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1755864

2032 年機器人穿梭巴士和自動駕駛公車市場預測：按組件、車輛類型、推進類型、自主等級、應用、最終用戶和地區進行的全球分析

Robot Shuttles and Autonomous Buses Market Forecasts to 2032 - Global Analysis By Component (Hardware, Software, and Services), Vehicle Type, Propulsion Type, Level of Autonomy, Application, End User, and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球機器人接駁車和自動駕駛巴士市場預計在 2025 年達到 3.6388 億美元，預計到 2032 年將達到 21.1665 億美元，預測期內的複合年成長率為 28.6%。

機器人穿梭巴士和自動駕駛公車是專為駕駛人而設計的自動駕駛公共交通工具。它們配備感測器、人工智慧和先進的導航系統，提供高效、安全且環保的出行解決方案。這些車輛通常由電力驅動，用於在都市區、校園和封閉迴路境中提供「首英里」和「最後一英里」的出行連接。它們已成為全球智慧城市和永續交通計劃的關鍵創新。

對智慧和永續旅行的需求不斷成長

人們對高效環保的交通解決方案的偏好日益成長，推動了自動駕駛接駁車的普及。世界各地的城市都在投資智慧運輸系統，以減少交通堵塞和排放。公共交通機構正在採用自動駕駛技術，以提高可及性和可靠性。電動車和自動駕駛汽車的普及與氣候變遷目標和永續性計劃一致。人工智慧和感測器技術的進步使自動駕駛公車更加安全、高效。

公眾的懷疑和安全擔憂

許多乘客仍不確定在動態城市環境中是否應該信任自動駕駛系統。備受矚目的事故和技術故障引發了人們對其可靠性和風險緩解策略的質疑。政府和行業領導者正在努力建立標準化的安全通訊協定，以安撫公眾。贏得公眾信任需要持續的測試和實際部署。

引入電動車以減少排放

碳中和交通運輸的推動為自動駕駛班車帶來了巨大的機會。各國政府和企業正在設定零排放目標，加速電動自動駕駛汽車的轉變。電動公車與自動駕駛系統的整合將降低營運成本並減少對環境的影響。電池技術的創新和充電基礎設施的擴展將支持電動機器人接駁車的廣泛應用。消費者對環保旅遊解決方案的日益偏好將進一步推動投資。

混合交通中即時導航的複雜性

應對複雜的交通狀況仍然是自動駕駛公車面臨的一大挑戰。行人、騎乘者和難以預測的駕駛交織在一起，需要精準的主導決策。即時感測器融合和機器學習必須不斷適應不斷變化的道路狀況。法律規範難以跟上自動駕駛出行技術的快速發展。基礎設施落後的城市可能難以無縫連接機器人接駁車。

COVID-19的影響

隨著城市尋求更安全的交通途徑，疫情加速了人們對非接觸式自動駕駛解決方案的興趣。勞動力減少凸顯了自動駕駛汽車在確保公共運輸持續暢通的重要性。各國政府優先發展自動駕駛和遠端控制交通途徑，以最大限度地減少人際互動。這場危機凸顯了彈性自動化交通網路在城市規劃中的重要性。疫情後的投資趨勢表明，自動駕駛出行技術將持續成長。

預計在預測期內硬體部分將成為最大的部分。

由於對先進感測器、AI 處理器和通訊模組的需求不斷成長，預計硬體領域將在預測期內佔據最大的市場佔有率。自動駕駛公車高度依賴LiDAR、雷達和攝影機系統來實現精確導航和障礙物偵測。對穩健車輛架構的需求推動自動駕駛技術組件的持續創新。邊緣運算和車載 AI 處理方面的硬體進步正在改善即時決策。

預計預測期內，交通運輸部門的複合年成長率最高。

預計交通運輸部門將在預測期內達到最高成長率。政府支持智慧城市發展的措施正在加速車輛的部署。人們對公共交通現代化日益成長的興趣推動了對人工智慧移動解決方案的投資。相關部門正在與自動駕駛汽車公司合作，以提高效率和永續性。對交通堵塞和環境影響日益成長的擔憂也促進了該部門的擴張。

比最大的地區

由於快速的都市化和大規模的智慧交通投資，預計亞太地區將在預測期內佔據最大的市場佔有率。中國、日本和韓國等國家是自動駕駛出行解決方案的早期採用者。政府支持的試驗計畫和補貼正在加速自動駕駛公車的商業化部署。不斷擴展的公共交通網路和完善的基礎設施將支持市場發展。

複合年成長率最高的地區

由於強力的監管支持和技術領先，北美地區預計將在預測期內呈現最高的複合年成長率。 Waymo、Cruise 和 Zoox 等公司正在開發自動駕駛解決方案。都市區和校園環境中機器人穿梭巴士的日益普及將推動市場擴張。人們對交通效率和環境影響的日益擔憂，正推動城市向自動駕駛出行解決方案邁進。

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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 研究範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 限制因素
  • 機會
  • 威脅
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買家的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球機器人穿梭巴士和自動駕駛巴士市場（按組件）

  • 硬體
    • 感應器
    • GPS/GNSS模組
    • 處理器/控制單元
    • 通訊系統
    • 電動馬達和電池系統
  • 軟體
    • 基於人工智慧的駕駛演算法
    • 地圖定位
    • 車輛管理系統
  • 服務
    • 部署和整合
    • 維護
    • 遠端操作

6. 全球機器人穿梭車和自動駕駛巴士市場（依車輛類型）

  • 自動穿梭巴士
  • 自動駕駛巴士

7. 全球機器人穿梭車和自動駕駛巴士市場（按推進類型）

  • 電
  • 混合
  • 氫燃料電池
  • 內燃機（ICE）

8. 全球機器人穿梭巴士和自動駕駛巴士市場（依自主程度分類）

  • 1級（駕駛輔助）
  • 2級（部分自動化）
  • 3級（有條件自動化）
  • 4級（高度自動化）
  • 5級（全自動）

9. 全球機器人穿梭巴士和自動駕駛巴士市場（按應用）

  • 公共運輸
  • 醫療保健和退休社區
  • 機場/校園接駁車
  • 主題樂園活動
  • 觀光
  • 商業園區和工業
  • 其他

第10章。全球機器人穿梭車和自動駕駛巴士市場（按最終用戶分類）

  • 地方政府
  • 交通運輸管理局
  • 私營部門營運商（技術或移動出行公司）
  • 企業客戶
  • 大學/校園
  • 其他

第 11 章。全球機器人穿梭車和自動駕駛巴士市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第13章 公司概況

  • Waymo
  • Baidu
  • EasyMile
  • Navya
  • May Mobility
  • Cruise
  • Zoox
  • Nuro
  • Mobileye
  • NVIDIA
  • Toyota
  • WeRide
  • Pony.ai
  • Local Motors
  • BYD
  • Daimler Truck Holding AG
  • Transdev
  • Continental
Product Code: SMRC29758

According to Stratistics MRC, the Global Robot Shuttles and Autonomous Buses Market is accounted for $363.88 million in 2025 and is expected to reach $2116.65 million by 2032 growing at a CAGR of 28.6% during the forecast period. Robot shuttles and autonomous buses are self-driving public transport vehicles designed to operate without a human driver. Equipped with sensors, AI, and advanced navigation systems, they provide efficient, safe, and eco-friendly mobility solutions. Typically electric-powered, these vehicles are used in urban areas, campuses, and closed environments to offer first-mile and last-mile connectivity. They represent a key innovation in smart city and sustainable transportation initiatives worldwide.

Market Dynamics:

Driver:

Rising demand for smart and sustainable mobility

The growing preference for autonomous shuttles is driven by the need for efficient, eco-friendly transportation solutions. Cities worldwide are investing in smart mobility systems to reduce congestion and emissions. Public transportation authorities are embracing self-driving technology to improve accessibility and reliability. Increased adoption of electric and autonomous fleets aligns with climate goals and sustainability initiatives. Advancements in AI and sensor technology are making autonomous buses safer and more efficient.

Restraint:

Public skepticism and safety concerns

Many passengers still have reservations about trusting autonomous systems in dynamic urban environments. High-profile accidents and technical failures raise questions about reliability and risk mitigation strategies. Governments and industry leaders are working to establish standardized safety protocols to reassure the public. Continuous testing and real-world deployments are required to build public confidence.

Opportunity:

Electric vehicle adoption for emission reduction

The push toward carbon-neutral transportation is a significant opportunity for autonomous shuttles. Governments and corporations are setting zero-emission targets, accelerating the shift to electric self-driving fleets. Integration of electric buses with autonomous systems reduces operational costs and environmental impact. Battery innovations and charging infrastructure expansion support the widespread deployment of electric robot shuttles. Growing consumer preference for green mobility solutions further drives investment.

Threat:

Complexities in real-time navigation in mixed traffic

Navigating heterogeneous traffic conditions remains a major challenge for autonomous buses. Mixed environments with pedestrians, cyclists, and unpredictable drivers require precise AI-driven decision-making. Real-time sensor fusion and machine learning must continually adapt to changing road scenarios. Regulatory frameworks struggle to keep pace with rapid technological advancements in autonomous mobility. Cities with legacy infrastructure may not be fully equipped for seamless robotic shuttle integration.

Covid-19 Impact

The pandemic accelerated interest in contactless, autonomous transit solutions as cities sought safer transportation alternatives. Reduced workforce availability emphasized the value of self-driving vehicles in ensuring continuous public transportation. Governments prioritized automated and remote-controlled transit options to minimize human interaction. The crisis highlighted the importance of resilient, automated transportation networks in urban planning. Post-pandemic investment trends indicate sustained growth in autonomous mobility technologies.

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, due to growing demand for advanced sensors, AI processors, and communication modules. Autonomous buses rely heavily on LiDAR, radar, and camera systems for precise navigation and obstacle detection. The need for robust vehicle architecture drives continuous innovation in self-driving technology components. Hardware advancements in edge computing and onboard AI processing are improving real-time decision-making.

The transportation authorities segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the transportation authorities segment is predicted to witness the highest growth rate. Government initiatives supporting smart city development accelerate fleet deployment. Increased focus on public transit modernization encourages investment in AI-powered mobility solutions. Authorities are partnering with autonomous vehicle firms to improve efficiency and sustainability. Rising concerns over traffic congestion and environmental impact fuel expansion.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share due to rapid urbanization and large-scale smart transportation investments. Countries like China, Japan, and South Korea are early adopters of autonomous mobility solutions. Government-backed pilot programs and subsidies accelerate the commercial deployment of self-driving buses. Expanding public transit networks and infrastructure development support market growth.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to strong regulatory support and technological leadership. Companies like Waymo, Cruise, and Zoox are pioneering autonomous transit solutions. Increasing adoption of robotic shuttles in urban and campus environments drives market expansion. Rising concerns over traffic efficiency and environmental impact push cities toward self-driving mobility solutions.

Key players in the market

Some of the key players profiled in the Robot Shuttles and Autonomous Buses Market include Waymo, Baidu, EasyMile, Navya, May Mobility, Cruise, Zoox, Nuro, Mobileye, NVIDIA, Toyota, WeRide, Pony.ai, Local Motors, BYD, Daimler Truck Holding AG, Transdev, and Continental.

Key Developments:

In June 2025, Daimler Truck, logistics provider DHL Group and commercial vehicle rental provider hylane GmbH signed a cooperation agreement in the field of fully electric trucks at the "transport logistic" trade fair in Munich. The partnership stipulates that DHL will obtain 30 electric trucks of the type Mercedes-Benz eActros 600 through hylane's "Transport as a Service model."

In April 2025, Continental has launched three all-new MTB tires, designed to provide riders with increased performance, durability, and ultimate grip on every trail. These tires, Dubnital, Trinotal, and Magnotal sit alongside the acclaimed Gravity range, ensuring that every rider, from XC racers to trail enthusiasts, finds the perfect tire for their chosen terrain.

Components Covered:

  • Hardware
  • Software
  • Services

Vehicle Types Covered:

  • Autonomous Shuttles
  • Autonomous Buses

Propulsion Types Covered:

  • Electric
  • Hybrid
  • Hydrogen Fuel Cell
  • Internal Combustion Engine (ICE)

Levels of Autonomy Covered:

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

Applications Covered:

  • Public Transportation
  • Healthcare and Retirement Communities
  • Airport & Campus Shuttles
  • Theme Parks and Events
  • Tourism & Sightseeing
  • Business Parks & Industrial Campuses
  • Other Applications

End Users Covered:

  • Municipal Governments
  • Transportation Authorities
  • Private Operators (Tech or Mobility Companies)
  • Corporate Clients
  • Universities & Campuses
  • Other End Users

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 2024, 2025, 2026, 2028, and 2032
  • 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

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Robot Shuttles and Autonomous Buses Market, By Component

  • 5.1 Introduction
  • 5.2 Hardware
    • 5.2.1 Sensors
    • 5.2.2 GPS/GNSS modules
    • 5.2.3 Processors and control units
    • 5.2.4 Communication systems
    • 5.2.5 Electric motors and battery systems
  • 5.3 Software
    • 5.3.1 AI-based driving algorithms
    • 5.3.2 Mapping & localization
    • 5.3.3 Fleet management systems
  • 5.4 Services
    • 5.4.1 Deployment & integration
    • 5.4.2 Maintenance
    • 5.4.3 Remote operations

6 Global Robot Shuttles and Autonomous Buses Market, By Vehicle Type

  • 6.1 Introduction
  • 6.2 Autonomous Shuttles
  • 6.3 Autonomous Buses

7 Global Robot Shuttles and Autonomous Buses Market, By Propulsion Type

  • 7.1 Introduction
  • 7.2 Electric
  • 7.3 Hybrid
  • 7.4 Hydrogen Fuel Cell
  • 7.5 Internal Combustion Engine (ICE)

8 Global Robot Shuttles and Autonomous Buses Market, By Level of Autonomy

  • 8.1 Introduction
  • 8.2 Level 1 (Driver Assistance)
  • 8.3 Level 2 (Partial Automation)
  • 8.4 Level 3 (Conditional Automation)
  • 8.5 Level 4 (High Automation)
  • 8.6 Level 5 (Full Automation)

9 Global Robot Shuttles and Autonomous Buses Market, By Application

  • 9.1 Introduction
  • 9.2 Public Transportation
  • 9.3 Healthcare and Retirement Communities
  • 9.4 Airport & Campus Shuttles
  • 9.5 Theme Parks and Events
  • 9.6 Tourism & Sightseeing
  • 9.7 Business Parks & Industrial Campuses
  • 9.8 Other Applications

10 Global Robot Shuttles and Autonomous Buses Market, By End User

  • 10.1 Introduction
  • 10.2 Municipal Governments
  • 10.3 Transportation Authorities
  • 10.4 Private Operators (Tech or Mobility Companies)
  • 10.5 Corporate Clients
  • 10.6 Universities & Campuses
  • 10.7 Other End Users

11 Global Robot Shuttles and Autonomous Buses Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Waymo
  • 13.2 Baidu
  • 13.3 EasyMile
  • 13.4 Navya
  • 13.5 May Mobility
  • 13.6 Cruise
  • 13.7 Zoox
  • 13.8 Nuro
  • 13.9 Mobileye
  • 13.10 NVIDIA
  • 13.11 Toyota
  • 13.12 WeRide
  • 13.13 Pony.ai
  • 13.14 Local Motors
  • 13.15 BYD
  • 13.16 Daimler Truck Holding AG
  • 13.17 Transdev
  • 13.18 Continental

List of Tables

  • Table 1 Global Robot Shuttles and Autonomous Buses Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Robot Shuttles and Autonomous Buses Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Robot Shuttles and Autonomous Buses Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 4 Global Robot Shuttles and Autonomous Buses Market Outlook, By Sensors (2024-2032) ($MN)
  • Table 5 Global Robot Shuttles and Autonomous Buses Market Outlook, By GPS/GNSS modules (2024-2032) ($MN)
  • Table 6 Global Robot Shuttles and Autonomous Buses Market Outlook, By Processors and control units (2024-2032) ($MN)
  • Table 7 Global Robot Shuttles and Autonomous Buses Market Outlook, By Communication systems (2024-2032) ($MN)
  • Table 8 Global Robot Shuttles and Autonomous Buses Market Outlook, By Electric motors and battery systems (2024-2032) ($MN)
  • Table 9 Global Robot Shuttles and Autonomous Buses Market Outlook, By Software (2024-2032) ($MN)
  • Table 10 Global Robot Shuttles and Autonomous Buses Market Outlook, By AI-based driving algorithms (2024-2032) ($MN)
  • Table 11 Global Robot Shuttles and Autonomous Buses Market Outlook, By Mapping & localization (2024-2032) ($MN)
  • Table 12 Global Robot Shuttles and Autonomous Buses Market Outlook, By Fleet management systems (2024-2032) ($MN)
  • Table 13 Global Robot Shuttles and Autonomous Buses Market Outlook, By Services (2024-2032) ($MN)
  • Table 14 Global Robot Shuttles and Autonomous Buses Market Outlook, By Deployment & integration (2024-2032) ($MN)
  • Table 15 Global Robot Shuttles and Autonomous Buses Market Outlook, By Maintenance (2024-2032) ($MN)
  • Table 16 Global Robot Shuttles and Autonomous Buses Market Outlook, By Remote operations (2024-2032) ($MN)
  • Table 17 Global Robot Shuttles and Autonomous Buses Market Outlook, By Vehicle Type (2024-2032) ($MN)
  • Table 18 Global Robot Shuttles and Autonomous Buses Market Outlook, By Autonomous Shuttles (2024-2032) ($MN)
  • Table 19 Global Robot Shuttles and Autonomous Buses Market Outlook, By Autonomous Buses (2024-2032) ($MN)
  • Table 20 Global Robot Shuttles and Autonomous Buses Market Outlook, By Propulsion Type (2024-2032) ($MN)
  • Table 21 Global Robot Shuttles and Autonomous Buses Market Outlook, By Electric (2024-2032) ($MN)
  • Table 22 Global Robot Shuttles and Autonomous Buses Market Outlook, By Hybrid (2024-2032) ($MN)
  • Table 23 Global Robot Shuttles and Autonomous Buses Market Outlook, By Hydrogen Fuel Cell (2024-2032) ($MN)
  • Table 24 Global Robot Shuttles and Autonomous Buses Market Outlook, By Internal Combustion Engine (ICE) (2024-2032) ($MN)
  • Table 25 Global Robot Shuttles and Autonomous Buses Market Outlook, By Level of Autonomy (2024-2032) ($MN)
  • Table 26 Global Robot Shuttles and Autonomous Buses Market Outlook, By Level 1 (Driver Assistance) (2024-2032) ($MN)
  • Table 27 Global Robot Shuttles and Autonomous Buses Market Outlook, By Level 2 (Partial Automation) (2024-2032) ($MN)
  • Table 28 Global Robot Shuttles and Autonomous Buses Market Outlook, By Level 3 (Conditional Automation) (2024-2032) ($MN)
  • Table 29 Global Robot Shuttles and Autonomous Buses Market Outlook, By Level 4 (High Automation) (2024-2032) ($MN)
  • Table 30 Global Robot Shuttles and Autonomous Buses Market Outlook, By Level 5 (Full Automation) (2024-2032) ($MN)
  • Table 31 Global Robot Shuttles and Autonomous Buses Market Outlook, By Application (2024-2032) ($MN)
  • Table 32 Global Robot Shuttles and Autonomous Buses Market Outlook, By Public Transportation (2024-2032) ($MN)
  • Table 33 Global Robot Shuttles and Autonomous Buses Market Outlook, By Healthcare and Retirement Communities (2024-2032) ($MN)
  • Table 34 Global Robot Shuttles and Autonomous Buses Market Outlook, By Airport & Campus Shuttles (2024-2032) ($MN)
  • Table 35 Global Robot Shuttles and Autonomous Buses Market Outlook, By Theme Parks and Events (2024-2032) ($MN)
  • Table 36 Global Robot Shuttles and Autonomous Buses Market Outlook, By Tourism & Sightseeing (2024-2032) ($MN)
  • Table 37 Global Robot Shuttles and Autonomous Buses Market Outlook, By Business Parks & Industrial Campuses (2024-2032) ($MN)
  • Table 38 Global Robot Shuttles and Autonomous Buses Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 39 Global Robot Shuttles and Autonomous Buses Market Outlook, By End User (2024-2032) ($MN)
  • Table 40 Global Robot Shuttles and Autonomous Buses Market Outlook, By Municipal Governments (2024-2032) ($MN)
  • Table 41 Global Robot Shuttles and Autonomous Buses Market Outlook, By Transportation Authorities (2024-2032) ($MN)
  • Table 42 Global Robot Shuttles and Autonomous Buses Market Outlook, By Private Operators (Tech or Mobility Companies) (2024-2032) ($MN)
  • Table 43 Global Robot Shuttles and Autonomous Buses Market Outlook, By Corporate Clients (2024-2032) ($MN)
  • Table 44 Global Robot Shuttles and Autonomous Buses Market Outlook, By Universities & Campuses (2024-2032) ($MN)
  • Table 45 Global Robot Shuttles and Autonomous Buses Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.