Artificial Intelligence in Transportation Market by Machine Learning (Deep Learning, Computer Vision, Context Awareness, NLP), Application (Semi & Full-Autonomous, HMI, Platooning), Offering (Hardware, Software), Process, and Region - Global Forecast to 2030
“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:
Magna International (Canada)
ZF Friedrichshafen (Germany)
Peloton Technology (US)
Zonar Systems (US)
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.
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