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市场调查报告书
商品编码
1804250

全球自动驾驶市场:各零件，各自动驾驶等级，各车辆类型，各推动类型，各车辆用途，各地区 - 市场规模，产业动态，机会分析，预测(2025年～2033年)

Global Autonomous Driving Market: Component, Autonomous Level, Vehicle Type, Propulsion Type, Vehicle Applications, Region-Market Size, Industry Dynamics, Opportunity Analysis and Forecast for 2025-2033
出版日期: | 出版商: Astute Analytica | 英文 374 Pages | 商品交期: 最快1-2个工作天内

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简介目录

受科技的快速进步和消费者对自动驾驶系统日益增长的信心推动，自动驾驶市场目前正呈现强劲上升势头。 2024 年，市场规模预估约 1,702.2 亿美元，预计到 2033 年将大幅成长至 6,686.4 亿美元。这一惊人成长体现了 2025 年至 2033 年 17.63% 的复合年增长率，凸显了自动驾驶领域技术创新和应用的加速发展。

按地区划分，全球自动驾驶市场呈现显着的成长模式，亚太地区成为最大市场，紧随其后的是北美。亚太地区的主导地位得益于政府支持、技术的快速进步以及主要汽车製造商在该地区的强大影响力。儘管北美目前占最大市场占有率，但由于积极的举措和投资，亚太地区预计将实现更快的成长。尤其是中国，它正透过政府的大力支持、广泛的测试项目以及自动驾驶计程车服务的推出，积极推动自动驾驶汽车的发展。

值得关注的市场发展

自动驾驶市场的特点是老牌汽车製造商和大型科技公司之间的激烈竞争，每家公司都采用独特的技术策略来抢占市场占有率。特斯拉仍然占主导地位，而 Waymo 也保持领先地位，在凤凰城、旧金山和洛杉矶等美国主要城市拥有超过 700 辆自动驾驶汽车在运作。到 2024 年中期，Waymo 的自动驾驶汽车预计将每週提供超过 15 万次付费乘车服务，这充分证明了其服务的规模和稳健性。

竞争格局也揭示了市场渗透和自动驾驶技术开发的各种不同方法。例如，苹果的 "泰坦计画" （Project Titan）最初传闻旨在实现完全自动驾驶，但后来转移了重点。虽然该公司缩减了对完全自动驾驶汽车的雄心，但它仍在大力投资高级驾驶辅助系统 (ADAS)。这些旨在提高车辆安全性和便利性的系统预计将于2028年左右投放市场。苹果更为谨慎、循序渐进的策略反映了行业的整体趋势，即企业需要在创新、监管课题和市场准备之间取得平衡。

核心推动因素

自动驾驶市场正以惊人的速度发展，主要驱动力是传统汽车製造商与尖端科技公司之间的策略联盟，这些联盟正在迅速改变产业格局。这些联盟将汽车製造专业知识与先进的人工智慧和感测器技术相结合，加速了自动驾驶汽车的开发和部署。一个显着的例子是优步于2024年1月宣布与Wayve合作，计划于2026年开始在伦敦测试完全无人驾驶的机器人计程车。此次合作利用Wayve的Embodied AI技术，旨在将自动驾驶功能无缝整合到优步庞大的网路中，目前该网路每天提供约12.5万次出行服务。这项举措标誌着优步朝着在全球最大城市市场之一实现无人驾驶出行服务商业化迈出了重要一步。

新机遇

在共享出行的浪潮中，自动驾驶市场正在经历重大转型，而机器人计程车在重塑城市交通方面发挥关键作用。这些自动驾驶叫车服务正成为关键的创新驱动力，让人们得以一窥城市出行的未来。预计到2030年，全球将有约250万辆机器人计程车投入运营，覆盖全球200多个城市。这项预期扩张既反映了技术进步，也反映了大众日益接受自动驾驶共享出行作为传统交通方式可行且高效的替代方案。

优化障碍

儘管自动驾驶技术发展迅速，但市场在赢得公众信任方面仍面临巨大课题，这主要源于普遍的怀疑态度和隐私担忧。许多消费者对采用自动驾驶汽车仍持谨慎态度，担心该技术带来的潜在风险。几起备受瞩目的网路安全事件暴露了车联网系统中的漏洞，加剧了这些担忧。例如，日产Connect EV专案遭遇重大漏洞，引发了人们对车辆软体可能被利用的担忧。此外，菲亚特克莱斯勒因发现软体漏洞而被迫召回140万辆汽车，凸显了软体缺陷对汽车安全构成的具体风险。

市场区隔详情

按组件划分，硬体组件在自动驾驶市场占主导地位，占超过 65% 的市场。这种主导地位反映了实体感测器和运算基础设施对于实现自动驾驶汽车功能的关键作用。开发和部署先进的感测器技术需要大量投资，而这些组件构成了车辆准确感知和解读周围环境的基石。

依自动驾驶等级划分，0 级（不具备驾驶自动化）的车辆占比相当高，为 43.63%。这一渗透率很大程度上反映了当前的经济现实和基础设施课题。目前道路上行驶的大多数车辆平均车龄为 12.5 年，早于自动驾驶技术的广泛应用。因此，大多数现有车辆缺乏支援任何级别自动化所需的硬体和软体功能。这也解释了为什么儘管人们对自动驾驶技术的兴趣日益浓厚，但 0 级车辆仍然占市场主导地位。

按车型划分，SUV 在自动驾驶市场占主导地位，约占 34.20% 的市场占有率。这种强劲的市场占有率很大程度上得益于 SUV 作为整合自动驾驶必不可少的先进感测器技术的平台所具备的先天优势。 SUV 的一大关键优势在于其较高的安装位置，这使得雷射雷达 (LiDAR) 和摄影机系统能够显着改善视野，通常比传统轿车的视野扩大 25-35 度。

按动力类型划分，电动车 (EV) 在自动驾驶市场占显着优势，占超过 45.36% 的市场占有率。这项优势很大程度上得益于电力传动系统与自动驾驶系统之间天然的技术协同作用。电动车尤其适合满足自动驾驶硬体的能源需求，因为自动驾驶硬体需要强劲且持续的动力。电动车中的高压架构可有效管理 3,000-5,000 瓦的连续运算能力，无需影响车辆传动系统的效率即可实现先进的自动功能。

各市场区隔明细

各零件

  • 硬体设备
    • LiDAR(光检测·测距)感测器
    • 相机
    • RADAR(电波探测·测距)感测器
    • 超音波感测器
    • GPS及IMU(惯性测量单位)
    • ECU(电控系统)
    • 连接性·模组(V2X，5G)
  • 软体
    • 解决方案
      • AI 演算法（机器学习、深度学习）
      • 地图绘製与定位软体
      • 感测器融合演算法
      • 路线规划与控制软体
      • 网路安全解决方案
    • 服务
        专业服务
      • 整合服务
      • 咨询服务
      • 客製化与开发
      • 託管服务
      • 远端监控与诊断
      • 软体更新与补丁
      • 车队管理
      • 资料储存与管理

各自动驾驶等级

  • 0级：无自动化
  • 1级：辅助驾驶
  • 2级：部分自动化
  • 3级：有条件自动化
  • 4级：高度自动化
  • 5级：完全自动化

各车辆类型

  • 轿车
  • SUV
  • 巴士
  • 卡车
  • 曳引机
  • 其他

推动因素各类型

  • 内燃机(ICE)车
  • 电动车(EV)
  • 混合动力汽车

各车辆用途

  • 小客车/私人汽车
  • 商用车
    • 召车
    • 大众运输
      • 自动驾驶公车和接驳车
      • 基于人工智慧的公共交通路线优化
    • 物流
      • 自动驾驶货车和送货车
      • 人工智慧驱动的最后一哩送货车辆
      • 用于仓库和配送中心的自动驾驶车辆
  • 重型车/越野车
    • 矿业
    • 仓库
    • 其他

各地区

  • 北美
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 波兰
    • 俄罗斯
    • 其他
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳洲·纽西兰
    • ASEAN
      • 马来西亚
      • 新加坡
      • 泰国
      • 印尼
      • 菲律宾
      • 越南
      • 其他
    • 其他地区
  • 中东·非洲
    • 阿拉伯联合大公国
    • 沙乌地阿拉伯
    • 南非
    • 其他
  • 南美
    • 阿根廷
    • 巴西
    • 其他

市场参与企业

  • NVIDIA Corporation
  • IPG Automotive GmbH
  • KPIT Technologies Ltd
  • Waymo LLC
  • Aptiv PLC
  • Infineon Technologies AG
  • Motional, Inc .
  • Tesla Inc.
  • 其他

目录

第1章 调查架构

第2章 调查手法

第3章 摘要整理:全球自动驾驶市场

第4章 全球自动驾驶市场概要

  • 产业价值链分析
    • 服务供应商
    • 终端用户
  • 产业展望
    • 先进驾驶辅助系统(ADAS)概要
    • 自动驾驶车概要
  • 大环境分析
  • 波特的五力分析
  • 市场动态和趋势
  • 市场成长与展望
  • 竞争仪表板
  • 实用的洞察(分析师的推荐事项)

第5章 全球自动驾驶市场分析(各零件)

  • 重要的洞察
  • 市场规模与预测，2020年～2033年(10亿美元)
    • 硬体设备
    • 软体

第6章 全球自动驾驶市场分析(各自动驾驶等级)

  • 重要的洞察
  • 市场规模与预测，2020年～2033年(10亿美元)
    • 0 级：无驾驶自动化
    • 1 级：驾驶辅助
    • 2 级：部分驾驶自动化
    • 3 级：有条件驾驶自动化
    • 4 级：高度驾驶自动化
    • 5 级：完全自动驾驶

第7章 全球自动驾驶市场分析(各车辆类型)

  • 重要的洞察
  • 市场规模与预测，2020年～2033年(10亿美元)
    • 轿车
    • SUV
    • 巴士
    • 卡车
    • 曳引机
    • 其他

第8章 全球自动驾驶市场分析(各推动类型)

  • 重要的洞察
  • 市场规模与预测，2020年～2033年(10亿美元)
    • 内燃机(ICE)车
    • 电动车(EV)
    • 混合动力汽车

第9章 全球自动驾驶市场分析(各车辆用途)

  • 重要的洞察
  • 市场规模与预测，2020年～2033年(10亿美元)
    • 小客车/私人汽车
    • 商用车
    • 重型车/越野车

第10章 全球自动驾驶市场分析(各地区)

  • 重要的洞察
  • 市场规模与预测，2020年～2033年(10亿美元)
    • 北美
    • 西欧
    • 东欧
    • 亚太地区
    • 中东
    • 非洲
    • 南美

第11章 北美的自动驾驶市场分析

第12章 西欧的自动驾驶市场分析

第13章 东欧的自动驾驶市场分析

第14章 亚太地区的自动驾驶市场分析

第15章 中东的自动驾驶市场分析

第16章 非洲的自动驾驶市场分析

第17章 南美的自动驾驶市场分析

第18章 中国的自动驾驶市场分析

第19章 日本的自动驾驶市场分析

第20章 印度的自动驾驶市场分析

第21章 企业简介

  • NVIDIA Corporation
  • IPG Automotive GmbH
  • KPIT Technologies Ltd
  • Waymo LLC
  • Aptiv PLC
  • Infineon Technologies AG
  • Motional, Inc .
  • Tesla Inc.
  • Other Prominent Players

第22章 附录

简介目录
Product Code: AA06251354

Today, the autonomous driving market is on a strong upward trajectory, propelled by rapid technological advancements and increasing consumer confidence in self-driving systems. In 2024, the market was valued at approximately US$170.22 billion and is projected to grow substantially, reaching a valuation of US$668.64 billion by 2033. This impressive expansion corresponds to a compound annual growth rate (CAGR) of 17.63% during the forecast period from 2025 to 2033, highlighting the accelerating pace of innovation and adoption within the autonomous driving sector.

Regionally, the global autonomous driving market is witnessing notable growth patterns, with the Asia Pacific region projected to emerge as the largest market, closely followed by North America. Asia Pacific's dominance is fueled by a combination of supportive government initiatives, rapid technological progress, and the strong presence of leading automakers in the region. Although North America currently holds the largest share of the market, Asia Pacific is expected to experience faster growth, driven by proactive measures and investments. China, in particular, is aggressively promoting the development of autonomous vehicles through substantial government backing, widespread testing programs, and the deployment of robotaxi services.

Noteworthy Market Developments

The autonomous driving market is characterized by intense competition between established automakers and leading technology giants, each following unique technological strategies to capture market share. Tesla remains a dominant force, but Waymo is a close contender, maintaining a leadership position with a fleet of over 700 vehicles actively operating in key U.S. cities such as Phoenix, San Francisco, and Los Angeles. By mid-2024, Waymo's autonomous vehicles were completing more than 150,000 paid rides every week, demonstrating both the scale and robustness of its service.

The competitive landscape also reveals a variety of distinct approaches toward market penetration and the development of autonomous technologies. For example, Apple's Project Titan, initially rumored to pursue full autonomy, has since shifted focus. Although the company has scaled back its ambitions for a fully autonomous vehicle, it continues to invest heavily in advanced driver assistance systems (ADAS). These systems aim to enhance vehicle safety and convenience and are expected to reach the market around 2028. Apple's more cautious and incremental approach reflects a broader trend in the industry where companies balance innovation with regulatory challenges and market readiness.

Core Growth Drivers

The autonomous driving market is progressing at an impressive pace, driven largely by strategic collaborations between traditional automakers and cutting-edge technology companies that are collectively reshaping the landscape of the industry. These partnerships enable the combination of automotive manufacturing expertise with advanced artificial intelligence and sensor technologies, accelerating the development and deployment of autonomous vehicles. A notable example occurred in January 2024, when Uber announced a partnership with Wayve to launch fully driverless robotaxi trials in London by 2026. This collaboration leverages Wayve's Embodied AI technology, which is designed to seamlessly integrate autonomous driving capabilities into Uber's extensive network that facilitates around 125,000 rides daily. The initiative represents a significant step toward commercializing driverless mobility services in one of the world's largest urban markets.

Emerging Opportunity Trends

The autonomous driving market is experiencing a profound transformation as it shifts toward shared mobility, with robotaxis playing a pivotal role in reshaping urban transportation. These autonomous ride-hailing services are becoming a key innovation driver, offering a glimpse into the future of city travel. Projections suggest that by 2030, approximately 2.5 million robotaxis will be operational around the world, covering more than 200 cities globally. This anticipated expansion reflects both technological progress and increasing public acceptance of autonomous shared mobility as a viable and efficient alternative to traditional transportation.

Barriers to Optimization

Despite rapid advancements in autonomous driving technology, the market continues to grapple with significant challenges in earning public trust, largely due to widespread skepticism and concerns over privacy. Many consumers remain cautious about embracing autonomous vehicles, fearing potential risks associated with the technology. This apprehension has been fueled by several high-profile cybersecurity incidents that have exposed vulnerabilities within connected vehicle systems. For instance, the Nissan Connect EV program suffered a notable breach, raising alarms about the possible exploitation of vehicle software. Additionally, Fiat Chrysler was compelled to recall 1.4 million vehicles due to identified software vulnerabilities, underscoring the tangible risks that software flaws can pose to vehicle safety and security.

Detailed Market Segmentation

By Component, in the autonomous driving market, hardware components hold a commanding position, accounting for more than 65% of the market share. This dominance reflects the critical importance of physical sensors and computing infrastructure in enabling autonomous vehicle functionality. The development and deployment of sophisticated sensor technology require substantial investment, as these components form the foundational elements that allow vehicles to perceive and interpret their surroundings accurately.

By Autonomous Level, vehicles classified as Level 0, which have no driving automation, hold a substantial 43.63% share. This prevalence is largely a reflection of current economic realities and infrastructural challenges. Most vehicles currently on the road are, on average, 12.5 years old, a period that predates the widespread introduction of autonomous driving technologies. As a result, the majority of the existing fleet lacks the hardware and software capabilities necessary to support any level of driving automation. This explains why Level 0 vehicles continue to dominate the market despite growing interest in autonomous technologies.

By Vehicle Type, in the autonomous driving market, SUVs hold a prominent position, capturing approximately 34.20% of the market share. This strong presence is largely due to the inherent advantages SUVs offer as platforms for integrating advanced sensor technologies essential for autonomous operation. One key benefit of SUVs is their elevated mounting positions, which allow LiDAR and camera systems to achieve a significantly improved field of view, typically enhanced by 25 to 35 degrees compared to traditional sedans.

By Propulsion Type, in the autonomous driving market, electric vehicles (EVs) hold a significant advantage, commanding over 45.36% of the market share. This dominance is largely due to the natural technological synergies between electric drivetrains and autonomous systems. Electric vehicles are particularly well-suited to support the energy demands of autonomous hardware, which requires substantial and sustained power. The high-voltage architectures found in EVs can efficiently manage continuous computing power ranging from 3,000 to 5,000 watts, enabling advanced autonomous functions without compromising the vehicle's drivetrain efficiency.

Segment Breakdown

By Component

  • Hardware
    • LiDAR (Light Detection and Ranging) Sensors
    • Cameras
    • RADAR (Radio Detection and Ranging) Sensors
    • Ultrasonic Sensors
    • GPS and IMU (Inertial Measurement Unit)
    • ECUs (Electronic Control Units)
    • Connectivity Modules (V2X, 5G)
  • Software
    • Solutions
      • AI Algorithms (Machine Learning, Deep Learning)
      • Mapping & Localization Software
      • Sensor Fusion Algorithms
      • Path Planning & Control Software
      • Cybersecurity Solutions
    • Services
      • Professional
      • Integration Services
      • Consulting Services
      • Customization & Development
      • Managed
      • Remote Monitoring & Diagnostics
      • Software Updates & Patches
      • Fleet Management
      • Data Storage & Management

By Autonomous Level

  • Level 0: no driving automation
  • Level 1: driver assistance
  • Level 2: partial driving automation
  • Level 3: conditional driving automation
  • Level 4: high driving automation
  • Level 5: full driving automation

By Vehicle Type

  • Sedans
  • SUVs
  • Buses
  • Truck
  • Tractor
  • Others

By Propulsion Type

  • Internal Combustion Engine (ICE) Vehicles
  • Electric Vehicles (EVs)
  • Hybrid Vehicles

By Vehicle Application

  • Passenger/Private Vehicles
  • Commercial Vehicles
    • Ride Hailing
    • Public Transport
      • Autonomous Buses & Shuttles
      • AI-Based Route Optimization for Mass Transit
    • Logistics
      • Autonomous Freight Trucks & Delivery Vans
      • AI-Powered Last-Mile Delivery Vehicles
      • Warehouse & Distribution Center Autonomous Fleets
  • Heavy/Off-road Vehicles
    • Mining
    • Warehouse
    • Others

By Region

  • North America
    • The U.S.
    • Canada
    • Mexico
  • Europe
    • The UK
    • Germany
    • France
    • Italy
    • Spain
    • Poland
    • Russia
    • Rest of Europe
  • Asia Pacific
    • China
    • India
    • Japan
    • South Korea
    • Australia & New Zealand
    • ASEAN
      • Malaysia
      • Singapore
      • Thailand
      • Indonesia
      • Philippines
      • Vietnam
      • Rest of ASEAN
    • Rest of Asia Pacific
  • Middle East & Africa
    • UAE
    • Saudi Arabia
    • South Africa
    • Rest of MEA
  • South America
    • Argentina
    • Brazil
    • Rest of South America

Leading Market Participants

  • NVIDIA Corporation
  • IPG Automotive GmbH
  • KPIT Technologies Ltd
  • Waymo LLC
  • Aptiv PLC
  • Infineon Technologies AG
  • Motional, Inc .
  • Tesla Inc.
  • Other Prominent Players

Table of Content

Chapter 1. Research Framework

  • 1.1. Research Objective
  • 1.2. Product Overview
  • 1.3. Market Segmentation

Chapter 2. Research Methodology

  • 2.1. Qualitative Research
    • 2.1.1. Primary & Secondary Sources
  • 2.2. Quantitative Research
    • 2.2.1. Primary & Secondary Sources
  • 2.3. Breakdown of Primary Research Respondents, By Region
  • 2.4. Assumption for the Study
  • 2.5. Market Size Estimation
  • 2.6. Data Triangulation

Chapter 3. Executive Summary: Global Autonomous Driving Market

Chapter 4. Global Autonomous Driving Market Overview

  • 4.1. Industry Value Chain Analysis
    • 4.1.1. Service Provider
    • 4.1.2. End User
  • 4.2. Industry Outlook
    • 4.2.1. Overview of Advanced Driving Assistance System (ADAS)
    • 4.2.2. Overview of Autonomous Vehicles
  • 4.3. PESTLE Analysis
  • 4.4. Porter's Five Forces Analysis
    • 4.4.1. Bargaining Power of Suppliers
    • 4.4.2. Bargaining Power of Buyers
    • 4.4.3. Threat of Substitutes
    • 4.4.4. Threat of New Entrants
    • 4.4.5. Degree of Competition
  • 4.5. Market Dynamics and Trends
    • 4.5.1. Growth Drivers
    • 4.5.2. Restraints
    • 4.5.3. Opportunities
    • 4.5.4. Key Trends
  • 4.6. Market Growth and Outlook
    • 4.6.1. Market Revenue Estimates and Forecast (US$ Bn), 2020-2033
    • 4.6.2. Price Trend Analysis
      • 4.6.2.1. By Vehicle Type
      • 4.6.2.2. By Propulsion
      • 4.6.2.3. By Automation Level
  • 4.7. Competition Dashboard
    • 4.7.1. Market Concentration Rate
    • 4.7.2. Company Market Share Analysis (Value %), 2024
    • 4.7.3. Competitor Mapping & Benchmarking
  • 4.8. Actionable Insights (Analyst's Recommendations)

Chapter 5. Global Autonomous Driving Market Analysis, By Component

  • 5.1. Key Insights
  • 5.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 5.2.1. Hardware
      • 5.2.1.1. LiDAR (Light Detection and Ranging) Sensors
      • 5.2.1.2. Cameras
      • 5.2.1.3. RADAR (Radio Detection and Ranging) Sensors
      • 5.2.1.4. Ultrasonic Sensors
      • 5.2.1.5. GPS and IMU (Inertial Measurement Unit)
      • 5.2.1.6. ECUs (Electronic Control Units)
      • 5.2.1.7. Connectivity Modules (V2X, 5G)
    • 5.2.2. Software
      • 5.2.2.1. Solutions
        • 5.2.2.1.1. AI Algorithms (Machine Learning, Deep Learning)
        • 5.2.2.1.2. Mapping & Localization Software
        • 5.2.2.1.3. Sensor Fusion Algorithms
        • 5.2.2.1.4. Path Planning & Control Software
        • 5.2.2.1.5. Cybersecurity Solutions
      • 5.2.2.2. Services
        • 5.2.2.2.1. Professional
          • 5.2.2.2.1.1. Integration Services
          • 5.2.2.2.1.2. Consulting Services
          • 5.2.2.2.1.3. Customization & Development
        • 5.2.2.2.2. Managed
          • 5.2.2.2.2.1. Remote Monitoring & Diagnostics
          • 5.2.2.2.2.2. Software Updates & Patches
          • 5.2.2.2.2.3. Fleet Management
          • 5.2.2.2.2.4. Data Storage & Management

Chapter 6. Global Autonomous Driving Market Analysis, By Autonomous Level

  • 6.1. Key Insights
  • 6.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 6.2.1. Level 0: no driving automation
    • 6.2.2. Level 1: driver assistance
    • 6.2.3. Level 2: partial driving automation
    • 6.2.4. Level 3: conditional driving automation
    • 6.2.5. Level 4: high driving automation
    • 6.2.6. Level 5: full driving automation

Chapter 7. Global Autonomous Driving Market Analysis, By Vehicle Type

  • 7.1. Key Insights
  • 7.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 7.2.1. Sedans
    • 7.2.2. SUVs
    • 7.2.3. Buses
    • 7.2.4. Truck
    • 7.2.5. Tractor
    • 7.2.6. Others

Chapter 8. Global Autonomous Driving Market Analysis, By Propulsion Type

  • 8.1. Key Insights
  • 8.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 8.2.1. Internal Combustion Engine (ICE) Vehicles
    • 8.2.2. Electric Vehicles (EVs)
    • 8.2.3. Hybrid Vehicles

Chapter 9. Global Autonomous Driving Market Analysis, By Vehicle Application

  • 9.1. Key Insights
  • 9.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 9.2.1. Passenger/Private Vehicles
    • 9.2.2. Commercial Vehicles
      • 9.2.2.1. Ride Hailing
      • 9.2.2.2. Public Transport
        • 9.2.2.2.1. Autonomous Buses & Shuttles
        • 9.2.2.2.2. AI-Based Route Optimization for Mass Transit
      • 9.2.2.3. Logistics
        • 9.2.2.3.1. Autonomous Freight Trucks & Delivery Vans
        • 9.2.2.3.2. AI-Powered Last-Mile Delivery Vehicles
        • 9.2.2.3.3. Warehouse & Distribution Center Autonomous Fleets
    • 9.2.3. Heavy/Off-road Vehicles
      • 9.2.3.1. Mining
      • 9.2.3.2. Warehouse
      • 9.2.3.3. Others

Chapter 10. Global Autonomous Driving Market Analysis, By Region

  • 10.1. Key Insights
  • 10.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 10.2.1. North America
      • 10.2.1.1. The U.S.
      • 10.2.1.2. Canada
      • 10.2.1.3. Mexico
    • 10.2.2. Western Europe
      • 10.2.2.1. The UK
      • 10.2.2.2. Germany
      • 10.2.2.3. France
      • 10.2.2.4. Italy
      • 10.2.2.5. Spain
      • 10.2.2.6. Rest of Western Europe
    • 10.2.3. Eastern Europe
      • 10.2.3.1. Poland
      • 10.2.3.2. Russia
      • 10.2.3.3. Hungary
      • 10.2.3.4. Rest of Eastern Europe
    • 10.2.4. Asia Pacific
      • 10.2.4.1. China
      • 10.2.4.2. India
      • 10.2.4.3. Japan
      • 10.2.4.4. South Korea
      • 10.2.4.5. Australia & New Zealand
      • 10.2.4.6. ASEAN
      • 10.2.4.7. Rest of Asia Pacific
    • 10.2.5. Middle East
      • 10.2.5.1. UAE
      • 10.2.5.2. Saudi Arabia
      • 10.2.5.3. Bahrain
      • 10.2.5.4. Kuwait
      • 10.2.5.5. Qatar
      • 10.2.5.6. Rest of Middle East
    • 10.2.6. Africa
      • 10.2.6.1. Morocco
      • 10.2.6.2. Egypt
      • 10.2.6.3. Nigeria
      • 10.2.6.4. South Africa
      • 10.2.6.5. Rest of Africa
    • 10.2.7. South America
      • 10.2.7.1. Argentina
      • 10.2.7.2. Brazil
      • 10.2.7.3. Rest of South America

Chapter 11. North America Autonomous Driving Market Analysis

  • 11.1. Key Insights
  • 11.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 11.2.1. By Component
    • 11.2.2. By Autonomous Level
    • 11.2.3. By Vehicle Type
    • 11.2.4. By Propulsion Type
    • 11.2.5. By Vehicle Application
    • 11.2.6. By Country

Chapter 12. Western Europe Autonomous Driving Market Analysis

  • 12.1. Key Insights
  • 12.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 12.2.1. By Component
    • 12.2.2. By Autonomous Level
    • 12.2.3. By Vehicle Type
    • 12.2.4. By Propulsion Type
    • 12.2.5. By Vehicle Application
    • 12.2.6. By Country

Chapter 13. Eastern Europe Autonomous Driving Market Analysis

  • 13.1. Key Insights
  • 13.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 13.2.1. By Component
    • 13.2.2. By Autonomous Level
    • 13.2.3. By Vehicle Type
    • 13.2.4. By Propulsion Type
    • 13.2.5. By Vehicle Application
    • 13.2.6. By Country

Chapter 14. Asia Pacific Autonomous Driving Market Analysis

  • 14.1. Key Insights
  • 14.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 14.2.1. By Component
    • 14.2.2. By Autonomous Level
    • 14.2.3. By Vehicle Type
    • 14.2.4. By Propulsion Type
    • 14.2.5. By Vehicle Application
    • 14.2.6. By Country

Chapter 15. Middle East Autonomous Driving Market Analysis

  • 15.1. Key Insights
  • 15.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 15.2.1. By Component
    • 15.2.2. By Autonomous Level
    • 15.2.3. By Vehicle Type
    • 15.2.4. By Propulsion Type
    • 15.2.5. By Vehicle Application
    • 15.2.6. By Country

Chapter 16. Africa Autonomous Driving Market Analysis

  • 16.1. Key Insights
  • 16.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 16.2.1. By Component
    • 16.2.2. By Autonomous Level
    • 16.2.3. By Vehicle Type
    • 16.2.4. By Propulsion Type
    • 16.2.5. By Vehicle Application
    • 16.2.6. By Country

Chapter 17. South America Autonomous Driving Market Analysis

  • 17.1. Key Insights
  • 17.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 17.2.1. By Component
    • 17.2.2. By Autonomous Level
    • 17.2.3. By Vehicle Type
    • 17.2.4. By Propulsion Type
    • 17.2.5. By Vehicle Application
    • 17.2.6. By Country

Chapter 18. China Autonomous Driving Market Analysis

  • 18.1. Key Insights
  • 18.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 18.2.1. By Component
    • 18.2.2. By Autonomous Level
    • 18.2.3. By Vehicle Type
    • 18.2.4. By Propulsion Type
    • 18.2.5. By Vehicle Application

Chapter 19. Japan Autonomous Driving Market Analysis

  • 19.1. Key Insights
  • 19.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 19.2.1. By Component
    • 19.2.2. By Autonomous Level
    • 19.2.3. By Vehicle Type
    • 19.2.4. By Propulsion Type
    • 19.2.5. By Vehicle Application

Chapter 20. India Autonomous Driving Market Analysis

  • 20.1. Key Insights
  • 20.2. Market Size and Forecast, 2020-2033 (US$ Bn)
    • 20.2.1. By Component
    • 20.2.2. By Autonomous Level
    • 20.2.3. By Vehicle Type
    • 20.2.4. By Propulsion Type
    • 20.2.5. By Vehicle Application

Chapter 21. Company Profile (Company Overview, Financial Matrix, Key Type landscape, Key Personnel, Key Competitors, Contact Address, and Business Strategy Outlook)

  • 21.1. NVIDIA Corporation
  • 21.2. IPG Automotive GmbH
  • 21.3. KPIT Technologies Ltd
  • 21.4. Waymo LLC
  • 21.5. Aptiv PLC
  • 21.6. Infineon Technologies AG
  • 21.7. Motional, Inc .
  • 21.8. Tesla Inc.
  • 21.9. Other Prominent Players

Chapter 22. Annexure

  • 22.1. List of Secondary Autonomous Levels
  • 22.2. Key Country Markets - Marco Economic Outlook/Indicators