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市场调查报告书
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1755864

2032 年机器人穿梭巴士和自动驾驶公车市场预测：按组件、车辆类型、推进类型、自主等级、应用、最终用户和地区进行的全球分析

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个工作天内

价格

根据 Stratistics MRC 的数据，全球机器人接驳车和自动驾驶巴士市场预计在 2025 年达到 3.6388 亿美元，预计到 2032 年将达到 21.1665 亿美元，预测期内的复合年增长率为 28.6%。

机器人穿梭巴士和自动驾驶公车是专为驾驶人而设计的自动驾驶公共交通工具。它们配备感测器、人工智慧和先进的导航系统，提供高效、安全且环保的出行解决方案。这些车辆通常由电力驱动，用于在都市区、校园和封闭环境中提供「首英里」和「最后一英里」的出行连接。它们已成为全球智慧城市和永续交通倡议的关键创新。

对智慧和永续旅行的需求不断增长

人们对高效环保的交通解决方案的偏好日益增长，推动了自动驾驶接驳车的普及。世界各地的城市都在投资智慧运输系统，以减少交通拥堵和排放。公共交通机构正在采用自动驾驶技术，以提高可及性和可靠性。电动车和自动驾驶汽车的普及与气候变迁目标和永续性倡议一致。人工智慧和感测器技术的进步使自动驾驶公车更加安全、高效。

公众的怀疑和安全担忧

许多乘客仍不确定在动态城市环境中是否应该信任自动驾驶系统。备受瞩目的事故和技术故障引发了人们对其可靠性和风险缓解策略的质疑。政府和行业领导者正在努力建立标准化的安全通讯协定，以安抚公众。赢得公众信任需要持续的测试和实际部署。

引入电动车以减少排放

碳中和交通运输的推动为自动驾驶班车带来了巨大的机会。各国政府和企业正在设定零排放目标，加速电动自动驾驶汽车的转变。电动公车与自动驾驶系统的整合将降低营运成本并减少对环境的影响。电池技术的创新和充电基础设施的扩展将支持电动机器人接驳车的广泛应用。消费者对环保旅游解决方案的日益偏好将进一步推动投资。

混合交通中即时导航的复杂性

应对复杂的交通状况仍然是自动驾驶公车面临的一大挑战。行人、骑乘者和难以预测的驾驶交织在一起，需要精准的主导决策。即时感测器融合和机器学习必须不断适应不断变化的道路状况。法律规范难以跟上自动驾驶出行技术的快速发展。基础设施落后的城市可能难以无缝连接机器人接驳车。

COVID-19的影响

随着城市寻求更安全的交通途径，疫情加速了人们对非接触式自动驾驶解决方案的兴趣。劳动力减少凸显了自动驾驶汽车在确保公共运输持续畅通的重要性。各国政府优先发展自动驾驶和远端控制交通途径，以最大限度地减少人际互动。这场危机凸显了弹性自动化交通网络在城市规划中的重要性。疫情后的投资趋势表明，自动驾驶出行技术将持续成长。

预计在预测期内硬体部分将成为最大的部分。

由于对先进感测器、AI 处理器和通讯模组的需求不断增长，预计硬体领域将在预测期内占据最大的市场占有率。自动驾驶公车高度依赖光达、雷达和摄影机系统来实现精确导航和障碍物侦测。对稳健车辆架构的需求推动自动驾驶技术组件的持续创新。边缘运算和车载 AI 处理方面的硬体进步正在改善即时决策。

预计预测期内，交通运输部门的复合年增长率最高。

预计交通运输部门将在预测期内达到最高成长率。政府支持智慧城市发展的措施正在加速车辆的部署。人们对公共交通现代化日益增长的兴趣推动了对人工智慧移动解决方案的投资。相关部门正在与自动驾驶汽车公司合作，以提高效率和永续性。对交通拥堵和环境影响日益增长的担忧也促进了该部门的扩张。

比最大的地区

由于快速的都市化和大规模的智慧交通投资，预计亚太地区将在预测期内占据最大的市场占有率。中国、日本和韩国等国家是自动驾驶出行解决方案的早期采用者。政府支持的试验计画和补贴正在加速自动驾驶公车的商业化部署。不断扩展的公共交通网络和完善的基础设施将支持市场发展。

复合年增长率最高的地区

由于强有力的监管支持和技术领先，北美地区预计将在预测期内呈现最高的复合年增长率。 Waymo、Cruise 和 Zoox 等公司正在开发自动驾驶解决方案。都市区和校园环境中机器人穿梭巴士的日益普及将推动市场扩张。人们对交通效率和环境影响的日益担忧，正推动城市向自动驾驶出行解决方案迈进。

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目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 研究范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 限制因素
  • 机会
  • 威胁
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买家的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球机器人穿梭巴士和自动驾驶巴士市场（按组件）

  • 硬体
    • 感应器
    • GPS/GNSS模组
    • 处理器/控制单元
    • 通讯系统
    • 电动马达和电池系统
  • 软体
    • 基于人工智慧的驾驶演算法
    • 地图定位
    • 车辆管理系统
  • 服务
    • 部署和集成
    • 维护
    • 远端操作

6. 全球机器人穿梭车和自动驾驶巴士市场（依车辆类型）

  • 自动穿梭巴士
  • 自动驾驶巴士

7. 全球机器人穿梭车和自动驾驶巴士市场（按推进类型）

  • 电
  • 杂交种
  • 氢燃料电池
  • 内燃机（ICE）

8. 全球机器人穿梭巴士和自动驾驶巴士市场（依自主程度划分）

  • 1级（驾驶辅助）
  • 2级（部分自动化）
  • 3级（有条件自动化）
  • 4级（高度自动化）
  • 5级（全自动）

9. 全球机器人穿梭巴士和自动驾驶巴士市场（按应用）

  • 公共运输
  • 医疗保健和退休社区
  • 机场/校园接驳车
  • 主题乐园活动
  • 观光
  • 商业园区和工业
  • 其他的

第十章。全球机器人穿梭车和自动驾驶巴士市场（按最终用户划分）

  • 地方政府
  • 交通运输管理局
  • 私营部门运营商（技术或移动出行公司）
  • 企业客户
  • 大学/校园
  • 其他的

第 11 章。全球机器人穿梭车和自动驾驶巴士市场（按地区）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十二章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十三章 公司概况

  • 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.