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市場調查報告書
商品編碼
1861535

交通運輸領域人工智慧市場：按應用、技術、組件、模式、部署類型和最終用戶分類－全球預測（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個工作天內

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預計到 2032 年，交通運輸領域的人工智慧市場規模將達到 73.5 億美元，複合年成長率為 14.26%。

主要市場統計數據
基準年 2024 25.2億美元
預計年份：2025年 28.8億美元
預測年份：2032年 73.5億美元
複合年成長率 (%) 14.26%

下一代出行策略目標和營運藍圖圖為人工智慧主導的交通轉型奠定了基礎。

本執行摘要旨在為全面分析人工智慧在運輸系統中的應用奠定客觀框架和範圍。其目的是為企業高管、政策制定者和技術領導者提供一份簡明扼要的綜合報告，闡述重塑出行方式的驅動力、決定競爭優勢的營運槓桿以及影響近期採購和部署決策的政策變數。本研究重點關注具有商業性價值的應用領域，包括自動駕駛、駕駛輔助、資產和車輛最佳化以及基礎設施智慧，並專注於分析技術能力、整合複雜性以及對相關人員的影響。

識別將重塑出行生態系統的變革性技術和商業變革；建構具有韌性的交通運輸法規結構和相關人員價值鏈

交通運輸領域正經歷快速的重組，這主要得益於運算能力的整合、感測器技術的日益成熟以及商業模式的不斷演進。感知技術堆疊、模型架構和邊緣運算的進步，使得曾經被視為實驗性技術的實際應用成為可能，從而將差異化競爭的焦點從單一功能的性能轉移到系統級的整合和生命週期管理。這使得那些能夠將強大的資料管道、嚴謹的檢驗流程以及緊密耦合的軟硬體協同設計相結合的企業，能夠將技術驗證轉化為可靠的服務。

評估美國2025年宣布的關稅調整對供應鏈採購和跨境流動策略的累積影響

美國政策制定者於2025年推出的關稅政策標誌著交通運輸人工智慧生態系統供應鏈設計、籌資策略和商業合約的轉捩點。其直接的營運影響是採購風險增加，迫使採購機構重新評估關鍵硬體（例如處理器、專用感測器和連接模組）的採購來源。為應對這項挑戰，供應商正在實現製造地多元化，重新評估合約條款，並加快對替代供應商的資格認證，以維持生產的連續性。

解讀細分市場主導的機遇，並指導從應用技術組件模式部署和最終用戶觀點的定向投資。

分析揭示了技術和應用交叉融合的領域，這些領域共同創造了差異化的價值提案和規模化路徑。按應用領域分類，市場涵蓋自動駕駛汽車、駕駛輔助系統、車隊管理、預測性維護和交通管理。自動駕駛汽車分為L4級和L5級部署，每個等級都有其自身的檢驗、地圖繪製和監管要求。駕駛輔助系統包括主動車距控制巡航系統、自動緊急煞車、盲點偵測和車道維持輔助等功能，安全性和使用者感知度的逐步提升決定了其普及程度。車隊管理涵蓋資產追蹤、駕駛員監控和路線最佳化，並設有與運作和利用率相關的明確營運KPI。預測性維護側重於狀態監控和故障診斷，從而實現基於狀態的服務交付並減少非計劃性停機時間。交通管理涵蓋擁塞預測、路口管理和號誌控制，將城市級數據轉化為通行能力和排放的改善。

區域戰略展望：重點分析美洲、歐洲、中東和非洲以及亞太地區的細微差別，以協助制定針對特定區域的打入市場策略。

區域趨勢將在塑造交通人工智慧價值鏈的普及速度和商業夥伴關係結構方面發揮重要作用。美洲已形成創新叢集，將深厚的軟體專業知識與成熟的汽車製造能力相結合，為連接車隊營運商和軟體整合商的端到端試點項目提供了沃土，從而展示如何降低總體擁有成本 (TCO) 並提高安全性。該地區成熟的創投和資本市場正在加速顛覆性解決方案的商業化，而州和地方政府的採購試點計畫則為擴大交通管理和車隊最佳化舉措提供了試驗平台。

競爭與企業資料分析，重點關注領先的交通運輸和人工智慧參與企業的策略趨勢、合作夥伴生態系統和創新重點。

在交通運輸人工智慧領域，競爭格局將更取決於夥伴關係、平台策略和差異化的系統整合能力，而非任何單一產品的優勢。硬體、軟體和服務領域的領導參與企業正在推行混合策略，將專有技術堆疊與開放介面結合，以加速客戶採用。這種混合方法能夠快速整合到現有車輛架構中，並支援功能增量交付，同時保留了隨著時間推移深入掌握平台技術的潛力。晶片組供應商、感測器製造商和演算法供應商之間的策略聯盟十分普遍，將長期支援和模型重訓練服務納入客戶合約的商業性安排也十分常見。

為工業領導者提供切實可行的、優先考慮的行動方案，以加速人工智慧的應用，降低供應鏈風險，並在行動旅行領域釋放營運和客戶價值。

為了將策略洞察轉化為營運優勢，領導者必須制定清晰且優先的行動計劃，以應對技術準備、商業性契合度和供應鏈韌性等問題。車隊營運商應先制定分階段的試點計劃，明確高價值的應用場景，例如降低營運成本和顯著提高運轉率，並確保合約條款能夠抵禦零件供應中斷的影響。同時，原始設備製造商 (OEM) 應優先考慮模組化架構和標準介面，以實現硬體替換並縮短整合前置作業時間，從而在關稅和不斷變化的採購環境中保持長期的靈活性。

一套嚴謹的調查方法，清楚闡述了資料來源、分析架構和檢驗過程管治措施，從而為研究結論提供了支持。

本執行摘要的分析融合了定性和定量方法，以確保研究結果是基於證據且具有可操作性。主要研究包括對高階主管、採購人員、工程經理和城市負責人進行結構化訪談，並輔以代表性認知和規劃方案的技術評估。次要研究包括對同儕審查文獻、監管文件、標準文件和供應商技術簡報進行系統性回顧，以闡明主要研究結果並檢驗技術論點。

將人工智慧洞察、建議和策略重點整合到交通運輸領域，以支援經營團隊決策和跨職能協作。

總之，人工智慧正在重塑交通運輸產業，從感測器到服務，沒有例外。那些將人工智慧視為系統整合挑戰而非單一解決方案的組織將從中獲益最多。成功需要工程、採購、法規事務和商務部門之間嚴謹的跨職能協作，以及嚴格的檢驗和穩健的風險管理實務。不同的法規環境和收費系統凸顯了分散式供應鏈和模組化設計的重要性，而基礎設施和政策的區域差異則需要專門的打入市場策略。

目錄

第1章：序言

第2章調查方法

第3章執行摘要

第4章 市場概覽

第5章 市場洞察

  • 利用電腦視覺和人工智慧技術最佳化城市交通網路中的即時交通號誌控制
  • 提出了一種用於複雜道路環境下自適應自主車輛導航的強化學習演算法
  • 透過為電動公車車隊整合基於人工智慧的預測性維護平台，減少營運中斷
  • 在交通應用程式中引入自然語言處理聊天機器人，用於乘客互動和即時出行協助。
  • 利用人工智慧驅動的多模態通路規劃系統最佳化首端物流效率
  • 應用機器學習分析車輛感測器數據，建立由駕駛行為驅動的動態保險定價模型
  • 面向下一代交通基礎設施的低延遲V2X（車聯網）通訊的邊緣人工智慧架構開發
  • 將人工智慧驅動的無人機配送協調系統與地面運輸結合，以提高都市區最後一公里物流的效率

第6章美國關稅的累積影響，2025年

第7章 人工智慧的累積影響，2025年

第8章 交通運輸領域人工智慧市場應用

  • 自動駕駛汽車
    • 4級
    • 5級
  • 駕駛輔助系統
    • 主動車距控制巡航系統
    • 自動緊急制動
    • 盲點偵測系統
    • 車道維持輔助系統
  • 車隊管理
    • 資產追蹤
    • 駕駛員監控
    • 路線最佳化
  • 預測性維護
    • 狀態監測
    • 故障診斷
  • 交通管理
    • 交通堵塞預測
    • 交叉路口管理
    • 訊號控制

9. 交通運輸領域的人工智慧市場（依技術分類）

  • 電腦視覺
    • 影像識別
    • 目標偵測
    • 影像分析
  • 深度學習
    • 卷積類神經網路
    • 生成對抗網路
    • 遞迴神經網
  • 機器學習
    • 強化學習
    • 監督式學習
    • 無監督學習
  • 自然語言處理
    • 聊天機器人
    • 語音辨識
    • 語音助理

第10章 交通運輸領域的人工智慧市場（按組件分類）

  • 硬體
    • 連接模組
    • 處理器
    • 感應器
  • 服務
    • 諮詢
    • 一體化
    • 支援
  • 軟體
    • 演算法
    • 中介軟體
    • 平台

第11章 依交通方式分類的交通運輸領域人工智慧市場

  • 空氣
  • 海路
  • 鐵路
  • 路

第12章 交通運輸領域人工智慧市場（依部署方式分類）

  • 雲
    • 私有雲端
    • 公共雲端
  • 混合
  • 本地部署

第13章 交通運輸領域人工智慧市場（依最終用戶分類）

  • 車隊營運商
    • 物流公司
    • 叫車公司
  • 基礎設施營運商
    • 市政府
    • 道路營運商
  • OEM
    • 商用車製造商
    • 乘用車製造商
  • 乘客
    • 個人用戶
    • 遊客

第14章 各地區交通運輸業的人工智慧市場

  • 美洲
    • 北美洲
    • 拉丁美洲
  • 歐洲、中東和非洲
    • 歐洲
    • 中東
    • 非洲
  • 亞太地區

第15章 交通運輸領域人工智慧市場（以群體分類）

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

第16章 各國交通運輸領域的人工智慧市場

  • 美國
  • 加拿大
  • 墨西哥
  • 巴西
  • 英國
  • 德國
  • 法國
  • 俄羅斯
  • 義大利
  • 西班牙
  • 中國
  • 印度
  • 日本
  • 澳洲
  • 韓國

第17章 競爭格局

  • 2024年市佔率分析
  • FPNV定位矩陣，2024
  • 競爭分析
    • 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.