Artificial Intelligence in Transportation Comprehensive Study by Application (Semi & Full-Autonomous, HMI, Platooning), Technology (Deep Learning, Computer Vision, Context Awareness, NLP), Process (Data Mining, Image Recognition, Signal Recognition), Offering (Hardware, Software) Players and Region - Global Market Outlook to 2025

Edison , NJ -- (SBWire) -- 03/06/2019 --Transportation industry is evolving significantly in terms of automations. The automated vehicles requires machine intelligence that is artificial intelligence which refers to computer operated tasks which otherwise have required human intelligence such as decision making and visual perception. Transportation is a vital application area for artificial intelligence, involving the use computer vision, decision making and natural language processing (NLP) technologies. Fully Automated vehicles use AI based systems with the set of hardware such as Lidar, RADAR sensors, Video Cameras and many others. Thus, such a wide scope applications will lead to increase the demand for AI in transportation in forecasting years.

This market research report looks into and analyzes the Global Artificial Intelligence in Transportation Market and illustrates a comprehensive evaluation of its evolution and its specifications. Another aspect that was considered is the cost analysis of the main products dominant in the Global Market considering the profit margin of the manufacturers.

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Major Key Players in This Report Include,
Microsoft Corporation (United States), IBM Corporation (United States), Continental (Germany), Alphabet Inc. (United States), Intel Corporation (United States), Magna (Canada), Robert Bosch GmbH (Germany), Nvidia Corporation (United States), Valeo SA (France), ZF Friedrichshafen AG (Germany)

This research is categorized differently considering the various aspects of this market. It also evaluates the current situation and the future of the market by using the forecast horizon. The forecast is analyzed based on the volume and revenue of this market. The tools used for analyzing the Global Artificial Intelligence in Transportation Market research report include SWOT analysis.

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 the leading region across the world. Whereas, owing to rising no. of research activities in countries such as China, India, and Japan, Asia Pacific region is also expected to exhibit higher growth rate the forecast period 2019-2025.

The Global Artificial Intelligence in Transportation Market in terms of investment potential in various segments of the market and illustrate the feasibility of explaining the feasibility of a new project to be successful in the near future. The core segmentation of the global market is based on product types, SMEs and large corporations. The report also collects data for each major player in the market based on current company profiles, gross margins, sales prices, sales revenue, sales volume, photos, product specifications and up-to-date contact information.

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Table of Content
1. Market Overview
1.1. Introduction
1.2. Scope/Objective of the Study
1.2.1. Research Objective
2. Executive Summary
2.1. Introduction
3. Market Dynamics
3.1. Introduction
3.2. Market Drivers
3.2.1. Increasing Demand for Safe and On Time Movement of Goods and Cargo
3.2.2. Minimizes Operational Cost as well as Increases Efficiency of the Vehicles
3.3. Market Challenges
3.3.1. Skilled Workforce is required
3.3.2. Data Privacy and Cyber Security
3.4. Market Trends
3.4.1. Upsurging Strategic Alliances with other key players to Gain Competitive Edge
3.4.2. Introduction to Advanced Driver Assistance Systems
4. Market Factor Analysis
4.1. Porters Five Forces
4.2. Supply/Value Chain
4.3. PESTEL analysis
4.4. Market Entropy
4.5. Patent/Trademark Analysis
5. Global Artificial Intelligence in Transportation, by Application, Technology, Process, Offering and Region (value) (2013-2018)

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