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市場調查報告書
商品編碼
2092991

本地行動智慧市場預測至2034年－按解決方案、部署模式、技術、最終用戶和區域分類的全球分析

Local Mobility Intelligence Market Forecasts to 2034 - Global Analysis By Solution, Deployment Mode, Technology, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球本地行動智慧市場規模將達到 45 億美元，並在預測期內以 24.0% 的複合年成長率成長，到 2034 年將達到 252 億美元。

本地出行智慧是指收集、分析和利用數據驅動的信息，以最佳化特定地理區域（例如社區、街區和市政邊界）內的交通和出行模式。這些系統包括交通分析平台、車輛管理智慧解決方案、公共交通分析、停車智慧系統、路線最佳化工具、出行資料平台和預測性出行分析。本地出行智慧利用人工智慧、電腦視覺、物聯網感測器和地理空間分析技術來監控交通流量、預測擁塞情況、最佳化公共交通時刻表並管理停車資源。這項技術使交通管理部門、市政當局和車輛營運商能夠提高城市出行效率，同時減少排放氣體並改善通勤者的出行體驗。

都市區堵塞危機

全球都市區交通擁擠日益嚴重，推動了對本地智慧交通管理解決方案的迫切需求。低效率的交通流和不合理的交通協調每年給城市造成數十億美元的生產力損失和燃油成本增加。本地交通智慧平台能夠即時呈現交通模式，進而實現號誌控制和路線引導的動態最佳化。多模態交通數據的整合提供了全面的交通狀況整體情況，有助於基礎設施投資決策。數據驅動的交通管理方法和交通方式轉換的推廣對於滿足旨在減少排放的環境法規至關重要。

數據孤島

由於交通運營商、私人企業和基礎設施管理者之間資料所有權分散，本地出行智慧的實施面臨許多挑戰。交通數據、公共交通時刻表、停車位資訊和共乘資訊通常儲存在格式和存取協議不相容的不同系統中。隱私法規限制了公共和私營部門相關人員之間共用個人出行資料。將傳統交通管理系統與現代分析平台整合的技術複雜性常常延緩實施進程。這種資料孤島限制了從本地出行智慧中獲得的洞察的整體性和準確性。

聯網汽車整合

聯網汽車自動駕駛車輛的普及為區域交通智慧平台提供了前所未有的機遇，使其能夠以前所未有的規模獲取即時交通和出行數據。車輛與基礎設施之間的通訊實現了車輛與交通管理系統之間的直接資料交換。來自聯網汽車的資料流能夠提供關於路況、事故地點和行程時間變化等方面的精細資訊。將自動駕駛車隊與區域交通智慧平台整合，可調整路線規劃並最佳化整個網路的交通流量分配。這些功能透過數據貨幣化和服務訂閱，為交通智慧提供者創造了新的收入來源。

對隱私和監控的擔憂

本地出行情報所需的大規模資料收集引發了人們對個人行蹤和出行模式追蹤的嚴重隱私擔憂。公民自由組織反對在公共場所部署基於攝影機的交通監控系統和車牌識別系統。出行資料使用的法律規範仍在不斷發展，且在不同司法管轄區之間存在差異。公眾對被視為監控基礎設施的強烈反對可能導致出行情報項目延期或取消。這些隱私方面的顧慮為平台提供者和正在考慮實施相關項目的市政當局帶來了營運上的不確定性。

新型冠狀病毒（COVID-19）的影響：

新冠疫情大幅改變了城市出行模式，遠距辦公的興起導致尖峰時段交通量減少，大眾運輸客流量也急劇下降。本地出行智慧平台已做出相應調整，以監測與疫情相關的交通變化，並協助引導緊急車輛。疫情期間，城市利用出行資料實施動態道路封閉及擴大步行區。疫情後，混合辦公模式的普及使交通模式更加不穩定，因此需要自適應智慧系統。此次危機加速了對靈活、數據驅動的出行管理能力的投資。

在預測期內，流量分析平台細分市場預計將佔據最大的市場佔有率。

預計在預測期內，交通分析平台細分市場將佔據最大的市場佔有率，因為它在監測和最佳化城市道路網路的車流方面發揮著至關重要的作用。交通分析平台處理來自攝影機、感測器和聯網汽車的數據，產生即時擁塞地圖和事故偵測警報。市政交通部門利用這些平台在緊急應變下最佳化交通號誌配時和路線規劃。預測分析的整合使相關部門能夠在交通瓶頸實際發生之前進行預測。企業級交通分析解決方案提供可擴展的架構，能夠服務從小規模市政機構到大都會圈等各種規模的客戶。

在預測期內，基於雲端的細分市場預計將呈現最高的複合年成長率。

在預測期內，基於雲端的細分市場預計將呈現最高的成長率，這主要得益於雲端架構在處理海量出行資料方面的擴充性和成本效益。雲端平台使交通管理部門無需維護昂貴的本地資料中心即可獲得高級分析功能。雲端基礎設施的彈性運算資源還可以應對特殊事件或緊急情況下交通數據的激增。基於雲端的出行智慧有助於共用轄區以及公共和私營部門相關人員之間的資料共用。軟體即服務 (SaaS)定價模式降低了預算緊張的地方政府交通部門的資本投資門檻。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其在美國各地廣泛部署的智慧型運輸系統(ITS) 和先進的交通管理基礎設施。美國在產業中處於領先地位，聯邦政府資助的計畫支持智慧交通舉措和聯網汽車先導計畫。包括Google、IBM 和思科在內的領先科技公司提供全面的出行智慧解決方案。北美各地的市政當局已在交通感測器網路和集中式交通管理中心方面投入大量資金。該地區成熟的汽車和技術生態系統正在加速出行數據分析領域的創新。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於中國、印度和東南亞國家快速的都市化和大規模智慧城市投資。中國的國家智慧交通舉措正在部署覆蓋全城的出行智慧系統，服務數百萬通勤者。印度的城市轉型計畫優先考慮在快速發展的大都會圈實施智慧交通管理。該地區不斷擴展的地鐵和快速公車（BRT）網路正在催生對綜合出行分析的需求。政府關於排放氣體和交通堵塞管理的法規正在推動區域出行智慧平台的持續部署。

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    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球本地行動智慧市場：按解決方案分類

  • 流量分析平台
  • 艦隊智慧解決方案
  • 大眾運輸分析
  • 停車智慧系統
  • 路線最佳化解決方案
  • 行動數據平台
  • 預測性移動性分析

第6章：全球本地行動智慧市場：依部署模式分類

  • 基於雲端的
  • 現場
  • 混合

第7章：全球本地行動智慧市場：依技術分類

  • 人工智慧
  • 物聯網 (IoT)
  • 電腦視覺
  • 巨量資料分析
  • 雲端運算
  • 地理資訊系統和位置智慧

第8章：全球本地行動智慧市場：依最終用戶分類

  • 交通管理局
  • 地方政府
  • 物流和車輛營運公司
  • 大眾運輸
  • 智慧城市管理機構
  • 機場和港口營運商

第9章：全球本地行動智慧市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第10章 戰略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第11章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第12章：公司簡介

  • TomTom NV
  • PTV Group
  • Siemens Mobility
  • Kapsch TrafficCom AG
  • Cisco Systems, Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • Intel Corporation
  • Cubic Corporation
  • Hitachi Rail
  • Thales Group
  • Hexagon AB
  • Trimble Inc.
  • Iteris, Inc.
  • Swarco AG
  • Verra Mobility Corporation
Product Code: SMRC38160

According to Stratistics MRC, the Global Local Mobility Intelligence Market is accounted for $4.5 billion in 2026 and is expected to reach $25.2 billion by 2034 growing at a CAGR of 24.0% during the forecast period. Local mobility intelligence refers to the collection, analysis, and application of data-driven insights to optimize transportation and movement patterns within defined geographic areas such as neighborhoods, districts, and municipal boundaries. These systems encompass traffic analytics platforms, fleet intelligence solutions, public transport analytics, parking intelligence systems, route optimization tools, mobility data platforms, and predictive mobility analytics. Local mobility intelligence leverages artificial intelligence, computer vision, Internet of Things sensors, and geospatial analytics to monitor traffic flows, predict congestion, optimize public transit schedules, and manage parking resources. The technology enables transportation authorities, municipal governments, and fleet operators to improve urban mobility efficiency while reducing emissions and enhancing commuter experiences.

Market Dynamics:

Driver:

Urban congestion crisis

Escalating traffic congestion in urban centers worldwide is creating urgent demand for intelligent mobility management solutions at the local level. Cities lose billions of dollars annually in productivity and fuel costs due to inefficient traffic flows and inadequate transportation coordination. Local mobility intelligence platforms provide real-time visibility into traffic patterns and enable dynamic signal optimization and route guidance. The integration of multimodal transportation data creates comprehensive mobility pictures that inform infrastructure investment decisions. Environmental mandates for emission reduction require data-driven approaches to traffic management and modal shift encouragement.

Restraint:

Data silo fragmentation

Local mobility intelligence deployment faces significant challenges from fragmented data ownership across transportation agencies, private operators, and infrastructure managers. Traffic data, transit schedules, parking availability, and ride-sharing information typically reside in separate systems with incompatible formats and access protocols. Privacy regulations restrict the sharing of individual movement data between public and private sector stakeholders. The technical complexity of integrating legacy transportation management systems with modern analytics platforms often leads to implementation delays. These data silos limit the comprehensiveness and accuracy of local mobility intelligence insights.

Opportunity:

Connected vehicle integration

The proliferation of connected and autonomous vehicles presents transformative opportunities for local mobility intelligence platforms to access unprecedented volumes of real-time traffic and movement data. Vehicle-to-infrastructure communication enables direct data exchange between automobiles and traffic management systems. Connected vehicle data streams provide granular insights into road conditions, incident locations, and travel time variability. The integration of autonomous vehicle fleets with local mobility platforms enables coordinated routing, optimizing network-wide traffic distribution. These capabilities create new revenue streams for mobility intelligence providers through data monetization and service subscriptions.

Threat:

Privacy surveillance concerns

The extensive data collection required for local mobility intelligence raises significant privacy concerns regarding the tracking of individual movements and travel patterns. Civil liberties organizations challenge the deployment of camera-based traffic monitoring and license plate recognition systems in public spaces. Regulatory frameworks for mobility data usage remain evolving and inconsistent across jurisdictions. Public backlash against perceived surveillance infrastructure can delay or cancel mobility intelligence projects. These privacy tensions create operational uncertainty for platform providers and municipal adopters.

Covid-19 Impact:

The COVID-19 pandemic dramatically altered urban mobility patterns, with remote work reducing peak-hour traffic volumes and public transit ridership plummeting. Local mobility intelligence platforms are adapted to monitor pandemic-related transportation changes and support emergency vehicle routing. Mid-pandemic, cities used mobility data to implement dynamic street closures and expanded pedestrian zones. Post-pandemic, hybrid work models have created more variable traffic patterns that require adaptive intelligence systems. The crisis accelerated investment in flexible, data-driven mobility management capabilities.

The traffic analytics platforms segment is expected to be the largest during the forecast period

The traffic analytics platforms segment is expected to account for the largest market share during the forecast period, due to its foundational role in monitoring and optimizing vehicular flows across urban road networks. Traffic analytics platforms process data from cameras, sensors, and connected vehicles to generate real-time congestion maps and incident detection alerts. Municipal transportation departments rely on these platforms for signal timing optimization and emergency response routing. The integration of predictive analytics enables authorities to anticipate traffic bottlenecks before they materialize. Enterprise-grade traffic analytics solutions offer scalable architectures that serve both small municipalities and large metropolitan regions.

The cloud-based segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud-based segment is predicted to witness the highest growth rate, driven by the computational scalability and cost efficiency of cloud architectures for processing massive mobility data volumes. Cloud platforms enable transportation authorities to access advanced analytics capabilities without maintaining expensive on-premises data centers. The elastic computing resources of cloud infrastructure accommodate traffic data spikes during special events and emergency conditions. Cloud-based mobility intelligence facilitates data sharing across jurisdictional boundaries and between public and private stakeholders. Software-as-a-service pricing models reduce capital expenditure barriers for budget-constrained municipal transportation departments.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to extensive intelligent transportation system deployments and advanced traffic management infrastructure across the United States. The United States leads with federal funding programs supporting smart transportation initiatives and connected vehicle pilot projects. Major technology companies, including Google, IBM, and Cisco, offer comprehensive mobility intelligence solutions. Municipalities across North America have invested significantly in traffic sensor networks and centralized traffic management centers. The region's mature automotive and technology ecosystems accelerate innovation in mobility data analytics.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, due to rapid urbanization and massive smart city investments across China, India, and Southeast Asian nations. China's national smart transportation initiatives deploy city-scale mobility intelligence systems serving millions of commuters. India's urban transformation programs prioritize intelligent traffic management for rapidly growing metropolitan areas. The region's expanding metro rail networks and bus rapid transit systems generate demand for integrated mobility analytics. Government mandates for emission reduction and traffic congestion management drive sustained procurement of local mobility intelligence platforms.

Key players in the market

Some of the key players in Local Mobility Intelligence Market include TomTom N.V., PTV Group, Siemens Mobility, Kapsch TrafficCom AG, Cisco Systems, Inc., IBM Corporation, Microsoft Corporation, Google LLC, Intel Corporation, Cubic Corporation, Hitachi Rail, Thales Group, Hexagon AB, Trimble Inc., Iteris, Inc., Swarco AG, and Verra Mobility Corporation.

Key Developments:

In June 2026, TomTom N.V. launched a real-time local mobility intelligence platform integrating traffic analytics with predictive congestion modeling for European metropolitan areas.

In May 2026, Siemens Mobility expanded its intelligent traffic management portfolio to include AI-powered adaptive signal control systems for neighborhood-level traffic optimization.

In April 2026, Google LLC introduced enhanced local mobility APIs enabling third-party developers to build applications using real-time traffic and transit data.

Solutions Covered:

  • Traffic Analytics Platforms
  • Fleet Intelligence Solutions
  • Public Transport Analytics
  • Parking Intelligence Systems
  • Route Optimization Solutions
  • Mobility Data Platforms
  • Predictive Mobility Analytics

Deployment Modes Covered:

  • Cloud-based
  • On-premises
  • Hybrid

Technologies Covered:

  • Artificial Intelligence
  • Internet of Things (IoT)
  • Computer Vision
  • Big Data Analytics
  • Cloud Computing
  • GIS & Location Intelligence

End Users Covered:

  • Transportation Authorities
  • Municipal Governments
  • Logistics & Fleet Operators
  • Public Transit Agencies
  • Smart City Authorities
  • Airport & Port Operators

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global Local Mobility Intelligence Market, By Solution

  • 5.1 Traffic Analytics Platforms
  • 5.2 Fleet Intelligence Solutions
  • 5.3 Public Transport Analytics
  • 5.4 Parking Intelligence Systems
  • 5.5 Route Optimization Solutions
  • 5.6 Mobility Data Platforms
  • 5.7 Predictive Mobility Analytics

6 Global Local Mobility Intelligence Market, By Deployment Mode

  • 6.1 Cloud-based
  • 6.2 On-premises
  • 6.3 Hybrid

7 Global Local Mobility Intelligence Market, By Technology

  • 7.1 Artificial Intelligence
  • 7.2 Internet of Things (IoT)
  • 7.3 Computer Vision
  • 7.4 Big Data Analytics
  • 7.5 Cloud Computing
  • 7.6 GIS & Location Intelligence

8 Global Local Mobility Intelligence Market, By End User

  • 8.1 Transportation Authorities
  • 8.2 Municipal Governments
  • 8.3 Logistics & Fleet Operators
  • 8.4 Public Transit Agencies
  • 8.5 Smart City Authorities
  • 8.6 Airport & Port Operators

9 Global Local Mobility Intelligence Market, By Geography

  • 9.1 North America
    • 9.1.1 United States
    • 9.1.2 Canada
    • 9.1.3 Mexico
  • 9.2 Europe
    • 9.2.1 United Kingdom
    • 9.2.2 Germany
    • 9.2.3 France
    • 9.2.4 Italy
    • 9.2.5 Spain
    • 9.2.6 Netherlands
    • 9.2.7 Belgium
    • 9.2.8 Sweden
    • 9.2.9 Switzerland
    • 9.2.10 Poland
    • 9.2.11 Rest of Europe
  • 9.3 Asia Pacific
    • 9.3.1 China
    • 9.3.2 Japan
    • 9.3.3 India
    • 9.3.4 South Korea
    • 9.3.5 Australia
    • 9.3.6 Indonesia
    • 9.3.7 Thailand
    • 9.3.8 Malaysia
    • 9.3.9 Singapore
    • 9.3.10 Vietnam
    • 9.3.11 Rest of Asia Pacific
  • 9.4 South America
    • 9.4.1 Brazil
    • 9.4.2 Argentina
    • 9.4.3 Colombia
    • 9.4.4 Chile
    • 9.4.5 Peru
    • 9.4.6 Rest of South America
  • 9.5 Rest of the World (RoW)
    • 9.5.1 Middle East
      • 9.5.1.1 Saudi Arabia
      • 9.5.1.2 United Arab Emirates
      • 9.5.1.3 Qatar
      • 9.5.1.4 Israel
      • 9.5.1.5 Rest of Middle East
    • 9.5.2 Africa
      • 9.5.2.1 South Africa
      • 9.5.2.2 Egypt
      • 9.5.2.3 Morocco
      • 9.5.2.4 Rest of Africa

10 Strategic Market Intelligence

  • 10.1 Industry Value Network and Supply Chain Assessment
  • 10.2 White-Space and Opportunity Mapping
  • 10.3 Product Evolution and Market Life Cycle Analysis
  • 10.4 Channel, Distributor, and Go-to-Market Assessment

11 Industry Developments and Strategic Initiatives

  • 11.1 Mergers and Acquisitions
  • 11.2 Partnerships, Alliances, and Joint Ventures
  • 11.3 New Product Launches and Certifications
  • 11.4 Capacity Expansion and Investments
  • 11.5 Other Strategic Initiatives

12 Company Profiles

  • 12.1 TomTom N.V.
  • 12.2 PTV Group
  • 12.3 Siemens Mobility
  • 12.4 Kapsch TrafficCom AG
  • 12.5 Cisco Systems, Inc.
  • 12.6 IBM Corporation
  • 12.7 Microsoft Corporation
  • 12.8 Google LLC
  • 12.9 Intel Corporation
  • 12.10 Cubic Corporation
  • 12.11 Hitachi Rail
  • 12.12 Thales Group
  • 12.13 Hexagon AB
  • 12.14 Trimble Inc.
  • 12.15 Iteris, Inc.
  • 12.16 Swarco AG
  • 12.17 Verra Mobility Corporation

List of Tables

  • Table 1 Global Local Mobility Intelligence Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global Local Mobility Intelligence Market Outlook, By Solution (2023-2034) ($MN)
  • Table 3 Global Local Mobility Intelligence Market Outlook, By Traffic Analytics Platforms (2023-2034) ($MN)
  • Table 4 Global Local Mobility Intelligence Market Outlook, By Fleet Intelligence Solutions (2023-2034) ($MN)
  • Table 5 Global Local Mobility Intelligence Market Outlook, By Public Transport Analytics (2023-2034) ($MN)
  • Table 6 Global Local Mobility Intelligence Market Outlook, By Parking Intelligence Systems (2023-2034) ($MN)
  • Table 7 Global Local Mobility Intelligence Market Outlook, By Route Optimization Solutions (2023-2034) ($MN)
  • Table 8 Global Local Mobility Intelligence Market Outlook, By Mobility Data Platforms (2023-2034) ($MN)
  • Table 9 Global Local Mobility Intelligence Market Outlook, By Predictive Mobility Analytics (2023-2034) ($MN)
  • Table 10 Global Local Mobility Intelligence Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 11 Global Local Mobility Intelligence Market Outlook, By Cloud-based (2023-2034) ($MN)
  • Table 12 Global Local Mobility Intelligence Market Outlook, By On-premises (2023-2034) ($MN)
  • Table 13 Global Local Mobility Intelligence Market Outlook, By Hybrid (2023-2034) ($MN)
  • Table 14 Global Local Mobility Intelligence Market Outlook, By Technology (2023-2034) ($MN)
  • Table 15 Global Local Mobility Intelligence Market Outlook, By Artificial Intelligence (2023-2034) ($MN)
  • Table 16 Global Local Mobility Intelligence Market Outlook, By Internet of Things (IoT) (2023-2034) ($MN)
  • Table 17 Global Local Mobility Intelligence Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 18 Global Local Mobility Intelligence Market Outlook, By Big Data Analytics (2023-2034) ($MN)
  • Table 19 Global Local Mobility Intelligence Market Outlook, By Cloud Computing (2023-2034) ($MN)
  • Table 20 Global Local Mobility Intelligence Market Outlook, By GIS & Location Intelligence (2023-2034) ($MN)
  • Table 21 Global Local Mobility Intelligence Market Outlook, By End User (2023-2034) ($MN)
  • Table 22 Global Local Mobility Intelligence Market Outlook, By Transportation Authorities (2023-2034) ($MN)
  • Table 23 Global Local Mobility Intelligence Market Outlook, By Municipal Governments (2023-2034) ($MN)
  • Table 24 Global Local Mobility Intelligence Market Outlook, By Logistics & Fleet Operators (2023-2034) ($MN)
  • Table 25 Global Local Mobility Intelligence Market Outlook, By Public Transit Agencies (2023-2034) ($MN)
  • Table 26 Global Local Mobility Intelligence Market Outlook, By Smart City Authorities (2023-2034) ($MN)
  • Table 27 Global Local Mobility Intelligence Market Outlook, By Airport & Port Operators (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.