driven optimization remain central to product refinement. Firms are also focusing on regulatory alignment and safety validation to accelerate approvals. Expansion into fleet-based and mobility service models is helping companies diversify revenue streams.

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 Level of Autonomy
    • 2.2.3 Propulsion
    • 2.2.4 Technology
    • 2.2.5 Vehicle
    • 2.2.6 Application
  • 2.3 TAM Analysis, 2026-2035
  • 2.4 CXO perspectives: Strategic imperatives
    • 2.4.1 Executive decision points
    • 2.4.2 Critical success factors
  • 2.5 Future outlook and strategic recommendations

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 Road safety and accident reduction
      • 3.2.1.2 Advancements in artificial intelligence and sensors
      • 3.2.1.3 Government testing approvals and regulations
      • 3.2.1.4 Growth of autonomous mobility services
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 High development and validation costs
      • 3.2.2.2 Regulatory uncertainty across regions
    • 3.2.3 Market opportunities
      • 3.2.3.1 Expansion of robotaxi and autonomous fleet services
      • 3.2.3.2 Autonomous logistics and freight transport
      • 3.2.3.3 Integration with smart city infrastructure
  • 3.3 Growth potential analysis
  • 3.4 Regulatory landscape
    • 3.4.1 North America
      • 3.4.1.1 US National Highway Traffic Safety Administration (NHTSA) FMVSS Updates for Automated Vehicles
      • 3.4.1.2 US Department of Transportation (DOT) Automated Vehicles Comprehensive Plan (AVCP)
      • 3.4.1.3 State-Level Autonomous Testing Permits (California DMV & Nevada DMV Guidelines)
      • 3.4.1.4 Transport Canada Guidelines for Testing Automated Driving Systems (ADS)
    • 3.4.2 Europe
      • 3.4.2.1 UNECE Regulation No. 157 on Automated Lane Keeping Systems (ALKS)
      • 3.4.2.2 European Union General Safety Regulation (GSR) for Type Approval of ADS
      • 3.4.2.3 Germany Federal Motor Transport Authority (KBA) Level 4 Operating Permits
      • 3.4.2.4 UK Automated Vehicles Act and Liability Frameworks
    • 3.4.3 Asia Pacific
      • 3.4.3.1 China Ministry of Industry and Information Technology (MIIT) ICV Market Access Guide
      • 3.4.3.2 Japan Ministry of Land, Infrastructure, Transport and Tourism (MLIT) Level 4 Licensing
      • 3.4.3.3 South Korea MOLIT Safety Standards for Autonomous Vehicle Commercialization
      • 3.4.3.4 Singapore Technical Reference 68 (TR 68) for Autonomous Vehicles
      • 3.4.3.5 India Ministry of Road Transport and Highways (MoRTH) Emerging ADAS Guidelines
    • 3.4.4 Latin America
      • 3.4.4.1 Brazil National Traffic Council (CONTRAN) Resolutions on Assisted Driving
      • 3.4.4.2 Mexico Mobility & Road Safety General Law (LGMSV) Implications for Automation
      • 3.4.4.3 Chile Ministry of Transport Regulations on Autonomous Pilot Testing
      • 3.4.4.4 Regional Alignment with UN World Forum for Harmonization of Vehicle Regulations (WP.29)
    • 3.4.5 Middle East & Africa
      • 3.4.5.1 UAE Roads and Transport Authority (RTA) Regulations for Autonomous Transport
      • 3.4.5.2 Saudi Arabia SASO Technical Standards for Electric and Autonomous Vehicles
      • 3.4.5.3 Israel Ministry of Transport Guidelines for Driverless Vehicle Trials
      • 3.4.5.4 South Africa Standards for Intelligent Transport Systems (ITS) Deployment
  • 3.5 Porter’s analysis
  • 3.6 PESTEL analysis
  • 3.7 Technology and innovation landscape
    • 3.7.1 Current technological trends
    • 3.7.2 Emerging technologies
  • 3.8 Price trends
    • 3.8.1 By region
    • 3.8.2 By product
  • 3.9 Production statistics
    • 3.9.1 Production hubs
    • 3.9.2 Consumption hubs
    • 3.9.3 Export and import
  • 3.10 Cost breakdown analysis
    • 3.10.1 Autonomous sensor suite acquisition (LiDAR, Radar, Cameras)
    • 3.10.2 High-performance compute (HPC) and AI semiconductor costs
    • 3.10.3 Software development, validation, and HD mapping expenses
    • 3.10.4 Teleoperation and fleet management infrastructure costs
    • 3.10.5 Regulatory homologation and safety certification fees
    • 3.10.6 Insurance premiums and liability coverage structure
  • 3.11 Patent analysis
  • 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 Go-to-Market strategies
    • 3.13.1 Robotaxi (MaaS) vs. Private Ownership commercialization models
    • 3.13.2 Strategic partnerships: OEM hardware + Tech Giant software stacks
    • 3.13.3 Subscription-based revenue models (FSD/Software-as-a-Service)
  • 3.14 R&D investment by leading manufacturers
    • 3.14.1 Emerging technologies like solid-state LiDAR and 4D imaging radar
    • 3.14.2 Intellectual property and patent disputes in autonomous vehicle development

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 Strategic outlook matrix
  • 4.6 Key developments
    • 4.6.1 Mergers & acquisitions
    • 4.6.2 Partnerships & collaborations
    • 4.6.3 New Product Launches
    • 4.6.4 Expansion Plans and funding

Chapter 5. Market Estimates & Forecast, By Level of Autonomy, 2022 2035 (USD Mn, Units)

  • 5.1 Key trends
  • 5.2 L1
  • 5.3 L2
  • 5.4 L3
  • 5.5 L4
  • 5.6 L5

Chapter 6. Market Estimates & Forecast, By Propulsion, 2022 - 2035 (USD Mn, Units)

  • 6.1 Key trends
  • 6.2 ICE
  • 6.3 Electric
  • 6.4 Hybrid vehicle

Chapter 7. Market Estimates & Forecast, By Technology, 2022 - 2035 (USD Mn, Units)

  • 7.1 Key trends
  • 7.2 Camera-Based Systems
  • 7.3 Radar-Based Systems
  • 7.4 LiDAR-Based Systems
  • 7.5 Sensor Fusion Systems

Chapter 8. Market Estimates & Forecast, By Vehicle, 2022 - 2035 (USD Mn, Units)

  • 8.1 Key trends
  • 8.2 Passenger cars
    • 8.2.1 Hatchbacks
    • 8.2.2 Sedans
    • 8.2.3 SUVs
    • 8.2.4 MPVs
  • 8.3 Commercial vehicles
    • 8.3.1 Light commercial vehicles (LCVs)
    • 8.3.2 Medium commercial vehicles (MCVs)
    • 8.3.3 Heavy commercial vehicles (HCVs)

Chapter 9. Market Estimates & Forecast, By Application, 2022 - 2035 (USD Mn, Units)

  • 9.1 Key trends
  • 9.2 Personal use
  • 9.3 Shared mobility
  • 9.4 Logistics & delivery
  • 9.5 Public transport
  • 9.6 Others

Chapter 10. Market Estimates & Forecast, By Region, 2022 - 2035 (USD Mn, Units)

  • 10.1 Key trends
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 France
    • 10.3.4 Italy
    • 10.3.5 Spain
    • 10.3.6 Russia
    • 10.3.7 Nordics
    • 10.3.8 Netherlands
    • 10.3.9 Sweden
  • 10.4 Asia Pacific
    • 10.4.1 China
    • 10.4.2 India
    • 10.4.3 Japan
    • 10.4.4 Australia
    • 10.4.5 South Korea
    • 10.4.6 Singapore
    • 10.4.7 Thailand
    • 10.4.8 Indonesia
    • 10.4.9 Vietnam
  • 10.5 Latin America
    • 10.5.1 Brazil
    • 10.5.2 Mexico
    • 10.5.3 Argentina
  • 10.6 MEA
    • 10.6.1 South Africa
    • 10.6.2 Saudi Arabia
    • 10.6.3 UAE
    • 10.6.4 Turkey

Chapter 11. Company Profiles

  • 11.1 Global Players
    • 11.1.1 BMW
    • 11.1.2 Daimler AG (Mercedes-Benz)
    • 11.1.3 Ford Motor Company
    • 11.1.4 General Motors (GM)
    • 11.1.5 Honda Motor
    • 11.1.6 Hyundai Motor
    • 11.1.7 Stellantis N.V.
    • 11.1.8 Tesla
    • 11.1.9 Toyota Motor
    • 11.1.10 Volkswagen Group
  • 11.2 Regional Players
    • 11.2.1 BYD
    • 11.2.2 Geely Holding Group
    • 11.2.3 Renault-Nissan-Mitsubishi Alliance
    • 11.2.4 SAIC Motor
    • 11.2.5 Tata Motors
  • 11.3 Emerging Players / Disruptors
    • 11.3.1 Aurora Innovation
    • 11.3.2 Baidu
    • 11.3.3 NIO Inc.
    • 11.3.4 Waymo
    • 11.3.5 XPeng Motors