Press release
Artificial Intelligence in Transportation Market Forecast to 2027 – Daimler AG, 2Volvo Group, Scania Group, PACCAR Inc, Robert Bosch GmbH, Valeo SA, NVIDIA Corp
Artificial intelligence is used in prediction & finding of traffic accidents and circumstances (by converting traffic sensors into intelligent agents with the help of cameras), it is used in deciding control & optimization problems. The rise in the government policy for vehicle safety, rising adoption of advanced driver assistance systems (ADAS), and progress of autonomous vehicles play a crucial role in the growth of artificial intelligence in transportation market . The major issues restraining the growth of the artificial intelligence in transportation market is the high price of artificial intelligence systems and infrastructure improvement cost. Truck Platooning and increasing level of autonomy are some prospects for artificial intelligence in transportation market. Cyber security, and data privacy are encounters for artificial intelligence in transportation market .Autonomous trucks are expected to be the firmest rising section of the global artificial intelligence in transportation market, by application. Autonomous trucks are the key objective for the submission of artificial intelligence technology. AI technology research was converging on traffic and navigation system, but now the focus has loosened to make fully autonomous trucks. Trucks are the key contributor to the transportation sector of North America.
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The List of Companies
1. Daimler AG
2. Volvo Group
3. Scania Group
4. PACCAR Inc
5. Robert Bosch GmbH
6. Valeo SA
7. NVIDIA Corp
8. Intel Corp
9. Continental AG
10. ZF Friedrichshafen AG
The latest research report on the “Artificial Intelligence in Transportation Market – Industry Analysis, Market Size, Opportunities and Forecast, 2020 – 2027” provides a comprehensive assessment of the Artificial Intelligence in Transportation market for the forecast period from 2020 to 2027, including market values for the years 2018 and 2019. The investigative report provides a detailed analysis of the impact of COVID-19 on various segments in the Artificial Intelligence in Transportation market based on product type, application, and end-use across numerous countries around the world.
Further, the report also provides insights into market developments, trends, supply and demand changes across various regions across the globe. Thereby, the report provides a holistic view on the Artificial Intelligence in Transportation Market in order to help decision makers with various strategic insights and future outlook. The Artificial Intelligence in Transportation market is expected to witness continued growth during the forecast period from 2020 to 2027.
This is a professional and in-depth study on the current state of the Artificial Intelligence in Transportation Market with a basic overview of the industry including definitions, classifications, applications and industry chain structure. The Strategic Insights and Development plans are also discussed and manufacturing processes and cost structures analyzed. Artificial Intelligence in Transportation Market import/export consumption, supply and demand figures and cost price and production value gross margins are also provided.
The report focuses on global major leading Artificial Intelligence in Transportation Market players providing information such as company profiles, product picture and specification, capacity, production, price, cost, revenue and contact information. Upstream raw materials and equipment and downstream demand analysis is also carried out.
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Reasons to Buy
• Highlights key business priorities to assist companies realign their business strategies.
• Features key findings and crucial progressive industry trends in the global Artificial Intelligence in Transportation market, thereby allowing players to develop effective long-term strategies.
• Develops/modifies business expansion plans by using substantial growth offering from developed and emerging markets.
• Scrutinizes in-depth market trends as well as key market drivers and restraints.
• Enhances the decision-making process by understanding the strategies that underpin commercial interest with respect to products, segmentation, and industry verticals.
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