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市場調查報告書
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2021743

高階駕駛輔助系統 (ADAS) 的人工智慧 (AI) 市場：未來預測（至 2034 年）—按組件、技術、自動駕駛等級、車輛類型、動力系統、應用和地區進行分析

AI in ADAS Market Forecasts to 2034 - Global Analysis By Component (Hardware, Software, and Services), Technology, Level of Autonomy, Vehicle Type, Propulsion Type, Application and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，到 2026 年，全球 ADAS 人工智慧市場規模將達到 120 億美元，預計在預測期內將以 24.8% 的複合年成長率成長，到 2034 年將達到 700 億美元。

人工智慧在高級駕駛輔助系統 (ADAS) 中的應用，融合了智慧演算法和機器學習技術，旨在提升車輛安全性、駕駛效率和自動化程度。這些系統分析來自感測器、攝影機和雷達的即時數據，以偵測障礙物、識別交通標誌、監控駕駛員行為並輔助決策。人工智慧支援車道維持輔助、主動式車距維持定速系統和碰撞避免等功能，從而減少人為錯誤，改善整體駕駛體驗，並加速邁向完全自動駕駛汽車的進程。

嚴格的車輛安全法規和NCAP要求

全球各國政府和汽車安全機構都在強制要求新車配備高級駕駛輔助系統（ADAS）。美國國家公路交通安全管理局（NHTSA）和歐洲新車安全評估協會（Euro NCAP）等監管機構要求車輛必須具備自動緊急煞車、車道偏離預警和行人偵測等功能才能獲得高安全評級。這些法規迫使汽車製造商將人工智慧驅動的ADAS整合到車輛中。此外，消費者道路安全意識的提高以及配備ADAS車輛的保險優惠政策也進一步加速了ADAS的普及。隨著全球安全標準的日益嚴格，汽車製造商被迫增加對基於人工智慧的感知和決策演算法的投資。這種監管壓力直接推動了對先進ADAS硬體和軟體的需求，使其成為市場成長的主要催化劑。

開發和檢驗人工智慧系統的成本很高。

為高階駕駛輔助系統 (ADAS) 開發人工智慧模型需要大量的標註資料集、高效能運算基礎設施和廣泛的現場測試。在各種天氣、光照和交通條件下進行系統檢驗既耗時又昂貴。汽車製造商還必須遵守 ISO 26262 等功能安全標準，這增加了軟體開發的複雜性和成本。這些前期投資可能成為二級和三級供應商的障礙，從而限制其市場參與企業。此外，空中升級和網路安全措施也會產生持續的成本。中小型汽車製造商和售後市場公司往往難以負擔這些成本，阻礙了技術的廣泛應用。因此，高昂的開發和認證成本仍然是 ADAS 人工智慧市場的主要阻礙因素。

電動車和自動駕駛汽車的快速發展

電動車依賴高效的能源管理，而人工智慧驅動的高級駕駛輔助系統（ADAS）可實現能量回收煞車和最佳化路線規劃。同時，無人駕駛計程車和L4級自動駕駛接駁車的開發需要先進的感測器融合和邊緣人工智慧技術。汽車製造商正與人工智慧晶片製造商和軟體公司建立策略合作夥伴關係，以加速這些技術的應用。此外，政府對智慧城市基礎設施和自動駕駛車輛測試車道的投入也支持了這一成長。隨著消費者對自動駕駛功能的信心不斷增強，人工智慧驅動的ADAS將在大眾市場中得到更廣泛的應用。電氣化和自動化的整合將為技術提供者和汽車製造商創造新的收入來源。

與網路安全漏洞和感測器可靠性相關的挑戰

人工智慧驅動的高級駕駛輔助系統（ADAS）高度依賴外部感測器和網路連接，因此極易受到網路攻擊，例如感測器欺騙、GPS干擾以及操縱物體識別的對抗性人工智慧攻擊。一旦ADAS系統遭到入侵，可能導致誤煞車、轉向失靈，甚至系統完全失效，進而危及人身安全。此外，現有感測器易受暴雨、霧霾、陽光直射和灰塵堆積等不利條件的影響，這些都會降低人工智慧模型的精確度。LiDAR和攝影機的時變性也會進一步降低可靠性。如果沒有強大的故障保護機制和即時異常偵測，這些漏洞將威脅到消費者的接受度。汽車製造商必須在冗餘、加密和反欺騙技術方面投入大量資金。在這些威脅徹底消除之前，具備進階自動駕駛功能的ADAS的廣泛應用仍面臨風險。

新冠疫情的影響：

新冠疫情透過半導體短缺、工廠停工和汽車產量下降，對ADAS（高級駕駛輔助系統）的人工智慧市場造成了衝擊。供應鏈瓶頸延緩了配備ADAS的新車型上市，尤其是在中階市場。然而，疫情也加速了人們對非接觸式移動和健康駕駛的需求，使自動代客泊車和車載空氣品質監測等功能備受關注。此外，ADAS也應用於物流和配送車輛，以提升最後一公里配送的安全性。隨著汽車生產的復甦，汽車製造商正優先考慮ADAS的整合，以滿足尚未落實的安全法規要求。此次危機也促使汽車製造商實現感測器在地化生產，並建構更完善的人工智慧開發平臺，增強了市場的長期前景。

在預測期內，硬體領域預計將佔據最大佔有率。

在預測期內，硬體部分預計將佔據最大的市場佔有率。該部分包括攝影機、雷達感測器、LiDAR感測器、超音波感測器和電控系統，它們構成了高級駕駛輔助系統（ADAS）的物理基礎。入門級和高階車輛對高解析度成像、遠距離探測和即時處理的需求，推動了硬體部分的領先地位。固態雷射雷達和4D成像雷達的持續進步，也進一步提升了對硬體的需求。

預計在預測期內，邊緣人工智慧領域將呈現最高的複合年成長率。

在預測期內，邊緣人工智慧系統領域預計將呈現最高的成長率。邊緣人工智慧在車輛晶片本地處理數據，從而降低延遲並減少對雲端連接的依賴。這對於諸如自動緊急煞車等即時高級駕駛輔助系統（ADAS）功能至關重要。專為汽車開發的人工智慧加速器，例如神經處理單元（NPU），在提高設備推理速度的同時，也能降低功耗。邊緣人工智慧也透過最大限度地減少資料傳輸到外部來源，從而有助於提高資料隱私性。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率。這主要得益於特斯拉、通用、福特以及英偉達和英特爾旗下Mobileye等ADAS晶片供應商的強大市場地位。消費者對先進安全功能的高度認可、美國國家公路交通安全管理局（NHTSA）的嚴格監管以及半自動駕駛技術的早期應用，都推動了市場成長。此外，該地區也集中了許多主要的ADAS軟體開發中心。成熟的電動車（EV）生態系統以及對自動駕駛出行服務的巨額投資，也鞏固了北美在全球ADAS人工智慧市場的領先地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於中國、日本和韓國汽車電氣化的快速發展。印度和東南亞政府對安全技術的強制性要求，以及雷射雷達和攝影機生產的積極本地化，將降低系統成本。比亞迪和蔚來等中國汽車製造商正在將先進的人工智慧模型融入其量產車型。自動駕駛測試區域的擴展和智慧基礎設施專案的推進將進一步加速人工智慧技術的應用。隨著車輛數量的增加和安全意識的提高，亞太地區將成為高級駕駛輔助系統（ADAS）人工智慧市場成長最快的地區。

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目錄

第1章執行摘要

第2章 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
  • 分析材料

第3章 市場趨勢分析

  • 促進因素
  • 抑制因子
  • 機會
  • 威脅
  • 產品分析
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章：波特五力分析

  • 供應商議價能力
  • 買方的議價能力
  • 替代產品的威脅
  • 新進入者的威脅
  • 競爭公司之間的競爭

第5章：全球ADAS人工智慧市場：按組件分類

  • 硬體
    • 相機
    • 超音波感測器
    • 雷達感測器
    • 電控系統（ECU）
    • LiDAR感測器
  • 軟體
    • AI中介軟體
    • 融合與決策演算法
    • 感知軟體
  • 服務
    • 整合與部署
    • 培訓和支持

第6章：全球ADAS人工智慧市場：按技術分類

  • 機器學習（ML）
  • 邊緣人工智慧
  • 深度學習（DL）
  • 感測器融合
  • 電腦視覺
  • 自然語言處理（NLP）

第7章：全球ADAS人工智慧市場：按自動駕駛等級分類

  • L1（駕駛輔助）
  • L2（部分自動駕駛）
  • L3（有條件自動駕駛）
  • L4（高度自動化）
  • L5（完全自動駕駛）

第8章：全球ADAS人工智慧市場：按車輛類型分類

  • 搭乘用車
  • 大型商用車輛
  • 輕型商用車

第9章：全球ADAS人工智慧市場：按實施方法分類

  • 內燃機車
  • 混合動力汽車
  • 電動車（EV）

第10章：全球ADAS人工智慧市場：按應用領域分類

  • 主動式車距維持定速系統（ACC）
  • 車道維持輔助系統（LKA）
  • 環景顯示系統
  • 自動緊急煞車（AEB）
  • 駕駛員監控系統（DMS）
  • 盲點偵測（BSD）
  • 交通標誌識別（TSR）
  • 停車協助

第11章 全球ADAS人工智慧市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 其他地區（ROW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第12章 策略市場資訊

  • 產業加值網路與供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第13章 產業趨勢與策略舉措

  • 企業合併（M&A）
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第14章：公司簡介

  • Tesla, Inc.
  • NVIDIA Corporation
  • Intel Corporation
  • Qualcomm Incorporated
  • Robert Bosch GmbH
  • Continental AG
  • ZF Friedrichshafen AG
  • Aptiv PLC
  • Valeo SA
  • Hyundai Mobis
  • Denso Corporation
  • Ambarella, Inc.
  • Horizon Robotics
  • Seeing Machines Ltd.
  • Plus.ai
Product Code: SMRC35023

According to Stratistics MRC, the Global AI in ADAS Market is accounted for $12.0 billion in 2026 and is expected to reach $70.0 billion by 2034 growing at a CAGR of 24.8% during the forecast period. AI in Advanced Driver Assistance Systems (ADAS) is the integration of intelligent algorithms and machine learning techniques to enhance vehicle safety, driving efficiency, and automation. These systems analyze real-time data from sensors, cameras, and radar to detect obstacles, recognize traffic signs, monitor driver behavior, and support decision-making. AI enables features such as lane-keeping assistance, adaptive cruise control, and collision avoidance, helping reduce human error and improve overall driving experience while advancing progress toward fully autonomous vehicles.

Market Dynamics:

Driver:

Stringent vehicle safety regulations and NCAP requirements

Governments and automotive safety organizations worldwide are mandating advanced driver assistance features in new vehicles. Regulatory bodies such as the NHTSA in the U.S. and Euro NCAP have made autonomous emergency braking, lane departure warning, and pedestrian detection compulsory for high safety ratings. These regulations force automakers to integrate AI-powered ADAS into their fleets. Additionally, rising consumer awareness about road safety and insurance incentives for equipped vehicles further accelerate adoption. As safety standards become more rigorous globally, automakers are compelled to invest heavily in AI-based perception and decision algorithms. This regulatory push directly drives demand for sophisticated ADAS hardware and software, making it a primary market growth catalyst.

Restraint:

High development and validation costs of AI systems

Developing AI models for ADAS requires massive labeled datasets, high-performance computing infrastructure, and extensive real-world testing. Validation of these systems under diverse weather, lighting, and traffic conditions is time-consuming and expensive. Automakers must also comply with functional safety standards like ISO 26262, which adds complexity and cost to software development. For tier-2 and tier-3 suppliers, these upfront investments can be prohibitive, limiting market participation. Additionally, over-the-air updates and cybersecurity measures add recurring expenses. Smaller automotive manufacturers and aftermarket players often struggle to absorb these costs, slowing down widespread adoption. Consequently, high development and certification expenses remain a significant restraint in the AI in ADAS market.

Opportunity:

Rapid growth of electric and autonomous vehicles

EVs rely on efficient energy management, and AI-powered ADAS can optimize regenerative braking and route planning. Meanwhile, the development of robotaxis and Level 4 autonomous shuttles demands advanced sensor fusion and edge AI capabilities. Automakers are forming strategic partnerships with AI chipmakers and software firms to accelerate deployment. Furthermore, government funding for smart city infrastructure and autonomous vehicle testing lanes supports this growth. As consumer trust in autonomous features increases, mass-market adoption of AI-driven ADAS will expand. This convergence of electrification and automation opens new revenue streams for technology providers and automakers alike.

Threat:

Cybersecurity vulnerabilities and sensor reliability issues

AI-driven ADAS relies heavily on external sensors and connectivity, making it susceptible to cyberattacks such as sensor spoofing, GPS jamming, and adversarial AI attacks that manipulate object recognition. A compromised ADAS system could lead to false braking, steering errors, or complete system failure, endangering lives. Additionally, current sensors struggle with adverse conditions like heavy rain, fog, direct sunlight, and dirt accumulation, which degrade AI model accuracy. LiDAR and camera misalignment over time further reduces reliability. Without robust fail-safe mechanisms and real-time anomaly detection, these vulnerabilities threaten consumer acceptance. Automakers must invest heavily in redundancy, encryption, and anti-spoofing technologies. Until these threats are fully mitigated, mass adoption of high-autonomy ADAS remains at risk.

Covid-19 Impact:

The COVID-19 pandemic disrupted the AI in ADAS market through semiconductor shortages, factory shutdowns, and reduced vehicle production. Supply chain bottlenecks delayed the rollout of new ADAS-equipped models, especially for mid-range vehicles. However, the pandemic accelerated demand for contactless mobility and health-conscious driving, with features like autonomous valet parking and in-cabin air quality monitoring gaining attention. Additionally, logistics and delivery fleets adopted ADAS for safer last-mile operations. As automotive production recovers, original equipment manufacturers are prioritizing ADAS integration to meet backlogged safety regulations. The crisis also pushed automakers to localize sensor production and adopt more resilient AI development pipelines, strengthening the long-term market outlook.

The hardware segment is expected to be the largest during the forecast period

The hardware segment is expected to account for the largest market share during the forecast period. This segment includes cameras, radar sensors, LiDAR sensors, ultrasonic sensors, and electronic control units that form the physical backbone of any ADAS. The essential need for high-resolution imaging, long-range detection, and real-time processing in both entry-level and premium vehicles drives this dominance. Ongoing advancements in solid-state LiDAR and 4D imaging radar increase hardware demand.

The edge AI segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the edge AI systems segment is predicted to witness the highest growth rate. Edge AI processes data locally on vehicle chips, reducing latency and dependency on cloud connectivity, which is critical for real-time ADAS functions like automatic emergency braking. The development of specialized automotive AI accelerators, such as neural processing units, enhances on-device inference speeds while lowering power consumption. Edge AI also improves data privacy by minimizing external data transmission.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, driven by strong presence of Tesla, General Motors, Ford, and ADAS chip suppliers like NVIDIA and Intel's Mobileye. High consumer acceptance of advanced safety features, stringent NHTSA regulations, and early adoption of semi-autonomous driving technologies fuel growth. The region also hosts major ADAS software development centers. Additionally, a mature electric vehicle ecosystem and heavy investment in autonomous ride-hailing services contribute to North America's dominant position in the global AI in ADAS market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, fueled by rapid vehicle electrification in China, Japan, and South Korea. Government mandates for safety technologies in India and Southeast Asia, along with aggressive localization of LiDAR and camera production, reduce system costs. Chinese automakers like BYD and NIO are integrating advanced AI models into mass-market vehicles. Expansion of autonomous mobility pilot zones and smart infrastructure projects further accelerate adoption. As fleet sizes grow and safety awareness rises, Asia Pacific becomes the fastest-growing AI in ADAS market.

Key players in the market

Some of the key players in AI in ADAS Market include Tesla, Inc., NVIDIA Corporation, Intel Corporation, Qualcomm Incorporated, Robert Bosch GmbH, Continental AG, ZF Friedrichshafen AG, Aptiv PLC, Valeo SA, Hyundai Mobis, Denso Corporation, Ambarella, Inc., Horizon Robotics, Seeing Machines Ltd., and Plus.ai.

Key Developments:

In March 2026, NVIDIA and Marvell Technology, Inc. announced a strategic partnership to connect Marvell to the NVIDIA AI factory and AI-RAN ecosystem through NVIDIA NVLink Fusion(TM), offering customers building on NVIDIA architectures greater choice and flexibility in developing next-generation infrastructure. The companies will also collaborate on silicon photonics technology.

In September 2025, NVIDIA and Intel Corporation announced a collaboration to jointly develop multiple generations of custom data center and PC products that accelerate applications and workloads across hyperscale, enterprise and consumer markets. The companies will focus on seamlessly connecting NVIDIA and Intel architectures using NVIDIA NVLink, integrating the strengths of NVIDIA's AI and accelerated computing with Intel's leading CPU technologies and x86 ecosystem to deliver cutting-edge solutions for customers.

Components Covered:

  • Hardware
  • Software
  • Services

Technologies Covered:

  • Machine Learning (ML)
  • Edge AI
  • Deep Learning
  • Sensor Fusion
  • Computer Vision
  • Natural Language Processing (NLP)

Level of Autonomy Covered:

  • L1 - Driver Assistance
  • L2 - Partial Automation
  • L3 - Conditional Automation
  • L4 - High Automation
  • L5 - Full Automation

Vehicle Types Covered:

  • Passenger Vehicles
  • Heavy Commercial Vehicles
  • Light Commercial Vehicles

Propulsion Types Covered:

  • ICE Vehicles
  • Hybrid Vehicles
  • Electric Vehicles (EVs)

Applications Covered:

  • Adaptive Cruise Control (ACC)
  • Lane Keeping Assist (LKA)
  • Surround View Systems
  • Autonomous Emergency Braking (AEB)
  • Driver Monitoring System (DMS)
  • Blind Spot Detection (BSD)
  • Traffic Sign Recognition (TSR)
  • Parking Assistance

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI in ADAS Market, By Component

  • 5.1 Hardware
    • 5.1.1 Cameras
    • 5.1.2 Ultrasonic Sensors
    • 5.1.3 Radar Sensors
    • 5.1.4 Electronic Control Units (ECUs)
    • 5.1.5 LiDAR Sensors
  • 5.2 Software
    • 5.2.1 AI Middleware
    • 5.2.2 Fusion & Decision Algorithms
    • 5.2.3 Perception Software
  • 5.3 Services
    • 5.3.1 Integration & Deployment
    • 5.3.2 Training & Support

6 Global AI in ADAS Market, By Technology

  • 6.1 Machine Learning (ML)
  • 6.2 Edge AI
  • 6.3 Deep Learning
  • 6.4 Sensor Fusion
  • 6.5 Computer Vision
  • 6.6 Natural Language Processing (NLP)

7 Global AI in ADAS Market, By Level of Autonomy

  • 7.1 L1 - Driver Assistance
  • 7.2 L2 - Partial Automation
  • 7.3 L3 - Conditional Automation
  • 7.4 L4 - High Automation
  • 7.5 L5 - Full Automation

8 Global AI in ADAS Market, By Vehicle Type

  • 8.1 Passenger Vehicles
  • 8.2 Heavy Commercial Vehicles
  • 8.3 Light Commercial Vehicles

9 Global AI in ADAS Market, By Propulsion Type

  • 9.1 ICE Vehicles
  • 9.2 Hybrid Vehicles
  • 9.3 Electric Vehicles (EVs)

10 Global AI in ADAS Market, By Application

  • 10.1 Adaptive Cruise Control (ACC)
  • 10.2 Lane Keeping Assist (LKA)
  • 10.3 Surround View Systems
  • 10.4 Autonomous Emergency Braking (AEB)
  • 10.5 Driver Monitoring System (DMS)
  • 10.6 Blind Spot Detection (BSD)
  • 10.7 Traffic Sign Recognition (TSR)
  • 10.8 Parking Assistance

11 Global AI in ADAS Market, By Geography

  • 11.1 North America
    • 11.1.1 United States
    • 11.1.2 Canada
    • 11.1.3 Mexico
  • 11.2 Europe
    • 11.2.1 United Kingdom
    • 11.2.2 Germany
    • 11.2.3 France
    • 11.2.4 Italy
    • 11.2.5 Spain
    • 11.2.6 Netherlands
    • 11.2.7 Belgium
    • 11.2.8 Sweden
    • 11.2.9 Switzerland
    • 11.2.10 Poland
    • 11.2.11 Rest of Europe
  • 11.3 Asia Pacific
    • 11.3.1 China
    • 11.3.2 Japan
    • 11.3.3 India
    • 11.3.4 South Korea
    • 11.3.5 Australia
    • 11.3.6 Indonesia
    • 11.3.7 Thailand
    • 11.3.8 Malaysia
    • 11.3.9 Singapore
    • 11.3.10 Vietnam
    • 11.3.11 Rest of Asia Pacific
  • 11.4 South America
    • 11.4.1 Brazil
    • 11.4.2 Argentina
    • 11.4.3 Colombia
    • 11.4.4 Chile
    • 11.4.5 Peru
    • 11.4.6 Rest of South America
  • 11.5 Rest of the World (RoW)
    • 11.5.1 Middle East
      • 11.5.1.1 Saudi Arabia
      • 11.5.1.2 United Arab Emirates
      • 11.5.1.3 Qatar
      • 11.5.1.4 Israel
      • 11.5.1.5 Rest of Middle East
    • 11.5.2 Africa
      • 11.5.2.1 South Africa
      • 11.5.2.2 Egypt
      • 11.5.2.3 Morocco
      • 11.5.2.4 Rest of Africa

12 Strategic Market Intelligence

  • 12.1 Industry Value Network and Supply Chain Assessment
  • 12.2 White-Space and Opportunity Mapping
  • 12.3 Product Evolution and Market Life Cycle Analysis
  • 12.4 Channel, Distributor, and Go-to-Market Assessment

13 Industry Developments and Strategic Initiatives

  • 13.1 Mergers and Acquisitions
  • 13.2 Partnerships, Alliances, and Joint Ventures
  • 13.3 New Product Launches and Certifications
  • 13.4 Capacity Expansion and Investments
  • 13.5 Other Strategic Initiatives

14 Company Profiles

  • 14.1 Tesla, Inc.
  • 14.2 NVIDIA Corporation
  • 14.3 Intel Corporation
  • 14.4 Qualcomm Incorporated
  • 14.5 Robert Bosch GmbH
  • 14.6 Continental AG
  • 14.7 ZF Friedrichshafen AG
  • 14.8 Aptiv PLC
  • 14.9 Valeo SA
  • 14.10 Hyundai Mobis
  • 14.11 Denso Corporation
  • 14.12 Ambarella, Inc.
  • 14.13 Horizon Robotics
  • 14.14 Seeing Machines Ltd.
  • 14.15 Plus.ai

List of Tables

  • Table 1 Global AI in ADAS Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI in ADAS Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI in ADAS Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 4 Global AI in ADAS Market Outlook, By Cameras (2023-2034) ($MN)
  • Table 5 Global AI in ADAS Market Outlook, By Ultrasonic Sensors (2023-2034) ($MN)
  • Table 6 Global AI in ADAS Market Outlook, By Radar Sensors (2023-2034) ($MN)
  • Table 7 Global AI in ADAS Market Outlook, By Electronic Control Units (ECUs) (2023-2034) ($MN)
  • Table 8 Global AI in ADAS Market Outlook, By LiDAR Sensors (2023-2034) ($MN)
  • Table 9 Global AI in ADAS Market Outlook, By Software (2023-2034) ($MN)
  • Table 10 Global AI in ADAS Market Outlook, By AI Middleware (2023-2034) ($MN)
  • Table 11 Global AI in ADAS Market Outlook, By Fusion & Decision Algorithms (2023-2034) ($MN)
  • Table 12 Global AI in ADAS Market Outlook, By Perception Software (2023-2034) ($MN)
  • Table 13 Global AI in ADAS Market Outlook, By Services (2023-2034) ($MN)
  • Table 14 Global AI in ADAS Market Outlook, By Integration & Deployment (2023-2034) ($MN)
  • Table 15 Global AI in ADAS Market Outlook, By Training & Support (2023-2034) ($MN)
  • Table 16 Global AI in ADAS Market Outlook, By Technology (2023-2034) ($MN)
  • Table 17 Global AI in ADAS Market Outlook, By Machine Learning (ML) (2023-2034) ($MN)
  • Table 18 Global AI in ADAS Market Outlook, By Edge AI (2023-2034) ($MN)
  • Table 19 Global AI in ADAS Market Outlook, By Deep Learning (2023-2034) ($MN)
  • Table 20 Global AI in ADAS Market Outlook, By Sensor Fusion (2023-2034) ($MN)
  • Table 21 Global AI in ADAS Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 22 Global AI in ADAS Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 23 Global AI in ADAS Market Outlook, By Level of Autonomy (2023-2034) ($MN)
  • Table 24 Global AI in ADAS Market Outlook, By L1 - Driver Assistance (2023-2034) ($MN)
  • Table 25 Global AI in ADAS Market Outlook, By L2 - Partial Automation (2023-2034) ($MN)
  • Table 26 Global AI in ADAS Market Outlook, By L3 - Conditional Automation (2023-2034) ($MN)
  • Table 27 Global AI in ADAS Market Outlook, By L4 - High Automation (2023-2034) ($MN)
  • Table 28 Global AI in ADAS Market Outlook, By L5 - Full Automation (2023-2034) ($MN)
  • Table 29 Global AI in ADAS Market Outlook, By Vehicle Type (2023-2034) ($MN)
  • Table 30 Global AI in ADAS Market Outlook, By Passenger Vehicles (2023-2034) ($MN)
  • Table 31 Global AI in ADAS Market Outlook, By Heavy Commercial Vehicles (2023-2034) ($MN)
  • Table 32 Global AI in ADAS Market Outlook, By Light Commercial Vehicles (2023-2034) ($MN)
  • Table 33 Global AI in ADAS Market Outlook, By Propulsion Type (2023-2034) ($MN)
  • Table 34 Global AI in ADAS Market Outlook, By ICE Vehicles (2023-2034) ($MN)
  • Table 35 Global AI in ADAS Market Outlook, By Hybrid Vehicles (2023-2034) ($MN)
  • Table 36 Global AI in ADAS Market Outlook, By Electric Vehicles (EVs) (2023-2034) ($MN)
  • Table 37 Global AI in ADAS Market Outlook, By Application (2023-2034) ($MN)
  • Table 38 Global AI in ADAS Market Outlook, By Adaptive Cruise Control (ACC) (2023-2034) ($MN)
  • Table 39 Global AI in ADAS Market Outlook, By Lane Keeping Assist (LKA) (2023-2034) ($MN)
  • Table 40 Global AI in ADAS Market Outlook, By Surround View Systems (2023-2034) ($MN)
  • Table 41 Global AI in ADAS Market Outlook, By Autonomous Emergency Braking (AEB) (2023-2034) ($MN)
  • Table 42 Global AI in ADAS Market Outlook, By Driver Monitoring System (DMS) (2023-2034) ($MN)
  • Table 43 Global AI in ADAS Market Outlook, By Blind Spot Detection (BSD) (2023-2034) ($MN)
  • Table 44 Global AI in ADAS Market Outlook, By Traffic Sign Recognition (TSR) (2023-2034) ($MN)
  • Table 45 Global AI in ADAS Market Outlook, By Parking Assistance (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.