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1755253

ADAS 軟體市場機會、成長動力、產業趨勢分析及 2025 - 2034 年預測

ADAS Software Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034
出版日期: | 出版商: Global Market Insights Inc. | 英文 190 Pages | 商品交期: 2-3個工作天內

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簡介目錄

2024年，全球ADAS軟體市場規模達100億美元，預計到2034年將以21.2%的複合年成長率成長，達到664億美元。這一顯著成長主要得益於消費者道路安全意識的提升，以及對配備自動駕駛輔助功能的車輛日益成長的需求。對自動車道維持和煞車輔助等功能的需求日益成長，使ADAS技術成為現代車輛的主流配置。此外，包括衛星、攝影機和雷射雷達技術在內的感測器系統技術創新，使這些系統更加高效、可靠且易於訪問，最終提升了整體性能並降低了營運成本。

ADAS 軟體市場 - IMG1

市場成長的另一個主要驅動力是人工智慧和機器學習與ADAS平台的整合。這些功能使車輛能夠處理即時資料並做出預測性決策，從而顯著提升態勢感知和反應能力。隨著全球監管機構強制執行更嚴格的車輛安全要求，汽車公司面臨整合高級輔助系統以滿足合規性的壓力。消費者也越來越傾向於半自動駕駛體驗，促使複雜的駕駛輔助功能迅速普及。因此，對更高水準車輛自動駕駛的追求正促使製造商大力投資於能夠支援日益複雜的駕駛功能的軟體。

市場範圍
起始年份 2024
預測年份 2025-2034
起始值 100億美元
預測值 664億美元
複合年成長率 21.2%

駕駛輔助功能日益複雜，這意味著軟體在自動緊急應變、智慧導航和車輛定位等系統中發揮著至關重要的作用。汽車製造商致力於實現 ADAS 軟體與更廣泛的車輛架構的無縫整合。對智慧、響應式系統的需求不斷成長，已使軟體成為競爭激烈的汽車產品的差異化因素。即時感測器融合和 AI 驅動的情境決策的持續創新將塑造 ADAS 解決方案的未來。

依組件分類，ADAS 軟體市場可細分為軟體平台、中介軟體、應用軟體和作業系統。 2024 年，應用軟體佔據最大市場佔有率，貢獻了約 60% 的總收入。預計在整個預測期內，該領域的複合年成長率將超過 22%。該領域在市場中佔據關鍵地位，因為它能夠與車輛感測器直接互動並實現基於演算法的決策過程。作為實現即時功能的主要元素，應用軟體確保高級駕駛輔助功能在所有車型上有效執行。

就系統而言，市場分為車道偏離預警 (LDW)、自適應巡航控制 (ACC)、自動緊急煞車 (AEB)、停車輔助、盲點偵測 (BSD)、夜視系統、交通標誌識別 (TSR) 等。自適應巡航控制在 2024 年佔據市場主導地位，佔據 24% 的收入佔有率。這種主導地位歸功於其在保持安全車距和提升駕駛舒適度方面發揮的重要作用，尤其是在交通堵塞或高速行駛的路況下。全球對部分自動駕駛汽車的青睞，進一步提升了此類系統在城市和高速公路駕駛場景中的普及率。

依車型分析，ADAS 軟體市場分為商用車和乘用車。受整合安全和便利技術需求成長的推動，乘用車在 2024 年佔據市場主導地位。這一趨勢在中階和入門級細分市場尤其明顯，因為這些市場的買家正在積極尋求安全性能更強的車輛。隨著汽車製造商不斷擴展產品線以滿足消費者的期望，ADAS 功能在私家車中的大規模整合將繼續成為關鍵的成長動力。

根據最終用途，市場分為原始設備製造商 (OEM) 和售後市場參與者。 2024 年，OEM 佔據了約 92% 的主導佔有率。這得益於他們能夠在車輛生產過程中整合 ADAS 軟體，從而實現更好的最佳化、更高的資料安全性和無縫的使用者體驗。汽車製造商意識到購車者對智慧安全技術的需求日益成長，因此積極將這些功能作為標配。

從地區來看，美國在2024年引領了ADAS軟體市場，市場規模約30億美元，約佔北美市場佔有率的85%。該地區的成長與政府安全措施以及對強制車輛輔助功能的監管支援密切相關。此外，對國內創新和國家安全的關注也促使對本土ADAS技術的投資增加。

隨著許多汽車公司和一級供應商致力於開發專有軟體生態系統，市場也正在經歷向垂直整合的轉變。這種方法可以提高相容性、安全性和系統控制能力，同時減少對第三方開發者的依賴。另一個重要趨勢是與人工智慧公司、半導體生產商和雲端服務供應商建立策略合作，以加強研發並加速創新。這些合作夥伴關係實現了可擴展性，並使企業能夠調整ADAS解決方案，以滿足全球市場不同的監管和道路要求。

目錄

第1章：方法論

  • 市場範圍和定義
  • 研究設計
    • 研究方法
    • 資料收集方法
  • 資料探勘來源
    • 全球的
    • 地區/國家
  • 基礎估算與計算
    • 基準年計算
    • 市場評估的主要趨勢
  • 初步研究和驗證
    • 主要來源
  • 預測模型
  • 研究假設和局限性

第2章：執行摘要

第3章：行業洞察

  • 產業生態系統分析
    • 供應商格局
    • 利潤率
    • 成本結構
    • 每個階段的增值
    • 影響價值鏈的因素
    • 中斷
  • 產業衝擊力
    • 成長動力
      • 自動駕駛和半自動駕駛汽車的需求不斷成長
      • 人工智慧和機器學習的融合度提高
      • 感測器和連接技術的進步
      • 快速城市化和智慧移動計劃
      • 消費者對車內安全性和便利性的需求
    • 產業陷阱與挑戰
      • 開發和整合成本高
      • 感測器融合和即時處理的複雜性
    • 市場機會
      • 與電動車（EV）整合
      • 雲端原生平台的興起
      • OEM軟體供應商合作夥伴關係
      • 人工智慧和機器學習整合
  • 成長潛力分析
  • 監管格局
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東和非洲
  • 波特的分析
  • PESTEL分析
  • 技術和創新格局
    • 當前的技術趨勢
    • 新興技術
  • 專利分析
  • 永續性和環境方面
    • 永續實踐
    • 減少廢棄物的策略
    • 生產中的能源效率
    • 環保舉措
    • 碳足跡考量

第4章：競爭格局

  • 介紹
  • 公司市佔率分析
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • MEA
  • 主要市場參與者的競爭分析
  • 競爭定位矩陣
  • 戰略展望矩陣
  • 關鍵進展
    • 併購
    • 夥伴關係與合作
    • 新產品發布
    • 擴張計劃和資金

第5章：市場估計與預測：按組件，2021 - 2034 年

  • 主要趨勢
  • 軟體平台
  • 中介軟體
  • 應用軟體
  • 作業系統

第6章：市場估計與預測：按系統，2021 - 2034 年

  • 主要趨勢
  • 自適應巡航控制 (ACC)
  • 車道偏離警示 (LDW)
  • 自動緊急煞車（AEB）
  • 盲點偵測（BSD）
  • 停車輔助
  • 交通標誌識別（TSR）
  • 夜視系統
  • 其他

第7章：市場估計與預測：依車型，2021 - 2034 年

  • 主要趨勢
  • 搭乘用車
    • 掀背車
    • 轎車
    • SUV（運動型多用途車）
    • MPV（多用途汽車）
  • 商用車
    • 輕型商用車（LCV）
    • 中型商用車（HCV）
    • 重型商用車（HCV）

第8章：市場估計與預測：依最終用途，2021 - 2034 年

  • 主要趨勢
  • OEM （原始設備製造商）
  • 售後市場

第9章：市場估計與預測：依自主級別，2021 - 2034 年

  • 主要趨勢
  • 1級（駕駛輔助）
  • 2級（部分自動化）
  • 3級（有條件自動化）
  • 4級（高度自動化）
  • 5級（全自動）

第10章：市場估計與預測：按地區，2021 - 2034 年

  • 主要趨勢
  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 北歐人
  • 亞太地區
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳新銀行
    • 新加坡
    • 馬來西亞
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • MEA
    • 阿拉伯聯合大公國
    • 沙烏地阿拉伯
    • 南非

第 11 章：公司簡介

  • Ambarella
  • Aptiv
  • Baidu Apollo
  • Bosch
  • Continental
  • Innoviz Technologies
  • Luminar Technologies
  • Magna International
  • Mobileye (Intel)
  • Nvidia
  • NXP Semiconductors
  • Qualcomm
  • Renesas Electronics
  • Sony
  • Tesla
  • Valeo
  • Velodyne Lidar (Ouster)
  • Waymo (Alphabet)
  • XPeng
  • ZF Friedrichshafen
簡介目錄
Product Code: 14036

The Global ADAS Software Market was valued at USD 10 billion in 2024 and is estimated to grow at a CAGR of 21.2% to reach USD 66.4 billion by 2034. This significant expansion is largely fueled by rising consumer awareness regarding road safety and a growing appetite for vehicles equipped with automated support features. Increasing demand for functionalities such as automated lane keeping and braking assistance has made ADAS technologies a mainstream requirement in modern vehicles. In addition, technological innovations in sensor systems, including satellite, camera, and Lidar technologies, have made these systems more efficient, reliable, and accessible, ultimately enhancing overall performance while reducing operational costs.

ADAS Software Market - IMG1

Another major driver of market growth is the integration of artificial intelligence and machine learning into ADAS platforms. These capabilities allow vehicles to process real-time data and make predictive decisions, significantly improving situational awareness and responsiveness. With global regulatory bodies enforcing more stringent vehicle safety requirements, automotive companies are under pressure to incorporate advanced assistance systems to meet compliance. Consumers are also leaning toward semi-autonomous driving experiences, prompting a rapid adoption of sophisticated driver-assist features. As a result, the push toward higher levels of vehicle autonomy is encouraging manufacturers to invest heavily in software that can support increasingly complex driving functions.

Market Scope
Start Year2024
Forecast Year2025-2034
Start Value$10 Billion
Forecast Value$66.4 Billion
CAGR21.2%

The growing complexity of driver-assistance features means software plays a critical role in enabling systems like automated emergency response, smart navigation, and vehicle positioning. Automakers are focused on achieving seamless integration of ADAS software within the broader vehicle architecture. The rise in demand for intelligent, responsive systems has turned software into a differentiator in competitive vehicle offerings. Continued innovation in real-time sensor fusion and AI-driven contextual decision-making will shape the future of ADAS solutions.

By component, the ADAS software market is segmented into software platform, middleware, application software, and operating system. In 2024, the application software segment accounted for the largest market share, contributing approximately 60% of total revenue. It is also anticipated to grow at a CAGR exceeding 22% throughout the forecast period. This segment holds a critical position in the market as it enables direct interaction with vehicle sensors and algorithm-based decision-making processes. As the primary element responsible for real-time functionality, application software ensures the effective execution of advanced driver-assistance features across all vehicle types.

In terms of systems, the market is categorized into lane departure warning (LDW), adaptive cruise control (ACC), automatic emergency braking (AEB), parking assistance, blind spot detection (BSD), night vision systems, traffic sign recognition (TSR), and others. Adaptive cruise control led the market in 2024, holding a 24% revenue share. This dominance is attributed to its essential role in maintaining safe vehicle spacing and enhancing driver comfort, especially in traffic-heavy or high-speed conditions. The global preference for vehicles that offer partial automation has amplified the popularity of such systems in both urban and highway driving scenarios.

When analyzed by vehicle type, the ADAS software market is divided into commercial vehicles and passenger cars. Passenger cars dominated the market in 2024, driven by heightened demand for integrated safety and convenience technologies. This trend is especially strong in the mid-range and entry-level segments, where buyers are actively seeking vehicles with enhanced safety features. The mass integration of ADAS functionality in personal vehicles continues to be a key growth driver as automakers expand offerings to meet consumer expectations.

Based on end use, the market is split between original equipment manufacturers (OEMs) and aftermarket players. OEMs held a commanding share of around 92% in 2024. This is due to their capability to integrate ADAS software during vehicle production, which results in better optimization, increased data security, and a seamless user experience. Automakers are proactively embedding these features as standard, recognizing the growing demand for intelligent safety technologies among car buyers.

Regionally, the United States led the ADAS software market in 2024, generating approximately USD 3 billion and representing about 85% of the North American share. The growth in this region is closely tied to government safety initiatives and regulatory support for mandatory vehicle assistance features. Additionally, the focus on domestic innovation and national security has led to increased investment in homegrown ADAS technologies.

The market is also witnessing a shift toward vertical integration, as many automotive companies and Tier 1 suppliers aim to develop proprietary software ecosystems. This approach improves compatibility, security, and system control while reducing reliance on third-party developers. Another significant trend involves strategic collaborations with AI firms, semiconductor producers, and cloud service providers to strengthen R&D and accelerate innovation. These partnerships enable scalability and allow companies to adapt ADAS solutions to meet varying regulatory and road requirements across global markets.

Table of Contents

Chapter 1 Methodology

  • 1.1 Market scope and definition
  • 1.2 Research design
    • 1.2.1 Research approach
    • 1.2.2 Data collection methods
  • 1.3 Data mining sources
    • 1.3.1 Global
    • 1.3.2 Regional/Country
  • 1.4 Base estimates and calculations
    • 1.4.1 Base year calculation
    • 1.4.2 Key trends for market estimation
  • 1.5 Primary research and validation
    • 1.5.1 Primary sources
  • 1.6 Forecast model
  • 1.7 Research assumptions and limitations

Chapter 2 Executive Summary

  • 2.1 Industry 3600 synopsis
  • 2.2 Key market trends
    • 2.2.1 Regional
    • 2.2.2 Component
    • 2.2.3 System
    • 2.2.4 Vehicle
    • 2.2.5 End use
    • 2.2.6 Level of autonomy
  • 2.3 TAM Analysis, 2025-2034
  • 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
    • 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 Rising demand for autonomous and semi-autonomous vehicles
      • 3.2.1.2 Increased integration of AI and machine learning
      • 3.2.1.3 Technological advancements in sensors and connectivity
      • 3.2.1.4 Rapid urbanization and smart mobility initiatives
      • 3.2.1.5 Consumer demand for in-vehicle safety and convenience
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 High development and integration costs
      • 3.2.2.2 Complexity in sensor fusion and real-time processing
    • 3.2.3 Market opportunities
      • 3.2.3.1 Integration with electric vehicles (EVs)
      • 3.2.3.2 The rise of cloud-native platforms
      • 3.2.3.3 OEM-software supplier partnerships
      • 3.2.3.4 AI and machine learning integration
  • 3.3 Growth potential analysis
  • 3.4 Regulatory landscape
    • 3.4.1 North America
    • 3.4.2 Europe
    • 3.4.3 Asia Pacific
    • 3.4.4 Latin America
    • 3.4.5 Middle East & Africa
  • 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 Patent analysis
  • 3.9 Sustainability and environmental aspects
    • 3.9.1 Sustainable practices
    • 3.9.2 Waste reduction strategies
    • 3.9.3 Energy efficiency in production
    • 3.9.4 Eco-friendly initiatives
    • 3.9.5 Carbon footprint considerations

Chapter 4 Competitive Landscape, 2024

  • 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 Component, 2021 - 2034 (USD Million)

  • 5.1 Key trends
  • 5.2 Software platform
  • 5.3 Middleware
  • 5.4 Application software
  • 5.5 Operating system

Chapter 6 Market Estimates & Forecast, By System, 2021 - 2034 (USD Million)

  • 6.1 Key trends
  • 6.2 Adaptive cruise control (ACC)
  • 6.3 Lane departure warning (LDW)
  • 6.4 Automatic emergency braking (AEB)
  • 6.5 Blind spot detection (BSD)
  • 6.6 Parking assistance
  • 6.7 Traffic sign recognition (TSR)
  • 6.8 Night vision system
  • 6.9 Others

Chapter 7 Market Estimates & Forecast, By Vehicle, 2021 - 2034 (USD Million)

  • 7.1 Key trends
  • 7.2 Passenger cars
    • 7.2.1 Hatchbacks
    • 7.2.2 Sedans
    • 7.2.3 SUVs (Sport utility vehicles)
    • 7.2.4 MPVs (Multi-purpose vehicles)
  • 7.3 Commercial vehicles
    • 7.3.1 Light commercial vehicles (LCVs)
    • 7.3.2 Medium commercial vehicles (HCVs)
    • 7.3.3 Heavy commercial vehicles (HCVs)

Chapter 8 Market Estimates & Forecast, By End Use, 2021 - 2034 (USD Million)

  • 8.1 Key trends
  • 8.2 OEM (Original equipment manufacturers)
  • 8.3 Aftermarket

Chapter 9 Market Estimates & Forecast, By Level of autonomy, 2021 - 2034 (USD Million)

  • 9.1 Key trends
  • 9.2 Level 1 (Driver assistance)
  • 9.3 Level 2 (Partial automation)
  • 9.4 Level 3 (Conditional automation)
  • 9.5 Level 4 (High automation)
  • 9.6 Level 5 (Full automation)

Chapter 10 Market Estimates & Forecast, By Region, 2021 - 2034 (USD Million)

  • 10.1 Key trends
  • 10.2 North America
    • 10.2.1 U.S.
    • 10.2.2 Canada
  • 10.3 Europe
    • 10.3.1 UK
    • 10.3.2 Germany
    • 10.3.3 France
    • 10.3.4 Italy
    • 10.3.5 Spain
    • 10.3.6 Russia
    • 10.3.7 Nordics
  • 10.4 Asia Pacific
    • 10.4.1 China
    • 10.4.2 India
    • 10.4.3 Japan
    • 10.4.4 South Korea
    • 10.4.5 ANZ
    • 10.4.6 Singapore
    • 10.4.7 Malaysia
  • 10.5 Latin America
    • 10.5.1 Brazil
    • 10.5.2 Mexico
    • 10.5.3 Argentina
  • 10.6 MEA
    • 10.6.1 UAE
    • 10.6.2 Saudi Arabia
    • 10.6.3 South Africa

Chapter 11 Company Profiles

  • 11.1 Ambarella
  • 11.2 Aptiv
  • 11.3 Baidu Apollo
  • 11.4 Bosch
  • 11.5 Continental
  • 11.6 Innoviz Technologies
  • 11.7 Luminar Technologies
  • 11.8 Magna International
  • 11.9 Mobileye (Intel)
  • 11.10 Nvidia
  • 11.11 NXP Semiconductors
  • 11.12 Qualcomm
  • 11.13 Renesas Electronics
  • 11.14 Sony
  • 11.15 Tesla
  • 11.16 Valeo
  • 11.17 Velodyne Lidar (Ouster)
  • 11.18 Waymo (Alphabet)
  • 11.19 XPeng
  • 11.20 ZF Friedrichshafen