Global Drone Payload Market 2023

Description
AI in transportation refers to the application of artificial intelligence technologies in various aspects of the transportation industry to improve efficiency, safety, and reliability. It encompasses a wide range of applications, including self-driving vehicles, traffic management, logistics optimization, predictive maintenance, and more. According to the latest research, the global AI in transportation market is poised to grow by USD 32.1 billion during 2023-2029, progressing at a CAGR of 13.41% during the forecast period.

The report covers market size and growth, segmentation, regional breakdowns, competitive landscape, trends and strategies for global AI in transportation market. It presents a quantitative analysis of the market to enable stakeholders to capitalize on the prevailing market opportunities. The report also identifies top segments for opportunities and strategies based on market trends and leading competitors' approaches.

Market Segmentation
Offering: hardware, software
Machine learning technology: deep learning, computer vision, natural language processing (NLP), context awareness
IoT communication technology: LTE, LPWAN, 5G
Application: semi-autonomous truck, truck platooning, predictive maintenance, precision and mapping, autonomous truck, human-machine interface (HMI), others
Region: Asia-Pacific, Europe, North America, Middle East and Africa (MEA), South America
Hardware: CPU, GPU, sensors, others
Software: AI platform, AI solution

This industry report offers market estimates and forecasts of the global market, followed by a detailed analysis of the offering, machine learning technology, IoT communication technology, application, and region. The global market for AI in transportation can be segmented by offering: hardware, software. The hardware segment captured the largest share of the market in 2022. AI in transportation market is further segmented by machine learning technology: deep learning, computer vision, natural language processing (NLP), context awareness. The deep learning segment held the largest share of the global AI in transportation market in 2022 and is anticipated to hold its share during the forecast period. Based on IoT communication technology, the AI in transportation market is segmented into: LTE, LPWAN, 5G. In 2022, the LTE segment made up the largest share of revenue generated by the AI in transportation market. On the basis of application, the AI in transportation market also can be divided into: semi-autonomous truck, truck platooning, predictive maintenance, precision and mapping, autonomous truck, human-machine interface (HMI), others. Among these, the semi-autonomous truck segment was accounted for the highest revenue generator in 2022. AI in transportation market by region is categorized into: Asia-Pacific, Europe, North America, Middle East and Africa (MEA), South America. North America captured the largest share of the market in 2022.

The hardware market is further segmented into CPU, GPU, sensors, others. According to the research, the CPU segment had the largest share in the global AI in transportation market. Furthermore, the software market has been categorized into AI platform, AI solution. The latest research indicates that the AI platform segment occupied the largest share of this market in 2022 and is expected to draw the highest demand in coming years.

Major Companies and Competitive Landscape
The global AI in transportation market report offers detailed information on several market vendors, including AB Volvo, Continental AG, Daimler AG, Huawei Technologies Co., Ltd., IBM Corporation, Intel Corporation, Magna International Inc., Microsoft Corporation, NEC Corporation, NVIDIA Corporation, Robert Bosch GmbH, Scania AB, Siemens Mobility GmbH, Valeo SA, ZF Friedrichshafen AG, among others. In this report, key players and their strategies are thoroughly analyzed to understand the competitive outlook of the market.

Scope of the Report
To analyze and forecast the market size of the global AI in transportation market.
To classify and forecast the global AI in transportation market based on offering, machine learning technology, IoT communication technology, application, region.
To identify drivers and challenges for the global AI in transportation market.
To examine competitive developments such as mergers & acquisitions, agreements, collaborations and partnerships, etc., in the global AI in transportation market.
To identify and analyze the profile of leading players operating in the global AI in transportation market.

Why Choose This Report
Gain a reliable outlook of the global AI in transportation market forecasts from 2023 to 2029 across scenarios.
Identify growth segments for investment.
Stay ahead of competitors through company profiles and market data.
The market estimate for ease of analysis across scenarios in Excel format.
Strategy consulting and research support for three months.
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