Global Artificial Intelligence in Transportation Market to reach USD 4.5 billion by 2025.
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.
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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.
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
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By Regions:
- North America
- U.S.
- Canada
- Europe
- UK
- Germany
- Asia Pacific
- China
- India
- Japan
- Latin America
- Brazil
- Mexico
- Rest of the World
The industry seems 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.
Some of the points from Global Artificial Intelligence in Transportation Market Research Report are
Chapter 1. Global Artificial Intelligence in Transportation Market Definition and Scope
Chapter 2. Research Methodology
Chapter 3. Executive Summary
Chapter 4. Global Artificial Intelligence in Transportation Market Dynamics
Chapter 5. Global Artificial Intelligence in Transportation Market, By Machine Learning Technology.
Chapter 6. Global Artificial Intelligence in Transportation Market, By Process
Chapter 7. Global Artificial Intelligence in Transportation Market, By Application
Chapter 8. Global Artificial Intelligence in Transportation Market, By Offering
Chapter 9. Global Artificial Intelligence in Transportation Market, by Regional Analysis
Chapter 10. Competitive Intelligence
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