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市场调查报告书
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1844312

汽车预测分析市场机会、成长动力、产业趋势分析及 2025 - 2034 年预测

Automotive Predictive Analytics Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034
出版日期: | 出版商: Global Market Insights Inc. | 英文 210 Pages | 商品交期: 2-3个工作天内

价格
简介目录

2024 年全球汽车预测分析市场价值为 17 亿美元，预计到 2034 年将以 23.1% 的复合年增长率增长至 129 亿美元。

汽车预测分析市场 - IMG1

随着连网汽车的普及以及感测器、GPS 和资讯娱乐系统等物联网设备产生的大量资料，市场有望快速扩张。汽车製造商正在利用预测分析来预测零件故障、优化性能并提供客製化服务。基于 5G 的远端资讯处理和车联网 (V2X) 通讯的日益普及进一步加速了预测机会，推动了原始设备製造商 (OEM)、车队营运商和售后服务提供商的广泛采用。预测分析有助于防止车辆意外故障，提供对车辆健康和性能的即时洞察，从而降低成本并延长车队资产的生命週期。此外，乘用车和商用车预测性维护软体的日益普及是全球市场成长的关键动力。

市场范围
起始年份 2024
预测年份 2025-2034
起始值 17亿美元
预测值 129亿美元
复合年增长率 23.1%

硬体领域在2024年占据了56%的市场份额，预计在2025年至2034年期间的复合年增长率将达到23.5%。光达、雷达、摄影机和远端资讯处理系统等感测器是预测分析的基础，它们可以提供有关车辆行为、驾驶习惯和环境状况的即时资料。随着安全要求的提高以及高级驾驶辅助系统 (ADAS) 的普及，对这些硬体组件的需求将持续飙升。

2024年，乘用车市场占了74%的市占率。原始设备製造商越来越注重提供个人化功能，包括资讯娱乐推荐和预测性维护警报。透过分析驾驶习惯、天气和车辆历史使用等资料，汽车製造商可以提供客製化服务，从而提升客户满意度、提升品牌忠诚度并促进数据驱动的拥有体验。

美国汽车预测分析市场占了89%的市场份额，2024年价值5.259亿美元。美国在全球自动驾驶汽车研发领域处于领先地位，硅谷、底特律以及众多技术OEM合作伙伴做出了重大贡献。这些创新在很大程度上依赖预测分析来实现事故避免、即时决策和交通预测。

全球汽车预测分析市场的领导公司包括博世、大陆、IBM、微软、恩智浦、甲骨文、PTC、SAP、SAS 和 ZF。这些市场参与者透过各种策略推动创新和市场扩张，例如併购、合作和新产品开发。这些方法有助于公司保持竞争力，增强其技术能力，并满足汽车产业对先进预测解决方案日益增长的需求。公司为加强其在汽车预测分析市场中的地位而采用的关键策略包括与其他行业领导者建立策略合作伙伴关係和合併，以利用共享技术并扩大其影响力。这些公司也大力投资开发下一代解决方案，例如先进的感测器、即时分析软体和基于云端的平台，以增强其产品的预测能力。

目录

第一章：方法论

  • 市场范围和定义
  • 研究设计
    • 研究方法
    • 资料收集方法
  • 资料探勘来源
    • 全球的
    • 地区/国家
  • 基础估算与计算
    • 基准年计算
    • 市场评估的主要趋势
  • 初步研究和验证
    • 主要来源
  • 预测模型
  • 研究假设和局限性

第二章：执行摘要

第三章：行业洞察

  • 产业生态系统分析
    • 供应商格局
    • 利润率分析
    • 成本结构
    • 每个阶段的增值
    • 影响价值链的因素
    • 中断
  • 产业衝击力
    • 成长动力
      • 都市化和基础设施发展
      • 政府对智慧城市和公共工程的投资不断增加
      • 技术进步
      • 转向电动和混合动力汽车预测分析
      • 租赁业繁荣
    • 产业陷阱与挑战
      • 资本和维护成本高
      • 原物料价格波动
      • 熟练操作员短缺
      • 监管和排放合规要求
    • 市场机会
      • 电气化和电池驱动机械
      • 原始设备製造商和租赁公司之间的策略合作伙伴关係
      • 人工智慧、自动化和机器人技术的集成
      • 亚太地区和非洲新兴市场的成长
      • 设备租赁和车队管理的数位平台
  • 成长潜力分析
  • 主要市场趋势和中断
  • 未来市场趋势
  • 监管格局
    • 全球监管格局概览
    • 北美监管环境
      • NHTSA 连网汽车法规 NHTSA
      • 联邦车队管理要求 GSA
      • DOT V2X 通讯标准 USDOT
    • 欧洲规范架构
      • 联合国欧洲经济委员会车辆法规与 WP.29 标准 联合国欧洲经济委员会
      • GDPR 对汽车数据分析的影响
      • 欧盟网路安全法与汽车应用
    • 亚太地区监管动态
      • 中国车联网国家标准
      • 日本社会5.0与汽车融合
      • 印度汽车使命计画2026分析要求
    • 新兴监管趋势和未来合规要求
    • 跨境资料传输法规及影响
  • 波特的分析
  • PESTEL分析
  • 技术和创新格局
    • 当前的技术趋势
    • 新兴技术
  • 专利分析
  • 成本分解分析
  • 永续性和环境方面
    • 永续实践
    • 减少废弃物的策略
    • 生产中的能源效率
    • 环保倡议
    • 碳足迹考虑

第四章：竞争格局

  • 介绍
  • 公司市占率分析
  • 主要市场参与者的竞争分析
  • 竞争定位矩阵
  • 战略展望矩阵
  • 关键进展
    • 併购
    • 伙伴关係与合作
    • 新产品发布
    • 扩张计划和资金

第五章：市场估计与预测：依组件划分，2021 - 2034 年

  • 主要趋势
  • 硬体
    • 机载计算单元
    • 远端资讯处理设备
    • 诊断工具
  • 软体
    • 预测性维护平台
    • 车队管理软体
    • 连网汽车和 ADAS 软体
    • 人工智慧/机器学习分析引擎
  • 服务
    • 专业的
    • 託管

第六章：市场估计与预测：以推进方式，2021 - 2034 年

  • 主要趋势
  • 汽油
  • 柴油引擎
  • 全电动
  • 油电混合车
  • 插电式混合动力
  • 燃料电池电动车

第七章：市场估计与预测：按应用，2021 - 2034

  • 主要趋势
  • 预测性维护
  • 车辆远端资讯处理
  • 驾驶员和行为分析
  • 车队管理
  • 保固分析
  • 其他的

第 8 章：市场估计与预测：按最终用途，2021 - 2034 年

  • 主要趋势
  • OEM
  • 车队营运商
  • 保险提供者
  • 其他的

第九章：市场估计与预测：依车型，2021 - 2034

  • 主要趋势
  • 搭乘用车
    • 掀背车
    • 轿车
    • SUV
  • 商用车
    • 轻型
    • 中型
    • 重负

第 10 章：市场估计与预测：按地区，2021-2034 年

  • 主要趋势
  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 俄罗斯
    • 北欧人
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳新银行
    • 东南亚
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • 多边环境协定
    • 南非
    • 沙乌地阿拉伯
    • 阿联酋

第 11 章：公司简介

  • 全球参与者
    • AWS
    • Bosch
    • Google
    • IBM
    • Intel
    • Microsoft
    • Nvidia
    • Oracle
    • Qualcomm
    • SAP
  • Regional Champions
    • Continental
    • Denso
    • Hitachi
    • John Deere
    • Komatsu
    • Liebherr
    • Mitsubishi
    • NXP
    • Volvo
    • ZF
  • 新兴企业和服务提供者
    • Fleet Complete
    • Geotab
    • Masternaut
    • Mix Telematics
    • Omnitracs
    • PTC
    • SAS
    • Teletrac
    • Trimble
    • XCMG
简介目录
Product Code: 14763

The Global Automotive Predictive Analytics Market was valued at USD 1.7 billion in 2024 and is estimated to grow at a CAGR of 23.1% to reach USD 12.9 billion by 2034.

Automotive Predictive Analytics Market - IMG1

The market is poised for rapid expansion, driven by the increasing adoption of connected cars and the extensive data generated by IoT devices such as sensors, GPS, and infotainment systems. Automakers are leveraging predictive analytics to anticipate component failures, optimize performance, and offer tailored services. The growing deployment of 5G-based telematics and Vehicle-to-Everything (V2X) communication further accelerates predictive opportunities, fueling widespread adoption across original equipment manufacturers (OEMs), fleet operators, and aftermarket service providers. Predictive analytics help in preventing unexpected vehicle breakdowns, providing real-time insights into vehicle health and performance, thereby reducing costs and extending the lifecycle of fleet assets. Additionally, the increasing popularity of predictive maintenance software for both passenger and commercial vehicles is a key growth driver for the market worldwide.

Market Scope
Start Year2024
Forecast Year2025-2034
Start Value$1.7 Billion
Forecast Value$12.9 Billion
CAGR23.1%

The hardware segment held a 56% share in 2024 and is expected to grow at a CAGR of 23.5% between 2025 and 2034. Sensors such as LiDAR, radar, cameras, and telematics systems are fundamental to predictive analytics, offering real-time data on vehicle behavior, driver habits, and environmental conditions. As safety requirements increase and the adoption of advanced driver-assistance systems (ADAS) rises, demand for these hardware components will continue to soar.

The passenger vehicle segment held a 74% share in 2024. OEMs are increasingly focusing on delivering personalized features, including infotainment recommendations and predictive maintenance alerts. By analyzing data such as driving habits, weather, and historical vehicle usage, automakers can offer customized services that enhance customer satisfaction, improve brand loyalty, and promote data-driven ownership experiences.

U.S. Automotive Predictive Analytics Market held 89% share and was valued at USD 525.9 million in 2024. The U.S. leads the global autonomous vehicle research and development (R&D) sector, with significant contributions from Silicon Valley, Detroit, and numerous tech-OEM partnerships. These innovations rely heavily on predictive analytics to enable accident avoidance, real-time decision-making, and traffic forecasting.

Leading companies in the Global Automotive Predictive Analytics Market include Bosch, Continental, IBM, Microsoft, NXP, Oracle, PTC, SAP, SAS, and ZF. These market players are driving innovation and market expansion through a variety of strategies, such as mergers and acquisitions, partnerships, and the development of new products. These approaches help companies stay competitive, enhance their technological capabilities, and meet the growing demand for advanced predictive solutions in the automotive sector. Key strategies employed by companies to strengthen their position in the automotive predictive analytics market include forming strategic partnerships and mergers with other industry leaders to leverage shared technologies and expand their reach. These companies are also heavily investing in the development of next-generation solutions, such as advanced sensors, real-time analytics software, and cloud-based platforms, to enhance the predictive capabilities of their offerings.

Table of Contents

Chapter 1 Methodology

  • 1.1 Market scope and definition
  • 1.2 Research design
    • 1.2.1 Research approach
    • 1.2.2 Data collection methods
  • 1.3 Data mining sources
    • 1.3.1 Global
    • 1.3.2 Regional/Country
  • 1.4 Base estimates and calculations
    • 1.4.1 Base year calculation
    • 1.4.2 Key trends for market estimation
  • 1.5 Primary research and validation
    • 1.5.1 Primary sources
  • 1.6 Forecast model
  • 1.7 Research assumptions and limitations

Chapter 2 Executive Summary

  • 2.1 Industry 3600 synopsis, 2021 - 2034
  • 2.2 Key market trends
    • 2.2.1 Regional
    • 2.2.2 Component
    • 2.2.3 Vehicle
    • 2.2.4 Propulsion
    • 2.2.5 Application
    • 2.2.6 End use
  • 2.3 TAM Analysis, 2025-2034
  • 2.4 CXO perspectives: Strategic imperatives
    • 2.4.1 Executive decision points
    • 2.4.2 Critical success factors
  • 2.5 Future outlook
    • 2.5.1 Technology Roadmap & Innovation Trends
    • 2.5.2 Emerging Use Cases & Applications
    • 2.5.3 Market Expansion Opportunities
    • 2.5.4 Investment & Funding Landscape
    • 2.5.5 Regulatory Evolution & Policy Impact
    • 2.5.6 Sustainability & Environmental Considerations
    • 2.5.7 Risk Assessment & Mitigation Strategies
  • 2.6 Strategic recommendations

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
    • 3.1.1 Supplier landscape
    • 3.1.2 Profit margin analysis
    • 3.1.3 Cost structure
    • 3.1.4 Value addition at each stage
    • 3.1.5 Factor affecting the value chain
    • 3.1.6 Disruptions
  • 3.2 Industry impact forces
    • 3.2.1 Growth drivers
      • 3.2.1.1 Urbanization and infrastructure development
      • 3.2.1.2 Rising government investments in smart cities & public works
      • 3.2.1.3 Technological advancements
      • 3.2.1.4 Shift toward electric and hybrid automotive predictive analytics
      • 3.2.1.5 Rental and leasing boom
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 High capital and maintenance costs
      • 3.2.2.2 Volatility in raw material prices
      • 3.2.2.3 Shortage of skilled operators
      • 3.2.2.4 Regulatory and emission compliance requirements
    • 3.2.3 Market opportunities
      • 3.2.3.1 Electrification and battery-powered machinery
      • 3.2.3.2 Strategic partnerships between OEMs and rental firms
      • 3.2.3.3 Integration of AI, automation & robotics
      • 3.2.3.4 Growth in emerging APAC & African markets
      • 3.2.3.5 Digital platforms for equipment rental & fleet management
  • 3.3 Growth potential analysis
  • 3.4 Major market trends and disruptions
  • 3.5 Future market trends
  • 3.6 Regulatory landscape
    • 3.6.1 Global Regulatory Landscape Overview
    • 3.6.2 North American Regulatory Environment
      • 3.6.2.1 NHTSA Connected Vehicle Regulations NHTSA
      • 3.6.2.2 Federal Fleet Management Requirements GSA
      • 3.6.2.3 DOT V2X Communication Standards USDOT
    • 3.6.3 European Regulatory Framework
      • 3.6.3.1 UNECE Vehicle Regulations & WP.29 Standards UNECE
      • 3.6.3.2 GDPR Impact on Automotive Data Analytics
      • 3.6.3.3 EU Cybersecurity Act & Automotive Applications
    • 3.6.4 Asia Pacific Regulatory Developments
      • 3.6.4.1 China's National Standards for Connected Vehicles
      • 3.6.4.2 Japan's Society 5.0 & Automotive Integration
      • 3.6.4.3 India's Automotive Mission Plan 2026 Analytics Requirements
    • 3.6.5 Emerging Regulatory Trends & Future Compliance Requirements
    • 3.6.6 Cross-Border Data Transfer Regulations & Impact
  • 3.7 Porter’s analysis
  • 3.8 PESTEL analysis
  • 3.9 Technology and innovation landscape
    • 3.9.1 Current technological trends
    • 3.9.2 Emerging technologies
  • 3.10 Patent analysis
  • 3.11 Cost breakdown analysis
  • 3.12 Sustainability and environmental aspects
    • 3.12.1 Sustainable practices
    • 3.12.2 Waste reduction strategies
    • 3.12.3 Energy efficiency in production
    • 3.12.4 Eco-friendly initiatives
    • 3.12.5 Carbon footprint considerations

Chapter 4 Competitive Landscape, 2024

  • 4.1 Introduction
  • 4.2 Company market share analysis
    • 4.2.1 North America
    • 4.2.2 Europe
    • 4.2.3 Asia Pacific
    • 4.2.4 Latin America
    • 4.2.5 MEA
  • 4.3 Competitive analysis of major market players
  • 4.4 Competitive positioning matrix
  • 4.5 Strategic outlook matrix
  • 4.6 Key developments
    • 4.6.1 Mergers & acquisitions
    • 4.6.2 Partnerships & collaborations
    • 4.6.3 New product launches
    • 4.6.4 Expansion plans and funding

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2034 ($Bn)

  • 5.1 Key trends
  • 5.2 Hardware
    • 5.2.1 Onboard computing units
    • 5.2.2 Telematics devices
    • 5.2.3 Diagnostics tools
  • 5.3 Software
    • 5.3.1 Predictive maintenance platforms
    • 5.3.2 Fleet management software
    • 5.3.3 Connected vehicle & ADAS software
    • 5.3.4 Ai/ml analytics engines
  • 5.4 Services
    • 5.4.1 Professional
    • 5.4.2 Managed

Chapter 6 Market Estimates & Forecast, By Propulsion, 2021 - 2034 ($Bn)

  • 6.1 Key trends
  • 6.2 Gasoline
  • 6.3 Diesel
  • 6.4 All-electric
  • 6.5 HEV
  • 6.6 PHEV
  • 6.7 FCEV

Chapter 7 Market Estimates & Forecast, By Application, 2021 - 2034 ($Bn)

  • 7.1 Key trends
  • 7.2 Predictive maintenance
  • 7.3 Vehicle telematics
  • 7.4 Driver & behavior analytics
  • 7.5 Fleet management
  • 7.6 Warranty analytics
  • 7.7 Others

Chapter 8 Market Estimates & Forecast, By End Use, 2021 - 2034 ($Bn)

  • 8.1 Key trends
  • 8.2 OEM
  • 8.3 Fleet operators
  • 8.4 Insurance providers
  • 8.5 Others

Chapter 9 Market Estimates & Forecast, By Vehicle, 2021 - 2034 ($Bn)

  • 9.1 Key trends
  • 9.2 Passenger car
    • 9.2.1 Hatchback
    • 9.2.2 Sedan
    • 9.2.3 SUV
  • 9.3 Commercial Vehicle
    • 9.3.1 Light duty
    • 9.3.2 Medium duty
    • 9.3.3 Heavy-duty

Chapter 10 Market Estimates & Forecast, By Region, 2021-2034 ($Bn)

  • 10.1 Key trends
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
  • 10.3 Europe
    • 10.3.1 UK
    • 10.3.2 Germany
    • 10.3.3 France
    • 10.3.4 Italy
    • 10.3.5 Spain
    • 10.3.6 Russia
    • 10.3.7 Nordics
  • 10.4 Asia Pacific
    • 10.4.1 China
    • 10.4.2 India
    • 10.4.3 Japan
    • 10.4.4 South Korea
    • 10.4.5 ANZ
    • 10.4.6 Southeast Asia
  • 10.5 Latin America
    • 10.5.1 Brazil
    • 10.5.2 Mexico
    • 10.5.3 Argentina
  • 10.6 MEA
    • 10.6.1 South Africa
    • 10.6.2 Saudi Arabia
    • 10.6.3 UAE

Chapter 11 Company Profiles

  • 11.1 Global Players
    • 11.1.1 AWS
    • 11.1.2 Bosch
    • 11.1.3 Google
    • 11.1.4 IBM
    • 11.1.5 Intel
    • 11.1.6 Microsoft
    • 11.1.7 Nvidia
    • 11.1.8 Oracle
    • 11.1.9 Qualcomm
    • 11.1.10 SAP
  • 11.2 Regional Champions
    • 11.2.1 Continental
    • 11.2.2 Denso
    • 11.2.3 Hitachi
    • 11.2.4 John Deere
    • 11.2.5 Komatsu
    • 11.2.6 Liebherr
    • 11.2.7 Mitsubishi
    • 11.2.8 NXP
    • 11.2.9 Volvo
    • 11.2.10 ZF
  • 11.3 Emerging Players & Service Providers
    • 11.3.1 Fleet Complete
    • 11.3.2 Geotab
    • 11.3.3 Masternaut
    • 11.3.4 Mix Telematics
    • 11.3.5 Omnitracs
    • 11.3.6 PTC
    • 11.3.7 SAS
    • 11.3.8 Teletrac
    • 11.3.9 Trimble
    • 11.3.10 XCMG