Vancouver, BC -- (SBWIRE) -- 04/21/2021 -- The Global Artificial Intelligence in Transportation Market study includes a profound analysis of this business sphere focusing on the overall remuneration over the projected period, as well as scrutinizing every single industry segment at length. It is further inclusive of significant information related to the industry size and the current market scenario. The report presents an overview of the key drivers, opportunities, and restraints of the market, which clearly define its position on a global level.

Artificial Intelligence (AI) in transportation is used to gather traffic data to decrease traffic congestion and enhance public transport scheduling. AI helps in streamlining traffic patterns through real-time tracking and intelligent traffic light algorithms, thereby enabling smooth traffic flow, which significantly improves various aspects in transportation. Besides, AI helps in decreasing fuel consumption and exhaust emissions, which would otherwise be higher in a normal setting as a result of numerous vehicles moving slowly during a traffic jam or congestion.

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Some Key Highlights in the Report

In October 2020, Daimler Trucks entered into a partnership agreement with Waymo for deployment of autonomous SAE L4 technology. The partnership is intended to combine the automated driver technology of Waymo with a cutting-edge version of Freightliner Cascadia of Daimler for autonomous driving.
Signal recognition segment accounted for largest revenue share in 2020. Signal recognition and processing is used in intelligent transportation systems, which comprise technologies deployed in roadways and vehicles for management and enhancement of traffic flow. Signal recognition-based systems are used for detection of vehicles as they approach an intersection, thereby enabling traffic control systems to regulate traffic lights when needed.
Computer vision finds widespread use in traffic management systems. It aids in maintaining a steady traffic flow, leading to fewer congestions. Computer vision is also used in smart cities in the functioning of ambient light detectors in streetlights.
The Artificial Intelligence in transportation market in Asia Pacific is expected to register the fastest revenue growth rate as compared to other regional markets over the forecast period, owing to rapid growth of the transportation sector, rising sales of heavy commercial vehicles, and increasing use of AI in transportation, traffic management, and logistics.
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.

Artificial Intelligence in Transportation Market Segmentation:

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; 2021–2028)
Signal Recognition
Object Recognition
Data Mining

Learning Technology Outlook (Revenue, USD Million; 2021–2028)
Deep Learning
Context Awareness
Computer Vision
Natural Language Processing

Application Outlook (Revenue, USD Million; 2021–2028)
Autonomous Trucks
HMI Trucks
Semi-autonomous Trucks

Key Regions analyzed in the report include:

North America (U.S., Canada)
Europe (U.K., Italy, Germany, France, Rest of EU)
AsiaPacific (India, Japan, China, South Korea, Australia, Rest of APAC)
Latin America (Chile, Brazil, Argentina, Rest of Latin America)
Middle East & Africa (Saudi Arabia, U.A.E., South Africa, Rest of MEA)

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Elucidating the competitive scenario of the Global Artificial Intelligence in Transportation Market:

The comprehensive global Artificial Intelligence in Transportation market analysis includes meaningful insights into the competitive spectrum of this business sphere. It goes on to enlist the detailed profiles of each market competitor.
The latest report includes the industry share, production facilities, development prospects,and geographies served by each market player.
The study also showcases the extensive product portfolios of the prominent market contenders and offers critical data and information about the application scope, as well as specifications of these products.
In addition, the study presents the fundamental market insights, pricing range of products offered by these companies, and the gross profits and losses experienced by these players throughout their market tenures.

Table of Content

Chapter 1. Methodology & Sources
    1.1. Market Definition
    1.2. Research Scope 
    1.3. Methodology
    1.4. Research Sources
          1.4.1. Primary
          1.4.2. Secondary
          1.4.3. Paid Sources
    1.5. Market Estimation Technique
Chapter 2. Executive Summary
    2.1. Summary Snapshot, 2019-2027
Chapter 3. Key Insights
Chapter 4. Artificial Intelligence in Transportation Market Segmentation & Impact Analysis
    4.1. Artificial Intelligence in Transportation Market Material Segmentation Analysis
    4.2. Industrial Outlook
          4.2.1. Market indicators analysis
          4.2.2. Market drivers analysis
                    4.2.2.1. Increasing demand for safety and security in transportation
                    4.2.2.2. Rising demand for operating efficiency
                    4.2.2.3. Growing demand for autonomous vehicles
                    4.2.2.4. Increasing demand for traffic management systems
          4.2.3. Market restraints analysis
                    4.2.3.1. Cost-prohibitive Artificial Intelligence systems
    4.3. Technological Insights
    4.4. Regulatory Framework
    4.5. Porter's Five Forces Analysis
    4.6. Competitive Metric Space Analysis
    4.7. Price trend Analysis
    4.8. Covid-19 Impact Analysis

Chapter 5. Artificial Intelligence in Transportation Market By Process Insights & Trends, Revenue (USD Million)  
    5.1. Process Dynamics & Market Share, 2019 & 2027
          5.1.1. Signal recognition
          5.1.2. Object recognition
          5.1.3. Data Mining

CONTINUED..!!

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