自动/无人驾驶班车市场规模 - 按车辆、燃料、自主程度和预测，2024 年至 2032 年

由于 RampD 投资的增加以及智慧城市计画的扩展，2024 年至 2032 年间，全球自动驾驶/无人驾驶班车市场规模的复合年增长率将超过 20%。这些投资正在推动创新，从而推动自主技术和基础设施的进步。

此外，智慧城市计画优先考虑高效和永续的交通解决方案，进一步为自动驾驶班车的采用创造有利的环境。随着世界各地的城市寻求缓解拥塞和减少排放，自动驾驶接驳车将成为可行的解决方案，推动其在城市环境中的部署。例如，2024 年 4 月，夏威夷交通部 HDOT 推出了一款新型自主电动客运接驳车，以补充丹尼尔·井上国际机场 (HNL) 目前的 Wiki Wiki 接驳车服务。

自动驾驶/无人驾驶班车市场根据车辆、燃料、自动驾驶水平和地区而分散。

透过车辆，饭店接驳车细分市场将在 2032 年实现显着的复合年增长率。此外，饭店物业还提供有明确路线的限制区域，这些巴士可以自行运行。为了满足以客户为中心的酒店业的需求，提供便利、安全和节省成本的服务而不断增加的使用量将有利于该细分市场的成长。

基于燃料，混合动力领域的自动驾驶/无人驾驶班车产业将在其多功能性和效率的推动下，到 2032 年将显着成长。透过将电动和传统燃油动力系统结合，混合动力接驳车为各种运行条件和更长的行驶范围提供了理想的解决方案。它们最适合充电基础设施较差的城市和郊区。它们还透过允许电力转换来帮助节省能源，降低整体营运成本，同时减少环境污染。

在快速城市化和政府推广智慧交通解决方案措施的推动下，2024年至2032年，亚太地区自动驾驶/无人驾驶班车产业规模将大幅复合年增长率。亚太地区城市人口稠密，特大城市蓬勃发展，为自动驾驶班车的部署提供了肥沃的土壤。此外，技术的进步和支持性监管框架将进一步加速区域市场的成长。

目录

第 1 章：方法与范围

第 2 章：执行摘要

第 3 章：产业洞察

• 产业生态系统分析
• 供应商格局
  • 原物料供应商
  • 元件供应商
  • 製造商
  • 技术提供者
  • 经销商
  • 终端用户
• 利润率分析
• 技术与创新格局
• 专利分析
• 重要新闻和倡议
  • 伙伴关係/协作
  • 併购
  • 投资
  • 产品发布和创新
• 监管环境
• 衝击力
  • 成长动力
    • 全球都市化不断发展
    • 最后一哩连线的需求不断增长
    • 对按需运输服务的需求不断增长
    • 汽车产业的快速技术进步
• 产业陷阱与挑战
  • 技术限制和可靠性问题
• 成长潜力分析
• 波特的分析
• PESTEL分析

第 4 章：竞争格局

• 介绍
• 公司市占率分析
• 竞争定位矩阵
• 战略展望矩阵

第 5 章：市场估计与预测：按车辆划分，2021-2032 年

• 主要趋势
• 机场接驳车
• 饭店接送
• 活动班车
• 校园接驳车
• 企业接驳车

第 6 章：市场估计与预测：依燃料分类，2021-2032 年

• 主要趋势
• 柴油引擎
• 电的
• 杂交种

第 7 章：市场估计与预测：依自治程度划分，2021-2032 年

• 主要趋势
• 1级
• 2级
• 3级
• 4级

第 8 章：市场估计与预测：按地区划分，2021-2032 年

• 主要趋势
• 北美洲
  • 我们
  • 加拿大
• 欧洲
  • 英国
  • 德国
  • 法国
  • 义大利
  • 俄罗斯
  • 比利时
  • 瑞典
  • 欧洲其他地区
• 亚太地区
  • 中国
  • 印度
  • 日本
  • 韩国
  • 印尼
  • 泰国
  • 越南
  • 亚太地区其他地区
• 拉丁美洲
  • 巴西
  • 墨西哥
  • 阿根廷
  • 拉丁美洲其他地区
• MEA
  • 南非
  • 沙乌地阿拉伯
  • 阿联酋
  • 伊朗
  • 土耳其
  • MEA 的其余部分

第 9 章：公司简介

• 2getthere
• Auro Robotics
• AutoX
• Baidu
• Coast Automonous
• e.Go
• EasyMile
• LeddarTech
• Local Motors
• May Mobility
• Navya
• Neolix
• Next
• Ohmio
• Optimus Ride
• Sensible4
• Softbank
• Toyota
• Transdev
• Yutong

Global Autonomous/driver less Shuttles Market size will register over 20% CAGR between 2024 and 2032, owing to increasing R&D investments coupled with the expansion of smart city initiatives. These investments are fueling innovations, leading to advancements in autonomous technologies and infrastructure.

Moreover, smart city projects are prioritizing efficient and sustainable transportation solutions, further creating a conducive environment for the adoption of autonomous shuttles. With cities worldwide seeking to alleviate congestion and reduce emissions, autonomous shuttles will emerge as viable solutions, driving their deployment in urban environments. For instance, in April 2024, the Hawai?i Department of Transportation HDOT inaugurated a novel autonomous electric passenger shuttle to complement the current Wiki Wiki shuttle bus service at the Daniel K. Inouye International Airport HNL.

The autonomous/driver less shuttles market is fragmented on the basis of vehicle, fuel, level of autonomy, and region.

By vehicle, the hotel shuttle segment will witness significant CAGR through 2032. Amidst the resurgence of the tourism sector and the call for better transportation systems, hotels have turned to self-driving shuttles to make the experiences of guests more enhancing. Moreover, hotel properties provide restricted areas with definite routes where these buses can operate on their own. Rising usage for offering convenient, safe, and cost-savings, in line with the customer-centric hotel industry demand will favor the segment growth.

Based on fuel, the autonomous/driver less shuttles industry from the hybrid segment will witness notable growth by 2032, driven by their versatility and efficiency. By combining electric and traditional fuel powered systems, hybrid shuttles offer an ideal solution for a wide range of operating conditions with extended reach. They are most suitable for urban and suburban areas with poor charging infrastructure. They also help to save energy by allowing power transformation, to lowers the overall cost of operation while reducing environmental pollution.

Asia Pacific autonomous/driver less shuttles industry size will experience a substantial CAGR from 2024 to 2032, propelled by rapid urbanization and government initiatives for promoting smart transportation solutions. With densely populated cities and burgeoning megacities, APAC presents a fertile ground for autonomous shuttle deployment. Additionally, advancements in technology and supportive regulatory frameworks will further accelerate the regional market growth."

Table of Contents

Chapter 1 Methodology & Scope

• 1.1 Research design
  • 1.1.1 Research approach
  • 1.1.2 Data collection methods
• 1.2 Base estimates and calculations
  • 1.2.1 Base year calculation
  • 1.2.2 Key trends for market estimates
• 1.3 Forecast model
• 1.4 Primary research & validation
  • 1.4.1 Primary sources
  • 1.4.2 Data mining sources
• 1.5 Market definitions

Chapter 2 Executive Summary

• 2.1 Industry 360° synopsis, 2021-2032

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Supplier landscape
  • 3.2.1 Raw material providers
  • 3.2.2 Component providers
  • 3.2.3 Manufacturers
  • 3.2.4 Technology providers
  • 3.2.5 Distributors
  • 3.2.6 End users
• 3.3 Profit margin analysis
• 3.4 Technology & innovation landscape
• 3.5 Patent analysis
• 3.6 Key news & initiatives
  • 3.6.1 Partnership/collaboration
  • 3.6.2 Merger/acquisition
  • 3.6.3 Investment
  • 3.6.4 Product launch and innovation
• 3.7 Regulatory landscape
• 3.8 Impact forces
  • 3.8.1 Growth drivers
    • 3.8.1.1 Growing urbanization across the globe
    • 3.8.1.2 Rising need for last-mile connectivity
    • 3.8.1.3 Growing demand for on-demand transportation services
    • 3.8.1.4 Rapid technological advancements in the automotive sector
• 3.9 Industry pitfalls & challenges
  • 3.9.1.1 Technical limitations and reliability issues
• 3.10 Growth potential analysis
• 3.11 Porter's analysis
• 3.12 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

• 4.1 Introduction
• 4.2 Company market share analysis
• 4.3 Competitive positioning matrix
• 4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Vehicle, 2021-2032 ($ Mn, Units)

• 5.1 Key trends
• 5.2 Airport shuttle
• 5.3 Hotel shuttle
• 5.4 Event shuttle
• 5.5 Campus shuttle
• 5.6 Corporate Shuttle

Chapter 6 Market Estimate & Forecast, By Fuel, 2021-2032 ($ Mn, Units)

• 6.1 Key trends
• 6.2 Diesel
• 6.3 Electric
• 6.4 Hybrid

Chapter 7 Market Estimates & Forecast, By Level of Autonomy, 2021-2032 ($ Mn, Units)

• 7.1 Key trends
• 7.2 Level 1
• 7.3 Level 2
• 7.4 Level 3
• 7.5 Level 4

Chapter 8 Market Estimates & Forecast, By Region, 2021-2032 ($ Mn, Units)

• 8.1 Key trends
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
• 8.3 Europe
  • 8.3.1 UK
  • 8.3.2 Germany
  • 8.3.3 France
  • 8.3.4 Italy
  • 8.3.5 Russia
  • 8.3.6 Belgium
  • 8.3.7 Sweden
  • 8.3.8 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 India
  • 8.4.3 Japan
  • 8.4.4 South Korea
  • 8.4.5 Indonesia
  • 8.4.6 Thailand
  • 8.4.7 Vietnam
  • 8.4.8 Rest of Asia Pacific
• 8.5 Latin America
  • 8.5.1 Brazil
  • 8.5.2 Mexico
  • 8.5.3 Argentina
  • 8.5.4 Rest of Latin America
• 8.6 MEA
  • 8.6.1 South Africa
  • 8.6.2 Saudi Arabia
  • 8.6.3 UAE
  • 8.6.4 Iran
  • 8.6.5 Turkey
  • 8.6.6 Rest of MEA

Chapter 9 Company Profiles

• 9.1 2getthere
• 9.2 Auro Robotics
• 9.3 AutoX
• 9.4 Baidu
• 9.5 Coast Automonous
• 9.6 e.Go
• 9.7 EasyMile
• 9.8 LeddarTech
• 9.9 Local Motors
• 9.10 May Mobility
• 9.11 Navya
• 9.12 Neolix
• 9.13 Next
• 9.14 Ohmio
• 9.15 Optimus Ride
• 9.16 Sensible4
• 9.17 Softbank
• 9.18 Toyota
• 9.19 Transdev
• 9.20 Yutong