AI in Transportation Market Overview
The global AI in transportation market is expected to attain a size of $1.4 billion in 2017 and is forecasted to reach $3.5 billion by 2023, registering a CAGR of 16.5% during 2018–2023. The major factors driving the market growth are increasing concerns for driver and vehicle safety, growing focus towards reducing the transportation costs and development of autonomous vehicles.
GLOBAL AI IN TRANSPORTATION MARKET, BY TECHNOLOGY, $M (2013‒2023)
AI refers to those computer-operated tasks which otherwise require human intelligence, such as visual perception and decision making. Transportation is an important application area for AI, involving the use of deep learning, computer vision, and natural language processing (NLP) technologies. Fully autonomous vehicles on trial, use AI based software and a set of hardware such as video camera, light detection and ranging (LiDAR), and radio detection and ranging (RADAR) sensors. Such wide scope of applications has influenced the dynamics of AI in transportation market.
On the basis of application, the global AI in transportation market can be categorized into HMI and ADAS. Of the two, HMI is estimated to account for a larger share in the global market, mainly due to its higher penetration in trucks than ADAS. However, it is estimated that during the forecast period, the penetration of ADAS will increase at a faster rate.
Based on technology, the AI in transportation market is categorized into deep learning, computer vision, and NLP. Among these, the deep learning category is estimated to account for the largest share, as this technology is being increasingly used in various AI related applications in the development of self-driving trucks. This category would also see a robust growth during the forecast period, with trucks becoming more intelligent to drive on varying situations such as road terrains and unfavorable weather conditions.
Based on process, the AI in transportation market can be categorized into signal recognition and data mining. Of these, signal recognition is estimated to account for the larger share in the global AI in transportation market. This is so because signals in the form of text, tracking, gestures, mapping etc are being increasingly used in various safety applications, such as traffic sign detection and ACC. However, the fastest growth during the forecast period is expected from data mining, with growing influence of artificial intelligence in car safety and infotainment, requiring more data in the form of images and signals to be processed and analysed.
Globally, North America is estimated to be the largest market for AI in transportation in 2017, with the U.S., accounting for a significant share in the total North American sales during the year. Europe follows it as the second largest AI in transportation market.
The end-users in both the above regions are less cost-sensitive and willing to pay extra costs for advanced safety and convenient features. This, coupled with government support in the form of funding, regulations, and industry collaborations is benefiting the AI in transportation market in the two regions. The Asia-Pacific and RoW markets are still in the nascent stage, however, are expected to grow considerably during the forecast period
AI in Transportation Market Dynamics
Recently, AI in transportation industry has witnessed significant number of mergers and acquisitions, and partnership activities. For instance, in February 2018, Continental AG and NVIDIA Corporation announced that they have established partnership to create AI self-driving vehicle systems on the basis of NVIDIA DRIVE platform, with a planned market introduction in 2021 for level 3 features. The considerable number of mergers and acquisitions, open partnerships, and collaborations among existing players and start-up companies will reduce the overall cost and complexity, and increase profit. The consolidation trends in the AI in transportation market is likely to accelerate during the forecast period.
The safe and on-time movement of goods and cargo around the globe is a costly logistical challenge across the globe. AI creates numerous opportunities to reduce costs and improve operations for trucks, thereby driving the AI in transportation market. The truck platooning technology maintains an optimum speed and distance between trucks in the group, thereby reducing the overall time spent on the road. Advanced navigation alerts the driver of the optimised routes to avoid traffic jams and speed up the deliveries.
AI based technologies such as AEB and ACC reduce driver fatigue and avoid potential road accidents, thereby saving lives and reducing delivery times. Even though implementing AI features in trucks is expensive when compared to passenger cars, the return on investment (ROI) for trucks is higher considering the reduced delivery times and improved customer satisfaction. Higher ROI is expected to benefit the AI in transportation market during the forecast period.
The major restraint to the growth and development of AI in transportation market is the high cost of AI system. Most of the artificial intelligence applications are complex in nature and so, very expensive, which restrict its growth, especially in emerging economies. The high cost of AI system is due to the following factors:
The cost of LIDAR/RADAR sensor, cameras, GPS devices, hard drive, graphics card and other hardware and software devices is high, and increases the overall cost of AI system.
The need of advanced features such as blind spot detection, ADAS, ACC, and control wheel steering also adds up to the total cost of the AI system.
Owing to the high cost, the adoption of AI for the transportation sector mainly happens by bigger manufacturers only; thus, restraining the growth of the AI in transportation market.
AI in Transportation Market Competitive Landscape
Some of the major players operating in the AI in transportation market are ZF Friedrichshafen AG, Robert Bosch GmbH, Continental AG, Valeo SA, NVIDIA Corporation, Intel Corporation, Microsoft Corporation, Alphabet Inc.