|
시장보고서
상품코드
2141545
자율주행차 시장 기회, 성장 촉진요인, 업계 동향 분석 및 예측(2026-2035년)Self-driving Cars Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2026 - 2035 |
||||||
세계의 자율주행차 시장은 2025년에 2,024억 달러 규모에 달하고, CAGR 5.4%로 성장하여 2035년까지 3,546억 달러에 달할 것으로 추정됩니다.
| 시장 범위 | |
|---|---|
| 시작 연도 | 2025년 |
| 예측 기간 | 2026-2035년 |
| 초기 시장 규모 | 2,024억 달러 |
| 예측액 | 3,546억 달러 |
| CAGR | 5.4% |
교통 관련 위험을 최소화하고 이동 효율성을 높이는 데 대한 관심이 높아지면서 도입이 지속적으로 가속화되고 있습니다. 통제된 시험 및 조기 도입을 지원하는 규제 체계가 자율주행 기술에 새로운 상용화 기회를 제공하고 있습니다. 인공지능, 센서 시스템 및 고성능 컴퓨팅의 발전으로 시스템의 신뢰성과 실제 환경에서의 성능이 향상되고 있습니다. 자율주행차와 스마트 도시 인프라의 통합은 커넥티드 교통 플랫폼, 차량과 인프라 간의 통신, 그리고 적응형 경로 설정 기능을 통해 시장의 성장세를 강화하고 있습니다. 이러한 기술들은 교통 흐름을 개선하고, 정체를 완화하며, 에너지 소비 감축을 지원하고 있습니다. 이러한 성장은 자율주행 모빌리티 플랫폼의 확장에 의해 더욱 가속화되고 있습니다. 이러한 플랫폼들은 도시 교통의 경제 구조를 재편하고 차량 군의 효율성을 향상시키는 동시에, 확장 가능한 자율주행 운송 모델을 실현하고 있습니다. AMaaS(Autonomous Mobility-as-a-Service) 플랫폼 시장은 차량 운영 사업자들이 자동화 중심 시스템을 도입한 후 최소 30%의 운영 비용 절감을 달성했다고 보고함에 따라 계속해서 확대되고 있습니다. 이러한 플랫폼들은 상업적으로 실현 가능하고 확장성이 있음이 입증되어, 자율주행 운송 서비스에 대한 장기적인 신뢰를 강화하고 있습니다.
레벨 3 자율주행 부문은 2025년에 46%의 점유율을 차지했으며, 2026년부터 2035년까지 연평균 성장률(CAGR) 5.2%로 성장할 것으로 전망됩니다. 레벨 3 차량은 운전자의 준비 태세를 확보하면서 운전 업무에서 부분적으로 벗어날 수 있기 때문에 여러 차량 카테고리에서 널리 채택되고 있습니다. 자율주행 개발 프로그램의 대부분은 계속해서 레벨 3 기능에 초점을 맞추고 있어 지속적인 수요를 뒷받침하고 있습니다.
내연기관 차량 부문은 2025년에 72%의 점유율을 차지했으며, 2035년까지 연평균 성장률(CAGR) 4.8%로 성장할 것으로 전망됩니다. 이러한 차량은 자동화 통합을 간소화하는 확립된 제조 플랫폼의 이점을 누리고 있습니다. 전기 자율주행차는 소프트웨어 주도 아키텍처, 첨단 센서 어레이, 중앙 집중식 컴퓨팅 시스템과의 호환성을 갖추고 있어 두 번째로 큰 부문을 차지하고 있습니다. 반면, 내연기관(ICE) 플랫폼은 기계적 성능 특성에 대한 의존도가 더 높습니다.
2025년, 미국의 자율주행차 시장은 83%의 점유율을 차지하며 336억 달러의 시장 규모를 기록했습니다. 활발한 투자 활동, 우호적인 정책 조치, 상용화 가속화로 인해 미국은 계속해서 자율주행차 개발 및 장기적인 시장 성장의 중심 거점으로서의 입지를 공고히 하고 있습니다.
자주 묻는 질문
목차
제1장 조사 방법
제2장 주요 요약
제3장 업계 인사이트
제4장 경쟁 구도
제5장 시장 추정·예측 : 자율주행 레벨별, 2022-2035년
제6장 시장 추정·예측 : 추진 방식별, 2022-2035년
제7장 시장 추정·예측 : 기술별, 2022-2035년
제8장 시장 추정·예측 : 차량별, 2022-2035년
제9장 시장 추정·예측 : 용도별, 2022-2035년
제10장 시장 추정·예측 : 지역별, 2022-2035년
제11장 기업 개요
KSM 26.10.12The 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 Year | 2025 |
| Forecast Year | 2026-2035 |
| Start Value | $202.4 Billion |
| Forecast Value | $354.6 Billion |
| CAGR | 5.4% |
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
- 1.2.1 GMI AI policy & data integrity commitment
- 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
- 1.5.1 Paid sources
- 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
- 1.7.1 Quantified market impact analysis
- 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
- 3.2.1 Growth drivers
- 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
- 3.4.1 North America
- 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
