Artificial Intelligence in transportation aids in acquiring traffic-related data, which in turn aids in reducing potential of traffic jams and helps to improve public transport efficiency through programming. AI is useful in reorganizing traffic patterns by using real-time tracking and intelligent traffic light scheduling algorithm, which enables smooth flow of traffic in areas of use. Vast volumes of traffic-related data are generated by traffic management systems, which are analyzed using AI systems to gain insights into traffic patterns. Rising demand for security and safety along with an increasing emphasis on decreasing operational transportation costs are factors driving demand for AI in transportation solutions.
Furthermore, AI assists in lowering fuel consumption and pollution levels, which otherwise would be higher in a conventional setting due to vehicles having to move slowly during traffic congestion and peak hours. E-commerce companies such as Amazon and Aliababa are investing in AI in order to improve efficiency of their respective distribution processes to gain an advantage in a highly competitive e-commerce industry.
The global Artificial Intelligence transportation market size is projected to reach USD 7,065.1 million in 2028 and register a CAGR of 17.2% during the forecast period. Growing emphasis on improving traffic management in various developed as well as developing countries is expected to result in increasing deployment of AI-based solutions and technologies and in turn, drive growth of the global AI in transportation market growth.
Rising demand for convenience and safety has provided OEMs with an opportunity to build new and advanced AI-based systems that will ease traffic-related challenges and also aid in further advancements going ahead. However, high cost of AI systems and slow infrastructure development are some major factors that could hamper market growth in the early phase of the forecast period.
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Some key Highlights in the report:
- The signal recognition segment contributed largest revenue share in 2020 due to increasing use of sensors in intelligent transportation systems for detecting vehicles heading towards an intersection.
- Deep learning segment accounted for largest revenue share in 2020 and is expected to register a significantly high CAGR during the forecast period. Deep learning algorithms assist in analyzing complex interactions of highways, traffic, roads, and even events leading to a vehicle accident. Deep learning has major potential in gathering and maintaining daily traffic data.
- The computer vision segment revenue is expected to register a significantly rapid CAGR during the forecast period. This can be attributed to vast utilization of computer vision applications in traffic management systems. Computer vision helps to maintain stable traffic flow and this solution has been gaining traction in street light detectors in smart cities.
- Asia Pacific is expected to register the fastest revenue CAGR in comparison to other regional markets throughout the forecast period owing to rapid developments in the transportation sector. Increasing sales of heavy commercial vehicles, and rising adoption of AI in transportation are factors expected to contribute to deployment of AI in transportation going ahead.
- Major companies operating in the Artificial Intelligence in transportation market include Daimler AG, Continental AG, Robert Bosch GmbH, VOLVO, PACCAR Inc., Magna International Inc., ZF Friedrichshafen AG, Scania AB, Valeo, and MAN SE.
- Daimler Trucks and Waymo signed a partnership agreement in October 2020 for the introduction of autonomous SAE L4 technology. Waymo’a automated driver technology will be combined with a cutting-edge version of Daimler’s Freightliner Cascadia for autonomous driving.
For the purpose of this report, Emergen Research has segmented the global Artificial Intelligence in transportation market in terms of process, learning technology, application, and region:
Process Outlook (Revenue, USD Million; 2018–2028)
- Signal Recognition
- Object Recognition
- Data Mining
Learning Technology Outlook (Revenue, USD Million; 2018–2028)
- Deep Learning
- Context Awareness
- Computer Vision
- Natural Language Processing
Application Outlook (Revenue, USD Million; 2018–2028)
- Autonomous Trucks
- HMI Trucks
- Semi-autonomous Trucks
Regional Outlook (Revenue, USD Million; 2018–2028)
North America
- S.
- Canada
Mexico
- Europe
- Germany
- UK
- France
- Italy
- Spain
- BENELUX
- Rest of Europe
Asia Pacific
- China
- India
- Japan
- South Korea
- Rest of APAC
Latin America
- Brazil
- Rest of LATAM
Middle East & Africa
- Saudi Arabia
- UAE
- South Africa
- Rest of Middle East & Africa
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