The latest market intelligence report, titled ‘Global Artificial Intelligence in Transportation Market’, is intended to provide the target audience with the necessary information about the global Artificial Intelligence in Transportation industry. The report comprises a detailed analysis of the vital elements of the Artificial Intelligence in Transportation market, including key drivers, constraints, opportunities, limitations, threats, and micro- and macro-economic factors. The report carefully investigates the present market scenario and the fundamental growth prospects. The report entails an organized database of the Artificial Intelligence in Transportation market dynamics that helps market analysts estimate the global market growth rate over the projected timeline. As a result, the report, released by Emergen Research, is a thorough compilation of the essential elements of the Artificial Intelligence in Transportation market, including the major market segments, top competitors, their company profiles, pricing strategies, production capabilities, revenue generation plans, technological advancements, and many others. It also includes the key players' product offerings, the broad application range of these products, the major market segments, and many others. The epidemic has had a significant impact on the world economy, which has disrupted the way the Artificial Intelligence in Transportation market functions. Organizations have been forced by the severe global crisis to effectively adapt to the quickly changing business environment. The study also assesses the pandemic's initial and long-term effects on the keyword market.

The global Artificial Intelligence in transportation market size is expected to reach USD 7,065.1 Million in 2028 and register a robust CAGR over the forecast period, according to latest analysis by Emergen Research. Steady revenue growth of the Artificial Intelligence in transportation market can be attributed to rising demand for safety and security in transportation and logistics and increasing deployment of more advanced traffic management solutions. Artificial Intelligence (AI) in transportation is used to gather traffic data to decrease traffic congestion and enhance public transport scheduling. AI helps in streamlining traffic patterns through real-time tracking and intelligent traffic light algorithms, thereby enabling smooth traffic flow, which significantly improves various aspects in transportation. Besides, AI helps in decreasing fuel consumption and exhaust emissions, which would otherwise be higher in a normal setting as a result of numerous vehicles moving slowly during a traffic jam or congestion.

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The global Artificial Intelligence in Transportation market has been categorized on the basis of key geographical regions into North America, Asia Pacific, Europe, Latin America, and Middle East & Africa. It evaluates the presence of the global Artificial Intelligence in Transportation market in the major regions with regards to market share, market size, revenue contribution, sales network and distribution channel, and other key elements.

Leading companies profiled in the report:

Daimler AG, Continental AG, Robert Bosch GmbH, VOLVO, PACCAR Inc., Magna International Inc., ZF Friedrichshafen AG, Scania AB, Valeo, and MAN SE

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The report also presents the analytical information in a well-organized fashion divided into graphs, tables, charts, figures, and diagrams. This makes it simple and useful for readers to comprehend the market situation. The research also tries to convey a forward-looking perspective and reach an insightful conclusion to help the reader make profitable business decisions. In summary, the report offers a thorough analysis of the market segments anticipated to dominate it, the regional division, the estimated market size and share, as well as a thorough SWOT analysis and Porter's Five Forces Analysis.

On the basis of type, the market is segmented into

  • Process Outlook (Revenue, USD Million; 2021–2028)

    • Signal Recognition
    • Object Recognition
    • Data Mining
  • Learning Technology Outlook (Revenue, USD Million; 2021–2028)

    • Deep Learning
    • Context Awareness
    • Computer Vision
    • Natural Language Processing
  • Application Outlook (Revenue, USD Million; 2021–2028)

    • Autonomous Trucks
    • HMI Trucks
    • Semi-autonomous Trucks

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