Artificial Intelligence in Transportation Market Report

Market Insights

The global artificial intelligence in transportation market is expected to grow from USD 2.89 billion in 2022 to USD 6.30 billion by 2029 at a CAGR of 11.8% during the forecast period.

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Artificial Intelligence (AI) in transportation refers to the use of AI technologies to enhance transportation systems and improve transportation efficiency. AI can be used to automate tasks, analyze data, and improve decision-making processes. For instance, AI can be used to optimize transportation routes, predict traffic congestion, and improve fuel efficiency.

Machine learning algorithms can analyze large amounts of data and identify patterns of behavior, enabling transportation companies to make more informed decisions and respond quickly to changes in demand or supply. Additionally, AI can be used to improve safety on the roads by detecting and responding to potential hazards and alerting drivers to potential risks.

The use of AI in transportation can improve operational efficiency, reduce costs, and enhance safety and sustainability. Overall, AI is transforming the transportation industry by enabling companies to work smarter and more efficiently while improving safety and sustainability.

Key Players

The major players operating in the global artificial intelligence in transportation market are:

• Volvo
• Daimler
• Scania
• Paccar
• Man
• Continental
• Magna
• Bosch
• Valeo
• ZF
• NVIDIA
• Alphabet
• Intel
• Microsoft
• Peloton
• Nauto
• Xevo
• Zonar

Market Dynamics

The growth of AI in the transportation market is being fueled by the advancement of autonomous vehicles. Major vehicle original equipment manufacturers (OEM) are making significant investments to optimize self-driving technology, particularly in the automotive industry. Consequently, the integration of autonomous vehicles with intelligent features is anticipated to drive market growth on a global scale.

Market growth is also being propelled by the rising need for traffic management solutions. Robust traffic management systems that incorporate cameras and sensors embedded in the road rely heavily on AI technology. These systems generate vast amounts of traffic-related data, which are then analyzed using AI systems to gain insights into traffic patterns. The increasing emphasis on improving traffic management in developed and developing countries is anticipated to further drive market growth in the foreseeable future.

AI is also being utilized to improve logistics operations, with the aim of reducing transportation costs. Through the implementation of better traffic management solutions, optimal routes can be identified for last-mile operations, leading to decreased freight costs. Major e-commerce companies like Alibaba and Amazon are making significant investments in AI technology to enhance the efficiency of their delivery processes and gain a competitive edge in the e-commerce market.

In Tokyo, autonomous taxis are already in operation, and their manufacturers claim that the technology will lead to a decrease in taxi service costs. This reduction in costs could potentially increase the availability of public transportation in remote areas. Additionally, the logistics industry in the US is adopting autonomous trucks to reap the many benefits they offer. Globally, 70% of goods are transported via trucks, according to a recent study.

In contrast, cloud-based AI systems require expensive bandwidth to power the system, which can lead to high operating costs. Additionally, AI is a new and rapidly developing technology solution that requires specialized training and skills, which can also increase the cost of implementation and operation.

The development and maintenance of the network of individual processors, relays, and other components that make up AI-operated machines also require a significant amount of energy, further contributing to the high cost of operation. These challenges can adversely affect the growth of AI in the transportation market. These significant challenges result in a high operating cost of AI when used in transportation.

The machines operated by AI consist of a network of individual processors, relays, and other components that require regular maintenance and replacement, as well as a substantial amount of energy to operate. These challenges negatively impact the growth of artificial intelligence in the transportation market.

Segment Analysis

Application Insights

The AI in transportation market is categorized by application into Autonomous Trucks, HMI in Trucks, and Semi-Autonomous Trucks. Among these, Autonomous Trucks held the largest market share globally in 2022. This is primarily due to the growing development in the trucking industry, which is increasing the demand for autonomous trucks.

Furthermore, the logistics industry's growth in the US for the transportation of goods is driving the need for autonomous trucks. The deployment of autonomous trucks is also expected to result in a reduction of maintenance and administrative expenses by about 45%. By 2029, HMI is projected to have a larger market share in the AI transportation market. This growth is mainly attributed to its higher penetration of HMI in trucks compared to advanced driver-assistance systems (ADAS) systems.

Offering Insights

The AI in transportation market is also categorized based on offering, with segments including Hardware and Software. In 2022, the software segment held a larger market share in the AI in transportation market. This is mainly due to the growing use of software as a service platforms (such as Microsoft Azure) in human-machine interface (HMI) applications.

Learning Technology Insights

The Artificial Intelligence in transportation market has been further segmented by learning technology into deep learning, context awareness, computer vision, and Natural Language Processing. In 2022, the deep learning segment held the highest revenue share contribution to the AI in transportation market compared to other regions.

Deep learning algorithms play a crucial role in exploring the complex interactions of highways, roads, traffic, crashes, and environmental elements. They also have significant potential in managing day-to-day traffic and collecting traffic data.

Geographic Analysis

The North American region held the largest share in the AI in transportation market, followed by Europe and Asia-Pacific in 2022. The use of automated cars and the integration of self-driving vehicles onto US roadways are major factors accelerating the growth of the market in North America. The transportation and logistics industry in the US is also driving the adoption of AI-based self-driving trucks for reduced operational costs, further boosting the market growth.

Asia Pacific is projected to grow at the highest compound annual growth rate (CAGR) during the forecast period (2022-2029). This is mainly due to the high sales of trucks in the region and the increasing adoption of AI in transportation in developing countries like Japan and China.

Japan is expected to be the fastest-growing country in the AI in transportation market during the forecast period. With the growing truck market in Japan, companies are finding new revenue streams by integrating AI-enabled features in trucks, which is further supporting the growth of AI in the transportation market in the Asia Pacific region.

Research Methodology

This report offers high-quality insights and is the outcome of a detailed research methodology comprising extensive secondary research, rigorous primary interviews with industry stakeholders, and validation and triangulation with Stratview Research’s internal database and statistical tools.

More than 1,000 authenticated secondary sources, such as company annual reports, fact books, press releases, journals, investor presentations, white papers, patents, and articles, have been leveraged to gather the data.

We conducted more than 15 detailed primary interviews with the market players across the value chain in all four regions and industry experts to obtain both qualitative and quantitative insights.

Report Features

This report provides market intelligence in the most comprehensive way. The report structure has been kept such that it offers maximum business value. It provides critical insights into the market dynamics and will enable strategic decision making for the existing market players as well as those willing to enter the market. The following are the key features of the report:

• Market structure: Overview, industry life cycle analysis, supply chain analysis.
• Market Environment analysis: Growth drivers and constraints, Porter’s five forces analysis, SWOT analysis.
• Market trend and forecast analysis.
• Market segment trend and forecast.
• Competitive landscape and dynamics: Market share, Product Portfolio, New Product Launches, etc.
• Attractive market segments and associated growth opportunities.
• Emerging trends.
• Strategic growth opportunities for the existing and new players.
• Key success factors.

Customization Options

With this detailed report, Stratview Research offers one of the following free customization options to our respectable clients:

Company Profiling

• Detailed profiling of additional market players (up to three players)
• SWOT analysis of key players (up to three players)

Competitive Benchmarking

• Benchmarking of key players on the following parameters: product portfolio, geographical reach, regional presence, and strategic alliances

Custom Research: Stratview research offers custom research services across the sectors. In case of any custom research requirement related to market assessment, competitive benchmarking, sourcing and procurement, target screening, and others, please send your inquiry to sales@Stratviewresearch.com

Recent Developments

• In February 2023, Mercedes-Benz and Google partnered to create next-generation navigation experience.
• In January 2023, Germany's Continental and US-based AI chip firm Ambarella entered into a partnership to make software and hardware systems for autonomous driving.
• In October 2022, Seeing Machines Limited, an advanced computer vision technology company that designs AI-powered operator monitoring systems to improve transport safety, signed a collaboration agreement with Magna International, to pursue driver and occupant monitoring system business aiming at the vehicle's interior rear-view mirror.