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1836361

2032年機器人計程車市場預測：按組件、車輛類型、自主性等級、經營模式、服務模式、推進類型、應用和地區進行的全球分析

Robotaxi Market Forecasts to 2032 - Global Analysis By Component, Vehicle Type, Autonomy Level, Business Model, Service Model, Propulsion Type, Application 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，全球自動駕駛計程車市場預計在 2025 年達到 97.7 億美元，到 2032 年將達到 5,710.4 億美元，預測期內的複合年成長率為 78.8%。

機器人計程車，也稱為自動駕駛計程車，是一種無人駕駛車輛，可在城市中提供便利的按需交通服務。機器人計程車配備人工智慧、LiDAR、雷達和先進感測器，旨在提高道路安全性，最大限度地減少堵塞，並降低與傳統計程車相比的營運成本。作為一種永續的替代方案，機器人計程車透過節能系統和減少排放氣體來支援更清潔的城市交通。科技公司和汽車製造商正在主要智慧城市擴大先導計畫，以適應不斷變化的法規。隨著城市密度的增加、消費者對經濟實惠的叫車服務的偏好以及自動駕駛技術的突破，機器人計程車有望改變出行生態系統，並為城市交通建立一個未來高效的模式。

根據美國汽車協會 (AAA) 的數據，到 2023 年，美國擁有一輛汽車的平均年成本將超過 12,000 美元。自動駕駛計程車提供了一種經濟高效的替代方案，特別是對於不經常開車的城市居民而言。

都市化和交通擁擠加劇

城市擴張和日益嚴重的交通堵塞是推動自動駕駛計程車市場成長的主要因素。隨著城市人口的成長，城市正面臨道路擁擠和停車位短缺的困境。自動駕駛計程車作為一種可行的替代方案，可以減少對私家車的依賴，並提供共用服務，從而緩解交通堵塞。其先進的路線規劃和車隊管理系統可改善交通流量，縮短行程時間。許多政府正在推行永續的城市交通戰略，進一步支持自動駕駛計程車的部署。隨著城市密度預計將不斷增加，人們對經濟高效的交通途徑的需求日益成長，以緩解交通堵塞，這為自動駕駛計程車在城市通勤中發揮核心作用創造了巨大的機會。

開發和營運成本高

由於開發和營運自動駕駛汽車的成本高昂，自動駕駛計程車市場面臨巨大挑戰。建構自動駕駛系統需要投資人工智慧、LiDAR和高精度感測器等先進工具，所有這些都會增加生產和部署成本。此外，持續進行的大量測試、監管核准和系統升級也推高了營運成本。由於進入市場需要大量的初始資本，車隊供應商難以盈利。雖然技術進步和規模經濟可能會在未來降低成本，但目前的高成本仍然是一個重大障礙，阻礙了自動駕駛計程車服務的大規模商業化。

共用和按需出行的需求不斷成長

共用和按需出行需求的激增為自動駕駛計程車市場創造了巨大的機會。高昂的擁有成本、有限的停車位和嚴重的交通堵塞，促使城市居民選擇付費叫車服務。自動駕駛計程車透過數位平台營運，為私家車提供了一種經濟實惠且便捷的交通途徑，讓用戶無需承擔擁有車輛的負擔即可享受可靠的通勤。融入出行即服務生態系統後，自動駕駛計程車變得觸手可及且極具吸引力，尤其對習慣於基於應用程式服務的年輕消費者而言。隨著都市化的加快，城市正在轉向共用交通方式，以減少擁塞和排放氣體。這一趨勢預計將加速自動駕駛計程車的普及，使其成為未來出行解決方案的核心組成部分。

公眾抵制和信任問題

消費者的抵制和缺乏信任仍然是阻礙機器人計程車市場發展的障礙。許多人對無人駕駛技術持懷疑態度，擔心媒體頻繁通報的潛在故障和事故。大眾對自動駕駛系統的認知和理解有限，進一步加劇了人們的猶豫。接受程度也因文化和世代因素而異，導致地區間採用率有差異。為了贏得信任，公司必須強調安全性，進行透明的試點測試，並提供可靠的證據。如果大眾信任度無法提升，機器人計程車的廣泛普及將舉步維艱，從而減緩市場擴張，並給尋求擴張的公司帶來挑戰。

COVID-19的影響：

新冠疫情對自動駕駛計程車市場產生了顯著影響，它再形成了城市出行行為，並優先考慮非接觸式交通途徑。為了降低感染風險，人們紛紛避免乘坐擁擠的公共交通，對駕駛人和按需出行車輛的需求隨之增加，這使得自動駕駛計程車成為更安全的通勤選擇。同時，疫情也導致自動駕駛汽車的生產、車隊部署和測試延遲，並引發封鎖和供應鏈中斷，暫時阻礙了市場擴張。儘管有短期挑戰，但新冠疫情凸顯了自動駕駛、衛生且可靠的出行解決方案的價值。這段時間凸顯了這些解決方案在後疫情時代城市環境中滿足不斷變化的安全和效率要求的潛力，最終增強了自動駕駛計程車的普及性。

預計預測期內 LiDAR 市場規模最大

預計在預測期內，雷射雷達 (LiDAR) 領域將佔據最大的市場佔有率，因為它在自動駕駛汽車導航和環境感知方面發揮著至關重要的作用。透過發射雷射光束並分析其反射，LiDAR 可以產生詳細的3D地圖，並在各種條件下準確識別障礙物、行人和周圍車輛。這種精確度對於確保無人駕駛計程車營運的安全性和可靠性至關重要，這使得 LiDAR 成為製造商和車隊管理者的首選技術。人工智慧演算法、感測器融合以及與其他自動駕駛系統的兼容性增強了情境察覺和決策能力。因此，LiDAR 仍然是自動駕駛計程車的主要感測解決方案，在感知技術市場中佔據了相當大的佔有率。

預計電池電動車 (BEV) 領域將在預測期內實現最高複合年成長率

純電動車 (BEV) 細分市場預計將在預測期內實現最高成長率，這得益於其環保、低維護和燃油成本以及與自動駕駛系統的無縫整合。 BEV 對於注重永續性和排放的都市區尤其有利。先進的電池技術、高效的充電基礎設施以及與人工智慧驅動系統的兼容性使其成為自動駕駛計程車的理想選擇。政府的支持性政策、補貼以及消費者對綠色交通日益成長的需求，進一步推動了自動駕駛計程車的普及。隨著城市優先考慮清潔且經濟高效的城市出行，BEV 預計將引領自動駕駛計程車服務的演變，推動電動自動駕駛交通的市場擴張和創新。

佔比最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其完善的技術生態系統、對自動駕駛汽車開發的大量投資以及大型汽車和科技公司的佈局。優惠的政府法規、廣泛的測試設施以及消費者對創新交通解決方案的開放態度，進一步鞏固了該地區的領先地位。對人工智慧系統、感測器技術和電動汽車的投資將增強自動駕駛計程車的性能，並支援市場擴張。此外，高城市密度、強勁的購買力以及對高效、安全和永續交通途徑日益成長的需求，正在推動其普及率的提高。

複合年成長率最高的地區：

預計亞太地區在預測期內將呈現最高的複合年成長率，這得益於快速的城市擴張、收入成長以及政府對自動駕駛旅行和智慧城市計畫的大力支持。中國、日本和韓國等主要市場正在大力投資人工智慧、自動駕駛汽車研究和電動車，為自動駕駛計程車的普及創造了有利環境。消費者對經濟實惠、高效環保的交通方式日益成長的偏好，加上支持性法規和對新型出行解決方案的接受度，將繼續推動市場成長。綜合來看，這些動態使亞太地區成為自動駕駛計程車成長最快的市場，為技術提供商和車隊營運商在全部區域建立和擴展自動駕駛計程車服務提供了重要機會。

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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
  • 調查範圍
  • 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
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 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
  • 買方的議價能力
  • 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Robotaxi 市場（按組件）

  • 騎士
  • 雷達
  • 相機
  • 超音波感測器
  • 人工智慧軟體
  • 連接模組
  • 感測器融合系統
  • V2X通訊單元

6.全球Robotaxi 市場（依車型）

  • 車
    • 轎車
    • 掀背車
  • 貨車
    • 穿梭
    • MPV

7. 全球自動駕駛計程車市場（按自動駕駛等級）

  • 4級（高度自動化）
  • 5級（全自動）

第8章全球機器人計程車市場（依經營模式）

  • OEM擁有的車隊
  • 平台許可證車隊
  • 第三方營運商

第9章全球機器人計程車市場（依服務模式）

  • 按需叫車服務
  • 車站接送服務
  • 定期自主運輸
  • 基於訂閱的行動性

第 10 章全球機器人計程車市場（依推進類型）

  • 純電動車（BEV）
  • 混合動力電動車（HEV）
  • 燃料電池電動車（FCEV）
  • 內燃機（ICE）

第 11 章全球機器人計程車市場（按應用）

  • 客運
  • 產品交付
  • 第一英里/最後一英里的連接
  • 車站接送服務
  • 多用途艦隊

第12章全球機器人計程車市場（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
    • 其他南美
  • 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13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14章 公司概況

  • Waymo LLC
  • Baidu Apollo
  • AutoX Inc.
  • Pony.ai
  • Zoox Inc.（Amazon-owned）
  • Tesla Inc.
  • DiDi Autonomous Driving
  • Aptiv
  • Navya SA
  • Yandex Self-Driving Group
  • Uber Technologies Inc.
  • Daimler AG
  • AutoMobilie.AI
  • Aurora Innovation
  • Cruise Inc
Product Code: SMRC31485

According to Stratistics MRC, the Global Robotaxi Market is accounted for $9.77 billion in 2025 and is expected to reach $571.04 billion by 2032 growing at a CAGR of 78.8% during the forecast period. Robotaxis, also known as autonomous taxis, are driverless vehicles providing convenient, on-demand transport in cities. Powered by artificial intelligence, LiDAR, radar, and advanced sensors, they are engineered to improve road safety, minimize congestion, and cut operating costs compared to conventional taxis. As sustainable alternatives, robotaxis support cleaner urban transport through energy-efficient systems and reduced emissions. Technology firms and automakers are expanding pilot projects across major smart cities, aligning with evolving regulations. With increasing urban density, consumer preference for affordable ride-hailing, and breakthroughs in self-driving technologies, robotaxis are set to transform mobility ecosystems and establish a futuristic, more efficient model of urban transportation.

According to AAA (American Automobile Association), the average annual cost of car ownership in the U.S. exceeded $12,000 in 2023. Robotaxis offer a cost-efficient alternative, especially for urban dwellers that drive infrequently.

Market Dynamics:

Driver:

Rising urbanization and congestion

Urban expansion and increasing congestion are major catalysts for the Robotaxi Market's growth. As urban populations swell, cities struggle with overcrowded roads and scarce parking availability. Robotaxis serve as a practical alternative by providing shared rides that reduce the reliance on private cars, thereby lowering traffic volumes. Their advanced route planning and fleet management systems improve flow and reduce travel time. Many governments are promoting sustainable urban mobility strategies, further supporting robotaxi deployment. With urban density expected to intensify, demand for affordable and efficient transportation that eases congestion is rising, creating substantial opportunities for robotaxis to play a central role in city commuting.

Restraint:

High development and operational costs

The Robotaxi Market faces significant hurdles from the high financial costs of developing and operating autonomous vehicles. Building self-driving systems demands investment in advanced tools like artificial intelligence, LiDAR, and precision sensors, all of which raise production and deployment expenses. Furthermore, ongoing requirements such as large-scale testing, regulatory approvals, and system upgrades add to operational costs. Fleet providers struggle to achieve profitability given the large initial capital needed for market entry. While technological progress and economies of scale may reduce expenses in the future, the current cost intensity continues to act as a major restraint, slowing the large-scale commercialization of robotaxi services.

Opportunity:

Growing demand for shared and on-demand mobility

The surge in demand for shared and on-demand transport is opening major opportunities in the Robotaxi Market. High costs of ownership, limited parking, and heavy congestion are prompting city dwellers to prefer pay-per-ride solutions. Robotaxis, operating through digital platforms, provide affordable and convenient alternatives to private cars, offering reliable commuting without ownership burdens. Their integration into mobility-as-a-service ecosystems makes them highly accessible and appealing, particularly to younger consumers accustomed to app-based services. As urbanization intensifies, cities are turning to shared transport options to reduce congestion and emissions. This trend is expected to accelerate robotaxi adoption, positioning them as central to future mobility solutions.

Threat:

Public resistance and trust issues

Consumer resistance and lack of trust continue to be barriers to the growth of the Robotaxi Market. Many people remain doubtful of driverless technology, fearing potential malfunctions or accidents, which are often highlighted in the media. Limited public awareness and understanding of autonomous systems further reinforce hesitation. Acceptance levels also vary based on cultural and generational factors, creating regional disparities in adoption. To gain trust, companies must emphasize safety, conduct transparent demonstrations, and provide strong evidence of reliability. Unless public confidence improves, widespread deployment of robotaxis will be difficult, delaying market expansion and creating challenges for companies aiming to scale operations.

Covid-19 Impact:

The COVID-19 outbreak had a notable impact on the Robotaxi Market by reshaping urban travel behavior and emphasizing contactless transportation. As people avoided crowded public transport to reduce infection risks, demand for driverless, on-demand vehicles increased, positioning robotaxis as a safer commuting option. At the same time, the pandemic caused delays in production, fleet deployment, and autonomous vehicle testing due to lockdowns and disrupted supply chains, temporarily hindering market expansion. Despite short-term challenges, COVID-19 underscored the value of autonomous, hygienic, and reliable mobility solutions. This period ultimately strengthened the case for robotaxi adoption, highlighting their potential to meet evolving safety and efficiency requirements in post-pandemic urban environments.

The LiDAR segment is expected to be the largest during the forecast period

The LiDAR segment is expected to account for the largest market share during the forecast period due to its indispensable role in autonomous vehicle navigation and environment perception. By sending out laser beams and analyzing their reflections, LiDAR generates detailed three-dimensional maps, accurately identifying obstacles, pedestrians, and surrounding vehicles under various conditions. This precision is crucial for ensuring the safety and reliability of driverless taxi operations, positioning LiDAR as a favored technology for manufacturers and fleet managers. Its compatibility with AI algorithms, sensor fusion, and other autonomous systems enhances situational awareness and decision-making. Consequently, LiDAR remains the leading sensing solution in robotaxis, commanding a prominent share of the perception technology market.

The battery electric vehicles (BEV) segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the battery electric vehicles (BEV) segment is predicted to witness the highest growth rate, driven by their environmentally friendly nature, lower maintenance and fuel costs, and seamless integration with autonomous systems. BEVs are especially advantageous for urban areas focusing on sustainability and emission reduction. Advanced battery technologies, efficient charging infrastructure, and compatibility with AI-driven driving systems enhance their suitability for robotaxi fleets. Supportive government policies, subsidies, and growing consumer demand for green transportation further fuel their adoption. As cities prioritize clean, cost-efficient urban mobility, BEVs are expected to lead the evolution of robotaxi services, fostering both market expansion and innovation in electric autonomous transportation.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, owing to its well-established technological ecosystem, substantial investments in autonomous vehicle development, and the presence of major automotive and tech corporations. Favorable government regulations, extensive testing facilities, and consumer openness to innovative transport solutions further reinforce the region's leadership. Investments in AI systems, sensor technologies, and electric mobility enhance the capabilities of robotaxi fleets, supporting market expansion. Moreover, high urban density, strong purchasing power, and growing demand for efficient, safe, and sustainable transportation options have propelled adoption rates.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid urban expansion, rising incomes, and strong governmental backing for autonomous mobility and smart city programs. Key markets like China, Japan, and South Korea are heavily investing in AI, autonomous vehicle research, and electric mobility, creating an enabling environment for robotaxi adoption. Rising consumer preference for affordable, efficient, and eco-friendly transportation, combined with supportive regulations and receptiveness to new mobility solutions, continues to drive market growth. Collectively, these dynamics make Asia-Pacific the fastest-growing market for robotaxis, with significant opportunities for technology providers and fleet operators to establish and scale autonomous taxi services across the region.

Key players in the market

Some of the key players in Robotaxi Market include Waymo LLC, Baidu Apollo, AutoX Inc., Pony.ai, Zoox Inc. (Amazon-owned), Tesla Inc., DiDi Autonomous Driving, Aptiv, Navya SA, Yandex Self-Driving Group, Uber Technologies Inc., Daimler AG, AutoMobilie.AI, Aurora Innovation and Cruise Inc.

Key Developments:

In July 2025, Baidu and global taxi-hailing firm Uber Technologies have agreed to work together to deploy thousands of Baidu Apollo Go robotaxis in markets outside the US and mainland China, a move that comes as Tesla seeks to expand its robotaxis in the US. The multi-year deal will see robotaxis deployed in Asia and the Middle East later this year.

In July 2025, Pony AI Inc. and Dubai's Roads and Transport Authority (RTA) recently held a robotaxi unveiling ceremony in Dubai, formalizing their partnership to advance L4 autonomous mobility solutions. Through this strategic collaboration, both sides have reaffirmed their commitment to integrating cutting-edge self-driving technology into Dubai's extensive transportation network.

In April 2025, Waymo and Toyota Motor Corporation ("Toyota") reached a preliminary agreement to explore a collaboration focused on accelerating the development and deployment of autonomous driving technologies. Woven by Toyota will also join the potential collaboration as Toyota's strategic enabler, contributing its strengths in advanced software and mobility innovation.

Components Covered:

  • LiDAR
  • RADAR
  • Cameras
  • Ultrasonic Sensors
  • AI Software
  • Connectivity Modules
  • Sensor Fusion Systems
  • V2X Communication Units

Vehicle Types Covered:

  • Cars
  • Vans

Autonomy Levels Covered:

  • Level 4 (High Automation)
  • Level 5 (Full Automation)

Business Models Covered:

  • OEM-Owned Fleets
  • Platform-Licensed Fleets
  • Third-Party Operators

Service Models Covered:

  • On-Demand Ride-Hailing
  • Station-Based Shuttles
  • Scheduled Autonomous Transit
  • Subscription-Based Mobility

Propulsion Types Covered:

  • Battery Electric Vehicles (BEV)
  • Hybrid Electric Vehicles (HEV)
  • Fuel Cell Electric Vehicles (FCEV)
  • Internal Combustion Engine (ICE)

Applications Covered:

  • Passenger Transport
  • Goods Delivery
  • First-Mile / Last-Mile Connectivity
  • Station-Based Shuttle Services
  • Mixed-Use Fleets

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 Emerging Markets
  • 3.8 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 Robotaxi Market, By Component

  • 5.1 Introduction
  • 5.2 LiDAR
  • 5.3 RADAR
  • 5.4 Cameras
  • 5.5 Ultrasonic Sensors
  • 5.6 AI Software
  • 5.7 Connectivity Modules
  • 5.8 Sensor Fusion Systems
  • 5.9 V2X Communication Units

6 Global Robotaxi Market, By Vehicle Type

  • 6.1 Introduction
  • 6.2 Cars
    • 6.2.1 Sedans
    • 6.2.2 Hatchbacks
  • 6.3 Vans
    • 6.3.1 Shuttles
    • 6.3.2 MPVs

7 Global Robotaxi Market, By Autonomy Level

  • 7.1 Introduction
  • 7.2 Level 4 (High Automation)
  • 7.3 Level 5 (Full Automation)

8 Global Robotaxi Market, By Business Model

  • 8.1 Introduction
  • 8.2 OEM-Owned Fleets
  • 8.3 Platform-Licensed Fleets
  • 8.4 Third-Party Operators

9 Global Robotaxi Market, By Service Model

  • 9.1 Introduction
  • 9.2 On-Demand Ride-Hailing
  • 9.3 Station-Based Shuttles
  • 9.4 Scheduled Autonomous Transit
  • 9.5 Subscription-Based Mobility

10 Global Robotaxi Market, By Propulsion Type

  • 10.1 Introduction
  • 10.2 Battery Electric Vehicles (BEV)
  • 10.3 Hybrid Electric Vehicles (HEV)
  • 10.4 Fuel Cell Electric Vehicles (FCEV)
  • 10.5 Internal Combustion Engine (ICE)

11 Global Robotaxi Market, By Application

  • 11.1 Introduction
  • 11.2 Passenger Transport
  • 11.3 Goods Delivery
  • 11.4 First-Mile / Last-Mile Connectivity
  • 11.5 Station-Based Shuttle Services
  • 11.6 Mixed-Use Fleets

12 Global Robotaxi Market, By Geography

  • 12.1 Introduction
  • 12.2 North America
    • 12.2.1 US
    • 12.2.2 Canada
    • 12.2.3 Mexico
  • 12.3 Europe
    • 12.3.1 Germany
    • 12.3.2 UK
    • 12.3.3 Italy
    • 12.3.4 France
    • 12.3.5 Spain
    • 12.3.6 Rest of Europe
  • 12.4 Asia Pacific
    • 12.4.1 Japan
    • 12.4.2 China
    • 12.4.3 India
    • 12.4.4 Australia
    • 12.4.5 New Zealand
    • 12.4.6 South Korea
    • 12.4.7 Rest of Asia Pacific
  • 12.5 South America
    • 12.5.1 Argentina
    • 12.5.2 Brazil
    • 12.5.3 Chile
    • 12.5.4 Rest of South America
  • 12.6 Middle East & Africa
    • 12.6.1 Saudi Arabia
    • 12.6.2 UAE
    • 12.6.3 Qatar
    • 12.6.4 South Africa
    • 12.6.5 Rest of Middle East & Africa

13 Key Developments

  • 13.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 13.2 Acquisitions & Mergers
  • 13.3 New Product Launch
  • 13.4 Expansions
  • 13.5 Other Key Strategies

14 Company Profiling

  • 14.1 Waymo LLC
  • 14.2 Baidu Apollo
  • 14.3 AutoX Inc.
  • 14.4 Pony.ai
  • 14.5 Zoox Inc. (Amazon-owned)
  • 14.6 Tesla Inc.
  • 14.7 DiDi Autonomous Driving
  • 14.8 Aptiv
  • 14.9 Navya SA
  • 14.10 Yandex Self-Driving Group
  • 14.11 Uber Technologies Inc.
  • 14.12 Daimler AG
  • 14.13 AutoMobilie.AI
  • 14.14 Aurora Innovation
  • 14.15 Cruise Inc

List of Tables

  • Table 1 Global Robotaxi Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Robotaxi Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Robotaxi Market Outlook, By LiDAR (2024-2032) ($MN)
  • Table 4 Global Robotaxi Market Outlook, By RADAR (2024-2032) ($MN)
  • Table 5 Global Robotaxi Market Outlook, By Cameras (2024-2032) ($MN)
  • Table 6 Global Robotaxi Market Outlook, By Ultrasonic Sensors (2024-2032) ($MN)
  • Table 7 Global Robotaxi Market Outlook, By AI Software (2024-2032) ($MN)
  • Table 8 Global Robotaxi Market Outlook, By Connectivity Modules (2024-2032) ($MN)
  • Table 9 Global Robotaxi Market Outlook, By Sensor Fusion Systems (2024-2032) ($MN)
  • Table 10 Global Robotaxi Market Outlook, By V2X Communication Units (2024-2032) ($MN)
  • Table 11 Global Robotaxi Market Outlook, By Vehicle Type (2024-2032) ($MN)
  • Table 12 Global Robotaxi Market Outlook, By Cars (2024-2032) ($MN)
  • Table 13 Global Robotaxi Market Outlook, By Sedans (2024-2032) ($MN)
  • Table 14 Global Robotaxi Market Outlook, By Hatchbacks (2024-2032) ($MN)
  • Table 15 Global Robotaxi Market Outlook, By Vans (2024-2032) ($MN)
  • Table 16 Global Robotaxi Market Outlook, By Shuttles (2024-2032) ($MN)
  • Table 17 Global Robotaxi Market Outlook, By MPVs (2024-2032) ($MN)
  • Table 18 Global Robotaxi Market Outlook, By Autonomy Level (2024-2032) ($MN)
  • Table 19 Global Robotaxi Market Outlook, By Level 4 (High Automation) (2024-2032) ($MN)
  • Table 20 Global Robotaxi Market Outlook, By Level 5 (Full Automation) (2024-2032) ($MN)
  • Table 21 Global Robotaxi Market Outlook, By Business Model (2024-2032) ($MN)
  • Table 22 Global Robotaxi Market Outlook, By OEM-Owned Fleets (2024-2032) ($MN)
  • Table 23 Global Robotaxi Market Outlook, By Platform-Licensed Fleets (2024-2032) ($MN)
  • Table 24 Global Robotaxi Market Outlook, By Third-Party Operators (2024-2032) ($MN)
  • Table 25 Global Robotaxi Market Outlook, By Service Model (2024-2032) ($MN)
  • Table 26 Global Robotaxi Market Outlook, By On-Demand Ride-Hailing (2024-2032) ($MN)
  • Table 27 Global Robotaxi Market Outlook, By Station-Based Shuttles (2024-2032) ($MN)
  • Table 28 Global Robotaxi Market Outlook, By Scheduled Autonomous Transit (2024-2032) ($MN)
  • Table 29 Global Robotaxi Market Outlook, By Subscription-Based Mobility (2024-2032) ($MN)
  • Table 30 Global Robotaxi Market Outlook, By Propulsion Type (2024-2032) ($MN)
  • Table 31 Global Robotaxi Market Outlook, By Battery Electric Vehicles (BEV) (2024-2032) ($MN)
  • Table 32 Global Robotaxi Market Outlook, By Hybrid Electric Vehicles (HEV) (2024-2032) ($MN)
  • Table 33 Global Robotaxi Market Outlook, By Fuel Cell Electric Vehicles (FCEV) (2024-2032) ($MN)
  • Table 34 Global Robotaxi Market Outlook, By Internal Combustion Engine (ICE) (2024-2032) ($MN)
  • Table 35 Global Robotaxi Market Outlook, By Application (2024-2032) ($MN)
  • Table 36 Global Robotaxi Market Outlook, By Passenger Transport (2024-2032) ($MN)
  • Table 37 Global Robotaxi Market Outlook, By Goods Delivery (2024-2032) ($MN)
  • Table 38 Global Robotaxi Market Outlook, By First-Mile / Last-Mile Connectivity (2024-2032) ($MN)
  • Table 39 Global Robotaxi Market Outlook, By Station-Based Shuttle Services (2024-2032) ($MN)
  • Table 40 Global Robotaxi Market Outlook, By Mixed-Use Fleets (2024-2032) ($MN)

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