Artificial Intelligence in Transportation Market Professional Survey with Product Specification & Regional Analysis

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Artificial Intelligence in Transportation Market is projected to grow at a CAGR of 17.87% from 2017 to 2030, and the market size is expected to grow from USD 1.21 Billion in 2017 to USD 10.30 Billion by 2030. The market growth is primarily driven by factors such as increasing demand for assisted driving, increasing level of automation, and enhanced connectivity. Other factors driving the growth of the artificial intelligence in transportation market are a reduction in the number of accidents caused due to human error and demand for reduced traffic congestion.
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The key strategy adopted by the major players in the artificial intelligence in transportation market is supply contracts/partnerships/joint ventures. OEMs along with Tier-I suppliers and software suppliers have joined hands to gain a competitive advantage in the artificial intelligence in transportation market. Leading players are collaborating with regional players to cater to the growing demand. For instance, in April 2017, Bosch and the University of Amsterdam decided to collaborate in the field of artificial intelligence. Over the next four years, Bosch will make a total investment of USD 3.34 million in this partnership. New product development is the second most widely followed strategy in the market. In July 2016, ZF launched a ‘Highway Driving Assist Multi-Lane’ system, which combines environmental sensing, braking, automatic steering, and acceleration to maintain vehicle control.

Key Players of Artificial Intelligence in Transportation Market:

Original Equipment Manufacturers (OEMS) :

  • Volvo
  •   Daimler
  •   Scania
  •   Paccar
  •   Man

Tier-I Suppliers :

  •   Continental
  •    Magna
  •    Bosch
  •    Valeo
  •    ZF

Software Suppliers :

  • Nvidia
  • Alphabet
  •  Intel
  •  Microsoft
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The artificial intelligence in transportation market is dominated by a few global players and comprises several regional players. In the software/service providers segment, NVIDIA (US) is a leading player in the artificial intelligence in transportation market and is among the world leaders in the visual computing business. The company has a well-established geographic footprint and deals with major OEMs and original design manufacturers (ODMs) across the globe. In addition, the company has a first-mover advantage with the launch of DRIVE PX, an open AI vehicle computing platform, in January 2017. The company has also made a substantial investment in its R&D division. It has adopted the strategy of supply contracts/partnerships/joint ventures to increase its presence in the artificial intelligence in transportation market. In July 2017, NVIDIA (US) partnered with Baidu (China) to bring the artificial intelligence (AI) technology to self-driving vehicles, cloud computing, and AI home assistants.
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Volvo (Sweden) is identified as the leading player among OEMs in the artificial intelligence in transportation market. The company has a robust product portfolio in transportation sector such as city buses, coaches, and others. The company offers premium products and services related to artificial intelligence such as self-driving trucks, HMI, fleet management, and others. Volvo (Sweden) has been working on truck automation for 20 years. The company follows the strategy of new product development to gain a competitive advantage in the artificial intelligence in transportation market. In July 2017, the company launched its new “VNL” series of semi-trucks, which offer many self-driving features and safety systems such as forward collision warning, adaptive cruise control, lane departure warning, and automatic emergency braking. Similarly, in May 2017, the company launched an integrated system for infotainment and services in vehicles.
Related Reports:
Artificial Intelligence in Transportation Market by Machine Learning (Deep Learning, Computer Vision, Context Awareness, NLP), Application (Semi & Full-Autonomous, HMI, Platooning), Offering (Hardware, Software), Process, and Region – Global Forecast to 2030
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