The ai in transportation market has grown rapidly in recent years. It will grow from $3.25 billion in 2023 to $3.86 billion in 2024 at a compound annual growth rate (CAGR) of 18.6%. The growth observed in the historical period can be attributed to several factors, including optimization in traffic management, advancements in autonomous vehicle development, the increasing demand for intelligent public transportation solutions, the implementation of predictive maintenance for vehicles, and the rise of smart infrastructure initiatives.
The ai in transportation market is expected to see rapid growth in the next few years. It will grow to $7.62 billion in 2028 at a compound annual growth rate (CAGR) of 18.5%. The anticipated growth in the forecast period can be attributed to several factors, including the expansion of electric and connected vehicles, the integration of AI in urban mobility solutions, a focus on developing sustainable and smart cities, the incorporation of enhanced safety features, and the implementation of remote operations and monitoring systems. Noteworthy trends expected in the forecast period encompass advancements in AI algorithms and machine learning, government initiatives and regulations promoting AI in transportation, advancements in autonomous vehicles, the application of predictive maintenance with AI, and the integration of multimodal transportation systems.
The burgeoning number of vehicles is anticipated to drive the growth of the AI in transportation market. The rise in the vehicle count can be attributed to factors such as population growth, economic development, and limitations in public transportation infrastructure. AI plays a crucial role in optimizing traffic flow, mitigating congestion, and reducing travel times by analyzing real-time traffic data. This analysis allows for adjustments to signal timings and lane configurations. For example, as of March 2023, Hedges & Company reported a 0.9% increase in registered cars in the United States, rising from 286.9 million cars in 2020 to 289.5 million cars in 2021. Consequently, the escalating number of vehicles is a key driver propelling the growth 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 report are 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 2023. 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.
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 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.
This product will be delivered within 3-5 business days.
The ai in transportation market is expected to see rapid growth in the next few years. It will grow to $7.62 billion in 2028 at a compound annual growth rate (CAGR) of 18.5%. The anticipated growth in the forecast period can be attributed to several factors, including the expansion of electric and connected vehicles, the integration of AI in urban mobility solutions, a focus on developing sustainable and smart cities, the incorporation of enhanced safety features, and the implementation of remote operations and monitoring systems. Noteworthy trends expected in the forecast period encompass advancements in AI algorithms and machine learning, government initiatives and regulations promoting AI in transportation, advancements in autonomous vehicles, the application of predictive maintenance with AI, and the integration of multimodal transportation systems.
The burgeoning number of vehicles is anticipated to drive the growth of the AI in transportation market. The rise in the vehicle count can be attributed to factors such as population growth, economic development, and limitations in public transportation infrastructure. AI plays a crucial role in optimizing traffic flow, mitigating congestion, and reducing travel times by analyzing real-time traffic data. This analysis allows for adjustments to signal timings and lane configurations. For example, as of March 2023, Hedges & Company reported a 0.9% increase in registered cars in the United States, rising from 286.9 million cars in 2020 to 289.5 million cars in 2021. Consequently, the escalating number of vehicles is a key driver propelling the growth 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 report are 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 2023. 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.
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 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.
This product will be delivered within 3-5 business days.
Table of Contents
1. Executive Summary2. AI in Transportation Market Characteristics3. AI in Transportation Market Trends and Strategies31. Global AI in Transportation Market Competitive Benchmarking32. Global AI in Transportation Market Competitive Dashboard33. Key Mergers and Acquisitions in the AI in Transportation Market
4. AI in Transportation Market - Macro Economic Scenario
5. Global AI in Transportation Market Size and Growth
6. AI in Transportation Market Segmentation
7. AI in Transportation Market Regional and Country Analysis
8. Asia-Pacific AI in Transportation Market
9. China AI in Transportation Market
10. India AI in Transportation Market
11. Japan AI in Transportation Market
12. Australia AI in Transportation Market
13. Indonesia AI in Transportation Market
14. South Korea AI in Transportation Market
15. Western Europe AI in Transportation Market
16. UK AI in Transportation Market
17. Germany AI in Transportation Market
18. France AI in Transportation Market
19. Italy AI in Transportation Market
20. Spain AI in Transportation Market
21. Eastern Europe AI in Transportation Market
22. Russia AI in Transportation Market
23. North America AI in Transportation Market
24. USA AI in Transportation Market
25. Canada AI in Transportation Market
26. South America AI in Transportation Market
27. Brazil AI in Transportation Market
28. Middle East AI in Transportation Market
29. Africa AI in Transportation Market
30. AI in Transportation Market Competitive Landscape and Company Profiles
34. AI in Transportation Market Future Outlook and Potential Analysis
35. Appendix
Executive Summary
This report provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses on ai in transportation market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
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Description
Where is the largest and fastest growing market for ai in transportation? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? This report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include:
- The impact of sanctions, supply chain disruptions, and altered demand for goods and services due to the Russian Ukraine war, impacting various macro-economic factors and parameters in the Eastern European region and its subsequent effect on global markets.
- The impact of higher inflation in many countries and the resulting spike in interest rates.
- The continued but declining impact of COVID-19 on supply chains and consumption patterns.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.
Scope
Markets Covered:1) By Components: Hardware; Software
2) By Process: Signal Recognition; Object Recognition; Data Mining
3) By Technology Type: Natural Language Processing; Deep Learning; Computer Vision; Context-Awareness
4) By Application: Semi-Autonomous Truck; Truck Platooning; Predictive Maintenance; Precision And Mapping; Autonomous Truck; Machine Human Interface; Other Applications
Key Companies Mentioned: Volvo AB; Mercedes-Benz Group AG; Alphabet Inc.; Intel Corporation; NVIDIA Corporation
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain
Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita
Data Segmentation: Country and regional historic and forecast data, market share of competitors, market segments
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes
Delivery Format: PDF, Word and Excel Data Dashboard
Companies Mentioned
- 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.
Methodology
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