AI in Transportation Market Analysis

AI in Transportation Market Overview

The AI in Transportation Market size is projected to grow from USD 2745.6 Million in 2024 to USD 6118.7 million by 2032, exhibiting a compound annual growth rate (CAGR) of 10.54% during the forecast period (2024 - 2032). Additionally, the market size for AI in Transportation was valued at USD 2402.1 million in 2023.

Artificial Intelligence (AI) is termed as one of the emerging fields transforming the transport sector. In recent years, AI has made a lot of progress, as machine learning techniques have been combined with technologies used to search and analyze the large quantities of data produced by the development of the digital world. The successful growth of AI can be attributed to the continuous development of communications networks and the Internet of Things, and the advancements in transport devices.

AI can make traffic more efficient, ease traffic congestion, free driver's time, make parking easier, and encourage car and ridesharing. As AI helps keep road traffic flowing, it can also reduce fuel consumption caused by vehicles idling when stationary and improve air quality and urban planning.

FIGURE 1: AI IN TRANSPORTATION MARKET SIZE 2019-2032 (USD MILLION)

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

As per Analyst at MRFR “The use of AI and 5G will ultimately improve road safety, reducing the total number of accidents on the road. Autonomous vehicles (AVs) or self-driving vehicles will be able to reduce the risk of alcohol or drug-impaired drivers getting behind the wheel of a conventional vehicle.”

AI in Transportation Market Trends

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  INCREASING FOCUS ON ENHANCING DRIVER AND VEHICLE SAFETY

  
  

A rising number of road accidents and deaths are a major global concern. Developing intelligent systems for road traffic is a way of solving road traffic safety and other such issues. Enabling an even faster connection between transport systems, the 5G network will offer new application options to advance autonomous cars. 5G is expected to have a positive impact on road maintenance with the rise of video and radar data. For instance, road maintenance crews will be able to receive alerts of life-threatening hazards on the road. The use of AI and 5G will ultimately improve road safety, reducing the total number of accidents on the road.

Autonomous vehicles (AVs) or self-driving vehicles will be able to reduce the risk of alcohol or drug-impaired drivers getting behind the wheel of a conventional vehicle. The continuing evolution of automotive technology aims to deliver greater safety benefits and deliver automated driving systems (ADS). Automated vehicles help reduce crashes, prevent injuries, and save lives. For instance, in June 2020, Mercedes-Benz partnered with NVIDIA to develop an in-vehicle computing system and an AI infrastructure for use in Mercedes models and is expected to roll out in 2024. NVIDIA’s AI computing architecture will aid Mercedes to streamline its progress in autonomous driving.

AI in Transportation Market Segment Insights

AI in Transportation Offering Insights

Based on Offering, the AI in Transportation Market segmentation includes (Hardware {CPU, GPU, Sensors, Others}, Services, Software {AI Platforms, AI Solutions}). Hardware will be the majority share in 2022, contributing around 48.2% to the market revenue. Rapid advancements in technology have enabled a variety of AI applications across industry verticals, one of which is transportation. However, every software application developed requires suitable hardware that forms a base to perform cognitive functions. Hardware components used in AI for transportation mainly consists of sensors, CPUs, GPUs, and others.

FIGURE 2: AI IN TRANSPORTATION MARKET, BY Offering, 2022 VS 2032 (USD BILLION)

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

AI in Transportation IoT Communication Technology Insights

Based on the IoT Communication Technology, the AI in Transportation Market segmentation is Cellular, LPWAN, LoRaWAN, Z-Wave, Zigbee, NFC, Bluetooth, Others. Cellular dominated the market in 2022. Cellular IoT technology for AI in the transportation market refers to incorporating artificial intelligence (AI) technologies into the cellular Internet of Things (IoT) ecosystem within the transportation industry. The cellular IoT technology allows devices and systems, such as vehicles, traffic lights, surveillance cameras, and infrastructure, to be connected and communicate using wireless cellular networks.

This connectivity enables data collection, real-time monitoring, and control of various aspects of transportation. With the integration of AI, cellular IoT technology can enhance the efficiency, safety, and overall performance of transportation systems. AI algorithms and machine learning models can analyse the vast data from IoT devices to make intelligent decisions and predictions in real time.

AI in Transportation Application Insights

Based on Application, the AI in Transportation Market segmentation includes Autonomous Truck, Semi-autonomous Truck, Truck Platooning, Human-Machine Interface (HMI), Predictive Maintenance, Precision & Mapping, Traffic Detection, Computer Vision-Powered Parking Management, Road Condition Monitoring, Automatic Traffic Incident Detection, Driver Monitoring, Others. The Predictive Maintenance held the majority share in 2022. Breakdown of vehicles may cause several annoying situations for an organization causing major delays in delivering goods, expensive repairs, and financial losses. Predictive maintenance may overcome this problem with data-driven insights designed with the help of algorithms and machine learning techniques. This system predicts when the parts will fail, based on the historical performance data gathered from the sensing technologies and other information to preventively manage the fleets and reduce the vehicle breakdown and cost required for heavy maintenance repairs.

AI in Transportation Machine Learning Technology Insights

Based on Machine Learning Technology, the AI in Transportation Market segmentation includes Deep Learning, Computer Vision, Natural Language Processing, Context Awareness. Computer Vision segment dominates the market in 2022 contributing 33.7% of total market share. Computer vision technology involves a high-performance computing system that interprets and gains knowledge from the graphical content generated and identified by the camera system enabled with deep learning models. With this, the organization can improve traffic management, driver and passenger safety, monitor & control criminal activities on-board, and asset protection.

AI in Transportation Regional Insights

By Region, the study provides market insights into North America, Europe, Asia-Pacific, Middle East and Africa and South America. The North America AI in Transportation market accounted for ~39.8% in 2022. North America is likely to be the largest contributor to the AI transportation market. This includes the US, Canada, and Mexico. Some of the factors responsible for the growth of the market include the rising need for enhanced operational efficiency and increasing adoption to enhance driver and vehicle. Moreover, the presence of established players such as Intel Corporation, Microsoft Corporation, IBM Corporation, Magna International Inc. is one of the factors driving the growth of the regional market.

Canada is likely to follow the US in terms of regional market share. The growth of the regional market can be attributed to the increasing need for vehicle safety in autonomous vehicles and achieving operational efficiency. For instance, in November 2020, The Magna International launched Gen5 “one-box” solution is a Mobileye EyeQ5-based system—one of the industry’s first where the forward-facing camera and related software are contained in a single assembly.

FIGURE 3: AI IN TRANSPORTATION MARKET SIZE BY REGION 2022 VS 2032

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

Further, the major countries studied in the market report are the U.S., Canada, Germany, France, the UK, Italy, Spain, China, Japan, India, South Korea, and Brazil.

AI in Transportation Key Market Players & Competitive Insights

The global market for AI in transportation has witnessed significant growth over the forecast period due to the growing need for enhanced vehicle safety. There are several domestic, regional, and global players operating in the AI in transportation market who continuously strive to gain a significant share of the overall market. During the study, MRFR has analyzed some of the major players in the AI in Transportation Market who have contributed to the market growth. These include Siemens Mobility, Nvidia Corporation, NEC Corporation, Huawei Technologies Co. Ltd, Valeo, Daimler AG, Scania, Continental AG, Magna International Inc., Intel Corporation, IBM Corporation, AB Volvo, Microsoft, Robert Bosch GmbH, and ZF Friedrichshafen AG.

Among these, Robert Bosch GmbH, Continental AG, Daimler AG, Nvidia Corporation, and ZF Friedrichshafen AG are among the top 5 players in the AI in Transportation Market. These players focus on expanding and enhancing their product portfolio and services to remain competitive and increase their customer base. Additionally, these players are focusing on partnerships & collaborations to expand their business and customer base to enhance their market position.

Key Companies in the AI in Transportation market include.

• Siemens Mobility


• Huawei Technologies Co.,Ltd.


• Intel Corporation


• NEC Corporation


• Microsoft


• IBM


• Robert Bosch GmbH


• Valeo


• Daimler AG


• Scania AB


• Continental AG


• Magna International Inc.


• Volvo


• ZF Friedrichshafen AG


• Nvidia

AI in Transportation Industry Developments

April 2024

Purdue University is at the forefront of endeavors to transform Indiana into the cyber crossroads of the United States. It is anticipated that by 2027, close to one million commercial unmanned aircraft systems (UAVs) will be operational across the United States, performing functions beyond parcel delivery. In addition to supplying aid for health care, defense, humanitarian assistance, and emergency services, these unmanned aerial vehicles will also aid in the fight against wildfires.

Purdue is establishing a pioneering center to employ machine learning (ML) and artificial intelligence (AI) in order to improve the safety, efficiency, and scalability of these transportation systems in response to this anticipated demand. AidA3, an initiative of the Center on AI for Digital, Autonomous and Augmented Aviation, is dedicated to generating advancements that can be readily expanded in response to the increasing demand for autonomous systems, including unmanned aerial vehicles (UAVs).

Founders of AIDA3, Purdue and Windracers, each contribute substantial capabilities that enable the rapid development of technologies for an ever-evolving market.

Windracers, a leader in low-cost logistics, is providing the Royal Mail, Royal Navy, and the British Antarctic Survey with invaluable real-world experience via its patented automation system on large-scale UAVs.

Purdue University possesses a substantial reservoir of research prowess spanning multiple academic fields, including agriculture, engineering, liberal arts, science, and polytechnic.

AIDA3 will investigate AI and ML models for autonomous transportation applications encompassing meteorological sensing, real-time weather prediction, and demand analytics and maintenance in commercial logistics.

Purdue is extremely proud to partner with Windracers because AIDA3 is committed to addressing urgent societal issues, according to Purdue's executive vice president of research, Karen Plaut. "The innovations we create in the laboratory will have a significant impact when implemented in the actual world. The combination of Purdue's research prowess and achievements in aviation and AI with Windracers' knowledge of future transportation constitutes a formidable innovation engine.

AI in Transportation Market Segmentation

AI in Transportation Offering Outlook

• Hardware
  
  
  
  • CPU
  
  
  • GPU
  
  
  • Sensors
  
  
  • Others
  
  
  
  


• Services
  
  
  
  • Software
  
  
  • AI Platforms
  
  
  • AI Solutions
  
  
  
  

AI in Transportation IoT Communication Technology Outlook

• Cellular


• LPWAN


• LoRaWAN


• Z-Wave


• Zigbee


• NFC


• Bluetooth


• Others

AI in Transportation Application Areas Outlook

• Autonomous Truck


• Semi-autonomous Truck


• Truck Platooning


• Human-Machine Interface (HMI)


• Predictive Maintenance


• Precision & Mapping


• Traffic Detection


• Computer Vision-Powered Parking Management


• Road Condition Monitoring


• Automatic Traffic Incident Detection


• Driver Monitoring


• Others

AI in Transportation Machine Learning Technology Outlook

• Deep Learning


• Computer Vision


• Natural Language Processing


• Context Awareness

AI in Transportation Regional Outlook

• North America
  
  
  
  • US
  
  
  • Canada
  
  
  
  


• Mexico
  
  
  
  • Europe
  
  
  • UK
  
  
  • Germany
  
  
  • France
  
  
  • Spain
  
  
  • Rest of Europe
  
  
  
  


• Asia-Pacific
  
  
  
  • China
  
  
  • Japan
  
  
  • India
  
  
  • Rest of Asia-Pacific
  
  
  
  


• Middle East & Africa
  
  
  
  • South America