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Artificial Intelligence in Transportation Market to Soar 17.8% CAGR to 2030: Key Companies Continental, Daimle, Scani, Pacca, MA, Magna International, Bosch and More

09-25-2018 11:14 AM CET | IT, New Media & Software

Press release from: WOM-Reports

Artificial Intelligence in Transportation Market to Soar 17.8%

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.

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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 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 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.

The report provides detailed profiles of the key companies such as 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) and Zonar Systems (US).

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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%

Related Report:

Artificial Intelligence in Supply Chain Market by Offering Technology Application (Fleet Management Supply Chain Planning Warehouse Management Virtual Assistant Freight Brokerage) End-User Industry and Geography - Global Forecast to 2025

The artificial intelligence in supply chain market is expected to reach USD 10,110.2 million by 2025 from USD 730.6 million in 2018, at a CAGR of 45.55%. Growth in this market can largely be attributed to factors such as growing big data, demand for greater visibility and transparency into supply chain data and processes, and adoption of AI for improving consumer services and their satisfaction. On the other hand, the limited number of artificial intelligence technology experts is expected to restrict adoption, which in turn may limit market growth to a certain extent.

North America is notable for its high adoption of artificial intelligence. The increasing demand for intelligent virtual assistants acts as a driving force for the growth of the artificial intelligence in supply chain market in the region. The market in North America is also characterized by high infrastructure costs and strict policies and regulatory frameworks. Companies such as IBM (US), Google (US), Microsoft (US), NVIDIA (US), Intel (US), and Amazon (US) are complementing the growth of the market in this region.

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Our only motivation is to provide clients with precise insights into their respective niche markets and offering them the most comprehensive portfolio of business information products.

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