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市場調查報告書
商品編碼
2083090

自動駕駛卡車市場：商業機會、成長要素、產業趨勢分析及2026-2035年預測

Self-Driving Truck Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2026 - 2035
出版日期: | 出版商: Global Market Insights Inc. | 英文 275 Pages | 商品交期: 2-3個工作天內

價格
簡介目錄

全球自動駕駛卡車市場預計到 2025 年將達到 20 億美元，到 2035 年將以 39.4% 的複合年成長率成長，達到 638 億美元。

自動駕駛卡車市場-IMG1

隨著長期人手不足、營運成本不斷上漲以及提高配送效率的壓力日益增大，貨運業正迅速擴張。經驗豐富的卡車駕駛人難以覓食，加上員工偏好不斷變化，促使物流公司投資自動駕駛技術，以確保貨物運輸的連續性，同時減少對人工操作的依賴。自動駕駛卡車可以長時間運作，不受駕駛人疲勞的限制，從而提高車輛運轉率和運輸效率。電子商務和國際貿易的持續成長進一步增加了對可靠貨運的需求，以滿足更快的配送需求。自動駕駛卡車透過最佳化路線、最大限度地減少等待時間和實現全天候運營，幫助物流運營商提高生產力並降低營運成本。此外，更穩定的駕駛模式有助於提高燃油效率並改善交通流量，進而提升自動駕駛卡車市場的長期成長前景。

市場範圍
開始年份 2025
預測期 2026-2035
上市時的市場規模 20億美元
預計金額 638億美元
複合年成長率 39.4%

預計到2025年，L3級自動駕駛卡車市佔率將達到64.4%，並在2035年之前以38.9%的複合年成長率成長。該細分市場之所以能夠持續保持最大的市場佔有率，是因為其在自動駕駛能力和人工監管之間實現了有效的平衡。 L3級自動駕駛卡車可以在規定的駕駛條件下執行大部分駕駛功能，同時允許駕駛員在必要時接管控制權。這種能力可以減輕駕駛者疲勞，提高燃油效率，並提升長途貨運效率。對高階駕駛輔助系統（ADAS）、高速公路自動駕駛技術和智慧車輛管理解決方案日益成長的需求，正在加速L3級自動駕駛卡車在商業物流營運的應用。

預計到2025年，硬體部分將佔據55.1%的市場佔有率，並在2026年至2035年間以38.8%的複合年成長率成長。由於自動駕駛卡車高度依賴主導的硬體組件，例如LiDAR、雷達、攝影機、超音波感測器、GPS模組、高性能處理器和車載運算系統，因此該部分保持領先地位。這些技術使車輛能夠感知周圍環境、識別障礙物、處理即時駕駛訊息，並在各種路況下安全行駛。為確保運作可靠性，對多個冗餘感測系統的需求不斷成長，並持續推動對先進硬體的需求。預計L3和L4級自動駕駛卡車的持續擴展部署將進一步加速對高性能自動駕駛組件的投資。

中國自動駕駛卡車市場目前佔據全球64.2%的佔有率，預計2025年市場規模將達到7億美元。中國市場成長的主要驅動力包括物流行業的持續擴張、人工智慧技術的快速發展以及對自動駕駛汽車研發的大量投資。大規模的貨運市場以及支援智慧型運輸系統（ITS）的政策進一步鞏固了市場成長。眾多自動駕駛技術開發商和製造商的存在也促進了持續創新，鞏固了中國在區域自動駕駛卡車市場的主導地位。

目錄

第1章：調查方法

第2章執行摘要

第3章 行業洞察

  • 產業生態系分析
    • 供應商情況
    • 利潤率分析
    • 成本結構
    • 每個階段增加的價值
    • 影響價值鏈的因素
    • 中斷
  • 影響產業的因素
    • 促進因素
      • 卡車運輸業正面臨日益嚴重的司機短缺問題。
      • 提高貨運效率的需求日益成長
      • 人工智慧、感測器和自動駕駛技術的進步
      • 人們越來越關注交通安全和減少事故。
    • 產業潛在風險與挑戰
      • 高昂的開發和實施成本
      • 監管和法律方面的不確定性
    • 市場機遇
      • 開發自主長途貨運網路
      • 自動駕駛卡車即服務 (TaaS) 模式的成長
      • 在採礦、港口和工業物流領域得到更廣泛的應用。
      • 增加對智慧交通基礎設施的投資
  • 成長潛力分析
  • 技術與創新展望
    • 最新科技趨勢
    • 新興技術
  • 價格分析
    • 對過去價格趨勢的分析
    • 依球員類型分類的定價策略（高級球員、超值球員、成本加成球員）
  • 監管指南
    • 北美洲
      • 美國：聯邦汽車運輸安全管理局 (FMCSA) 的自動駕駛商用車框架和國家公路交通安全管理局 (NHTSA) 的自動駕駛系統 (ADS) 法規
      • 加拿大：加拿大運輸部關於自動駕駛和聯網汽車。
    • 歐洲
      • 德國：《自動駕駛法》（AFGBV）及聯邦車輛管理局（KBA）對自動駕駛車輛核准的要求
      • 英國：自動駕駛車輛法案和互聯自動駕駛出行法規結構（CAM）
      • 法國：《以移動性為導向的法律》（LOM）和關於自動化道路運輸系統的法規
      • 義大利：智慧道路條例和聯合國歐洲經濟委員會關於汽車車道維持系統（ALKS）的合規要求
    • 亞太地區
      • 中國：智慧網聯汽車示範試驗和自動化貨物運輸的法規和指南
      • 印度：公路運輸和公路部（MoRTH）車輛自動化政策和AIS安全標準
      • 日本：國土交通省《自動駕駛車輛安全標準與道路運輸車輛法》
      • 韓國：自動駕駛汽車商業化法案及K-City自動駕駛測試框架
      • 澳洲：國家運輸委員會 (NTC) 對自動駕駛汽車和《重型車輛國家法案》(HVNL) 進行監管改革
    • 拉丁美洲
      • 巴西：CONTRAN的聯網汽車法規和自動化貨物運輸試點計畫框架
      • 墨西哥：NOM商用車輛安全標準與智慧型運輸系統（ITS）法規
      • 阿根廷：國家公路交通安全管理局 (ANSV)聯網汽車法規結構與自動駕駛示範項目
    • 中東和非洲
      • 阿拉伯聯合大公國：阿拉伯聯合大公國自動駕駛交通戰略和智慧貨運交通法規
      • 沙烏地阿拉伯：交通運輸總局 (TGA) 自動駕駛車輛指南和 SASO 商用車輛標準
      • 南非：《國家道路交通法》及連網自動駕駛車輛測試框架
  • 波特的分析
  • PESTLE分析
  • 專利趨勢
  • 貿易數據分析
    • 進出口量及進口額趨勢
    • 主要貿易路線及關稅的影響
  • 生產能力和生產情況
    • 設備產能：按地區和主要生產商分類
    • 運轉率和擴張計劃
  • 成本細分分析
  • 人工智慧和生成式人工智慧對市場的影響
    • 利用人工智慧改造現有經營模式
    • 按細分市場分類的生成式人工智慧用例和部署藍圖
    • 風險、限制和監管考量
  • 預測假設和情境分析
    • 基本案例：驅動複合年成長率的關鍵宏觀經濟與產業變量
    • 樂觀情境：宏觀經濟與產業的順風
    • 悲觀情景：宏觀經濟放緩或產業逆風

第4章 競爭情勢

  • 介紹
  • 企業市佔率分析
  • 主要市場公司的競爭分析
  • 競爭定位矩陣
  • 主要進展
    • 併購
    • 夥伴關係和聯盟
    • 新產品發布
    • 業務拓展計劃及資金籌措
  • 按公司規模進行基準測試
    • 排名分類標準與遴選標準
    • 按銷售額、地區和創新能力分類的層級定位矩陣。

第5章 市場估價與預測：依自動駕駛等級分類，2022-2035年

  • 3級
  • 4級
  • 5級

第6章 市場估計與預測：依組件分類，2022-2035年

  • 硬體
    • LiDAR感測器
    • 雷達感測器
    • 相機和視覺系統
    • 超音波感測器
    • 計算單元（ECU/GPU/AI晶片）
    • GPS和高清地圖模組
    • V2X 通訊硬體
  • 軟體
    • 感知/人工智慧/機器學習演算法
    • 路線規劃與決策平台
    • 模擬和虛擬測試軟體
    • OTA 更新與車隊管理軟體
  • 服務
    • 系統整合和實施服務
    • 遠端監控和遠端控制服務
    • 維護和支援服務
    • 數據分析與洞察服務

第7章 市場估計與預測：依應用領域分類，2022-2035年

  • 長途貨物運輸
  • 樞紐間運輸
  • 最後一公里配送/本地配送
  • 礦業和建築物流
  • 港口和堆場作業
  • 工業物流
  • 其他

第8章 市場估算與預測：依最終使用者分類，2022-2035年

  • 物流/運輸公司
  • 電子商務公司
  • 零售和消費品公司
  • 製造公司
  • 礦業公司
  • 政府/國防
  • 其他

第9章 市場估計與預測：依促進因素分類，2022-2035年

  • 內燃機（ICE）
  • 電的
    • 電池式電動車（BEV）
    • 燃料電池電動車（FCEV）
  • 混合

第10章 市場估價與預測：依車輛類別分類，2022-2035年

  • 四年級
  • 五年級
  • 六年級
  • 七年級
  • 八年級

第11章 市場估價與預測：按地區分類，2022-2035年

  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 荷蘭
    • 比利時
  • 亞太地區
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 韓國
    • 紐西蘭
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • 中東和非洲
    • 南非
    • 沙烏地阿拉伯
    • UAE

第12章：公司簡介

  • 世界公司
    • Applied Intuition
    • Aurora Innovation
    • Daimler Truck
    • Einride
    • PACCAR
    • Plus（PlusAI）
    • Tesla
    • TRATON
    • Volvo
    • Waabi
  • 本地公司
    • DeepWay
    • Gatik
    • Hyundai Motor Company
    • Inceptio Technology
    • Isuzu Motors
    • Kodiak Robotics
    • Pony.ai
  • 新興企業
    • Bot Auto
    • RideFlux
    • Trunk Technology
簡介目錄
Product Code: 16152

The Global Self-Driving Truck Market was valued at USD 2 billion in 2025 and is estimated to grow at a CAGR of 39.4% to reach USD 63.8 billion by 2035.

Self-Driving Truck Market - IMG1

The market is expanding rapidly as the freight transportation industry seeks solutions to address persistent workforce shortages, rising operating costs, and increasing pressure to improve delivery efficiency. The declining availability of experienced truck drivers, coupled with changing workforce preferences, has encouraged logistics companies to invest in autonomous transportation technologies that reduce reliance on human operators while ensuring continuous cargo movement. Self-driving trucks offer the ability to operate for extended periods without the limitations associated with driver fatigue, improving fleet utilization and transportation efficiency. The continued expansion of e-commerce activities and international trade is further increasing demand for reliable freight transportation capable of supporting faster delivery schedules. Autonomous trucking also enables better route optimization, minimizes idle time, and supports around-the-clock operations, helping logistics providers improve productivity and lower operating expenses. In addition, more consistent driving patterns contribute to greater fuel efficiency and smoother traffic flow, reinforcing the long-term growth prospects of the self-driving truck market.

Market Scope
Start Year2025
Forecast Year2026-2035
Start Value$2 Billion
Forecast Value$63.8 Billion
CAGR39.4%

The Level 3 segment accounted for 64.4% share in 2025 and is projected to grow at a CAGR of 38.9% through 2035. This segment continues to hold the largest market share because it provides an effective balance between automated driving capabilities and human oversight. Level 3 autonomous trucks can perform most driving functions under defined operating conditions while allowing the driver to assume control whenever necessary. This capability helps reduce driver fatigue, improve fuel efficiency, and enhance the performance of long-distance freight transportation. Growing demand for advanced driver assistance systems (ADAS), highway automation technologies, and intelligent fleet management solutions continues to accelerate the adoption of Level 3 autonomous trucks across commercial logistics operations.

The hardware segment held 55.1% share in 2025 and is anticipated to grow at a CAGR of 38.8% between 2026 and 2035. The segment maintains its leading position because autonomous trucks rely heavily on sophisticated hardware components, including LiDAR, radar, cameras, ultrasonic sensors, GPS modules, high-performance processors, and onboard computing systems. These technologies enable vehicles to detect their surroundings, identify obstacles, process real-time driving information, and navigate safely under varying road conditions. The increasing requirement for multiple redundant sensing systems to ensure operational reliability continues to drive demand for advanced hardware. Growing deployment of Level 3 and Level 4 autonomous trucks is expected to further accelerate investment in high-performance autonomous driving components.

China Self-Driving Truck Market held 64.2% share, generating USD 0.7 billion in 2025. Market growth in the country is supported by the continued expansion of the logistics industry, rapid advancements in artificial intelligence technologies, and significant investment in autonomous vehicle development. A large freight transportation sector, combined with supportive policies promoting intelligent transportation systems, continues to strengthen market growth. The presence of numerous autonomous driving technology developers and manufacturers also contributes to continuous innovation, reinforcing China's leadership within the regional self-driving truck market.

Major companies operating in the global self-driving truck market include Tesla, Volvo, Daimler Truck, Waabi, DeepWay, TRATON, Pony.ai, Plus (PlusAI), Einride, and Inceptio Technology. Companies operating in the self-driving truck market are strengthening their competitive position by investing heavily in autonomous driving software, advanced sensing technologies, and artificial intelligence to improve vehicle safety and operational performance. Many industry participants are expanding strategic partnerships with logistics providers, technology developers, and fleet operators to accelerate commercialization and large-scale deployment. Continuous research and development efforts are focused on enhancing autonomous driving capabilities, improving sensor accuracy, and increasing system reliability. Businesses are also investing in high-performance hardware platforms, cloud-connected fleet management solutions, and over-the-air software updates to optimize vehicle operations.

Table of Contents

Chapter 1 Methodology

  • 1.1 Research approach
  • 1.2 Quality Commitments
    • 1.2.1 GMI AI policy & data integrity commitment
      • 1.2.1.1 Source consistency protocol
  • 1.3 Research Trail & Confidence Scoring
    • 1.3.1 Research Trail Components
    • 1.3.2 Scoring Components
  • 1.4 Data Collection
    • 1.4.1 Partial list of primary sources
  • 1.5 Data mining sources
    • 1.5.1 Paid sources
      • 1.5.1.1 Sources, by region
  • 1.6 Base estimates and calculations
    • 1.6.1 Base year calculation
  • 1.7 Forecast Model
    • 1.7.1 Quantified market impact analysis
      • 1.7.1.1 Mathematical impact of growth parameters on forecast
  • 1.8 Research transparency addendum
    • 1.8.1 Source attribution framework
    • 1.8.2 Quality assurance metrics
    • 1.8.3 Our commitment to trust

Chapter 2 Executive Summary

  • 2.1 Industry 360° synopsis, 2022 - 2035
  • 2.2 Key market trends
    • 2.2.1 Regional
    • 2.2.2 Level of autonomy
    • 2.2.3 Component
    • 2.2.4 Application
    • 2.2.5 End user
    • 2.2.6 Propulsion
    • 2.2.7 Vehicle Class
  • 2.3 TAM Analysis, 2026-2035
  • 2.4 CXO perspectives: Strategic imperatives

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
    • 3.1.1 Supplier landscape
    • 3.1.2 Profit margin analysis
    • 3.1.3 Cost structure
    • 3.1.4 Value addition at each stage
    • 3.1.5 Factor affecting the value chain
    • 3.1.6 Disruptions
  • 3.2 Industry impact forces
    • 3.2.1 Growth drivers
      • 3.2.1.1 Rising driver shortages in the trucking industry
      • 3.2.1.2 Growing demand for freight transportation efficiency
      • 3.2.1.3 Advancements in AI, sensors, and autonomous driving technologies
      • 3.2.1.4 Increasing focus on road safety and accident reduction
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 High development and deployment costs
      • 3.2.2.2 Regulatory and legal uncertainties
    • 3.2.3 Market opportunities
      • 3.2.3.1 Development of autonomous long-haul freight networks
      • 3.2.3.2 Growth of autonomous truck-as-a-service (TaaS) models
      • 3.2.3.3 Expansion in mining, port, and industrial logistics applications
      • 3.2.3.4 Increasing investments in smart transportation infrastructure
  • 3.3 Growth potential analysis
  • 3.4 Technology and Innovation landscape
    • 3.4.1 Current technological trends
    • 3.4.2 Emerging technologies
  • 3.5 Pricing Analysis (Driven by Primary Research)
    • 3.5.1 Historical Price Trend Analysis
    • 3.5.2 Pricing Strategy by Player Type (Premium / Value / Cost-plus)
  • 3.6 Regulatory guidelines
    • 3.6.1 North America
      • 3.6.1.1 U.S.: FMCSA Autonomous Commercial Vehicle Framework & NHTSA Automated Driving System (ADS) Regulations
      • 3.6.1.2 Canada: Transport Canada Automated and Connected Vehicle Policy Framework & Motor Vehicle Safety Regulations.
    • 3.6.2 Europe
      • 3.6.2.1 Germany: Autonomous Driving Act (AFGBV) & KBA Automated Vehicle Approval Requirements
      • 3.6.2.2 UK: Automated Vehicles Act & Connected and Automated Mobility (CAM) Regulatory Framework
      • 3.6.2.3 France: Mobility Orientation Law (LOM) & Automated Road Transport System Regulations
      • 3.6.2.4 Italy: Smart Road Decree & UNECE Automated Lane Keeping System (ALKS) Compliance Requirements
    • 3.6.3 Asia Pacific
      • 3.6.3.1 China: Intelligent Connected Vehicle (ICV) Pilot Regulations & Autonomous Freight Transport Guidelines
      • 3.6.3.2 India: Ministry of Road Transport & Highways (MoRTH) Vehicle Automation Policies & AIS Safety Standards
      • 3.6.3.3 Japan: MLIT Automated Driving Vehicle Safety Standards & Road Transport Vehicle Act
      • 3.6.3.4 South Korea: Autonomous Vehicle Commercialization Act & K-City Autonomous Driving Testing Framework
      • 3.6.3.5 Australia: National Transport Commission (NTC) Automated Vehicle Regulatory Reforms & Heavy Vehicle National Law (HVNL)
    • 3.6.4 Latin America
      • 3.6.4.1 Brazil: CONTRAN Connected Vehicle Regulations & Autonomous Freight Mobility Pilot Framework
      • 3.6.4.2 Mexico: NOM Commercial Vehicle Safety Standards & Intelligent Transport System (ITS) Regulations
      • 3.6.4.3 Argentina: National Road Safety Agency (ANSV) Connected Vehicle Compliance Framework & Automated Mobility Pilot Programs
    • 3.6.5 MEA
      • 3.6.5.1 UAE: UAE Autonomous Transportation Strategy & Smart Freight Mobility Regulations
      • 3.6.5.2 Saudi Arabia: Transport General Authority (TGA) Autonomous Vehicle Guidelines & SASO Commercial Vehicle Standards
      • 3.6.5.3 South Africa: National Road Traffic Act & Connected and Automated Vehicle Testing Framework
  • 3.7 Porter's analysis
  • 3.8 PESTEL analysis
  • 3.9 Patent Landscape (Driven by Primary Research)
  • 3.10 Trade Data Analysis (Driven by paid database)
    • 3.10.1 Import/export volume & value trends
    • 3.10.2 Key trade corridors & tariff impact
  • 3.11 Capacity & Production Landscape (Driven by Primary Research)
    • 3.11.1 Installed Capacity by Region & Key Producer
    • 3.11.2 Capacity Utilization Rates & Expansion Pipelines
  • 3.12 Cost breakdown analysis
  • 3.13 Impact of AI & Generative AI on the Market (Driven by Primary Research)
    • 3.13.1 AI-Driven Disruption of Existing Business Models
    • 3.13.2 GenAI Use Cases & Adoption Roadmap by Segment
    • 3.13.3 Risks, Limitations & Regulatory Considerations
  • 3.14 Forecast assumptions & scenario analysis (Driven by Primary Research)
    • 3.14.1 Base Case - Key Macro & Industry Variables Driving CAGR
    • 3.14.2 Optimistic Scenarios - Favourable macro and industry tailwinds
    • 3.14.3 Pessimistic Scenario - Macroeconomic slowdown or industry headwinds

Chapter 4 Competitive Landscape, 2025

  • 4.1 Introduction
  • 4.2 Company market share analysis
    • 4.2.1 North America
    • 4.2.2 Europe
    • 4.2.3 Asia Pacific
    • 4.2.4 Latin America
    • 4.2.5 MEA
  • 4.3 Competitive analysis of major market players
  • 4.4 Competitive positioning matrix
  • 4.5 Key developments
    • 4.5.1 Mergers & acquisitions
    • 4.5.2 Partnerships & collaborations
    • 4.5.3 New Product Launches
    • 4.5.4 Expansion Plans and funding
  • 4.6 Company Tier Benchmarking
    • 4.6.1 Tier Classification Criteria & Qualifying Thresholds
    • 4.6.2 Tier Positioning Matrix by Revenue, Geography & Innovation

Chapter 5 Market Estimates & Forecast, By Level of Autonomy, 2022 - 2035 ($Bn, Units)

  • 5.1 Key trends
  • 5.2 Level 3
  • 5.3 Level 4
  • 5.4 Level 5

Chapter 6 Market Estimates & Forecast, By Component, 2022 - 2035 ($Bn, Units)

  • 6.1 Key trends
  • 6.2 Hardware
    • 6.2.1 LiDAR sensors
    • 6.2.2 Radar sensors
    • 6.2.3 Cameras & vision systems
    • 6.2.4 Ultrasonic sensors
    • 6.2.5 Compute units (ECUs / GPUs / AI Chips)
    • 6.2.6 GPS & HD mapping modules
    • 6.2.7 V2X communication hardware
  • 6.3 Software
    • 6.3.1 Perception & AI/ML algorithms
    • 6.3.2 Path planning & decision-making platforms
    • 6.3.3 Simulation & virtual testing software
    • 6.3.4 OTA update & fleet management software
  • 6.4 Services
    • 6.4.1 System integration & deployment services
    • 6.4.2 Remote monitoring & teleoperation services
    • 6.4.3 Maintenance & support services
    • 6.4.4 Data analytics & insights services

Chapter 7 Market Estimates & Forecast, By Application, 2022 - 2035 ($Bn, Units)

  • 7.1 Key trends
  • 7.2 Long-haul freight transportation
  • 7.3 Hub-to-hub transportation
  • 7.4 Last-mile & regional delivery
  • 7.5 Mining & construction logistics
  • 7.6 Port & yard operations
  • 7.7 Industrial logistics
  • 7.8 Others

Chapter 8 Market Estimates & Forecast, By End User, 2022 - 2035 ($Bn, Units)

  • 8.1 Key trends
  • 8.2 Logistics & transportation companies
  • 8.3 E-commerce companies
  • 8.4 Retail & consumer goods companies
  • 8.5 Manufacturing companies
  • 8.6 Mining companies
  • 8.7 Government & defense
  • 8.8 Others

Chapter 9 Market Estimates & Forecast, By Propulsion, 2022 - 2035 ($Bn, Units)

  • 9.1 Key trends
  • 9.2 Internal combustion engine (ICE)
  • 9.3 Electric
    • 9.3.1 Battery electric vehicles (BEV)
    • 9.3.2 Fuel cell electric vehicle (FCEV)
  • 9.4 Hybrid

Chapter 10 Market Estimates & Forecast, By Vehicle Class, 2022 - 2035 ($Bn, Units)

  • 10.1 Key trends
  • 10.2 Class 4
  • 10.3 Class 5
  • 10.4 Class 6
  • 10.5 Class 7
  • 10.6 Class 8

Chapter 11 Market Estimates & Forecast, By Region, 2022 - 2035 ($Bn, Units)

  • 11.1 Key trends
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 France
    • 11.3.4 Italy
    • 11.3.5 Spain
    • 11.3.6 Russia
    • 11.3.7 Netherlands
    • 11.3.8 Belgium
  • 11.4 Asia Pacific
    • 11.4.1 China
    • 11.4.2 India
    • 11.4.3 Japan
    • 11.4.4 Australia
    • 11.4.5 South Korea
    • 11.4.6 New Zealand
  • 11.5 Latin America
    • 11.5.1 Brazil
    • 11.5.2 Mexico
    • 11.5.3 Argentina
  • 11.6 MEA
    • 11.6.1 South Africa
    • 11.6.2 Saudi Arabia
    • 11.6.3 UAE

Chapter 12 Company Profiles

  • 12.1 Global Players
    • 12.1.1 Applied Intuition
    • 12.1.2 Aurora Innovation
    • 12.1.3 Daimler Truck
    • 12.1.4 Einride
    • 12.1.5 PACCAR
    • 12.1.6 Plus (PlusAI)
    • 12.1.7 Tesla
    • 12.1.8 TRATON
    • 12.1.9 Volvo
    • 12.1.10 Waabi
  • 12.2 Regional Players
    • 12.2.1 DeepWay
    • 12.2.2 Gatik
    • 12.2.3 Hyundai Motor Company
    • 12.2.4 Inceptio Technology
    • 12.2.5 Isuzu Motors
    • 12.2.6 Kodiak Robotics
    • 12.2.7 Pony.ai
  • 12.3 Emerging Players
    • 12.3.1 Bot Auto
    • 12.3.2 RideFlux
    • 12.3.3 Trunk Technology