운송용 AI 시장 : 예측(2024-2029년)

The AI in transportation market is expected to grow at a CAGR of 11.80%, reaching a market size of US$6.196 billion in 2029 from US$3.797 billion in 2024.

AI technology and algorithms are being integrated into as many areas of transportation systems as possible in a bid to increase efficiency, safety, and sustainability. The key to developing and deploying the autonomous car is using AI to traverse safe environments and detect surroundings using computer vision, sensor fusion, machine learning, and deep learning to analyze complicated traffic in real-time.

Other AI application areas in traffic management include sensors, cameras, and other forms of data monitoring and optimizing traffic flow in cities and highways. AI technologies have ensured safety and security within transportation systems by detecting and managing risks such as accidents and other security-related issues. Computer vision systems analyze traffic and airports, and machine learning models compile the analysis for further application. AI-based optimization algorithms further improve traffic flow by decreasing emissions, reducing congestion, and promoting alternative fuels and modes.

AI in transportation market drivers

• Rising Mobility-as-a-Service (MaaS) is contributing to AI in the transportation market growth

MaaS was developed to provide transport services in one platform and a unified solution that can create leverage for AI adoption. In MaaS systems, AI algorithms are applied to optimize routes, predict demand, and thus provide individual travel experiences. Of the various products in the market, the Hitachi Predictive Maintenance for Fleet Operations powered by Google Cloud brings together IoT data, RCM methodologies, and AI technology that optimize fleet maintenance efficiency and asset dependability. This is done through augmented reality, machine learning algorithms, and external data, allowing for real-time inspections and repairs of mission-critical fleet assets.

Overall, the advent of Mobility-as-a-Service is what boosts AI technologies in the transportation market, opening doors for commuting and travel to more efficient, convenient, and sustainable mobility solutions.

AI in transportation market geographical outlook

• North America is witnessing exponential growth during the forecast period

North American transportation firms, government organizations, and communities were among the first to employ AI technology to improve transportation networks' efficiency, safety, and sustainability. This early adoption has driven the area to the top of AI in the transportation industry.

Overall, North America's leadership in AI technology, together with its supporting ecosystem, strong industrial presence, and early adoption of AI in transportation, establishes it as a prominent participant in the worldwide market.

Reasons for buying this report:-

• Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
• Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
• Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
• Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
• Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

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Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

• Historical data & forecasts from 2022 to 2029
• Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
• Competitive Positioning, Strategies, and Market Share Analysis
• Revenue Growth and Forecast Assessment of segments and regions including countries
• Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

The AI in transportation market is segmented and analyzed as follows:

By Technology

• Deep Learning
• Natural learning process
• Machine Learning
• Others

By Deployment

• Cloud
• On-Premise

By Application

• Route optimization
• Shipping volume prediction
• Predictive Fleet Maintenance
• Real-time Vehicle tracking
• Others

By Geography

• North America
• USA
• Canada
• Mexico
• South America
• Brazil
• Argentina
• Others
• Europe
• Germany
• France
• UK
• Spain
• Others
• Middle East and Africa
• Saudi Arabia
• UAE
• Israel
• Others
• Asia Pacific
• China
• Japan
• India
• South Korea
• Indonesia
• Taiwan
• Others

TABLE OF CONTENTS

1. INTRODUCTION

• 1.1. Market Overview
• 1.2. Market Definition
• 1.3. Scope of the Study
• 1.4. Market Segmentation
• 1.5. Currency
• 1.6. Assumptions
• 1.7. Base and Forecast Years Timeline
• 1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY

• 2.1. Research Design
• 2.2. Research Processes

3. EXECUTIVE SUMMARY

• 3.1. Key Findings
• 3.2. CXO Perspective

4. MARKET DYNAMICS

• 4.1. Market Drivers
• 4.2. Market Restraints
• 4.3. Porter's Five Forces Analysis
  • 4.3.1. Bargaining Power of Suppliers
  • 4.3.2. Bargaining Power of Buyers
  • 4.3.3. Threat of New Entrants
  • 4.3.4. Threat of Substitutes
  • 4.3.5. Competitive Rivalry in the Industry
• 4.4. Industry Value Chain Analysis
• 4.5. Analyst View

5. AI IN TRANSPORTATION MARKET BY TECHNOLOGY

• 5.1. Introduction
• 5.2. Deep Learning
• 5.3. Natural learning process
• 5.4. Machine Learning
• 5.5. Others

6. AI IN TRANSPORTATION MARKET BY DEPLOYMENT

• 6.1. Introduction
• 6.2. Cloud
• 6.3. On-Premise

7. AI IN TRANSPORTATION MARKET BY APPLICATION

• 7.1. Introduction
• 7.2. Route optimization
• 7.3. Shipping volume prediction
• 7.4. Predictive Fleet Maintenance
• 7.5. Real-time Vehicle tracking
• 7.6. Others

8. AI IN TRANSPORTATION MARKET BY GEOGRAPHY

• 8.1. Introduction
• 8.2. North America
  • 8.2.1. By Technology
  • 8.2.2. By Deployment
  • 8.2.3. By Application
  • 8.2.4. By Country
    • 8.2.4.1. USA
    • 8.2.4.2. Canada
    • 8.2.4.3. Mexico
• 8.3. South America
  • 8.3.1. By Technology
  • 8.3.2. By Deployment
  • 8.3.3. By Application
  • 8.3.4. By Country
    • 8.3.4.1. Brazil
    • 8.3.4.2. Argentina
    • 8.3.4.3. Others
• 8.4. Europe
  • 8.4.1. By Technology
  • 8.4.2. By Deployment
  • 8.4.3. By Application
  • 8.4.4. By Country
    • 8.4.4.1. Germany
    • 8.4.4.2. France
    • 8.4.4.3. UK
    • 8.4.4.4. Spain
    • 8.4.4.5. Others
• 8.5. Middle East and Africa
  • 8.5.1. By Technology
  • 8.5.2. By Deployment
  • 8.5.3. By Application
  • 8.5.4. By Country
    • 8.5.4.1. Saudi Arabia
    • 8.5.4.2. UAE
    • 8.5.4.3. Israel
    • 8.5.4.4. Others
• 8.6. Asia Pacific
  • 8.6.1. By Technology
  • 8.6.2. By Deployment
  • 8.6.3. By Application
  • 8.6.4. By Country
    • 8.6.4.1. China
    • 8.6.4.2. Japan
    • 8.6.4.3. India
    • 8.6.4.4. South Korea
    • 8.6.4.5. Indonesia
    • 8.6.4.6. Taiwan
    • 8.6.4.7. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

• 9.1. Major Players and Strategy Analysis
• 9.2. Market Share Analysis
• 9.3. Mergers, Acquisitions, Agreements, and Collaborations
• 9.4. Competitive Dashboard

10. COMPANY PROFILES

• 10.1. Hitachi
• 10.2. Wialon (Gurtam)
• 10.3. AltexSoft
• 10.4. Planung Transport Verkehr GmbH
• 10.5. Integrated Roadways
• 10.6. Maticz
• 10.7. FlowSpace
• 10.8. Axestrack