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市場調查報告書
商品編碼
1804250

全球自動駕駛市場:各零件，各自動駕駛等級，各車輛類型，各推動類型，各車輛用途，各地區 - 市場規模，產業動態，機會分析，預測(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個工作天內

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簡介目錄

受科技的快速進步和消費者對自動駕駛系統日益增長的信心推動，自動駕駛市場目前正呈現強勁上升勢頭。 2024 年，市場規模預估約 1,702.2 億美元，預計到 2033 年將大幅成長至 6,686.4 億美元。這一驚人成長體現了 2025 年至 2033 年 17.63% 的複合年增長率，凸顯了自動駕駛領域技術創新和應用的加速發展。

按地區劃分，全球自動駕駛市場呈現顯著的成長模式，亞太地區成為最大市場，緊隨其後的是北美。亞太地區的主導地位得益於政府支持、技術的快速進步以及主要汽車製造商在該地區的強大影響力。儘管北美目前佔最大市場佔有率，但由於積極的舉措和投資，亞太地區預計將實現更快的成長。尤其是中國，它正透過政府的大力支持、廣泛的測試項目以及自動駕駛計程車服務的推出，積極推動自動駕駛汽車的發展。

值得關注的市場發展

自動駕駛市場的特點是老牌汽車製造商和大型科技公司之間的激烈競爭，每家公司都採用獨特的技術策略來搶佔市場佔有率。特斯拉仍然佔主導地位，而 Waymo 也保持領先地位，在鳳凰城、舊金山和洛杉磯等美國主要城市擁有超過 700 輛自動駕駛汽車在運作。到 2024 年中期，Waymo 的自動駕駛汽車預計將每週提供超過 15 萬次付費乘車服務，這充分證明了其服務的規模和穩健性。

競爭格局也揭示了市場滲透和自動駕駛技術開發的各種不同方法。例如，蘋果的 "泰坦計畫" （Project Titan）最初傳聞旨在實現完全自動駕駛，但後來轉移了重點。雖然該公司縮減了對完全自動駕駛汽車的雄心，但它仍在大力投資高級駕駛輔助系統 (ADAS)。這些旨在提高車輛安全性和便利性的系統預計將於2028年左右投放市場。蘋果更為謹慎、循序漸進的策略反映了行業的整體趨勢，即企業需要在創新、監管課題和市場準備之間取得平衡。

核心推動因素

自動駕駛市場正以驚人的速度發展，主要驅動力是傳統汽車製造商與尖端科技公司之間的策略聯盟，這些聯盟正在迅速改變產業格局。這些聯盟將汽車製造專業知識與先進的人工智慧和感測器技術相結合，加速了自動駕駛汽車的開發和部署。一個顯著的例子是優步於2024年1月宣布與Wayve合作，計劃於2026年開始在倫敦測試完全無人駕駛的機器人計程車。此次合作利用Wayve的Embodied AI技術，旨在將自動駕駛功能無縫整合到優步龐大的網路中，目前該網路每天提供約12.5萬次出行服務。這項舉措標誌著優步朝著在全球最大城市市場之一實現無人駕駛出行服務商業化邁出了重要一步。

新機遇

在共享出行的浪潮中，自動駕駛市場正在經歷重大轉型，而機器人計程車在重塑城市交通方面發揮關鍵作用。這些自動駕駛叫車服務正成為關鍵的創新驅動力，讓人們得以一窺城市出行的未來。預計到2030年，全球將有約250萬輛機器人計程車投入運營，覆蓋全球200多個城市。這項預期擴張既反映了技術進步，也反映了大眾日益接受自動駕駛共享出行作為傳統交通方式可行且高效的替代方案。

優化障礙

儘管自動駕駛技術發展迅速，但市場在贏得公眾信任方面仍面臨巨大課題，這主要源於普遍的懷疑態度和隱私擔憂。許多消費者對採用自動駕駛汽車仍持謹慎態度，擔心該技術帶來的潛在風險。幾起備受矚目的網路安全事件暴露了車聯網系統中的漏洞，加劇了這些擔憂。例如，日產Connect EV專案遭遇重大漏洞，引發了人們對車輛軟體可能被利用的擔憂。此外，菲亞特克萊斯勒因發現軟體漏洞而被迫召回140萬輛汽車，凸顯了軟體缺陷對汽車安全構成的具體風險。

市場區隔詳情

按組件劃分，硬體組件在自動駕駛市場佔主導地位，佔超過 65% 的市場。這種主導地位反映了實體感測器和運算基礎設施對於實現自動駕駛汽車功能的關鍵作用。開發和部署先進的感測器技術需要大量投資，而這些組件構成了車輛準確感知和解讀周圍環境的基石。

依自動駕駛等級劃分，0 級（不具備駕駛自動化）的車輛佔比相當高，為 43.63%。這一滲透率很大程度上反映了當前的經濟現實和基礎設施課題。目前道路上行駛的大多數車輛平均車齡為 12.5 年，早於自動駕駛技術的廣泛應用。因此，大多數現有車輛缺乏支援任何級別自動化所需的硬體和軟體功能。這也解釋了為什麼儘管人們對自動駕駛技術的興趣日益濃厚，但 0 級車輛仍然佔市場主導地位。

按車型劃分，SUV 在自動駕駛市場佔主導地位，約佔 34.20% 的市場佔有率。這種強勁的市場佔有率很大程度上得益於 SUV 作為整合自動駕駛必不可少的先進感測器技術的平台所具備的先天優勢。 SUV 的一大關鍵優勢在於其較高的安裝位置，這使得雷射雷達 (LiDAR) 和攝影機系統能夠顯著改善視野，通常比傳統轎車的視野擴大 25-35 度。

按動力類型劃分，電動車 (EV) 在自動駕駛市場佔顯著優勢，佔超過 45.36% 的市場佔有率。這項優勢很大程度上得益於電力傳動系統與自動駕駛系統之間天然的技術協同作用。電動車尤其適合滿足自動駕駛硬體的能源需求，因為自動駕駛硬體需要強勁且持續的動力。電動車中的高壓架構可有效管理 3,000-5,000 瓦的連續運算能力，無需影響車輛傳動系統的效率即可實現先進的自動功能。

各市場區隔明細

各零件

  • 硬體設備
    • LiDAR(光檢測·測距)感測器
    • 相機
    • RADAR(電波探測·測距)感測器
    • 超音波感測器
    • GPS及IMU(慣性測量單位)
    • ECU(電控系統)
    • 連接性·模組(V2X，5G)
  • 軟體
    • 解決方案
      • AI 演算法（機器學習、深度學習）
      • 地圖繪製與定位軟體
      • 感測器融合演算法
      • 路線規劃與控制軟體
      • 網路安全解決方案
    • 服務
        專業服務
      • 整合服務
      • 諮詢服務
      • 客製化與開發
      • 託管服務
      • 遠端監控與診斷
      • 軟體更新與補丁
      • 車隊管理
      • 資料儲存與管理

各自動駕駛等級

  • 0級：無自動化
  • 1級：輔助駕駛
  • 2級：部分自動化
  • 3級：有條件自動化
  • 4級：高度自動化
  • 5級：完全自動化

各車輛類型

  • 轎車
  • SUV
  • 巴士
  • 卡車
  • 曳引機
  • 其他

推動因素各類型

  • 內燃機(ICE)車
  • 電動車(EV)
  • 混合動力汽車

各車輛用途

  • 小客車/私人汽車
  • 商用車
    • 召車
    • 大眾運輸
      • 自動駕駛公車和接駁車
      • 基於人工智慧的公共交通路線優化
    • 物流
      • 自動駕駛貨車和送貨車
      • 人工智慧驅動的最後一哩送貨車輛
      • 用於倉庫和配送中心的自動駕駛車輛
  • 重型車/越野車
    • 礦業
    • 倉庫
    • 其他

各地區

  • 北美
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 波蘭
    • 俄羅斯
    • 其他
  • 亞太地區
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲·紐西蘭
    • ASEAN
      • 馬來西亞
      • 新加坡
      • 泰國
      • 印尼
      • 菲律賓
      • 越南
      • 其他
    • 其他地區
  • 中東·非洲
    • 阿拉伯聯合大公國
    • 沙烏地阿拉伯
    • 南非
    • 其他
  • 南美
    • 阿根廷
    • 巴西
    • 其他

市場參與企業

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

目錄

第1章 調查架構

第2章 調查手法

第3章 摘要整理:全球自動駕駛市場

第4章 全球自動駕駛市場概要

  • 產業價值鏈分析
    • 服務供應商
    • 終端用戶
  • 產業展望
    • 先進駕駛輔助系統(ADAS)概要
    • 自動駕駛車概要
  • 大環境分析
  • 波特的五力分析
  • 市場動態和趨勢
  • 市場成長與展望
  • 競爭儀表板
  • 實用的洞察(分析師的推薦事項)

第5章 全球自動駕駛市場分析(各零件)

  • 重要的洞察
  • 市場規模與預測，2020年～2033年(10億美元)
    • 硬體設備
    • 軟體

第6章 全球自動駕駛市場分析(各自動駕駛等級)

  • 重要的洞察
  • 市場規模與預測，2020年～2033年(10億美元)
    • 0 級：無駕駛自動化
    • 1 級：駕駛輔助
    • 2 級：部分駕駛自動化
    • 3 級：有條件駕駛自動化
    • 4 級：高度駕駛自動化
    • 5 級：完全自動駕駛

第7章 全球自動駕駛市場分析(各車輛類型)

  • 重要的洞察
  • 市場規模與預測，2020年～2033年(10億美元)
    • 轎車
    • SUV
    • 巴士
    • 卡車
    • 曳引機
    • 其他

第8章 全球自動駕駛市場分析(各推動類型)

  • 重要的洞察
  • 市場規模與預測，2020年～2033年(10億美元)
    • 內燃機(ICE)車
    • 電動車(EV)
    • 混合動力汽車

第9章 全球自動駕駛市場分析(各車輛用途)

  • 重要的洞察
  • 市場規模與預測，2020年～2033年(10億美元)
    • 小客車/私人汽車
    • 商用車
    • 重型車/越野車

第10章 全球自動駕駛市場分析(各地區)

  • 重要的洞察
  • 市場規模與預測，2020年～2033年(10億美元)
    • 北美
    • 西歐
    • 東歐
    • 亞太地區
    • 中東
    • 非洲
    • 南美

第11章 北美的自動駕駛市場分析

第12章 西歐的自動駕駛市場分析

第13章 東歐的自動駕駛市場分析

第14章 亞太地區的自動駕駛市場分析

第15章 中東的自動駕駛市場分析

第16章 非洲的自動駕駛市場分析

第17章 南美的自動駕駛市場分析

第18章 中國的自動駕駛市場分析

第19章 日本的自動駕駛市場分析

第20章 印度的自動駕駛市場分析

第21章 企業簡介

  • 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 附錄

簡介目錄
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