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市場調査レポート

輸送における人工知能 (AI) の世界市場 2030年:ディープラーニング・コンピュータービジョン・コンテキストアウェアネス・NLP

Artificial Intelligence in Transportation Market by Machine Learning (Deep Learning, Computer Vision, Context Awareness, NLP), Application (Semi & Full-Autonomous, HMI, Platooning), Offering, Process, and Region - Global Forecast to 2030

発行 MarketsandMarkets 商品コード 580733
出版日 ページ情報 英文 189 Pages
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本日の銀行送金レート: 1USD=109.78円で換算しております。
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輸送における人工知能 (AI) の世界市場 2030年:ディープラーニング・コンピュータービジョン・コンテキストアウェアネス・NLP Artificial Intelligence in Transportation Market by Machine Learning (Deep Learning, Computer Vision, Context Awareness, NLP), Application (Semi & Full-Autonomous, HMI, Platooning), Offering, Process, and Region - Global Forecast to 2030
出版日: 2017年11月15日 ページ情報: 英文 189 Pages
概要

輸送における人工知能 (AI) の市場規模は、2017年の12億1,000万米ドルから2030年までに103億米ドルへ、予測期間中に17.87%のCAGR (年間複合成長率) で拡大すると予測されています。自動運転車およびアダプティブクルーズコントロール (ACC) 、衝突警告、車線逸脱防止支援システム、および先進運転車支援システム (ADAS) といった安全機能の実施に向けた業界統一規格は、輸送におけるAI市場の成長を促進しています。同時に、AIシステムの高コストおよびインフラ開発の不足は、輸送におけるAIの成長を抑制する主な要因となっています。

当レポートでは、輸送における人工知能 (AI) の世界市場について調査し、市場の概要、提供品、マシンラーニング技術、プロセス、用途、および地域別の市場分析と予測、市場成長への各種影響要因の分析、競合情勢、主要企業のプロファイルなど、体系的な情報を提供しています。

FIGURE 15 ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET

第1章 イントロダクション

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 重要考察

  • 輸送における人工知能 (AI) 市場の魅力的な機会
  • 輸送における人工知能 (AI) 市場:地域別
  • 輸送における人工知能 (AI) 市場:提供品別
  • 輸送における人工知能 (AI) 市場:マシンラーニング技術別
  • 輸送における人工知能 (AI) 市場:プロセス別
  • 輸送における人工知能 (AI) 市場:用途別
  • 人工知能 (AI) 向けトラックプラトゥーニング市場:地域別

第5章 市場概要

  • イントロダクション
  • 市場ダイナミクス
    • 促進要因
    • 阻害要因
    • 機会
    • 課題

第6章 技術概要

  • イントロダクション
  • 輸送における人工知能 (AI) 市場の現在の利用例
    • HMI (ヒューマンマシンインターフェース) 予知保全
    • 自律走行トラック
    • トラックプラトゥーニング
    • 先進運転車支援システム (ADAS)
    • 精度・マッピング

第7章 輸送における人工知能 (AI) 市場:マシンラーニング技術別

  • イントロダクション
  • コンピュータービジョン
  • コンテキストアウェアネス
  • ディープラーニング
  • 自然言語処理

第8章 輸送における人工知能 (AI) 市場:プロセス別

  • イントロダクション
  • データマイニング
  • 画像認識
  • シグナル認識

第9章 輸送における人工知能 (AI) 市場:用途別

  • イントロダクション
  • 自律走行トラック
  • トラックにおけるHMI
  • 半自律走行トラック

第10章 人工知能 (AI) 向けトラックプラトゥーニング市場:地域別

  • イントロダクション
    • サービス別
    • 地域別

第11章 輸送における人工知能 (AI) 市場:提供品別

  • イントロダクション
  • ハードウェア
  • ソフトウェア

第12章 輸送における人工知能 (AI) 市場:地域別

  • イントロダクション
  • アジアオセアニア
  • 欧州
  • 北米
  • その他

第13章 競合環境

  • イントロダクション
  • 市場ランキング分析
  • 競合状況・動向

第14章 企業プロファイル

  • OEM
  • ティア1サプライヤー
  • ソフトウェアサプライヤー
  • 新興企業

第15章 付録

図表

LIST OF TABLES

  • TABLE 1: CURRENCY EXCHANGE RATES (W.R.T. USD)
  • TABLE 2: WORLD'S MOST CONGESTED COUNTRIES, 2016
  • TABLE 3: US DEPARTMENT OF TRANSPORTATION'S FATALITY ANALYSIS REPORTING SYSTEM (FARS).
  • TABLE 4: HOURS OF SERVICE REGULATIONS
  • TABLE 5: KEY PLAYERS IN THE GLOBAL TRUCK PLATOONING MARKET
  • TABLE 6: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY MACHINE LEARNING TECHNOLOGY, 2016-2030 (USD MILLION)
  • TABLE 7: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR COMPUTER VISION, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 8: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR COMPUTER VISION, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 9: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR COMPUTER VISION, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 10: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR CONTEXT AWARENESS, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 11: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR CONTEXT AWARENESS, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 12: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR CONTEXT AWARENESS, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 13: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR DEEP LEARNING, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 14: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR DEEP LEARNING, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 15: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR DEEP LEARNING, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 16: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR NATURAL LANGUAGE PROCESSING, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 17: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR NATURAL LANGUAGE PROCESSING, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 18: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY PROCESS, 2016-2030 (USD MILLION)
  • TABLE 19: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR DATA MINING, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 20: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR DATA MINING, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 21: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR IMAGE RECOGNITION, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 22: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR IMAGE RECOGNITION, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 23: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SIGNAL RECOGNITION, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 24: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SIGNAL RECOGNITION, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 25: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 26: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR AUTONOMOUS TRUCKS, BY PROCESS, 2016-2030 (USD MILLION)
  • TABLE 27: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR AUTONOMOUS TRUCKS, BY MACHINE LEARNING TECHNOLOGY, 2016-2030 (USD MILLION)
  • TABLE 28: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR AUTONOMOUS TRUCKS, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 29: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR HMI IN TRUCKS, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 30: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR HMI IN TRUCKS, BY MACHINE LEARNING TECHNOLOGY, 2016-2030 (USD MILLION)
  • TABLE 31: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR HMI IN TRUCKS, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 32: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SEMI-AUTONOMOUS TRUCKS, BY PROCESS, 2016-2030 (USD MILLION)
  • TABLE 33: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SEMI-AUTONOMOUS TRUCKS, BY MACHINE LEARNING TECHNOLOGY, 2016-2030 (USD MILLION)
  • TABLE 34: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SEMI-AUTONOMOUS TRUCKS, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 35: TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 36: TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY REGION, 2016-2030 ('000 UNITS)
  • TABLE 37: TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 38: ASIA OCEANIA: TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 39: EUROPE: TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 40: NORTH AMERICA: TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 41: REST OF THE WORLD: TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 42: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY OFFERING, 2016-2030 (USD MILLION)
  • TABLE 43: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR HARDWARE, BY COMPUTING TYPE, 2016-2030 (USD MILLION)
  • TABLE 44: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR HARDWARE, BY MACHINE LEARNING TECHNOLOGY, 2016-2030 (USD MILLION)
  • TABLE 45: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR HARDWARE, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 46: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SOFTWARE, BY COMPUTING TYPE, 2016-2030 (USD MILLION)
  • TABLE 47: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SOFTWARE, BY MACHINE LEARNING TECHNOLOGY, 2016-2030 (USD MILLION)
  • TABLE 48: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SOFTWARE, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 49: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY REGION, 2016-2030 (USD MILLION)
  • TABLE 50: ASIA OCEANIA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY COUNTRY, 2016-2030 (USD MILLION)
  • TABLE 51: ASIA OCEANIA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 52: CHINA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 53: INDIA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 54: JAPAN: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 55: SOUTH KOREA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 56: REST OF ASIA OCEANIA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 57: EUROPE: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY COUNTRY, 2016-2030 (USD MILLION)
  • TABLE 58: EUROPE: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 59: FRANCE: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 60: GERMANY: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 61: UK: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 62: REST OF EUROPE: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 63: NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY COUNTRY, 2016-2030 (USD MILLION)
  • TABLE 64: NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 65: CANADA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 66: MEXICO: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 67: US: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 68: REST OF THE WORLD: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY COUNTRY, 2016-2030 (USD MILLION)
  • TABLE 69: REST OF THE WORLD: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 70: BRAZIL: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 71: RUSSIA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 72: ROW OTHERS: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2016-2030 (USD MILLION)
  • TABLE 73: SUPPLY CONTRACTS/PARTNERSHIPS/JOINT VENTURES, 2017
  • TABLE 74: NEW PRODUCT DEVELOPMENTS, 2017
  • TABLE 75: EXPANSIONS, 2016-2017
  • TABLE 76: MERGERS & ACQUISITIONS, 2016-2017

LIST OF FIGURES

  • FIGURE 1: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET: RESEARCH DESIGN
  • FIGURE 2: RESEARCH DESIGN MODEL
  • FIGURE 3: BREAKDOWN OF PRIMARY INTERVIEWS
  • FIGURE 4: LEVEL OF AUTOMATION WITH ADDITION OF ADAS FEATURES
  • FIGURE 5: SENSOR FUSION
  • FIGURE 6: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION: TOP-DOWN APPROACH
  • FIGURE 7: DATA TRIANGULATION
  • FIGURE 8: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY REGION, 2017 VS 2030 (USD MILLION)
  • FIGURE 9: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2017 VS 2030 (USD MILLION)
  • FIGURE 10: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET GROWTH, BY COUNTRY, 2017-2030 (USD MILLION)
  • FIGURE 11: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY MACHINE LEARNING TECHNOLOGY, 2017 VS 2030 (USD MILLION)
  • FIGURE 12: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY OFFERING, 2016 - 2030 (USD MILLION)
  • FIGURE 13: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY PROCESS, 2017 VS 2022 (USD MILLION)
  • FIGURE 14: TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY REGION, 2019 VS 2030 (USD MILLION)
  • FIGURE 15: INCREASING FOCUS TOWARD SAFETY, SECURITY, & OPERATING COST EFFICIENCY TO DRIVE THE ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET DURING THE FORECAST PERIOD
  • FIGURE 16: NORTH AMERICA TO HOLD THE LARGEST SHARE IN THE ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, 2017 VS 2030 (USD MILLION)
  • FIGURE 17: SOFTWARE SEGMENT TO HOLD THE LARGEST MARKET SIZE IN THE ARTIFICIAL INTELLIGENCE IN TRANSPORTATION, 2016-2030 (USD MILLION)
  • FIGURE 18: DEEP LEARNING TECHNOLOGY TO LEAD IN THE ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, 2017 VS 2030 (USD MILLION)
  • FIGURE 19: SIGNAL RECOGNITION PROCESS TO LEAD THE ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY PROCESS, 2016-2030 (USD MILLION)
  • FIGURE 20: SEMI-AUTONOMOUS TRUCKS TO HAVE THE LARGEST SHARE IN ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, 2025 VS 2030 (USD MILLION)
  • FIGURE 21: NORTH AMERICA REGION TO HAVE THE LARGEST MARKET SIZE IN THE TRUCK PLATOONING FOR ARTIFICIAL INTELLIGENCE MARKET, 2019-2030 (USD MILLION)
  • FIGURE 22: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET: MARKET DYNAMICS
  • FIGURE 23: ADOPTION TREND OF AUTONOMOUS VEHICLES
  • FIGURE 24: TRUCK PLATOONING: YEARLY CO2 REDUCTION, 2020-2035
  • FIGURE 25: LEVEL OF AUTOMATION
  • FIGURE 26: ARTIFICIAL INTELLIGENCE (AI) ADOPTION
  • FIGURE 27: ARTIFICIAL INTELLIGENCE ENABLED TRANSPORTATION
  • FIGURE 28: ROLE OF ARTIFICIAL INTELLIGENCE IN TRANSPORTATION INDUSTRY
  • FIGURE 29: SAE & NHTSA VEHICLE AUTOMATION LEVELS
  • FIGURE 30: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY MACHINE LEARNING TECHNOLOGY, 2017 VS 2030
  • FIGURE 31: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY PROCESS, 2017 VS 2030 (USD MILLION)
  • FIGURE 32: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION, 2017 VS 2030
  • FIGURE 33: NORTH AMERICA IS EXPECTED TO ACCOUNT FOR THE LARGEST MARKET SIZE IN THE TRUCK PLATOONING MARKET DURING THE FORECAST PERIOD, (USD MILLION)
  • FIGURE 34: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY OFFERING, 2017 VS 2030
  • FIGURE 35: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR HARDWARE, BY COMPUTING TYPE, 2017 VS 2030
  • FIGURE 36: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET FOR SOFTWARE, BY COMPUTING TYPE, 2017 VS 2030
  • FIGURE 37: REGION-WISE SNAPSHOT OF THE ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET: NORTH AMERICA ACCOUNTS FOR THE LARGEST MARKET SHARE, 2017 VS 2030
  • FIGURE 38: ASIA OCEANIA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SNAPSHOT
  • FIGURE 39: NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET SNAPSHOT
  • FIGURE 40: VOLVO: COMPANY SNAPSHOT
  • FIGURE 41: DAIMLER: COMPANY SNAPSHOT
  • FIGURE 42: SCANIA: COMPANY SNAPSHOT
  • FIGURE 43: PACCAR: COMPANY SNAPSHOT
  • FIGURE 44: MAN: COMPANY SNAPSHOT
  • FIGURE 45: CONTINENTAL: COMPANY SNAPSHOT
  • FIGURE 46: MAGNA: COMPANY SNAPSHOT
  • FIGURE 47: BOSCH: COMPANY SNAPSHOT
  • FIGURE 48: VALEO: COMPANY SNAPSHOT
  • FIGURE 49: ZF: COMPANY SNAPSHOT
  • FIGURE 50: NVIDIA: COMPANY SNAPSHOT
  • FIGURE 51: ALPHABET: COMPANY SNAPSHOT
  • FIGURE 52: INTEL: COMPANY SNAPSHOT
  • FIGURE 53: MICROSOFT: COMPANY SNAPSHOT
目次
Product Code: AT 5736

"The rising number of accidents due to human error and increasing focus toward reducing transportation operating cost will fuel the demand for the artificial intelligence in transportation market"

The artificial intelligence in transportation market is projected to grow at a CAGR of 17.87% during the forecast period, and the market size is expected to grow from USD 1.21 billion in 2017 to USD 10.30 billion by 2030. The development of autonomous vehicles and industry-wide standards to implement safety features such as the adaptive cruise control (ACC), collision warning, lane-keep assist, and advanced driver assistance systems (ADAS) would drive the growth of the artificial intelligence in transportation market. Also, the growing demand for convenience and safety has created an opportunity for OEMs to develop new and innovative artificial intelligence systems that would attract customers. At the same time, the high cost of artificial intelligence systems and lack of infrastructure development have been major obstacles to the growth of the artificial intelligence in transportation market.

"The market for autonomous trucks is estimated to witness the fastest growth in the artificial intelligence in transportation market"

The development of autonomous trucks is considered the key focus of the artificial intelligence technology in the transportation industry. In a fully autonomous truck, the system performs all driving functions on all road types, at all speed ranges and environmental situations. While fully autonomous trucks have not yet entered the market, several companies are planning to develop them in the near future. The increasing concern for road accidents caused due to human error and a global shortage of truck drivers have accentuated the need for autonomous trucks.

"The market for deep learning technology is estimated to hold the largest share in the artificial intelligence in transportation market"

The increasing adoption of autonomous and semi-autonomous vehicles is driving the market for deep learning technology in the artificial intelligence in transportation market. Deep learning technology uses artificial neural networks to study multiple levels of data such as images, text, and sound. Deep learning technology thrives on data. In this technology, a large amount of data and experiences needs to be fed. This helps to identify and generalize the patterns experienced from the data and helps to drive safely. The autonomous vehicle needs to see, think, drive, and learn. Many companies are investing in the development of autonomous vehicles in which the deep learning technology is used for image processing, speech recognition, and data analysis. Presently, the deep learning technology is used in object detection, advanced driver assistance system (ADAS), crash avoidance, and vehicle telematics control using speech recognition and others.

"North America: The largest region in the artificial intelligence in transportation market"

North America is estimated to dominate the artificial intelligence in transportation market. Factors such as strong financial position, shortage of truck drivers, strict government regulations for road safety, and presence of leading technology firms have made North America the largest market for artificial intelligence in transportation. According to a New York Times report, the US government spent USD 4.00 billion in 2016 to accelerate the acceptance of autonomous vehicles on US roads.

The US accounts for the largest share of the North American artificial intelligence in transportation market. The demand and sales of commercial vehicles are expected to grow in the US in the future. Most of the vehicles in the US are equipped with advanced features such as adaptive cruise control, lane departure, warning systems, voice recognition system, gesture recognition, and blind spot detection. These factors would contribute to the growth of artificial intelligence in transportation market in this region during the forecast period.

BREAKDOWN OF PRIMARIES:

The study contains insights provided by various industry experts, ranging from automotive OEMs to artificial intelligence technology providers. The breakdown of the primaries is as follows:

  • By Company Type: OEMs-20%, Tier-II-50%, and Tier-I-30%
  • By Designation: D level-20%, C level-45%, and Others**-35%
  • By Region: Asia Oceania-38%, North America-12%, Europe-25%, and RoW-25%

Note: Tier-I are hardware suppliers, Tier-II are service/solution providers.

*Others include researchers, consultants, and sales managers/marketing managers.

Company tiers are based on the value chain; revenue of the company has not been considered.

The report provides detailed profiles of the following companies:

  • Continental (Germany)
  • Daimler (Germany)
  • Scania (Sweden)
  • Paccar (US)
  • MAN (Germany)
  • Magna International (Canada)
  • Bosch (Germany)
  • Valeo (France)
  • ZF Friedrichshafen (Germany)
  • NVIDIA (US)
  • Alphabet (US)
  • Intel (US)
  • Microsoft (US)
  • Peloton Technology (US)
  • Nauto (US)
  • Xevo (US)
  • Zonar Systems (US)

Research Coverage:

The report provides a picture of the artificial intelligence in transportation market across different verticals and regions. It aims at estimating the market size and future growth potential of the artificial intelligence in transportation market, by application, offering, machine learning technology, process, region, and truck platooning market for artificial intelligence. Furthermore, the report also includes an in-depth competitive analysis of the key players in the market along with their company profiles, competitive landscape, recent developments, and key market strategies.

Reasons to Buy the Report:

The report provides insights into the following points:

  • Market Penetration: The report provides comprehensive information on artificial intelligence technologies offered by the top players in the industry.
  • Market Development: The report provides comprehensive information on various artificial intelligence technology trends. The report analyzes the markets for various artificial intelligence in transportation technologies across the countries.
  • Market Diversification: The report provides exhaustive information about emerging technologies, recent developments, and investments in the global artificial intelligence in transportation market.
  • Competitive Landscape: The report offers an in-depth assessment of recent developments of the supply chain players which include OEMs, software/solution providers, Tier-1 companies, and startups.

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. OBJECTIVES OF THE STUDY
  • 1.2. MARKET DEFINITION
  • 1.3. MARKET SCOPE
    • 1.3.1. YEARS CONSIDERED IN THE STUDY
  • 1.4. CURRENCY
  • 1.5. PACKAGE SIZE
  • 1.6. LIMITATIONS
  • 1.7. STAKEHOLDERS

2. RESEARCH METHODOLOGY

  • 2.1. RESEARCH DATA
  • 2.2. SECONDARY DATA
    • 2.2.1. KEY SECONDARY SOURCES
    • 2.2.2. KEY DATA FROM SECONDARY SOURCES
  • 2.3. PRIMARY DATA
    • 2.3.1. SAMPLING TECHNIQUES & DATA COLLECTION METHODS
    • 2.3.2. PRIMARY PARTICIPANTS
  • 2.4. FACTOR ANALYSIS
    • 2.4.1. DEMAND-SIDE ANALYSIS
      • 2.4.1.1. Traffic control and reduced congestion
      • 2.4.1.2. Increasing number of ADAS features in trucks with the increasing level of automation
    • 2.4.2. SUPPLY-SIDE ANALYSIS
      • 2.4.2.1. Technological development - sensor fusion
      • 2.4.2.2. Highway autopilot
  • 2.5. MARKET SIZE ESTIMATION
    • 2.5.1. TOP-DOWN APPROACH
    • 2.5.2. MARKET BREAKDOWN AND DATA TRIANGULATION
    • 2.5.3. ASSUMPTIONS

3. EXECUTIVE SUMMARY

4. PREMIUM INSIGHTS

  • 4.1. ATTRACTIVE OPPORTUNITIES IN THE ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET
  • 4.2. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY REGION
  • 4.3. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY OFFERING
  • 4.4. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY MACHINE LEARNING TECHNOLOGY
  • 4.5. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY PROCESS
  • 4.6. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION
  • 4.7. TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY REGION

5. MARKET OVERVIEW

  • 5.1. INTRODUCTION
  • 5.2. MARKET DYNAMICS
    • 5.2.1. DRIVERS
      • 5.2.1.1. Safety and security
      • 5.2.1.2. Operating cost efficiency
    • 5.2.2. RESTRAINTS
      • 5.2.2.1. High cost of artificial intelligence systems
      • 5.2.2.2. Infrastructure cost
    • 5.2.3. OPPORTUNITIES
      • 5.2.3.1. Truck platooning
      • 5.2.3.2. Increasing level of autonomy (Self-driving trucks)
    • 5.2.4. CHALLENGES
      • 5.2.4.1. Machine learning is data driven (public acceptance)
      • 5.2.4.2. Cybersecurity and data privacy

6. TECHNOLOGICAL OVERVIEW

  • 6.1. INTRODUCTION
  • 6.2. CURRENT USE CASES IN ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET
    • 6.2.1. HUMAN-MACHINE INTERFACE
    • 6.2.2. PREDICTIVE MAINTENANCE
    • 6.2.3. AUTONOMOUS TRUCK
    • 6.2.4. TRUCK PLATOONING
    • 6.2.5. ADVANCED DRIVER ASSISTANCE SYSTEM
    • 6.2.6. PRECISION AND MAPPING

7. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY MACHINE LEARNING TECHNOLOGY

  • 7.1. INTRODUCTION
  • 7.2. COMPUTER VISION
    • 7.2.1. BY OFFERING
    • 7.2.2. BY APPLICATION
    • 7.2.3. BY REGION
  • 7.3. CONTEXT AWARENESS
    • 7.3.1. BY OFFERING
    • 7.3.2. BY APPLICATION
    • 7.3.3. BY REGION
  • 7.4. DEEP LEARNING
    • 7.4.1. BY OFFERING
    • 7.4.2. BY APPLICATION
    • 7.4.3. BY REGION
  • 7.5. NATURAL LANGUAGE PROCESSING
    • 7.5.1. BY OFFERING
    • 7.5.2. BY REGION

[Note: The Chapter is Further Segmented By Offering (Hardware & Software), Application (Autonomous Trucks, HMI in Trucks, and Semi-Autonomous Trucks), and Region (Asia Oceania. Europe, North America, and RoW)]

8. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY PROCESS

  • 8.1. INTRODUCTION
  • 8.2. DATA MINING
    • 8.2.1. BY APPLICATION
    • 8.2.2. BY REGION
  • 8.3. IMAGE RECOGNITION
    • 8.3.1. BY APPLICATION
    • 8.3.2. BY REGION
  • 8.4. SIGNAL RECOGNITION
    • 8.4.1. BY APPLICATION
    • 8.4.2. BY REGION

[Note: The Chapter is Further Segmented By Application (Autonomous Trucks, HMI in Trucks, and Semi-Autonomous Trucks), and Region (Asia Oceania. Europe, North America, and RoW)]

9. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY APPLICATION

  • 9.1. INTRODUCTION
  • 9.2. AUTONOMOUS TRUCKS
    • 9.2.1. BY PROCESS
    • 9.2.2. BY MACHINE LEARNING TECHNOLOGY
    • 9.2.3. BY REGION
  • 9.3. HMI IN TRUCKS
    • 9.3.1. BY PROCESS
    • 9.3.2. BY MACHINE LEARNING TECHNOLOGY
    • 9.3.3. BY REGION
  • 9.4. SEMI-AUTONOMOUS TRUCKS
    • 9.4.1. BY PROCESS
    • 9.4.2. BY MACHINE LEARNING TECHNOLOGY
    • 9.4.3. BY REGION

[Note: The Chapter is Further Segmented By Process (Data Mining, Image Recognition, and Signal Recognition), Machine Learning Technology (Computer Vision, Context Awareness, Deep Learning, and Natural Language Processing) and Region (Asia Oceania. Europe, North America, and RoW)]

10. TRUCK PLATOONING MARKET FOR ARTIFICIAL INTELLIGENCE, BY REGION

  • 10.1. INTRODUCTION
    • 10.1.1. BY OFFERING
    • 10.1.2. BY REGION
      • 10.1.2.1. Asia Oceania
      • 10.1.2.2. Europe
      • 10.1.2.3. North America
      • 10.1.2.4. Rest of the World

[Note: The Chapter is Further Segmented By Offering (Hardware & Software), Region (Asia Oceania. Europe, North America, and RoW)]

11. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY OFFERING

  • 11.1. INTRODUCTION
  • 11.2. HARDWARE
    • 11.2.1. BY COMPUTING TYPE
    • 11.2.2. BY MACHINE LEARNING TECHNOLOGY
    • 11.2.3. BY REGION
  • 11.3. SOFTWARE
    • 11.3.1. BY COMPUTING TYPE
    • 11.3.2. BY MACHINE LEARNING TECHNOLOGY
    • 11.3.3. BY REGION

[Note: The Chapter is Further Segmented By Computing Type (Hardware (Neuromorphic architecture & von Neumann architecture) and Software(Platform & Solutions)), Machine Learning Technology (Computer Vision, Context Awareness, Deep Learning, and Natural Language Processing), and Region (Asia Oceania. Europe, North America, and RoW)]

12. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION MARKET, BY REGION

  • 12.1. INTRODUCTION
  • 12.2. ASIA OCEANIA
    • 12.2.1. CHINA
    • 12.2.2. INDIA
    • 12.2.3. JAPAN
    • 12.2.4. SOUTH KOREA
    • 12.2.5. REST OF ASIA OCEANIA
  • 12.3. EUROPE
    • 12.3.1. FRANCE
    • 12.3.2. GERMANY
    • 12.3.3. UK
    • 12.3.4. REST OF EUROPE
  • 12.4. NORTH AMERICA
    • 12.4.1. CANADA
    • 12.4.2. MEXICO
    • 12.4.3. US
  • 12.5. REST OF THE WORLD
    • 12.5.1. BRAZIL
    • 12.5.2. RUSSIA
    • 12.5.3. ROW OTHERS

[Note: The Chapter is Further Segmented By Application (Autonomous Trucks, HMI in Trucks, and Semi-Autonomous Trucks)]

13. COMPETITIVE LANDSCAPE

  • 13.1. INTRODUCTION
  • 13.2. ARTIFICIAL INTELLIGENCE IN TRANSPORTATION: MARKET RANKING ANALYSIS
    • 13.2.1. MARKET RANKING ANALYSIS OF OEMS
    • 13.2.2. MARKET RANKING ANALYSIS OF TIER-I SUPPLIERS
    • 13.2.3. MARKET RANKING ANALYSIS OF SOFTWARE/SERVICE PROVIDERS
  • 13.3. COMPETITIVE SITUATION & TRENDS
    • 13.3.1. COMPETITIVE SITUATION & TRENDS: SUPPLY CONTRACTS/ PARTNERSHIPS/JOINT VENTURES WAS THE MOST WIDELY ADOPTED STRATEGY
    • 13.3.2. SUPPLY CONTRACTS/PARTNERSHIPS/JOINT VENTURES
    • 13.3.3. NEW PRODUCT DEVELOPMENTS
    • 13.3.4. EXPANSIONS
    • 13.3.5. MERGERS & ACQUISITIONS

14. COMPANY PROFILES (Overview, Services offered, Strength of service portfolio, Business strategy excellence, Recent developments)*

  • 14.1. ORIGINAL EQUIPMENT MANUFACTURERS (OEMS)
    • 14.1.1. VOLVO
    • 14.1.2. DAIMLER
    • 14.1.3. SCANIA
    • 14.1.4. PACCAR
    • 14.1.5. MAN
  • 14.2. TIER-I SUPPLIERS
    • 14.2.1. CONTINENTAL
    • 14.2.2. MAGNA
    • 14.2.3. BOSCH
    • 14.2.4. VALEO
    • 14.2.5. ZF
  • 14.3. SOFTWARE SUPPLIERS
    • 14.3.1. NVIDIA
    • 14.3.2. ALPHABET
    • 14.3.3. INTEL
    • 14.3.4. MICROSOFT
  • 14.4. START-UP'S
    • 14.4.1. PELOTON
      • 14.4.1.1. Funding Details
    • 14.4.2. NAUTO
      • 14.4.2.1. Funding Details
    • 14.4.3. XEVO
      • 14.4.3.1. Funding Details
    • 14.4.4. ZONAR
      • 14.4.4.1. Funding Details

*Details on Overview, Services offered, Strength of service portfolio, Business strategy excellence, Recent developments might not be captured in case of unlisted companies.

15. APPENDIX

  • 15.1. INSIGHTS OF INDUSTRY EXPERTS
  • 15.2. DISCUSSION GUIDE
  • 15.3. KNOWLEDGE STORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
  • 15.4. INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE
  • 15.5. AVAILABLE CUSTOMIZATIONS
    • 15.5.1. ARTIFICIAL INTELLIGENCE MARKET IN BUSES, BY APPLICATION
      • 15.5.1.1. Semi-Autonomous Buses
      • 15.5.1.2. Autonomous Buses
      • 15.5.1.3. HMI in Buses
    • 15.5.2. ARTIFICIAL INTELLIGENCE MARKET IN BUSES, BY REGION
      • 15.5.2.1. Asia Oceania
      • 15.5.2.2. Europe
      • 15.5.2.3. North America
      • 15.5.2.4. RoW
    • 15.5.3. ARTIFICIAL INTELLIGENCE MARKET IN FLEETS, BY REGION
      • 15.5.3.1. Asia Oceania
      • 15.5.3.2. Europe
      • 15.5.3.3. North America
      • 15.5.3.4. RoW
  • 15.6. RELATED REPORTS
  • 15.7. AUTHOR DETAILS
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