AI in Transportation Market to Hit USD 44,885.8 Million by 2026 at 17.5% CAGR – Report by Market Research Future (MRFR)

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New York, US, Aug. 11, 2021 (GLOBE NEWSWIRE) — Market Overview:
According to a comprehensive research report by Market Research Future (MRFR), “Global AI in Transportation Market information by Offering, by Software, by Application and Region – forecast to 2026” the market size is expected to grow from USD 18,520.0 million in 2020 to USD 44,885.8 million by 2026 at a CAGR of 17.5%

Dominant Key Players on AI in Transportation Market Covered Are:

  • Siemens Mobility Solutions (Germany)
  • Huawei Technologies Co. Ltd (China)
  • Intel Corporation (US)
  • NEC Corporation (Japan)
  • Microsoft Corporation (US)
  • IBM Corporation (US)
  • Robert Bosch GmbH (Germany)
  • Valeo (France)
  • Daimler AG (Germany)
  • Scania AB (Sweden)
  • Continental AG (Germany)
  • Magna International (Canada)
  • Volvo (Sweden)
  • ZF Friedrichshafen AG (Germany)
  • Nvidia (US)

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Market USP Exclusively Encompassed:
AI in Transportation Market Drivers
The global AI in transportation market is expected to witness favorable growth during the forecast period. Factors such as the increasing adoption to enhance driver and vehicle safety and the rising need for enhanced operational efficiency are anticipated to drive the market growth during the study period. The increasing demand for AI solutions in railway cargo transportation has created a growth opportunity for the AI in transportation market. However, the high cost of implementation and lack of skilled personnel are likely to restrict the growth of the global Artificial intelligence in transportation market.

Segmentation of Market Covered in the Research:
The global AI in transportation market has been segmented based on offering, machine learning (ML) technology, application, IoT communication, and region.

Based on offering, the global Artificial intelligence in transportation market has been segmented into hardware and software. The hardware segment is further subdivided into Central Processing Unit (CPU), Graphics Processing Unit (GPU), sensors, and others. The hardware segment accounted for the larger market value in 2019, reaching a value of USD 10,819.1 million; it is expected to register a CAGR of 17.0% during the forecast period. The software segment was valued at USD 5,868.9 million; it is projected to register a higher CAGR of 18.3%. Rapid advancements in technology have enabled various AI applications across industry verticals, one of which is transportation. However, every software application developed requires suitable hardware that forms a base to perform cognitive functions. Hardware components used in AI for transportation mainly consist of sensors, CPUs, and GPUs, among others.

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Based on ML technology, the AI in transportation market has been segmented into deep learning, computer vision, NLP, and context awareness. The deep learning segment held a larger market share in 2019, with a market value of USD 9,480.7 million; it is expected to register a CAGR of 17.3% during the forecast period. The computer vision segment was the second-largest market in 2019, valued at USD 3,992.1 million; it is projected to register a higher CAGR of 18.0%. Rapid developments across data generation and in computational technologies such as graphical processing unit (GPU) have developed a class of machine learning called Deep Learning (DL) is gaining popularity having the competence to address bulk volumes of raw data, fetching insights from complex systems making them a powerful as well as a practical answer to intelligent transportation system (ITS). For instance, advanced driver assistance systems based on deep learning algorithms provide collision warnings, detect blind spots in electronic coverage, and lane departure warning systems to alert vehicle drivers if a vehicle is beginning to leave the current lane. Computer vision technology involves a high-performance computing system that interprets and gains knowledge from the graphical content generated and identified by the camera system enabled with deep learning models. With this, the organization can improve traffic management, driver and passenger safety, monitor & control criminal activities on-board, and asset protection.

Based on application, the AI in transportation market has been segmented into autonomous truck, semi-autonomous truck, truck platooning, human-machine interface (HMI), predictive maintenance, precision mapping, and others. The semi-autonomous truck segment held the largest market share in 2019, with a market value of USD 3,736.1 million; it is expected to register a CAGR of 17.2% during the forecast period. The truck platooning was the second-largest segment in 2019, valued at USD 3,489.7 million; it is projected to register a 15.5% CAGR during the forecast period. Semi-autonomous trucks require little human intervention to manage and control the truck using technologies such as adaptive cruise control, lane assistance, blind spot detection, intelligent parking assistance, traffic jam assistance, and others. This type of truck enables truck drivers to operate longer distances with lesser strain with the help of automated safety functions, sensing & driving conditions as per the surrounding environment on the road, and eliminating human errors in driving that can be harmful to both the driver and the vehicle owner. Truck platooning is involved with a driving support system of connectivity & automated driving support systems in a number of trucks in a caravan that automatically maintains a set and close distance of over 50 to 60 feet, delivering higher fuel efficiency, enhanced safety, quicker response system, reduce traffic jams, and other such benefits. It is said that the two-truck platooning delivers savings of over 10% on fuel consumption for the following truck and over 4-5 % for the leading truck. This also results in lesser carbon emissions and a reduction in the friction caused due to air drag.

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Based on IoT communication, the AI in transportation market has been segmented into LTE, LPWAN, and 5G. The LTE segment held the largest market share in 2019, with a market value of USD 14,382.1 million; it is expected to register a CAGR of 3.8% during the forecast period. The LPWAN segment was the second-largest market in 2019, valued at USD 2,305.9 million; it is projected to register a 14.5% CAGR. However, the 5G segment is expected to register the highest CAGR of 90.4% during the forecast period. Fifth generation (5G) mobile networks can connect and communicate virtually with and among machines, objects, and devices. 5G is meant to deliver higher data transmission speeds than the previous generations, a lower latency rate, increased reliability, capacity to serve an increased number of consumers, increased availability, and ubiquitous network user experience.

Regional Analysis
The regional analysis for the global AI in transportation has been done for North America, Europe, Asia-Pacific, the Middle East & Africa, and South America. In 2019, North America accounted for 41.8% of the market share in the AI in transportation market due to the presence of key market players such as Intel Corporation, Microsoft Corporation, IBM Corporation, Magna International, and Nvidia. The region is predicted to witness considerable growth over the study period due to the increasing urbanization, advancements in digital technology, and high per capita disposable income.

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