Global Artificial Intelligence in Transportation Market Size study, by Machine Learning Technology, by Process (Data Mining, Image Recognition, Signal Recognition), by Application (Autonomous Truck, HMI in Trucks, Semi-Autonomous Truck), by Offering and by Regional Forecasts 2018-2025

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Global Artificial Intelligence in Transportation Market valued approximately USD 1.2 billion in 2017 is anticipated to grow with a healthy growth rate of more than 18% over the forecast period 2018-2025. The growth of the Artificial Intelligence in Transportation market is majorly driven by the development of autonomous vehicles and increasing focus towards reducing the operating cost of transportation. Major developments in Market are related to software. Companies such as IBM and Alphabet Inc. are investing heavily in Artificial Intelligence software, which is benefiting the market of the category. Furthermore, the declining prices of hardware will increase the share of the software category in the market by 2025.

 The regional analysis of Global Artificial Intelligence in Transportation Market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is estimated to account for the largest share in the global AI in transportation market, valued at more than 44.0% in 2017. The region includes developed countries such as the U.S. and Canada, which are prominent markets of AI in transportation. Government support and sales of long-haul and premium trucks are driving the market in the region. The U.S. has accounted for a major portion of market revenues in the region till now, due to considerable government and private sector investment, coupled with a favorable policy framework. A well-developed trucking industry with an estimated 15 million registered trucks in the country, ensures considerable long-term opportunity for AI in transportation.

Global Artificial Intelligence in Transportation Market The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Machine Learning Technology:

  • Computer Vision
  • Context Awareness
  • Deep Learning
  • Natural Language processing

By Process:

  • Data Mining
  • Image Recognition
  • Signal Recognition

By Application:

  • Autonomous Trucks
  • HMI in Trucks
  • Semi-Autonomous Truck

By Offering:

  • Hardware
  • Software

By Regions:

  • North America
    • U.S.
    • Canada
  • Europe
    • UK
    • Germany
  • Asia Pacific
    • China
    • India
    • Japan
  • Latin America
    • Brazil
    • Mexico
  • Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2015, 2016

Base year – 2017

Forecast period – 2018 to 2025

The industry is seeming to be fairly competitive. Some of the leading market players include Volvo, Daimler, Scania, Paccar, Continental, Magna, Bosch, ZF, Nvidia, Intel, Microsoft and so on. Acquisitions and effective mergers are some of the strategies adopted by the key manufacturers. New product launches and continuous technological innovations are the key strategies adopted by the major players.

Target Audience of the Global Artificial Intelligence in Transportation Market in Market Study:

  • Key Consulting Companies & Advisors
  • Large, medium-sized, and small enterprises
  • Venture capitalists
  • Value-Added Resellers (VARs)
  • Third-party knowledge providers
  • Investment bankers
  • Investors

Chapter 1.           Global Artificial Intelligence in Transportation Market Definition and Scope

1.1.         Research Objective

1.2.         Market Definition

1.3.         Scope of The Study

1.4.         Years Considered for The Study

1.5.         Currency Conversion Rates

1.6.         Report Limitation

Chapter 2.           Research Methodology

2.1.         Research Process

2.1.1.     Data Mining

2.1.2.     Analysis

2.1.3.     Market Estimation

2.1.4.     Validation

2.1.5.     Publishing

2.2.         Research Assumption

Chapter 3.           Executive Summary

3.1.         Global & Segmental Market Estimates & Forecasts, 2015-2025 (USD Billion)

3.2.         Key Trends

Chapter 4.           Global Artificial Intelligence in Transportation Market Dynamics

4.1.         Growth Prospects

4.1.1.     Drivers

4.1.2.     Restraints

4.1.3.     Opportunities

4.2.         Industry Analysis

4.2.1.     Porter’s 5 Force Model

4.2.2.     PEST Analysis

4.2.3.     Value Chain Analysis

4.3.         Analyst Recommendation & Conclusion

Chapter 5.           Global Artificial Intelligence in Transportation Market, By Machine Learning Technology.

5.1.         Market Snapshot

5.2.         Market Performance – Potential Model

5.3.         Global Artificial Intelligence in Transportation Market, Sub Segment Analysis

5.3.1.     Computer Vision

5.3.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.3.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

5.3.2.     Context Awareness

5.3.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.3.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

5.3.3.     Deep Learning

5.3.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.3.3.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

5.3.4.     Natural Language Processing

5.3.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.3.4.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 6.           Global Artificial Intelligence in Transportation Market, By Process

6.1.         Market Snapshot

6.2.         Market Performance – Potential Model

6.3.         Global Artificial Intelligence in Transportation Market, Sub Segment Analysis

6.3.1.     Data Mining

6.3.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

6.3.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

6.3.2.     Image Recognition

6.3.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

6.3.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

6.3.3.     Signal Recognition

6.3.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

6.3.3.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 7.           Global Artificial Intelligence in Transportation Market, By Application

7.1.         Market Snapshot

7.2.         Market Performance – Potential Model

7.3.         Global Artificial Intelligence in Transportation Market, Sub Segment Analysis

7.3.1.     Autonomous Trucks

7.3.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

7.3.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

7.3.2.     HMI in Trucks

7.3.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

7.3.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

7.3.3.     Semi-Autonomous Trucks

7.3.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

7.3.3.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 8.           Global Artificial Intelligence in Transportation Market, By Offering

8.1.         Market Snapshot

8.2.         Market Performance – Potential Model

8.3.         Global Artificial Intelligence in Transportation Market, Sub Segment Analysis

8.3.1.     Hardware

8.3.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

8.3.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

8.3.2.     Software

8.3.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

8.3.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 9.           Global Artificial Intelligence in Transportation Market, by Regional Analysis

9.1.         Artificial Intelligence in Transportation Market, Regional Market Snapshot (2015-2025)

9.2.         North America Artificial Intelligence in Transportation Market Snapshot

9.2.1.     U.S.

9.2.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.2.1.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.2.1.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.2.1.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.2.1.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.2.2.     Canada

9.2.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.2.2.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.2.2.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.2.2.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.2.2.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.         Europe Artificial Intelligence in Transportation Market Snapshot

9.3.1.     U.K.

9.3.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.3.1.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.1.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.1.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.1.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.2.     Germany

9.3.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.3.2.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.2.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.2.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.2.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.3.     France

9.3.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.3.3.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.3.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.3.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.3.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.4.     Rest of Europe

9.3.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.3.4.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.4.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.4.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.3.4.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.         Asia Artificial Intelligence in Transportation Market Snapshot

9.4.1.     China

9.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.4.1.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.1.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.1.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.1.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.2.     India

9.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.4.2.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.2.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.2.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.2.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.3.     Japan

9.4.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.4.3.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.3.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.3.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.3.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.4.     Rest of Asia Pacific

9.4.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.4.4.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.4.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.4.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.4.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.5.         Latin America Artificial Intelligence in Transportation Market Snapshot

9.5.1.     Brazil

9.5.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.5.1.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.5.1.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.5.1.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.5.1.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.5.2.     Mexico

9.5.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.5.2.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.5.2.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.5.2.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.5.2.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.6.         Rest of The World

9.6.1.     South America

9.6.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.6.1.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.6.1.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.6.1.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.6.1.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.6.2.     Middle East and Africa

9.6.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.6.2.2. Machine Learning Technology breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.6.2.3. Process breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.6.2.4. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.6.2.5. Offering breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 10.         Competitive Intelligence

10.1.      Company Market Share (Subject to Data Availability)

10.2.      Top Market Strategies

10.3.      Company Profiles

10.3.1.   Volvo

10.3.1.1.               Overview

10.3.1.2.               Financial (Subject to Data Availability)

10.3.1.3.               Product Summary

10.3.1.4.               Recent Developments

10.3.2.   Daimler

10.3.3.   Scania.

10.3.4.   Paccar

10.3.5.   Continental

10.3.6.   Magna

10.3.7.   Bosch

10.3.8.   ZF

10.3.9.   Nvidia

10.3.10.                Intel.

10.3.11.                Microsoft

The Research Methodology for Global Artificial Intelligence in Transportation Market Study deeply focuses on the entire value chain of the market. However, all of the statistical estimates are purely based on the consumption/implementation side of the value chain wherein the market sizes have been calculated by analyzing the prices i.e. sale price or cost prices along with the average demand/ procedures/usage/ deployment/execution of Artificial Intelligence in Transportation across various industries / end-use/applications.

The whole Artificial Intelligence in Transportation industry has been divided into various segments i.e. Machine Learning Technology, Process, Application, Offering and Regions and each of which is studied as an individual study by our research analysts and consultants. Each of the subsegments has been analyzed and estimated at country level to form a regional scope. After finalizing the regional and segmental revenues the total revenue for Global Artificial Intelligence in Transportation Market is calculated as a sum of all the different segments.

Some of the key data points considered under the Research Methodology to calculate the revenue for Global Artificial Intelligence in Transportation Market includes:

  • Revenues from key companies
  • Company market share analysis
  • Consumer spending analysis
  • Regional export and import analysis
  • Regulatory Trends
  • Sales revenue generated by various products/applications in different countries/geographies

The Research Methodology starts with extensive data mining, using paid & free authentic information sources such as white papers, industry journals, trade magazines, Hoovers, Factiva, Statista, news websites, technical publications, independent studies etc. a team of dedicated research analysts and associates work on all of the gathered data to extract relevant information. Key factors such as ongoing & upcoming industry trends, external & internal driving factors, restraining factors, growth opportunities and value chain analysis have been verified in order form qualitative part of the report and to back the estimation team for quantitative analysis.

We utilize a combination of top-down and bottom-up methodology for industry estimations & forecasts. Additionally, we employ data triangulation techniques to verify each of the estimates and forecasts through primary interviews and feedbacks. An extensive primary and secondary research have been conducted with the key industry people, through questionnaires, telephonic conversations, email conversations, and interviews to verify industry trends and estimations. Various government websites/portals and paid data sources are considered as a key source of secondary research.

All of the estimates are derived from simulation models which is our proprietary technique. Each of these models is different from another. These models are a combination of correlation, regression and time series analysis. Each of these models is basically divided into two types namely economic and technological. Economical models are used to determine short-term market estimates and technological models are used for long-term estimates & forecasts. Both the types are used collectively in order to derive market estimates for the base year as well as for forecast period.


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