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市場調查報告書
商品編碼
2141113

全球無人駕駛計程車市場（第一版）

The Global Robotaxi Market - 1st Edition
出版日期: | 出版商: Berg Insight | 英文 85 Pages | 商品交期: 最快1-2個工作天內

價格

自動駕駛計程車市場的最新趨勢是什麼？根據 Berg Insight 估計，全球自動駕駛運作數量預計將從 2025 年底的 6,500 輛增至 2036 年的 153 萬輛，複合年成長率 (CAGR) 高達 64.4%。本報告說明了自動駕駛計程車價值鏈的各個方面，涵蓋了 22 家自動駕駛計程車技術和旅遊平台提供者。您將了解有關自動駕駛計程車車隊營運商、技術和平台提供商，甚至汽車製造商 (OEM) 的最新資訊。

本報告要點：

  • 透過對市場上領先公司主管的多次訪談，我們獲得了許多見​​解。
  • 自動駕駛計程車價值鏈的全面概述。
  • 對市場趨勢和關鍵發展進行詳細分析。
  • 詳細介紹 22 家機器人計程車技術和旅遊平台提供者。
  • 區域市場預測至2036年

目錄

圖表一覽

摘要整理

第1章：機器人計程車簡介

  • 定義和分類
  • 機器人計程車服務概述
    • 無人駕駛計程車業的歷史
    • 目前已有機器人計程車服務
  • 法規環境
  • 機器人計程車應用案例和服務模式
    • Robotaxi 調度服務
    • 公共交通和市政服務
    • 貨運服務
    • 民防服務

第2章：機器人計程車技術棧

  • 感知、規劃和行動過程以及基於人工智慧的方法
  • 感應器
    • 相機
    • 雷達
    • LiDAR
    • 超音波感測器
    • 慣性導航系統
  • 計算平台
    • 元素計算
    • 計算單元的整合和部署
  • 自動駕駛軟體堆疊
    • 感知層
    • 感測器融合層
    • 位置識別和映射層
    • 運動規劃層
    • 控制層
  • 車輛執行系統和乘客介面系統
    • 車輛控制和執行器的整合
    • 備份系統和操作風險極低
    • 乘客、客艙和外部通訊系統
  • 連接性和離線功能
    • 車載資訊服務和OTA更新
    • 位置追蹤和車輛監控
    • 地圖和地理圍欄
    • 遠端協助和遠端操作

第3章：公司概況與策略

  • 機器人計程車技術提供商
    • Avride
    • Baidu (Apollo)
    • May Mobility
    • Mobileye
    • Momenta
    • Motional
    • Pony.ai
    • Tesla
    • Waymo
    • Wayve
    • WeRide
    • Zoox
    • 其他無人駕駛計程車技術提供商
  • 行動平台提供者
    • Amap
    • Bolt
    • CaoCao Mobility
    • DiDi
    • GO
    • Grab
    • Kakao Mobility
    • Lyft
    • T3 Mobility
    • Uber

第4章 市場預測與趨勢

  • 機器人計程車部署和業務收益預測
    • 區域機器人計程車部署預測
    • 區域自動駕駛計程車業務收益預測
  • 價值鏈分析
    • 汽車OEM廠商
    • 自動駕駛及相關技術提供商
    • 機器人計程車技術提供商
    • 行程與需求聚合平台
    • 機器人計程車營運商和所有者
  • 市場趨勢
    • 汽車製造商將在無人駕駛計程車服務中扮演更具選擇性的角色。
    • 端到端人工智慧提高了自動駕駛的地理擴充性。
    • 私人擁有的自動駕駛汽車正被用於無人駕駛計程車服務。
    • 自動駕駛汽車供應商在沒有出行平台合作夥伴的情況下推出機器人計程車服務。
    • 大規模機隊部署需要提高單位經濟效益。
    • 自動駕駛服務仍將依賴人工操作支援。
    • 地理擴充性將決定無人計程車的部署速度。
    • 消費者的接受程度將影響無人駕駛計程車的普及。
  • 併購

縮寫和簡稱列表

What are the latest developments on the robotaxi market? Berg Insight estimates that the number of robotaxis operating worldwide will grow at a CAGR of 64.4 percent from 6,500 at the end of 2025 to 1.53 million by 2036. The report explains all parts of the robotaxi value chain and covers 22 robotaxi technology and mobility platform providers. Get up to date with the latest information about robotaxi fleet operators, technology and platform providers as well as the involvement from the automotive OEMs.

Highlights from the report:

  • Insights from numerous executive interviews with market leading companies.
  • Comprehensive overview of the robotaxi value chain.
  • In-depth analysis of market trends and key developments.
  • Detailed profiles of 22 robotaxi technology and mobility platform providers.
  • Market forecasts by region lasting until 2036.

Table of Contents

List of Figures

Executive Summary

1 Introduction to Robotaxis

  • 1.1 Definitions and classifications
  • 1.2 Overview of robotaxi services
    • 1.2.1 Brief history of the robotaxi industry
    • 1.2.2 Current robotaxi offerings
  • 1.3 The regulatory environment
  • 1.4 Robotaxi use cases and service models
    • 1.4.1 Robotaxi ridehailing services
    • 1.4.2 Public transport and municipal services
    • 1.4.3 Goods transportation services
    • 1.4.4 Civil defence services

2 The Robotaxi Technology Stack

  • 2.1 Sense-Plan-Act process and AI-based approaches
  • 2.2 Sensors
    • 2.2.1 Cameras
    • 2.2.2 Radar
    • 2.2.3 LiDAR
    • 2.2.4 Ultrasonic sensors
    • 2.2.5 Inertial navigation system
  • 2.3 Compute platforms
    • 2.3.1 Compute elements
    • 2.3.2 Integration and deployment of compute elements
  • 2.4 The automated driving software stack
    • 2.4.1 Perception layer
    • 2.4.2 Sensor fusion layer
    • 2.4.3 Localisation and mapping layer
    • 2.4.4 Motion planning layer
    • 2.4.5 Control layer
  • 2.5 Vehicle execution and passenger interface systems
    • 2.5.1 Vehicle control and actuator integration
    • 2.5.2 Backup systems and minimal-risk manoeuvres
    • 2.5.3 Passenger, cabin and external communication systems
  • 2.6 Connectivity and offboard enablement
    • 2.6.1 Telematics and OTA updates
    • 2.6.2 Location tracking and fleet monitoring
    • 2.6.3 Maps and geofencing
    • 2.6.4 Remote assistance and teleoperation

3 Company Profiles and Strategies

  • 3.1 Robotaxi technology providers
    • 3.1.1 Avride
    • 3.1.2 Baidu (Apollo)
    • 3.1.3 May Mobility
    • 3.1.4 Mobileye
    • 3.1.5 Momenta
    • 3.1.6 Motional
    • 3.1.7 Pony.ai
    • 3.1.8 Tesla
    • 3.1.9 Waymo
    • 3.1.10 Wayve
    • 3.1.11 WeRide
    • 3.1.12 Zoox
    • 3.1.13 Additional robotaxi technology providers
  • 3.2 Mobility platform providers
    • 3.2.1 Amap
    • 3.2.2 Bolt
    • 3.2.3 CaoCao Mobility
    • 3.2.4 DiDi
    • 3.2.5 GO
    • 3.2.6 Grab
    • 3.2.7 Kakao Mobility
    • 3.2.8 Lyft
    • 3.2.9 T3 Mobility
    • 3.2.10 Uber

4 Market Forecasts and Trends

  • 4.1 Robotaxi deployment and service revenue forecasts
    • 4.1.1 Robotaxi deployment forecast by region
    • 4.1.2 Robotaxi service revenue forecast by region
  • 4.2 Value chain analysis
    • 4.2.1 Automotive OEMs
    • 4.2.2 Autonomous driving and enabling technology providers
    • 4.2.3 Robotaxi technology providers
    • 4.2.4 Mobility and demand aggregation platforms
    • 4.2.5 Robotaxi fleet operators and owners
  • 4.3 Market trends
    • 4.3.1 Automotive OEMs take more selective roles in robotaxi services
    • 4.3.2 End-to-end AI improves the geographic scalability of autonomous driving
    • 4.3.3 Privately owned autonomous vehicles to be used in robotaxi services
    • 4.3.4 AV providers to launch robotaxi services without mobility platform partners
    • 4.3.5 Improved unit economics will be required for large-scale fleet deployment
    • 4.3.6 Driverless services will continue to depend on human operational support
    • 4.3.7 Geographical scalability will determine the pace of the robotaxi fleet rollout
    • 4.3.8 Consumer acceptance will have an impact on robotaxi adoption
  • 4.4 Mergers and acquisitions

List of Acronyms and Abbreviations

List of Figures

  • Figure 1.1: SAE International levels of driving automation
  • Figure 1.2: Overview of robotaxi services (World Q3-2026)
  • Figure 2.1: The Sense-Plan-Act process
  • Figure 2.2: Overview of sensors used for automated driving
  • Figure 2.3: Typical LiDAR 3D depiction integrated with a digital map
  • Figure 2.4: Examples of sensors in a passenger car
  • Figure 2.5: Overview of the automated driving software stack
  • Figure 2.6: Overview of the sensor-fusion architecture for automated driving
  • Figure 2.7: Example of an HD map for automated driving
  • Figure 3.1: Robotaxi technology and mobility platform providers (2026)
  • Figure 3.2: Overview of L4 robotaxi technology providers (Q3-2026)
  • Figure 3.3: Avride and Uber robotaxi vehicle in Dallas
  • Figure 3.4: Motional robotaxi in Las Vegas
  • Figure 3.5: Overview of Waymo robotaxi services (Q2-2026)
  • Figure 3.6: Wayve robotaxi
  • Figure 4.1: Robotaxi deployments by region (World 2025–2036)
  • Figure 4.2: Robotaxi deployments by region (World 2025–2036)
  • Figure 4.3: Robotaxi service revenue by region (World 2025–2036)
  • Figure 4.4: Examples of OEM vehicle models leveraged in robotaxi services (World 2026)
  • Figure 4.5: Mergers and acquisitions in the automated driving industry (2016–2026)