미국의 소프트웨어 정의 차량 시장 규모, 점유율, 동향 분석 : 배포 방식별, 유형별, 최종 용도별, 부문별 예측(2025-2033년)

Market Size & Trends:

The U.S. software-defined vehicles market size was estimated at USD 7.63 billion in 2024 and is projected to reach USD 70.82 billion by 2033, growing at a CAGR of 28.2% from 2025 to 2033. The U.S. Software-Defined Vehicle (SDV) market growth is driven by the increasing integration of AI into vehicle systems. Automakers are focusing on utilizing advanced software platforms to enhance vehicle functionality and performance. This trend is promoting the development of more intelligent and adaptable in-vehicle systems. It is also encouraging frequent software updates and continuous feature improvements. The emphasis on AI and software innovation is accelerating the transformation toward fully software-defined vehicles in the U.S. For instance, in March 2025, General Motors, a U.S.-based automotive company, announced an expanded partnership with NVIDIA to integrate AI into its future vehicles and manufacturing processes. The partnership will utilize NVIDIA's Omniverse platform to create digital twins of factories, improving efficiency, and will use NVIDIA DRIVE AGX for advanced driver-assistance systems and in-vehicle experiences.

A stronger emphasis on software-driven vehicle functionality is driving the U.S. software-defined vehicles industry. Automakers are prioritizing continuous improvements and updates to enhance vehicle performance. Advanced system integration is becoming a key focus to ensure seamless operation across vehicle components. This approach allows vehicles to be more adaptable and responsive to user needs. The shift toward software-centric design is accelerating the growth of the SDV market in the U.S. For instance, in August 2025, Ford Motor Company announced its Universal EV platform, which will support a range of affordable, software-defined electric vehicles starting with a $30,000 mid-size pickup truck slated for production in 2027. The platform and its new production system are designed to reduce costs, improve efficiency, and enable advanced features such as over-the-air updates and hands-free driving.

Over-the-air (OTA) updates have become an essential component of modern vehicle design, allowing manufacturers to remotely deliver comprehensive software improvements and introduce entirely new functionalities without requiring a visit to a service center. This capability enables vehicles to receive critical performance optimizations, security patches, and bug fixes directly from the manufacturer in a timely and efficient manner, ensuring both safety and reliability. Beyond maintenance, OTA updates allow automakers to continuously add innovative features and enhance the user experience over the vehicle's entire lifecycle. Drivers benefit from a more personalized and adaptive driving experience, as software can be customized to their preferences and usage patterns. The widespread adoption of OTA updates is transforming vehicles into dynamic, continuously evolving platforms that combine convenience, efficiency, and advanced technological integration.

U.S. Software-Defined Vehicles Market Report Segmentation

This report offers revenue growth forecasts at the country level and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the U.S. software-defined vehicles market report based on deployment mode, type, and end use:

• Deployment Mode Outlook (Revenue, USD Billion, 2021 - 2033)
• On-Board (Edge)
• Cloud-Based
• Type Outlook (Revenue, USD Billion, 2021 - 2033)
• Autonomous Software-Defined Vehicles
• Connected Software-Defined Vehicles
• Electric Software-Defined Vehicles
• Infotainment and Comfort Software-Defined Vehicles
• Hybrid Software-Defined Vehicles
• End Use Outlook (Revenue, USD Billion, 2021 - 2033)
• Advanced Driver-Assistance Systems (ADAS)
• Autonomous Driving
• Infotainment Systems
• Electric Vehicle (EV) Management
• Vehicle-to-Everything (V2X) Communication
• Personalization

Table of Contents

Chapter 1. Methodology and Scope

• 1.1. Market Segmentation & Scope
• 1.2. Market Definition
• 1.3. Information Procurement
  • 1.3.1. Purchased Database
  • 1.3.2. GVR's Internal Database
  • 1.3.3. Secondary Sources & Third-Party Perspectives
  • 1.3.4. Primary Research
• 1.4. Information Analysis
  • 1.4.1. Data Analysis Models
• 1.5. Market Formulation & Data Visualization
• 1.6. Data Validation & Publishing

Chapter 2. Executive Summary

• 2.1. Market Insights
• 2.2. Segmental Outlook
• 2.3. Competitive Outlook

Chapter 3. U.S. Software-Defined Vehicles Market Variables, Trends & Scope

• 3.1. U.S. Software-Defined Vehicles Market Outlook
• 3.2. Industry Value Chain Analysis
• 3.3. Market Dynamics
  • 3.3.1. Market Driver Analysis
  • 3.3.2. Market Restraint Analysis
  • 3.3.3. Industry Challenges
• 3.4. Porter's Five Forces Analysis
  • 3.4.1. Supplier Power
  • 3.4.2. Buyer Power
  • 3.4.3. Substitution Threat
  • 3.4.4. Threat from New Entrant
  • 3.4.5. Competitive Rivalry
• 3.5. PESTEL Analysis
  • 3.5.1. Political Landscape
  • 3.5.2. Economic Landscape
  • 3.5.3. Social Landscape
  • 3.5.4. Technological Landscape
  • 3.5.5. Environmental Landscape
  • 3.5.6. Legal Landscape

Chapter 4. U.S. Software-Defined Vehicles Market: Deployment Mode Estimates & Forecasts

• 4.1. U.S. Software-Defined Vehicles Market: Deployment Mode Movement Analysis, 2024 & 2033
  • 4.1.1. On-Board (Edge)
    • 4.1.1.1. On-Board (Edge) Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 4.1.2. Cloud-Based
    • 4.1.2.1. Cloud-Based Market estimates and forecast, 2021 - 2033 (USD Billion)

Chapter 5. U.S. Software-Defined Vehicles Market: Type Outlook Estimates & Forecasts

• 5.1. U.S. Software-Defined Vehicles Market: Type Movement Analysis, 2024 & 2033
  • 5.1.1. Autonomous Software-Defined Vehicles
    • 5.1.1.1. Autonomous Software-Defined Vehicles Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 5.1.2. Connected Software-Defined Vehicles
    • 5.1.2.1. Connected Software-Defined Vehicles Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 5.1.3. Electric Software-Defined Vehicles
    • 5.1.3.1. Electric Software-Defined Vehicles Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 5.1.4. Infotainment and Comfort Software-Defined Vehicles
    • 5.1.4.1. Infotainment and Comfort Software-Defined Vehicles Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 5.1.5. Hybrid Software-Defined Vehicles
    • 5.1.5.1. Hybrid Software-Defined Vehicles Market estimates and forecast, 2021 - 2033 (USD Billion)

Chapter 6. U.S. Software-Defined Vehicles Market: End Use Outlook Estimates & Forecasts

• 6.1. U.S. Software-Defined Vehicles Market: End Use Movement Analysis, 2024 & 2033
  • 6.1.1. Advanced Driver-Assistance Systems (ADAS)
    • 6.1.1.1. Advanced Driver-Assistance Systems (ADAS) Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 6.1.2. Autonomous Driving
    • 6.1.2.1. Autonomous Driving Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 6.1.3. Infotainment Systems
    • 6.1.3.1. Infotainment Systems Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 6.1.4. Electric Vehicle (EV) Management
    • 6.1.4.1. Electric Vehicle (EV) Management Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 6.1.5. Vehicle-to-Everything (V2X) Communication
    • 6.1.5.1. Vehicle-to-Everything (V2X) Communication Market estimates and forecast, 2021 - 2033 (USD Billion)
  • 6.1.6. Personalization
    • 6.1.6.1. Personalization Market estimates and forecast, 2021 - 2033 (USD Billion)

Chapter 7. U.S. Software-Defined Vehicles Market: Competitive Landscape

• 7.1. Recent Developments & Impact Analysis, By Key Market Participants
• 7.2. Vendor Landscape
  • 7.2.1. Company categorization
  • 7.2.2. List of Key Distributors and Channel Partners
  • 7.2.3. List of Potential Customers/Listing
• 7.3. Competitive Dynamics
  • 7.3.1. Competitive Benchmarking
  • 7.3.2. Strategy Mapping
  • 7.3.3. Heat Map Analysis
• 7.4. Company Profiles/Listing
  • 7.4.1. Aptiv PLC
    • 7.4.1.1. Participant's overview
    • 7.4.1.2. Financial performance
    • 7.4.1.3. Deployment Mode benchmarking
    • 7.4.1.4. Strategic initiatives
  • 7.4.2. Aurora Operations, Inc.
    • 7.4.2.1. Participant's overview
    • 7.4.2.2. Financial performance
    • 7.4.2.3. Deployment Mode benchmarking
    • 7.4.2.4. Strategic initiatives
  • 7.4.3. Ford Motor Company
    • 7.4.3.1. Participant's overview
    • 7.4.3.2. Financial performance
    • 7.4.3.3. Deployment Mode benchmarking
    • 7.4.3.4. Strategic initiatives
  • 7.4.4. General Motors (GM)
    • 7.4.4.1. Participant's overview
    • 7.4.4.2. Financial performance
    • 7.4.4.3. Deployment Mode benchmarking
    • 7.4.4.4. Strategic initiatives
  • 7.4.5. Mobileye
    • 7.4.5.1. Participant's overview
    • 7.4.5.2. Financial performance
    • 7.4.5.3. Deployment Mode benchmarking
    • 7.4.5.4. Strategic initiatives
  • 7.4.6. NVIDIA Corporation
    • 7.4.6.1. Participant's overview
    • 7.4.6.2. Financial performance
    • 7.4.6.3. Deployment Mode benchmarking
    • 7.4.6.4. Strategic initiatives
  • 7.4.7. Rivian Automotive, Inc.
    • 7.4.7.1. Participant's overview
    • 7.4.7.2. Financial performance
    • 7.4.7.3. Deployment Mode benchmarking
    • 7.4.7.4. Strategic initiatives
  • 7.4.8. Tesla, Inc.
    • 7.4.8.1. Participant's overview
    • 7.4.8.2. Financial performance
    • 7.4.8.3. Deployment Mode benchmarking
    • 7.4.8.4. Strategic initiatives
  • 7.4.9. Waymo LLC
    • 7.4.9.1. Participant's overview
    • 7.4.9.2. Financial performance
    • 7.4.9.3. Deployment Mode benchmarking
    • 7.4.9.4. Strategic initiatives
  • 7.4.10. Zoox, Inc.
    • 7.4.10.1. Participant's overview
    • 7.4.10.2. Financial performance
    • 7.4.10.3. Deployment Mode benchmarking
    • 7.4.10.4. Strategic initiatives