AI in Transportation Market Research Report- Forecast till 2023
Market Highlights
The AI in transportation market 2020 is presumed to gain traction in the coming months. AI has the potential to ease the traffic and facilitate efficient management. It is transforming the transportation industry and is likely to gain a quick mileage over the next couple of years. It has many advantages which the governments are now raising awareness about. This, in turn, is expected to drive the growth of the market in the near future. An observation provided by Market Research Future (MRFR) presents that the global AI in transportation market is expected to mark 18.03% CAGR over the forecast period 2017 to 2023. The AI in transportation market size is anticipated to increase from USD 1.2 Bn in the year 2017 to USD 3.07 Bn by 2023 end.
Increasing adoption of AI in the transportation sector is highly supported by the governments of developed economies. In addition, the developing nations are also inclining towards the adoption of AI technology in the transportation industry. These factors are presumed to augment the AI in transportation industry in the upcoming years. In addition, the utilization of the technology ensures smooth flow of traffic. Increasing road traffic problems over the world is anticipated to drive the expansion of the AI in transportation market in the near future. The sales of automobiles are projected to further increase, which is prognosticated to catapult the AI in transportation market on upward trajectory. Furthermore, AI is expected to find applications in aviation and railways. Rising tourism industry is also forecasted to impact the market greatly. The growing amount of air traffic is anticipated to lead the AI in transportation market growth in the foreseeable future. Technological innovations are further projected to influence the AI in transportation market greatly.
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Segmentation:
On the basis of offerings, the AI in transportation market has been divided into hardware and software. The sub-segments of the software segment are AI platforms and AI solutions. The sub-segmentation of the hardware segment covers sensors, GPUs, CPUs, and others.
Based on IoT communications technology, the AI in transportation market has been segmented into 5G, LTE, and LPWAN.
On the basis of machine learning technology, the AI in transportation market has been segmented into deep learning, natural language processing, computer vision, and context awareness.
Based on application, the AI in transportation market has been segmented into autonomous truck, precision and mapping, semi-autonomous trucks, human-machine interface (HMI), truck platooning, predictive maintenance, and others (driverless buses and smart traffic management).
Regional Analysis
The geographical evaluation of the global AI in transportation market is included in this report. The segments based on region covered in the assessment are North America, Asia-Pacific, Europe, and the Rest of the World. These regional segments are narrowed down for a country-level study of the market. North America is anticipated to have a leading share of the market and retain it across the assessment period. Prominent countries such as Canada and the U.S, that are technologically advanced, are based out of the region. It is projected to catalyze the growth rate of the AI in transportation market in the region. Europe is also a crucial regional market for AI in transportation. The rising investments in the integration of AI into transportation industry by the European Union are expected to impact the growth pattern of the AI in transportation market in Europe positively.
Competitive Dashboard
AG, NVIDIA Corporation, Robert Bosch GmbH, Microsoft Corporation, Daimler AG, Volvo Group, Scania Group, Magna International Inc, ZF Friedrichshafen AG, MAN SEPACCAR Inc., Valeo SA, Alphabet Inc., Intel Corporation, and IBM Corporation are the key holders of the AI in transportation market share.
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AI in Transportation Market Research Report by Offerings (Hardware, Software), IoT communication Technologies (LTE, 5G, and LPWAN), Machine learning technology (Deep learning, Computer vision, Natural language processing, and Others), Application (Autonomous truck, Semi-autonomous trucks, Truck platooning, and Others), and Region–Global Forecast to 2023
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