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市场调查报告书
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1861535

交通运输领域人工智慧市场：按应用、技术、组件、模式、部署类型和最终用户划分－全球预测（2025-2032）

Artificial Intelligence in Transportation Market by Application Area, Technology, Component, Mode, Deployment, End User - Global Forecast 2025-2032
出版日期: | 出版商: 360iResearch | 英文 189 Pages | 商品交期: 最快1-2个工作天内

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预计到 2032 年，交通运输领域的人工智慧市场规模将达到 73.5 亿美元，复合年增长率为 14.26%。

主要市场统计数据
基准年 2024 25.2亿美元
预计年份：2025年 28.8亿美元
预测年份：2032年 73.5亿美元
复合年增长率 (%) 14.26%

下一代出行策略目标和营运蓝图图为人工智慧主导的交通转型奠定了基础。

本执行摘要旨在为全面分析人工智慧在运输系统中的应用奠定客观框架和范围。其目的是为企业高管、政策制定者和技术领导者提供一份简明扼要的综合报告，阐述重塑出行方式的驱动力、决定竞争优势的营运槓桿以及影响近期采购和部署决策的政策变数。本研究重点关注具有商业性价值的应用领域，包括自动驾驶、驾驶辅助、资产和车辆优化以及基础设施智能，并专注于分析技术能力、整合复杂性以及对相关人员的影响。

识别将重塑出行生态系统的变革性技术和商业变革；建构具有韧性的交通运输法规结构和相关人员价值链

交通运输领域正经历快速的重组，这主要得益于运算能力的整合、感测器技术的日益成熟以及商业模式的不断演进。感知技术堆迭、模型架构和边缘运算的进步，使得曾经被视为实验性技术的实际应用成为可能，从而将差异化竞争的焦点从单一功能的性能转移到系统级的整合和生命週期管理。这使得那些能够将强大的资料管道、严谨的检验流程以及紧密耦合的软硬体协同设计相结合的企业，能够将技术验证转化为可靠的服务。

评估美国2025年宣布的关税调整对供应链采购和跨境流动策略的累积影响

美国政策制定者于2025年推出的关税政策标誌着交通运输人工智慧生态系统供应链设计、筹资策略和商业合约的转捩点。其直接的营运影响是采购风险增加，迫使采购机构重新评估关键硬体（例如处理器、专用感测器和连接模组）的采购来源。为应对这项挑战，供应商正在实现製造地多元化，重新评估合约条款，并加快对替代供应商的资格认证，以维持生产的连续性。

解读细分市场主导的机会，并指导从应用技术组件模式部署和最终用户观点的定向投资。

分析揭示了技术和应用交叉融合的领域，这些领域共同创造了差异化的价值提案和规模化路径。按应用领域划分，市场涵盖自动驾驶汽车、驾驶辅助系统、车队管理、预测性维护和交通管理。自动驾驶汽车分为L4级和L5级部署，每个等级都有其自身的检验、地图绘製和监管要求。驾驶辅助系统包括主动车距控制巡航系统、自动紧急煞车、盲点侦测和车道维持辅助等功能，安全性和使用者感知度的逐步提升决定了其普及程度。车队管理涵盖资产追踪、驾驶员监控和路线优化，并设有与运作和利用率相关的明确营运KPI。预测性维护侧重于状态监控和故障诊断，从而实现基于状态的服务交付并减少非计划性停机时间。交通管理涵盖拥塞预测、路口管理和号誌控制，将城市级数据转化为通行能力和排放的改善。

区域战略展望：重点分析美洲、欧洲、中东和非洲以及亚太地区的细微差别，以协助制定针对特定区域的打入市场策略。

区域趋势将在塑造交通人工智慧价值链的普及速度和商业伙伴关係结构方面发挥重要作用。美洲已形成创新丛集，将深厚的软体专业知识与成熟的汽车製造能力相结合，为连接车队营运商和软体整合商的端到端试点项目提供了沃土，从而展示如何降低总体拥有成本 (TCO) 并提高安全性。该地区成熟的创投和资本市场正在加速颠覆性解决方案的商业化，而州和地方政府的采购试点计画则为扩大交通管理和车队优化倡议提供了试验平台。

竞争与企业资料分析，重点关注领先的交通运输和人工智慧参与企业的策略趋势、合作伙伴生态系统和创新重点。

在交通运输人工智慧领域，竞争格局将更取决于伙伴关係、平台策略和差异化的系统整合能力，而非任何单一产品的优势。硬体、软体和服务领域的领导参与企业正在推行混合策略，将专有技术堆迭与开放介面结合，以加速客户采用。这种混合方法能够快速整合到现有车辆架构中，并支援功能增量交付，同时保留了随着时间推移深入掌握平台技术的潜力。晶片组供应商、感测器製造商和演算法供应商之间的策略联盟十分普遍，将长期支援和模型重训练服务纳入客户合约的商业性安排也十分常见。

为工业领导者提供切实可行的、优先考虑的行动方案，以加速人工智慧的应用，降低供应链风险，并在行动旅行领域释放营运和客户价值。

为了将策略洞察转化为营运优势，领导者必须制定清晰且优先的行动计划，以应对技术准备、商业性契合度和供应链韧性等问题。车队营运商应先制定分阶段的试点计划，明确高价值的应用场景，例如降低营运成本和显着提高运转率，并确保合约条款能够抵御零件供应中断的影响。同时，原始设备製造商 (OEM) 应优先考虑模组化架构和标准接口，以实现硬体替换并缩短整合前置作业时间，从而在关税和不断变化的采购环境中保持长期的灵活性。

一套严谨的调查方法，清楚阐述了资料来源、分析架构和检验过程管治措施，从而为研究结论提供了支持。

本执行摘要的分析融合了定性和定量方法，以确保研究结果是基于证据且具有可操作性。主要研究包括对高阶主管、采购人员、工程经理和城市负责人进行结构化访谈，并辅以代表性认知和规划方案的技术评估。次要研究包括对同侪审查文献、监管文件、标准文件和供应商技术简报进行系统性回顾，以阐明主要研究结果并检验技术论点。

将人工智慧洞察、建议和策略重点整合到交通运输领域，以支援经营团队决策和跨职能协作。

总之，人工智慧正在重塑交通运输产业，从感测器到服务，没有例外。那些将人工智慧视为系统整合挑战而非单一解决方案的组织将从中获益最多。成功需要工程、采购、法规事务和商务部门之间严谨的跨职能协作，以及严格的检验和稳健的风险管理实务。不同的法规环境和收费系统凸显了分散式供应链和模组化设计的重要性，而基础设施和政策的区域差异则需要专门的打入市场策略。

目录

第一章：序言

第二章调查方法

第三章执行摘要

第四章 市场概览

第五章 市场洞察

  • 利用电脑视觉和人工智慧技术优化城市交通网路中的即时交通号誌控制
  • 提出了一种用于复杂道路环境下自适应自主车辆导航的强化学习演算法
  • 透过为电动公车车队整合基于人工智慧的预测性维护平台，减少营运中断
  • 在交通应用程式中引入自然语言处理聊天机器人，用于乘客互动和即时出行协助。
  • 利用人工智慧驱动的多模态通路规划系统优化首端物流效率
  • 应用机器学习分析车辆感测器数据，建立由驾驶行为驱动的动态保险定价模型
  • 面向下一代交通基础设施的低延迟V2X（车联网）通讯的边缘人工智慧架构开发
  • 将人工智慧驱动的无人机配送协调系统与地面运输结合，以提高都市区最后一公里物流的效率

第六章美国关税的累积影响，2025年

第七章 人工智慧的累积影响，2025年

第八章 交通运输领域人工智慧市场应用

  • 自动驾驶汽车
    • 4级
    • 5级
  • 驾驶辅助系统
    • 主动车距控制巡航系统
    • 自动紧急制动
    • 盲点侦测系统
    • 车道维持辅助系统
  • 车队管理
    • 资产追踪
    • 驾驶员监控
    • 路线优化
  • 预测性维护
    • 状态监测
    • 故障诊断
  • 交通管理
    • 交通拥堵预测
    • 交叉路口管理
    • 讯号控制

9. 交通运输领域的人工智慧市场（依技术划分）

  • 电脑视觉
    • 影像识别
    • 目标侦测
    • 影像分析
  • 深度学习
    • 卷积类神经网路
    • 生成对抗网络
    • 递迴神经网
  • 机器学习
    • 强化学习
    • 监督式学习
    • 无监督学习
  • 自然语言处理
    • 聊天机器人
    • 语音辨识
    • 语音助理

第十章 交通运输领域的人工智慧市场（按组件划分）

  • 硬体
    • 连接模组
    • 处理器
    • 感应器
  • 服务
    • 咨询
    • 一体化
    • 支援
  • 软体
    • 演算法
    • 中介软体
    • 平台

第十一章 依交通方式分類的交通运输领域人工智慧市场

  • 空气
  • 海路
  • 铁路
  • 路

第十二章 交通运输领域人工智慧市场（依部署方式划分）

  • 云
    • 私有云端
    • 公共云端
  • 杂交种
  • 本地部署

第十三章 交通运输领域人工智慧市场（依最终用户划分）

  • 车队营运商
    • 物流公司
    • 叫车公司
  • 基础设施营运商
    • 市政府
    • 道路运营商
  • OEM
    • 商用车製造商
    • 乘用车製造商
  • 乘客
    • 个人用户
    • 游客

第十四章 各地区交通运输业的人工智慧市场

  • 美洲
    • 北美洲
    • 拉丁美洲
  • 欧洲、中东和非洲
    • 欧洲
    • 中东
    • 非洲
  • 亚太地区

第十五章 交通运输领域人工智慧市场（以群体划分）

  • ASEAN
  • GCC
  • EU
  • BRICS
  • G7
  • NATO

第十六章 各国交通运输领域的人工智慧市场

  • 美国
  • 加拿大
  • 墨西哥
  • 巴西
  • 英国
  • 德国
  • 法国
  • 俄罗斯
  • 义大利
  • 西班牙
  • 中国
  • 印度
  • 日本
  • 澳洲
  • 韩国

第十七章 竞争格局

  • 2024年市占率分析
  • FPNV定位矩阵，2024
  • 竞争分析
    • NVIDIA Corporation
    • Tesla, Inc.
    • Waymo LLC
    • Mobileye NV
    • Baidu, Inc.
    • Aptiv PLC
    • Robert Bosch GmbH
    • Valeo SA
    • Aurora Innovation, Inc.
    • Uber Technologies, Inc.
Product Code: MRR-69324464D21F

The Artificial Intelligence in Transportation Market is projected to grow by USD 7.35 billion at a CAGR of 14.26% by 2032.

KEY MARKET STATISTICS
Base Year [2024] USD 2.52 billion
Estimated Year [2025] USD 2.88 billion
Forecast Year [2032] USD 7.35 billion
CAGR (%) 14.26%

Setting the stage for AI-driven transportation transformation with strategic scope objectives and an operational roadmap for next-generation mobility

This executive summary establishes the objective framework and scope for a comprehensive analysis of artificial intelligence across transportation systems. The intent is to equip executives, policy makers, and technical leaders with a concise synthesis of the forces reshaping mobility, the operational levers that determine competitive differentiation, and the policy variables that will influence near-term procurement and deployment decisions. The research foregrounds technological capability, integration complexity, and stakeholder impact, while concentrating on commercially relevant applications such as automated mobility, driver assistance, asset and fleet optimization, and infrastructure intelligence.

The scope spans software and hardware stacks, emergent algorithmic approaches, and the ecosystems of suppliers, integrators, and end users that together determine adoption velocity. In doing so, the analysis privileges actionable insight over abstract theory and emphasizes interoperability, safety assurance, and resiliency as principal evaluation criteria. Methodologically, the work triangulates practitioner interviews, technical assessment, and scenario analysis to surface pragmatic recommendations for engineering organizations, fleet operators, and public authorities. Ultimately, the introduction clarifies the report's organizing logic and positions the subsequent sections to inform strategic choices about investment priorities, procurement frameworks, and pilot-to-scale pathways for AI-enabled transportation solutions.

Identifying transformative technological and business shifts reshaping mobility ecosystems regulatory frameworks and stakeholder value chains for resilient transport

The transportation landscape is undergoing a rapid reconfiguration driven by a convergence of computational capability, sensor maturity, and evolving commercial models. Advances in perception stacks, model architectures, and edge compute have enabled real-world functionality once considered experimental, and, consequently, the locus of differentiation has shifted from isolated feature performance to systems-level integration and lifecycle management. As a result, organizations that combine robust data pipelines, disciplined validation processes, and tightly coupled hardware-software co-design are positioned to convert technical proofs into reliable services.

Equally consequential are shifts in regulatory and procurement regimes that emphasize safety assurance, data governance, and interoperability. Where regulation once lagged technological capability, jurisdictions are now experimenting with modular, outcomes-focused frameworks that accelerate controlled deployments while preserving public safety. This regulatory momentum is accompanied by commercial shifts: fleet operators demand predictable total-cost-of-ownership outcomes, OEMs pursue platform-driven revenue streams, and infrastructure providers view AI as a tool to optimize asset utilization and urban flow. Together these forces produce a dynamic in which partnerships and standards matter as much as model accuracy, and where successful strategies combine technological excellence with supply-chain resilience and clear value articulation for end users.

Assessing the cumulative impacts of United States tariff adjustments announced in 2025 on supply chains component sourcing and cross-border mobility strategies

Recent tariff measures introduced by United States policy makers in 2025 have created an inflection point for supply-chain design, component sourcing strategies, and commercial contracting across the transportation AI ecosystem. The immediate operational effect has been to elevate procurement risk and to force procurement organizations to reassess sourcing geographies for critical hardware such as processors, specialized sensors, and connectivity modules. In turn, suppliers are responding by diversifying manufacturing footprints, re-evaluating contract clauses, and accelerating qualification of alternate vendors to preserve production continuity.

Beyond procurement, the tariff environment is catalyzing a strategic reassessment of localization and supplier consolidation strategies. Some OEMs and fleet operators are exploring nearshoring and dual-sourcing to shorten lead times and reduce exposure to cross-border tariff volatility, while software and service vendors emphasize modular architectures that allow substitution of hardware layers without re-engineering higher-level applications. At the systems level, this turbulence is increasing the value of robust component abstraction, standard interfaces, and long-term purchasing agreements that incorporate tariff contingency clauses. Moreover, regulatory compliance and trade policy analysis must now be integral to technical roadmaps, since trade measures can materially affect unit cost structures and the feasibility of certain deployment profiles. In sum, the tariff environment of 2025 sharpens the need for cross-functional procurement strategies, resilient supplier ecosystems, and design choices that decouple software value from hardware-specific constraints.

Decoding segmentation-driven opportunities across application technology component mode deployment and end-user perspectives to guide targeted investments

A segmentation-driven analysis reveals where technology and applications intersect to create differentiated value propositions and scale pathways. Based on application area, the market encompasses Autonomous Vehicles, Driver Assistance Systems, Fleet Management, Predictive Maintenance, and Traffic Management. Autonomous Vehicles break down into Level 4 and Level 5 deployments, each carrying distinct validation, mapping, and regulatory demands. Driver Assistance Systems include features such as Adaptive Cruise Control, Automated Emergency Braking, Blind Spot Detection, and Lane Keep Assist, where incremental safety gains and customer perception determine adoption. Fleet Management spans Asset Tracking, Driver Monitoring, and Route Optimization, with clear operational KPIs tied to uptime and utilization. Predictive Maintenance focuses on Condition Monitoring and Fault Diagnosis, enabling condition-based servicing and reduced unscheduled downtime. Traffic Management covers Congestion Prediction, Intersection Management, and Traffic Signal Control, translating city-scale data into throughput and emissions improvements.

When organized by technology, solutions derive from Computer Vision, Deep Learning, Machine Learning, and Natural Language Processing. Computer Vision capabilities include Image Recognition, Object Detection, and Video Analytics, which form the sensory foundation for higher-order behaviors. Deep Learning architectures such as Convolutional Neural Networks, Generative Adversarial Networks, and Recurrent Neural Networks support perception and temporal reasoning, while Machine Learning methods including Reinforcement Learning, Supervised Learning, and Unsupervised Learning drive decision policies and anomaly detection. Natural Language Processing features like Chatbots, Speech Recognition, and Voice Assistants are increasingly relevant for passenger interfaces and driver assistance.

Component segmentation separates Hardware, Services, and Software. Hardware comprises Connectivity Modules, Processors, and Sensors that anchor system reliability; Services include Consulting, Integration, and Support necessary for deployment and lifecycle maintenance; Software covers Algorithms, Middleware, and Platforms that deliver functional differentiation. The mode of operation spans Air, Maritime, Rail, and Road, each with unique environmental, regulatory, and operational constraints that influence sensor selection and model design. Deployment models cover Cloud, Hybrid, and On Premises topologies with the Cloud further divided into Private Cloud and Public Cloud options, reflecting trade-offs between latency, cost, and data sovereignty. Finally, end users range across Fleet Operators, Infrastructure Operators, OEMs, and Passengers. Fleet Operators include Logistics Companies and Ride Hailing Companies with distinct utilization patterns. Infrastructure Operators encompass City Authorities and Road Operators who prioritize system-scale resilience. OEMs include Commercial Vehicle OEMs and Passenger Vehicle OEMs focused on platform extensibility. Passengers span Individual Users and Tourists, whose acceptance and trust are essential for sustained adoption.

Collectively, these segmentation lenses highlight where investments unlock disproportionate value, where integration complexity is highest, and where regulatory and operational constraints will be the binding considerations for deployment.

Regional strategic outlook highlighting nuanced dynamics across Americas Europe Middle East & Africa and Asia-Pacific to inform localized go-to-market approaches

Regional dynamics play an outsized role in shaping both the pace of adoption and the structure of commercial partnerships across the transportation AI value chain. In the Americas, innovation clusters combine deep software expertise with established automotive manufacturing capabilities, creating fertile ground for end-to-end pilots that pair fleet operators with software integrators to validate TCO improvements and safety uplift. This region's advanced venture and capital markets also accelerate commercialization of disruptive solutions, while state and municipal procurement experiments provide laboratories for scaling traffic management and fleet optimization initiatives.

Europe, Middle East & Africa exhibits a heterogeneous landscape where stringent regulatory frameworks intersect with ambitious urban decarbonization agendas. Across this region, regulatory emphasis on safety, data protection, and emissions reduction drives demand for solutions that can demonstrate compliance and measurable sustainability outcomes. Many cities and national agencies are prioritizing interoperability and public procurement models that favor long-term operational resilience, which benefits vendors capable of delivering certified, standards-aligned platforms.

Asia-Pacific is characterized by rapid digital infrastructure rollout, high urban density challenges, and aggressive automation agendas across logistics and public transit. In several markets, the combination of dense transport networks and strong manufacturing ecosystems supports rapid iteration from prototype to large-scale deployment, particularly for fleet telematics, driver assistance retrofits, and traffic signal automation. Consequently, regional strategies must be tailored: supply-chain resilience and manufacturing proximity matter most where tariff and trade dynamics impose commercial constraints, while regulatory alignment and localized validation regimes are critical where public safety and citizen acceptance are frontline concerns.

Competitive and corporate intelligence insights revealing strategic moves partner ecosystems and innovation priorities among leading transportation and AI players

Competitive dynamics in transportation AI are defined less by single-product dominance and more by the architecture of partnerships, platform strategies, and differentiated system integration capabilities. Leading players across hardware, software, and services are pursuing hybrid strategies that blend proprietary stacks with open interfaces to accelerate customer adoption; this hybrid approach enables rapid integration with legacy vehicle architectures and supports incremental feature delivery while preserving the potential for deeper platform capture over time. Strategic alliances between chipset providers, sensor manufacturers, and algorithm vendors are common, as are commercial arrangements that embed long-term support and model re-training services into customer contracts.

Mature suppliers emphasize software-defined vehicle strategies and recurring revenue models that include subscription services, over-the-air updates, and performance-based contracts that align vendor incentives with operational outcomes. At the same time, specialized startups are focused on narrow but high-value niches such as semantic perception for complex urban environments or predictive analytics tuned to heavy-duty fleet operations. Investors and corporate development teams are increasingly prioritizing capabilities that complement existing route-to-market strengths, such as installation networks for retrofits or municipal procurement experience for infrastructure projects. In response to tariff and supply-chain pressures, several firms are also accelerating vertical integration and reshoring initiatives for critical components, while others hedge risk through diversified manufacturing partnerships. Importantly, the competitive environment rewards vendors that can demonstrate proven safety cases, clear integration pathways, and measurable operational value for both private and public sector customers.

Practical and prioritized actions for industry leaders to accelerate AI adoption mitigate supply-chain risks and unlock operational and customer value across mobility sectors

To convert strategic insight into operational advantage, leaders must pursue a clear set of prioritized actions that address technology readiness, commercial alignment, and supply-chain resilience. Organizations with fleet operations should begin by defining a phased pilot roadmap that isolates the highest-value use cases-those that reduce operating expense or materially improve uptime-and by securing contractual terms that protect against component supply disruption. Meanwhile, OEMs should prioritize modular architectures and standard interfaces that enable hardware substitution and reduce integration lead time, thereby preserving long-term flexibility in the face of tariff and sourcing volatility.

Infrastructure operators are advised to focus on interoperable data platforms that can aggregate multi-modal telemetry and expose standardized APIs for third-party innovation. Regulators and city planners should adopt outcome-based testing protocols and sandbox arrangements that encourage controlled experimentation while ensuring public safety and transparency. Across all stakeholders, investment in robust validation and explainability processes will accelerate trust and adoption; therefore, establishing clear metrics for performance, safety, and user acceptance is indispensable. Finally, procurement teams should embed trade-policy clauses into supplier agreements and pursue dual-sourcing or nearshoring strategies for mission-critical components. By sequencing these actions-pilot to scale, modular design to integration, governance to deployment-organizations can reduce risk while maximizing the strategic upside of AI in transportation.

Robust research methodology outlining data sources analytical frameworks validation processes and governance measures that support the study conclusions

The analysis underpinning this executive summary integrates qualitative and quantitative methods to ensure findings are both evidence-based and actionable. Primary research consisted of structured interviews with C-suite executives, procurement leads, engineering managers, and city technologists, complemented by technical assessments of representative perception and planning stacks. Secondary research involved systematic review of peer-reviewed literature, regulatory filings, standards documentation, and supplier technical briefs to contextualize primary insights and validate technology claims.

Analytical techniques included scenario planning to explore alternative trade-policy and regulatory trajectories, supply-chain mapping to identify concentration risks for critical components, and capability benchmarking to compare algorithmic approaches across representative operational settings. Validation was achieved through cross-referencing interview data with deployment case studies and by engaging neutral domain experts to review safety and integration assumptions. Governance of the research process emphasized transparency in source attribution, reproducible methods for comparative analysis, and a clear audit trail for model and scenario assumptions. Where projections were used to illustrate operational impact, sensitivity analyses tested the robustness of conclusions across plausible parameter ranges. The resulting methodology delivers a defensible and replicable foundation for strategic decision-making while explicitly surfacing assumptions and limitations that executives should account for when applying these insights.

Concluding synthesis connecting insights implications and strategic priorities to support executive decision-making and cross-functional alignment in transport AI

In closing, artificial intelligence is reshaping transportation from sensor to service, and the organizations best positioned to benefit will be those that treat AI as a systems integration challenge rather than a point-solution exercise. Success demands disciplined cross-functional collaboration among engineering, procurement, regulatory affairs, and commercial teams alongside rigorous validation and robust risk-management practices. The regulatory and tariff environment heightens the importance of supply-chain diversification and modular design, while regional differences in infrastructure and policy require localized go-to-market strategies.

Decision-makers should therefore prioritize pilots with measurable operational KPIs, invest in modular architectures that enable hardware flexibility, and institutionalize safety and explainability practices to accelerate stakeholder trust. When these elements are combined with proactive supplier strategies and clear regulatory engagement, organizations can both mitigate near-term risks and capture long-term value from AI-enabled mobility services. The conclusion reinforces a pragmatic posture: prioritize deployments that clearly improve operating metrics, safeguard against supply-side shocks, and align with regulatory and societal expectations to ensure sustainable scale-up.

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Implementation of computer vision and AI for real-time traffic signal optimization across urban networks
  • 5.2. Deployment of reinforcement learning algorithms for adaptive autonomous vehicle navigation in complex road environments
  • 5.3. Integration of AI-based predictive maintenance platforms for electric bus fleets to reduce service disruptions
  • 5.4. Adoption of natural language processing chatbots for passenger engagement and real-time travel assistance in transit apps
  • 5.5. Use of AI-driven multimodal route planning systems to optimize first-mile and last-mile logistics efficiency
  • 5.6. Application of machine learning to analyze vehicular sensor data for dynamic insurance pricing models based on driving behavior
  • 5.7. Development of edge AI architectures for low-latency vehicle-to-everything communication in next-generation transport infrastructure
  • 5.8. Integration of AI-powered drone delivery coordination with ground transport for urban last-mile logistics efficiency gains

6. Cumulative Impact of United States Tariffs 2025

7. Cumulative Impact of Artificial Intelligence 2025

8. Artificial Intelligence in Transportation Market, by Application Area

  • 8.1. Autonomous Vehicles
    • 8.1.1. Level 4
    • 8.1.2. Level 5
  • 8.2. Driver Assistance Systems
    • 8.2.1. Adaptive Cruise Control
    • 8.2.2. Automated Emergency Braking
    • 8.2.3. Blind Spot Detection
    • 8.2.4. Lane Keep Assist
  • 8.3. Fleet Management
    • 8.3.1. Asset Tracking
    • 8.3.2. Driver Monitoring
    • 8.3.3. Route Optimization
  • 8.4. Predictive Maintenance
    • 8.4.1. Condition Monitoring
    • 8.4.2. Fault Diagnosis
  • 8.5. Traffic Management
    • 8.5.1. Congestion Prediction
    • 8.5.2. Intersection Management
    • 8.5.3. Traffic Signal Control

9. Artificial Intelligence in Transportation Market, by Technology

  • 9.1. Computer Vision
    • 9.1.1. Image Recognition
    • 9.1.2. Object Detection
    • 9.1.3. Video Analytics
  • 9.2. Deep Learning
    • 9.2.1. Convolutional Neural Networks
    • 9.2.2. Generative Adversarial Networks
    • 9.2.3. Recurrent Neural Networks
  • 9.3. Machine Learning
    • 9.3.1. Reinforcement Learning
    • 9.3.2. Supervised Learning
    • 9.3.3. Unsupervised Learning
  • 9.4. Natural Language Processing
    • 9.4.1. Chatbots
    • 9.4.2. Speech Recognition
    • 9.4.3. Voice Assistants

10. Artificial Intelligence in Transportation Market, by Component

  • 10.1. Hardware
    • 10.1.1. Connectivity Modules
    • 10.1.2. Processors
    • 10.1.3. Sensors
  • 10.2. Services
    • 10.2.1. Consulting
    • 10.2.2. Integration
    • 10.2.3. Support
  • 10.3. Software
    • 10.3.1. Algorithms
    • 10.3.2. Middleware
    • 10.3.3. Platforms

11. Artificial Intelligence in Transportation Market, by Mode

  • 11.1. Air
  • 11.2. Maritime
  • 11.3. Rail
  • 11.4. Road

12. Artificial Intelligence in Transportation Market, by Deployment

  • 12.1. Cloud
    • 12.1.1. Private Cloud
    • 12.1.2. Public Cloud
  • 12.2. Hybrid
  • 12.3. On Premises

13. Artificial Intelligence in Transportation Market, by End User

  • 13.1. Fleet Operators
    • 13.1.1. Logistics Companies
    • 13.1.2. Ride Hailing Companies
  • 13.2. Infrastructure Operators
    • 13.2.1. City Authorities
    • 13.2.2. Road Operators
  • 13.3. Oems
    • 13.3.1. Commercial Vehicle Oems
    • 13.3.2. Passenger Vehicle Oems
  • 13.4. Passengers
    • 13.4.1. Individual Users
    • 13.4.2. Tourists

14. Artificial Intelligence in Transportation Market, by Region

  • 14.1. Americas
    • 14.1.1. North America
    • 14.1.2. Latin America
  • 14.2. Europe, Middle East & Africa
    • 14.2.1. Europe
    • 14.2.2. Middle East
    • 14.2.3. Africa
  • 14.3. Asia-Pacific

15. Artificial Intelligence in Transportation Market, by Group

  • 15.1. ASEAN
  • 15.2. GCC
  • 15.3. European Union
  • 15.4. BRICS
  • 15.5. G7
  • 15.6. NATO

16. Artificial Intelligence in Transportation Market, by Country

  • 16.1. United States
  • 16.2. Canada
  • 16.3. Mexico
  • 16.4. Brazil
  • 16.5. United Kingdom
  • 16.6. Germany
  • 16.7. France
  • 16.8. Russia
  • 16.9. Italy
  • 16.10. Spain
  • 16.11. China
  • 16.12. India
  • 16.13. Japan
  • 16.14. Australia
  • 16.15. South Korea

17. Competitive Landscape

  • 17.1. Market Share Analysis, 2024
  • 17.2. FPNV Positioning Matrix, 2024
  • 17.3. Competitive Analysis
    • 17.3.1. NVIDIA Corporation
    • 17.3.2. Tesla, Inc.
    • 17.3.3. Waymo LLC
    • 17.3.4. Mobileye N.V.
    • 17.3.5. Baidu, Inc.
    • 17.3.6. Aptiv PLC
    • 17.3.7. Robert Bosch GmbH
    • 17.3.8. Valeo S.A.
    • 17.3.9. Aurora Innovation, Inc.
    • 17.3.10. Uber Technologies, Inc.

LIST OF FIGURES

  • FIGURE 1. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, 2018-2032 (USD MILLION)
  • FIGURE 2. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY APPLICATION AREA, 2024 VS 2032 (%)
  • FIGURE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY APPLICATION AREA, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TECHNOLOGY, 2024 VS 2032 (%)
  • FIGURE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TECHNOLOGY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPONENT, 2024 VS 2032 (%)
  • FIGURE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPONENT, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MODE, 2024 VS 2032 (%)
  • FIGURE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MODE, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEPLOYMENT, 2024 VS 2032 (%)
  • FIGURE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEPLOYMENT, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY END USER, 2024 VS 2032 (%)
  • FIGURE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY END USER, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY REGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 15. AMERICAS ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SUBREGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 16. NORTH AMERICA ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 17. LATIN AMERICA ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 18. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SUBREGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 19. EUROPE ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 20. MIDDLE EAST ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 21. AFRICA ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 22. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY GROUP, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 24. ASEAN ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 25. GCC ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 26. EUROPEAN UNION ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 27. BRICS ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 28. G7 ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 29. NATO ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 31. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SHARE, BY KEY PLAYER, 2024
  • FIGURE 32. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, FPNV POSITIONING MATRIX, 2024

LIST OF TABLES

  • TABLE 1. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
  • TABLE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, 2018-2024 (USD MILLION)
  • TABLE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, 2025-2032 (USD MILLION)
  • TABLE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY APPLICATION AREA, 2018-2024 (USD MILLION)
  • TABLE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY APPLICATION AREA, 2025-2032 (USD MILLION)
  • TABLE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTONOMOUS VEHICLES, 2018-2024 (USD MILLION)
  • TABLE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTONOMOUS VEHICLES, 2025-2032 (USD MILLION)
  • TABLE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTONOMOUS VEHICLES, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTONOMOUS VEHICLES, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTONOMOUS VEHICLES, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTONOMOUS VEHICLES, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTONOMOUS VEHICLES, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTONOMOUS VEHICLES, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 4, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 4, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 4, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 4, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 4, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 20. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 4, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 21. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 5, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 22. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 5, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 5, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 24. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 5, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 25. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 5, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 26. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LEVEL 5, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 27. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER ASSISTANCE SYSTEMS, 2018-2024 (USD MILLION)
  • TABLE 28. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER ASSISTANCE SYSTEMS, 2025-2032 (USD MILLION)
  • TABLE 29. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER ASSISTANCE SYSTEMS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER ASSISTANCE SYSTEMS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 31. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER ASSISTANCE SYSTEMS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 32. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER ASSISTANCE SYSTEMS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 33. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER ASSISTANCE SYSTEMS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 34. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER ASSISTANCE SYSTEMS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 35. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ADAPTIVE CRUISE CONTROL, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 36. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ADAPTIVE CRUISE CONTROL, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 37. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ADAPTIVE CRUISE CONTROL, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 38. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ADAPTIVE CRUISE CONTROL, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 39. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ADAPTIVE CRUISE CONTROL, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 40. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ADAPTIVE CRUISE CONTROL, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 41. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTOMATED EMERGENCY BRAKING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 42. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTOMATED EMERGENCY BRAKING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 43. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTOMATED EMERGENCY BRAKING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 44. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTOMATED EMERGENCY BRAKING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 45. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTOMATED EMERGENCY BRAKING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 46. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY AUTOMATED EMERGENCY BRAKING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 47. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY BLIND SPOT DETECTION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 48. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY BLIND SPOT DETECTION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 49. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY BLIND SPOT DETECTION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 50. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY BLIND SPOT DETECTION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 51. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY BLIND SPOT DETECTION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 52. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY BLIND SPOT DETECTION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 53. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LANE KEEP ASSIST, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 54. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LANE KEEP ASSIST, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 55. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LANE KEEP ASSIST, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 56. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LANE KEEP ASSIST, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 57. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LANE KEEP ASSIST, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 58. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY LANE KEEP ASSIST, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 59. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FLEET MANAGEMENT, 2018-2024 (USD MILLION)
  • TABLE 60. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FLEET MANAGEMENT, 2025-2032 (USD MILLION)
  • TABLE 61. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FLEET MANAGEMENT, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 62. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FLEET MANAGEMENT, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 63. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FLEET MANAGEMENT, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 64. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FLEET MANAGEMENT, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 65. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FLEET MANAGEMENT, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 66. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FLEET MANAGEMENT, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 67. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ASSET TRACKING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 68. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ASSET TRACKING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 69. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ASSET TRACKING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 70. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ASSET TRACKING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 71. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ASSET TRACKING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 72. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ASSET TRACKING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 73. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER MONITORING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 74. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER MONITORING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 75. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER MONITORING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 76. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER MONITORING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 77. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER MONITORING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 78. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DRIVER MONITORING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 79. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ROUTE OPTIMIZATION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 80. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ROUTE OPTIMIZATION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 81. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ROUTE OPTIMIZATION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 82. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ROUTE OPTIMIZATION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 83. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ROUTE OPTIMIZATION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 84. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY ROUTE OPTIMIZATION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 85. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2024 (USD MILLION)
  • TABLE 86. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2025-2032 (USD MILLION)
  • TABLE 87. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PREDICTIVE MAINTENANCE, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 88. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PREDICTIVE MAINTENANCE, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 89. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PREDICTIVE MAINTENANCE, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 90. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PREDICTIVE MAINTENANCE, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 91. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PREDICTIVE MAINTENANCE, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 92. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PREDICTIVE MAINTENANCE, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 93. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONDITION MONITORING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 94. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONDITION MONITORING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 95. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONDITION MONITORING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 96. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONDITION MONITORING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 97. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONDITION MONITORING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 98. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONDITION MONITORING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 99. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FAULT DIAGNOSIS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 100. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FAULT DIAGNOSIS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 101. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FAULT DIAGNOSIS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 102. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FAULT DIAGNOSIS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 103. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FAULT DIAGNOSIS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 104. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY FAULT DIAGNOSIS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 105. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC MANAGEMENT, 2018-2024 (USD MILLION)
  • TABLE 106. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC MANAGEMENT, 2025-2032 (USD MILLION)
  • TABLE 107. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC MANAGEMENT, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 108. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC MANAGEMENT, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 109. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC MANAGEMENT, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 110. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC MANAGEMENT, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 111. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC MANAGEMENT, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 112. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC MANAGEMENT, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 113. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONGESTION PREDICTION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 114. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONGESTION PREDICTION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 115. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONGESTION PREDICTION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 116. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONGESTION PREDICTION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 117. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONGESTION PREDICTION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 118. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONGESTION PREDICTION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 119. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY INTERSECTION MANAGEMENT, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 120. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY INTERSECTION MANAGEMENT, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 121. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY INTERSECTION MANAGEMENT, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 122. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY INTERSECTION MANAGEMENT, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 123. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY INTERSECTION MANAGEMENT, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 124. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY INTERSECTION MANAGEMENT, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 125. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC SIGNAL CONTROL, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 126. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC SIGNAL CONTROL, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 127. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC SIGNAL CONTROL, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 128. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC SIGNAL CONTROL, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 129. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC SIGNAL CONTROL, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 130. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TRAFFIC SIGNAL CONTROL, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 131. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TECHNOLOGY, 2018-2024 (USD MILLION)
  • TABLE 132. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY TECHNOLOGY, 2025-2032 (USD MILLION)
  • TABLE 133. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPUTER VISION, 2018-2024 (USD MILLION)
  • TABLE 134. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPUTER VISION, 2025-2032 (USD MILLION)
  • TABLE 135. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPUTER VISION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 136. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPUTER VISION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 137. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPUTER VISION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 138. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPUTER VISION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 139. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPUTER VISION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 140. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPUTER VISION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 141. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY IMAGE RECOGNITION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 142. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY IMAGE RECOGNITION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 143. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY IMAGE RECOGNITION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 144. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY IMAGE RECOGNITION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 145. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY IMAGE RECOGNITION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 146. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY IMAGE RECOGNITION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 147. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY OBJECT DETECTION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 148. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY OBJECT DETECTION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 149. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY OBJECT DETECTION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 150. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY OBJECT DETECTION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 151. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY OBJECT DETECTION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 152. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY OBJECT DETECTION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 153. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VIDEO ANALYTICS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 154. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VIDEO ANALYTICS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 155. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VIDEO ANALYTICS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 156. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VIDEO ANALYTICS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 157. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VIDEO ANALYTICS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 158. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VIDEO ANALYTICS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 159. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEEP LEARNING, 2018-2024 (USD MILLION)
  • TABLE 160. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEEP LEARNING, 2025-2032 (USD MILLION)
  • TABLE 161. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEEP LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 162. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEEP LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 163. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEEP LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 164. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEEP LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 165. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEEP LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 166. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY DEEP LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 167. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONVOLUTIONAL NEURAL NETWORKS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 168. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONVOLUTIONAL NEURAL NETWORKS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 169. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONVOLUTIONAL NEURAL NETWORKS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 170. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONVOLUTIONAL NEURAL NETWORKS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 171. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONVOLUTIONAL NEURAL NETWORKS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 172. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONVOLUTIONAL NEURAL NETWORKS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 173. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY GENERATIVE ADVERSARIAL NETWORKS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 174. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY GENERATIVE ADVERSARIAL NETWORKS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 175. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY GENERATIVE ADVERSARIAL NETWORKS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 176. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY GENERATIVE ADVERSARIAL NETWORKS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 177. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY GENERATIVE ADVERSARIAL NETWORKS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 178. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY GENERATIVE ADVERSARIAL NETWORKS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 179. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY RECURRENT NEURAL NETWORKS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 180. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY RECURRENT NEURAL NETWORKS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 181. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY RECURRENT NEURAL NETWORKS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 182. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY RECURRENT NEURAL NETWORKS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 183. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY RECURRENT NEURAL NETWORKS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 184. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY RECURRENT NEURAL NETWORKS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 185. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MACHINE LEARNING, 2018-2024 (USD MILLION)
  • TABLE 186. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MACHINE LEARNING, 2025-2032 (USD MILLION)
  • TABLE 187. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 188. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 189. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MACHINE LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 190. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MACHINE LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 191. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MACHINE LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 192. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY MACHINE LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 193. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY REINFORCEMENT LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 194. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY REINFORCEMENT LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 195. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY REINFORCEMENT LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 196. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY REINFORCEMENT LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 197. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY REINFORCEMENT LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 198. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY REINFORCEMENT LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 199. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SUPERVISED LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 200. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SUPERVISED LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 201. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SUPERVISED LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 202. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SUPERVISED LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 203. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SUPERVISED LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 204. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SUPERVISED LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 205. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY UNSUPERVISED LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 206. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY UNSUPERVISED LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 207. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY UNSUPERVISED LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 208. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY UNSUPERVISED LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 209. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY UNSUPERVISED LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 210. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY UNSUPERVISED LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 211. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2024 (USD MILLION)
  • TABLE 212. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2025-2032 (USD MILLION)
  • TABLE 213. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 214. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 215. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 216. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 217. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 218. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 219. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CHATBOTS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 220. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CHATBOTS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 221. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CHATBOTS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 222. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CHATBOTS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 223. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CHATBOTS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 224. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CHATBOTS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 225. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SPEECH RECOGNITION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 226. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SPEECH RECOGNITION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 227. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SPEECH RECOGNITION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 228. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SPEECH RECOGNITION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 229. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SPEECH RECOGNITION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 230. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY SPEECH RECOGNITION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 231. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VOICE ASSISTANTS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 232. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VOICE ASSISTANTS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 233. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VOICE ASSISTANTS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 234. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VOICE ASSISTANTS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 235. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VOICE ASSISTANTS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 236. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY VOICE ASSISTANTS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 237. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPONENT, 2018-2024 (USD MILLION)
  • TABLE 238. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY COMPONENT, 2025-2032 (USD MILLION)
  • TABLE 239. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY HARDWARE, 2018-2024 (USD MILLION)
  • TABLE 240. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY HARDWARE, 2025-2032 (USD MILLION)
  • TABLE 241. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY HARDWARE, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 242. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY HARDWARE, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 243. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY HARDWARE, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 244. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY HARDWARE, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 245. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY HARDWARE, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 246. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY HARDWARE, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 247. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONNECTIVITY MODULES, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 248. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONNECTIVITY MODULES, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 249. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONNECTIVITY MODULES, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 250. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONNECTIVITY MODULES, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 251. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONNECTIVITY MODULES, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 252. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY CONNECTIVITY MODULES, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 253. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PROCESSORS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 254. GLOBAL ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SIZE, BY PROCESSORS, BY REGION, 2025-2032 (USD MILLION)

TABLE 255.