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市场调查报告书
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2021740

人工智慧（AI）在自动驾驶汽车领域的市场：未来预测（至2034年）－按组件、自动驾驶等级、车辆类型、类别、应用、最终用户和地区进行分析

AI in Autonomous Vehicles Market Forecasts to 2034 - Global Analysis By Component (Hardware, Software, and Services), Level of Autonomy, Vehicle Type, Type, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，预计到 2026 年，全球自动驾驶汽车人工智慧市场规模将达到 280 亿美元，并在预测期内以 26.5% 的复合年增长率增长，到 2034 年将达到 1800 亿美元。

自动驾驶汽车中的人工智慧技术利用先进的演算法和机器学习技术，使车辆能够感知周围环境、做出决策并实现无人驾驶。它融合了电脑视觉、感测器融合和即时数据处理等技术，能够识别物体、进行道路导航并应对动态路况。这项技术使车辆能够适应交通状况、侦测障碍物，并透过数据驱动的学习不断提升性能，从而提高安全性、效率和驾驶便利性。

对提高道路安全和减少事故的需求日益增长

人工智慧系统能够消除人为错误，例如驾驶注意力分散、超速行驶和判断力下降，这些错误占道路交通事故的90%以上。配备人工智慧演算法的高级驾驶辅助系统（ADAS）能够实现即时危险侦测、自动紧急煞车和车道维持辅助。世界各国政府和安全机构都在强制要求新车配备自动紧急煞车和行人侦测等功能。此外，随着已开发国家人口老化，人们对更安全的出行解决方案的需求日益增长。随着消费者安全意识的增强，汽车製造商正在加速人工智慧的集成，以提升车辆的安全评级，这直接推动了自动驾驶技术市场的成长。

高昂的开发和检验成本

自动驾驶系统的检验和认证过程极其复杂，通常需要在各种天气和交通状况下进行数百万英里的测试行驶。监管机构尚未制定L4和L5级自动驾驶的通用安全标准，导致各地合规要求不一致。此外，为现有汽车平臺加装自动驾驶功能需要进行重大设计变更、软体整合方面的挑战以及网路安全措施的实施。这些初始投资可能成为中小型汽车製造商和科技Start-Ups的障碍。此外，频繁的软体更新和空中下载（OTA）维护会增加长期营运成本，从而限制其在成本敏感市场的普及。

自动驾驶叫车与出游即服务 (MaaS) 的扩展

Waymo、Cruise 和百度等公司已在特定都市区部署了无人驾驶计程车车队，证明了其商业性可行性。人工智慧能够实现高效的车辆调度、动态路线优化和预测性车辆维护，从而降低服务供应商的营运成本。此外，用于机场接送、校园交通和最后一公里配送的自动驾驶接驳车也日益普及。世界各国政府都在支持利用专用车道和监管沙盒开展自动驾驶车辆试验计画。随着消费者接受度的提高和单位经济效益的改善，从车辆所有权向基于订阅的自动驾驶出行服务的转变将推动全球对人工智慧驱动的导航、感知和车辆管理解决方案的巨大需求。

网路安全漏洞和资料隐私问题

骇客可能利用人工智慧决策演算法和空中升级系统中的漏洞，控制车辆的转向、煞车或加速。针对GPS和雷射雷达的欺骗攻击会损害车辆对周围环境的感知，导致危险的驾驶决策。此外，自动驾驶车辆会持续收集大量位置、行为和生物识别数据，引发消费者和监管机构对隐私的严重担忧。即使是一起备受瞩目的安全漏洞事件，也可能严重损害民众信任，并延缓监管核准流程。如果没有强大的加密技术、入侵侦测系统和标准化的网路安全框架，这些威胁将继续成为全自动驾驶车辆广泛应用的主要障碍。

新型冠状病毒（COVID-19）的影响：

新冠疫情初期，资金筹措创业投资，自动驾驶汽车市场受到衝击。封锁措施限制了道路资料收集和人工智慧模型的实际检验。然而，疫情也加速了对非接触式旅游解决方案的需求，包括自动送货机器人和消毒车。社交距离的规范提升了人们对个人自动驾驶接驳车和小型载客机器人计程车的兴趣。半导体价值链的限制暂时影响了人工智慧晶片的供应，但很快就恢復。随着经济活动的復苏，各国政府优先发展智慧城市项目，其中包括对自动驾驶汽车基础设施的投资。疫情凸显了人工智慧物流和最后一公里配送的价值，加速了其在商用车和叫车服务领域的长期应用。

在预测期内，硬体领域预计将占据最大的市场份额。

在预测期内，硬体领域预计将占据最大的市场份额。该领域包括雷射雷达感测器、摄影机、雷达单元、GPS模组以及高性能人工智慧处理器（例如GPU和TPU），它们构成了任何自动驾驶系统的物理基础。这一主导地位源于即时环境感知和边缘运算对于半自动驾驶和全自动驾驶车辆都至关重要。此外，固态雷射雷达和神经形态晶片的持续进步正在提高精度的同时降低成本。

预计在预测期内，全自动驾驶汽车细分市场将呈现最高的复合年增长率。

在预测期内，全自动驾驶汽车（L5级）细分市场预计将呈现最高的成长率。儘管L5级汽车的商业性仍处于早期阶段，但它完全无需人为干预，因此对冗余感测器套件、故障安全型人工智慧演算法和高可靠性计算平台的需求不断增长。客製化设计的自动驾驶班车、无人计程车和最后一公里配送舱的开发正在加速该细分市场的成长。端到端深度学习技术的进步，以及光达和摄影机成本的降低，正在提高全自动驾驶的可行性。

市占率最大的地区：

在整个预测期内，北美预计将保持最大的市场份额。这主要得益于Waymo、特斯拉、Cruise和NVIDIA等领先的自动驾驶技术公司以及雄厚的创业投资资金筹措。该地区有利的法规环境，尤其是在加利福尼亚州和亚利桑那州，为广泛的实地测试提供了支持。此外，成熟的汽车生态系统、消费者对ADAS功能的高度接受度以及在都市区早期部署的无人驾驶计程车服务，都促进了高普及率的实现。

复合年增长率最高的地区：

在预测期内，亚太地区预计将呈现最高的复合年增长率，这主要得益于快速的都市化进程、可支配收入的增长以及中国、韩国和日本政府积极推进智慧城市建设。中国在百度Apollo和国内电动车生产领域的主导地位正在加速自动驾驶汽车的普及。新加坡和印度等国家新建的自动驾驶汽车测试区和製造地正在推动对人工智慧感知和规划软体的需求。各国政府正大力投资提升国产雷射雷达和人工智慧晶片技术的能力。

免费客製化服务：

订阅本报告的用户可享有以下免费自订选项之一：

  • 公司简介
    • 对其他公司（最多 3 家公司）进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域分类
    • 根据客户兴趣量身定制的主要国家/地区的市场估算、预测和复合年增长率（註：基于可行性检查）
  • 竞争性标竿分析
    • 根据产品系列、地理覆盖范围和策略联盟对主要企业进行基准分析。

目录

第一章执行摘要

  • 市场概览及主要亮点
  • 成长要素、挑战与机会
  • 竞争格局概述
  • 战略考虑和建议

第二章：分析框架

  • 分析的目标和范围
  • 相关人员分析
  • 分析的前提条件与限制
  • 分析方法

第三章 市场动态与趋势分析

  • 市场定义与结构
  • 主要市场驱动因素
  • 市场限制与挑战
  • 投资成长机会和重点领域
  • 产业威胁与风险评估
  • 科技与创新趋势
  • 新兴市场和高成长市场
  • 监管和政策环境
  • 感染疾病的影响及恢復前景

第四章：竞争环境与策略评估

  • 波特五力分析
    • 供应商议价能力
    • 买方的议价能力
    • 替代产品的威胁
    • 新进入者的威胁
    • 竞争公司之间的竞争
  • 主要企业市占率分析
  • 产品基准评效和效能比较

第五章：全球自动驾驶汽车人工智慧市场：按组件划分

  • 硬体
    • 感应器
    • 相机
    • AI处理器晶片组
    • GPS导航系统
  • 软体
    • 感知演算法
    • 路线规划与决策
    • 控制系统
    • 模拟软体
  • 服务
    • 整合与部署
    • 维护和支援
    • 资讯服务

第六章：全球自动驾驶汽车人工智慧市场：以自动驾驶等级划分

  • 一级（驾驶辅助）
  • 二级（部分自动化）
  • 3级（有条件自动驾驶）
  • 4级（高度自动化）
  • 5级（完全自动驾驶）

第七章：全球自动驾驶汽车人工智慧市场：按车辆类型划分

  • 搭乘用车
  • 商用车辆
  • 特种车辆

第八章：全球自动驾驶汽车人工智慧市场：按类型划分

  • 半自动驾驶汽车
  • 全自动驾驶汽车

第九章：全球自动驾驶汽车人工智慧市场：按应用领域划分

  • 高级驾驶辅助系统（ADAS）
  • 自动驾驶系统
  • 车队管理
  • 预测性保护
  • 地图绘製和位置识别
  • 运输/物流
  • 其他用途

第十章：全球自动驾驶汽车人工智慧市场：按最终用户划分

  • OEM（目的地设备製造商）
  • 行动服务供应商
  • 车队营运商
  • 叫车公司
  • 研究与发展机构

第十一章：全球自动驾驶汽车人工智慧市场：按地区划分

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 荷兰
    • 比利时
    • 瑞典
    • 瑞士
    • 波兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 泰国
    • 马来西亚
    • 新加坡
    • 越南
    • 其他亚太国家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 智利
    • 秘鲁
    • 其他南美国家
  • 世界其他地区（RoW）
    • 中东
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 以色列
      • 其他中东国家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲国家

第十二章 策略市场资讯

  • 工业价值网络和供应链评估
  • 空白区域和机会地图
  • 产品演进与市场生命週期分析
  • 通路、经销商和打入市场策略的评估

第十三章 产业趋势与策略倡议

  • 併购
  • 伙伴关係、联盟和合资企业
  • 新产品发布和认证
  • 扩大生产能力和投资
  • 其他策略倡议

第十四章：公司简介

  • Tesla, Inc.
  • Waymo LLC
  • NVIDIA Corporation
  • Pony.ai
  • Aurora Innovation, Inc.
  • Zoox, Inc.
  • Baidu, Inc.
  • Mobileye Global Inc.
  • Aptiv PLC
  • Continental AG
  • Robert Bosch GmbH
  • Kodiak AI, Inc.
  • Wayve Technologies Ltd
  • Waabi
  • DeepRoute.ai
Product Code: SMRC35022

According to Stratistics MRC, the Global AI in Autonomous Vehicles Market is accounted for $28.0 billion in 2026 and is expected to reach $180.0 billion by 2034 growing at a CAGR of 26.5% during the forecast period. AI in autonomous vehicles involves the use of advanced algorithms and machine learning techniques to enable vehicles to perceive their environment, make decisions, and operate without human intervention. It integrates technologies such as computer vision, sensor fusion, and real-time data processing to identify objects, navigate roads, and respond to dynamic conditions. This technology enhances safety, efficiency, and driving convenience by allowing vehicles to adapt to traffic patterns, detect obstacles, and continuously improve performance through data-driven learning.

Market Dynamics:

Driver:

Increasing demand for enhanced road safety and accident reduction

AI-powered systems eliminate human errors such as distracted driving, speeding, and impaired judgment, which account for over 90% of road accidents. Advanced driver assistance systems (ADAS) equipped with AI algorithms enable real-time hazard detection, automatic emergency braking, and lane-keeping assistance. Governments and safety organizations worldwide are mandating features like autonomous emergency braking and pedestrian detection in new vehicles. Additionally, aging populations in developed regions require safer mobility solutions. As consumers become more safety-conscious, automakers are accelerating AI integration to achieve higher safety ratings, directly boosting market growth for autonomous driving technologies.

Restraint:

High development and validation costs

Validation and certification processes for self-driving systems are extremely complex, often requiring millions of test miles under diverse weather and traffic conditions. Regulatory bodies have not yet established universal safety standards for Level 4 and Level 5 autonomy, leading to fragmented compliance requirements across regions. Additionally, retrofitting existing vehicle platforms with autonomous capabilities involves significant engineering changes, software integration challenges, and cybersecurity implementations. For smaller automotive manufacturers and technology startups, these upfront capital expenditures can be prohibitive. Furthermore, frequent software updates and over-the-air maintenance add long-term operational expenses, limiting widespread adoption in cost-sensitive markets.

Opportunity:

Expansion of autonomous ride-hailing and mobility-as-a-service

Companies like Waymo, Cruise, and Baidu are already deploying robotaxi fleets in select urban corridors, demonstrating commercial viability. AI enables efficient fleet dispatching, dynamic route optimization, and predictive vehicle maintenance, reducing operational costs for service providers. Additionally, autonomous shuttles for airport transfers, campus transportation, and last-mile delivery are gaining traction. Governments are supporting pilot programs with dedicated autonomous vehicle lanes and regulatory sandboxes. As consumer acceptance increases and unit economics improve, the shift from vehicle ownership to subscription-based autonomous mobility services will drive massive demand for AI-powered navigation, perception, and fleet management solutions globally.

Threat:

Cybersecurity vulnerabilities and data privacy concerns

Hackers could potentially gain control over steering, braking, or acceleration by exploiting vulnerabilities in AI decision-making algorithms or over-the-air update systems. Spoofing attacks on GPS or LiDAR can corrupt environmental perception, leading to dangerous driving decisions. Additionally, autonomous vehicles continuously collect vast amounts of location, behavioral, and biometric data, raising serious privacy concerns among consumers and regulators. A single high-profile security breach could severely damage public trust and slow down regulatory approvals. Without robust encryption, intrusion detection systems, and standardized cybersecurity frameworks, these threats remain a significant barrier to mass adoption of fully autonomous vehicles.

Covid-19 Impact:

The COVID-19 pandemic initially disrupted the autonomous vehicle market due to halted production lines, delayed testing programs, and reduced venture capital funding. Lockdowns limited on-road data collection and real-world validation for AI models. However, the pandemic accelerated demand for contactless mobility solutions, including autonomous delivery robots and sanitizing vehicles. Social distancing norms increased interest in personal autonomous shuttles and low-occupancy robotaxis. Supply chain constraints for semiconductors temporarily affected AI chip availability, but recovery was swift. As economies reopened, governments prioritized smart city initiatives with autonomous vehicle infrastructure investments. The pandemic underscored the value of AI-driven logistics and last-mile delivery, driving long-term adoption across commercial fleets and ride-hailing services.

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 LiDAR sensors, cameras, radar units, GPS modules, and high-performance AI processors such as GPUs and TPUs that form the physical backbone of any autonomous driving system. The essential need for real-time environmental sensing and edge computing in both semi-autonomous and fully autonomous vehicles drives this dominance. Additionally, ongoing advancements in solid-state LiDAR and neuromorphic chips reduce costs while improving accuracy.

The fully autonomous vehicles segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the fully autonomous vehicles (Level 5) segment is predicted to witness the highest growth rate. Although commercially nascent, Level 5 vehicles require no human intervention, driving demand for redundant sensor suites, fail-safe AI algorithms, and high-reliability compute platforms. The development of purpose-built autonomous shuttles, robotaxis, and last-mile delivery pods accelerates this segment. Breakthroughs in end-to-end deep learning, combined with falling LiDAR and camera costs, make full autonomy more feasible.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, driven by the presence of major autonomous technology leaders such as Waymo, Tesla, Cruise, and NVIDIA, along with robust venture capital funding. The region's favorable regulatory environment in states like California and Arizona supports extensive real-world testing. Additionally, a mature automotive ecosystem, high consumer acceptance of ADAS features, and early adoption of robotaxi services in urban centers contribute to high adoption rates.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, fueled by rapid urbanization, rising disposable incomes, and aggressive government initiatives for smart cities in China, South Korea, and Japan. China's leadership in Baidu Apollo and domestic EV production accelerates autonomous vehicle deployment. The establishment of new autonomous vehicle testing zones and manufacturing hubs in countries like Singapore and India drives demand for AI perception and planning software. Governments are investing heavily in indigenous LiDAR and AI chip capabilities.

Key players in the market

Some of the key players in AI in Autonomous Vehicles Market include Tesla, Inc., Waymo LLC, NVIDIA Corporation, Pony.ai, Aurora Innovation, Inc., Zoox, Inc., Baidu, Inc., Mobileye Global Inc., Aptiv PLC, Continental AG, Robert Bosch GmbH, Kodiak AI, Inc., Wayve Technologies Ltd, Waabi, and DeepRoute.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 August 2025, Bosch and CARIAD are intensifying their cooperation within the Automated Driving Alliance: the partners are developing their software stack for Level 2 and 3 assisted and automated driving by making full use of artificial intelligence. To this end, Bosch and CARIAD are expanding their existing approaches to include state-of-the-art AI methods. This should lead to more powerful, more intelligent driver assistance systems that act as naturally as a human driver taking the driving experience to a new level and making it even safer. The software stack covers all essential cognitive tasks of perception, interpretation, decision-making, and action.

Components Covered:

  • Hardware
  • Software
  • Services

Levels of Autonomy Covered:

  • Level 1 (Driver Assistance)
  • Level 2 (Partial Automation)
  • Level 3 (Conditional Automation)
  • Level 4 (High Automation)
  • Level 5 (Full Automation)

Vehicle Types Covered:

  • Passenger Vehicles
  • Commercial Vehicles
  • Special Purpose Vehicles

Types Covered:

  • Semi-Autonomous Vehicles
  • Fully Autonomous Vehicles

Applications Covered:

  • Advanced Driver Assistance Systems (ADAS)
  • Autonomous Driving Systems
  • Fleet Management
  • Predictive Maintenance
  • Mapping & Localization
  • Transportation & Logistics
  • Other Applications

End Users Covered:

  • Original Equipment Manufacturers (OEMs)
  • Mobility Service Providers
  • Fleet Operators
  • Ride-Hailing Companies
  • Research & Development Organizations

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 Autonomous Vehicles Market, By Component

  • 5.1 Hardware
    • 5.1.1 Sensors
    • 5.1.2 Cameras
    • 5.1.3 AI Processors & Chipsets
    • 5.1.4 GPS & Navigation Systems
  • 5.2 Software
    • 5.2.1 Perception Algorithms
    • 5.2.2 Path Planning & Decision-Making
    • 5.2.3 Control Systems
    • 5.2.4 Simulation Software
  • 5.3 Services
    • 5.3.1 Integration & Deployment
    • 5.3.2 Maintenance & Support
    • 5.3.3 Data Services

6 Global AI in Autonomous Vehicles Market, By Level of Autonomy

  • 6.1 Level 1 (Driver Assistance)
  • 6.2 Level 2 (Partial Automation)
  • 6.3 Level 3 (Conditional Automation)
  • 6.4 Level 4 (High Automation)
  • 6.5 Level 5 (Full Automation)

7 Global AI in Autonomous Vehicles Market, By Vehicle Type

  • 7.1 Passenger Vehicles
  • 7.2 Commercial Vehicles
  • 7.3 Special Purpose Vehicles

8 Global AI in Autonomous Vehicles Market, By Type

  • 8.1 Semi-Autonomous Vehicles
  • 8.2 Fully Autonomous Vehicles

9 Global AI in Autonomous Vehicles Market, By Application

  • 9.1 Advanced Driver Assistance Systems (ADAS)
  • 9.2 Autonomous Driving Systems
  • 9.3 Fleet Management
  • 9.4 Predictive Maintenance
  • 9.5 Mapping & Localization
  • 9.6 Transportation & Logistics
  • 9.7 Other Applications

10 Global AI in Autonomous Vehicles Market, By End User

  • 10.1 Original Equipment Manufacturers (OEMs)
  • 10.2 Mobility Service Providers
  • 10.3 Fleet Operators
  • 10.4 Ride-Hailing Companies
  • 10.5 Research & Development Organizations

11 Global AI in Autonomous Vehicles 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 Waymo LLC
  • 14.3 NVIDIA Corporation
  • 14.4 Pony.ai
  • 14.5 Aurora Innovation, Inc.
  • 14.6 Zoox, Inc.
  • 14.7 Baidu, Inc.
  • 14.8 Mobileye Global Inc.
  • 14.9 Aptiv PLC
  • 14.10 Continental AG
  • 14.11 Robert Bosch GmbH
  • 14.12 Kodiak AI, Inc.
  • 14.13 Wayve Technologies Ltd
  • 14.14 Waabi
  • 14.15 DeepRoute.ai

List of Tables

  • Table 1 Global AI in Autonomous Vehicles Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI in Autonomous Vehicles Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI in Autonomous Vehicles Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 4 Global AI in Autonomous Vehicles Market Outlook, By Sensors (2023-2034) ($MN)
  • Table 5 Global AI in Autonomous Vehicles Market Outlook, By Cameras (2023-2034) ($MN)
  • Table 6 Global AI in Autonomous Vehicles Market Outlook, By AI Processors & Chipsets (2023-2034) ($MN)
  • Table 7 Global AI in Autonomous Vehicles Market Outlook, By GPS & Navigation Systems (2023-2034) ($MN)
  • Table 8 Global AI in Autonomous Vehicles Market Outlook, By Software (2023-2034) ($MN)
  • Table 9 Global AI in Autonomous Vehicles Market Outlook, By Perception Algorithms (2023-2034) ($MN)
  • Table 10 Global AI in Autonomous Vehicles Market Outlook, By Path Planning & Decision-Making (2023-2034) ($MN)
  • Table 11 Global AI in Autonomous Vehicles Market Outlook, By Control Systems (2023-2034) ($MN)
  • Table 12 Global AI in Autonomous Vehicles Market Outlook, By Simulation Software (2023-2034) ($MN)
  • Table 13 Global AI in Autonomous Vehicles Market Outlook, By Services (2023-2034) ($MN)
  • Table 14 Global AI in Autonomous Vehicles Market Outlook, By Integration & Deployment (2023-2034) ($MN)
  • Table 15 Global AI in Autonomous Vehicles Market Outlook, By Maintenance & Support (2023-2034) ($MN)
  • Table 16 Global AI in Autonomous Vehicles Market Outlook, By Data Services (2023-2034) ($MN)
  • Table 17 Global AI in Autonomous Vehicles Market Outlook, By Level of Autonomy (2023-2034) ($MN)
  • Table 18 Global AI in Autonomous Vehicles Market Outlook, By Level 1 (Driver Assistance) (2023-2034) ($MN)
  • Table 19 Global AI in Autonomous Vehicles Market Outlook, By Level 2 (Partial Automation) (2023-2034) ($MN)
  • Table 20 Global AI in Autonomous Vehicles Market Outlook, By Level 3 (Conditional Automation) (2023-2034) ($MN)
  • Table 21 Global AI in Autonomous Vehicles Market Outlook, By Level 4 (High Automation) (2023-2034) ($MN)
  • Table 22 Global AI in Autonomous Vehicles Market Outlook, By Level 5 (Full Automation) (2023-2034) ($MN)
  • Table 23 Global AI in Autonomous Vehicles Market Outlook, By Vehicle Type (2023-2034) ($MN)
  • Table 24 Global AI in Autonomous Vehicles Market Outlook, By Passenger Vehicles (2023-2034) ($MN)
  • Table 25 Global AI in Autonomous Vehicles Market Outlook, By Commercial Vehicles (2023-2034) ($MN)
  • Table 26 Global AI in Autonomous Vehicles Market Outlook, By Special Purpose Vehicles (2023-2034) ($MN)
  • Table 27 Global AI in Autonomous Vehicles Market Outlook, By Type (2023-2034) ($MN)
  • Table 28 Global AI in Autonomous Vehicles Market Outlook, By Semi-Autonomous Vehicles (2023-2034) ($MN)
  • Table 29 Global AI in Autonomous Vehicles Market Outlook, By Fully Autonomous Vehicles (2023-2034) ($MN)
  • Table 30 Global AI in Autonomous Vehicles Market Outlook, By Application (2023-2034) ($MN)
  • Table 31 Global AI in Autonomous Vehicles Market Outlook, By Advanced Driver Assistance Systems (ADAS) (2023-2034) ($MN)
  • Table 32 Global AI in Autonomous Vehicles Market Outlook, By Autonomous Driving Systems (2023-2034) ($MN)
  • Table 33 Global AI in Autonomous Vehicles Market Outlook, By Fleet Management (2023-2034) ($MN)
  • Table 34 Global AI in Autonomous Vehicles Market Outlook, By Predictive Maintenance (2023-2034) ($MN)
  • Table 35 Global AI in Autonomous Vehicles Market Outlook, By Mapping & Localization (2023-2034) ($MN)
  • Table 36 Global AI in Autonomous Vehicles Market Outlook, By Transportation & Logistics (2023-2034) ($MN)
  • Table 37 Global AI in Autonomous Vehicles Market Outlook, By Other Applications (2023-2034) ($MN)
  • Table 38 Global AI in Autonomous Vehicles Market Outlook, By End User (2023-2034) ($MN)
  • Table 39 Global AI in Autonomous Vehicles Market Outlook, By Original Equipment Manufacturers (OEMs) (2023-2034) ($MN)
  • Table 40 Global AI in Autonomous Vehicles Market Outlook, By Mobility Service Providers (2023-2034) ($MN)
  • Table 41 Global AI in Autonomous Vehicles Market Outlook, By Fleet Operators (2023-2034) ($MN)
  • Table 42 Global AI in Autonomous Vehicles Market Outlook, By Ride-Hailing Companies (2023-2034) ($MN)
  • Table 43 Global AI in Autonomous Vehicles Market Outlook, By Research & Development Organizations (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.