AI in Transportation Market Report 2025

The AI in transportation market size has grown rapidly in recent years. It will grow from $3.78 billion in 2024 to $4.43 billion in 2025 at a compound annual growth rate (CAGR) of 17.4%. The growth in the historic period can be attributed to traffic management optimization, autonomous vehicles development, demand for intelligent public transportation, predictive maintenance for vehicles, rise in smart infrastructure.

The AI in transportation market size is expected to see exponential growth in the next few years. It will grow to $9.31 billion in 2029 at a compound annual growth rate (CAGR) of 20.4%. The growth in the forecast period can be attributed to expansion of electric and connected vehicles, integration of AI in urban mobility, focus on sustainable and smart cities, enhanced safety features, remote operations and monitoring. Major trends in the forecast period include advancements in AI algorithms and machine learning, government initiatives and regulations, autonomous vehicles advancements, predictive maintenance with ai, multimodal integration.

The increasing number of vehicles is projected to drive the growth of the AI in transportation market in the coming years. This rise in vehicles on the road can be linked to various factors, such as population growth, economic development, and the shortcomings of public transportation infrastructure. AI can enhance traffic management by analyzing real-time traffic data to optimize traffic flow, alleviate congestion, and decrease travel times through adjustments in signal timings and lane configurations. For example, a report released in June 2024 by Statistics Canada, a national statistical agency in Canada, noted that the total number of registered road motor vehicles in the country reached 26.3 million in 2022, reflecting a modest increase of 0.3% from 2021. Consequently, the growing number of vehicles is fueling the expansion of the AI in transportation market.

The rising incidence of road accidents is also expected to fuel the growth of the AI in transportation market. Road accidents are defined as collisions involving at least one vehicle on a public road resulting in at least one person being injured or killed. AI in transportation is deployed to manage traffic congestion, enhance traffic flow, and minimize the likelihood of accidents. For instance, the National Highway Traffic Safety Administration reported an estimated 20,175 fatalities in on-road car accidents during the first half of 2022 in the United States, reflecting a 0.5% increase from 2021. Consequently, the increasing number of road accidents is a driving force behind the adoption of AI in the transportation sector.

Major companies in the AI in transportation market are forming strategic partnerships to leverage valuable information and resources, fostering innovation and the development of new technologies. These partnerships enable collaboration, allowing companies to pool their expertise and resources to create innovative AI-driven transportation solutions. For example, in October 2023, Amazon, a US-based e-commerce giant, entered into a partnership with UVeye, an automatic vehicle inspection provider, to develop an AI-based technology called Automated Vehicle Inspection (AVI). AVI is designed to inspect delivery vans for anomalies such as tire deformities, undercarriage wear, and body deformations. The system performs a quick full-vehicle scan while the vehicle is moving at 5 mph, identifies issues, classifies them by severity, and sends results to a computer. This technology aims to enhance the safety of Amazon's delivery fleet and reduce the need for manual inspections.

Technological advancements are a prominent trend in the AI in transportation market, with major companies adopting new technologies to maintain their competitive positions. In March 2023, Alibaba Cloud, a Singapore-based cloud computing services provider, introduced EasyDispatch, an AI-driven logistics solution. This solution features an AI-powered real-time service dispatch system that enhances supply chain management and reduces logistics costs. It offers high-accuracy address processing and field service dispatch capabilities, providing high performance, stability, and fast access from any location.

In October 2022, Velodyne Lidar, a US-based lidar technology company, acquired the AI software company Bluecity for an undisclosed amount. This acquisition expands Velodyne's capabilities by incorporating AI-powered autonomous vision systems and lidar-based solutions to address safety, traffic, and infrastructure challenges. Bluecity, based in Canada, specializes in AI software for next-generation lidar-based solutions that detect and identify vehicles, bicycles, and pedestrians.

Major companies operating in the AI in transportation market include Volvo AB, Mercedes-Benz Group AG, Alphabet Inc., Intel Corporation, NVIDIA Corporation, Valeo SA, ZF Friedrichshafen AG, Continental AG, Magna International Inc., Microsoft Corporation, PACCAR Inc., Robert Bosch GmbH, Scania Group, Xevo Inc., Zonar Systems Inc., Daimler AG, Waymo LLC, Tesla Inc., Uber Technologies Inc., Mobileye Global Inc., Aptiv plc, TomTom N.V., HERE Technologies, Siemens AG, Cisco Systems Inc., IBM Corporation, Cognata Ltd., Argo AI, Aurora Innovation Inc., Zoox Inc., Embark Technology Inc., TuSimple Holdings Inc., PlusAI Inc.

North America was the largest region in the AI in transportation market in 2024. The regions covered in the ai in transportation market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the ai in transportation market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

AI in transportation involves the application of artificial intelligence technologies in various aspects of transportation, including autonomous vehicles, traffic management, and logistics. The primary goals of AI in transportation include improving passenger safety, reducing accidents and traffic congestion, minimizing carbon emissions, and lowering overall costs.

The main components of AI in transportation comprise hardware and software. Hardware refers to the physical infrastructure that forms the basis for computer systems and other electronic devices to operate. In AI transportation processes, key activities include signal recognition, object recognition, and data mining. Various technology types, such as natural language processing, deep learning, computer vision, and context-awareness, are applied in applications such as semi-autonomous trucks, truck platooning, predictive maintenance, precision mapping, autonomous trucks, machine-human interface, and others.

The AI in transportation market research report is one of a series of new reports that provides AI in transportation market statistics, including AI in transportation industry global market size, regional shares, competitors with a AI in transportation market share, detailed AI in transportation market segments, market trends and opportunities, and any further data you may need to thrive in the AI in transportation industry. This AI in transportation market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The AI in transportation market consists of revenues earned by entities by providing Intelligent traffic management, safety management, automatic traffic incident detection, advanced driver-assistance systems and route optimization. The market value includes the value of related goods sold by the service provider or included within the service offering. The AI in transportation market also includes sales of storage devices, network connectors, and storage IOPS. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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