Artificial Intelligence in Transportation Market Applications, Future Trends, Recent Demand, Growth Analysis, Insights, Outlook, Size and Forecasts Report 2027

The study methodologies used to examine the Artificial Intelligence in Transportation market for the forecast period, 2020 – 2027 further classifies the industry by type, geography, end-use and end-user to add more precision and bring to light factors responsible for augmenting business development.

The global Artificial Intelligence in transportation market size is expected to reach USD 7,065.1 Million in 2028 and register a robust CAGR over the forecast period, according to latest analysis by Emergen Research. Steady revenue growth of the Artificial Intelligence in transportation market can be attributed to rising demand for safety and security in transportation and logistics and increasing deployment of more advanced traffic management solutions.

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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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.

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

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The subject matter experts conducting the study offer a deep understanding of how prominent leaders have managed to navigate the potential buyers and competitive dynamics influencing their brand positioning in the industry The Artificial Intelligence in Transportation market analysis provides everything a business owner needs in order to succeed.

Key questions answered in the report

What will be the market size in terms of value and volume in the next five years?

Which segment is currently leading the market?

In which region will the market find its highest growth?

Which players will take the lead in the market?

What are the key drivers and restraints of the market’s growth?

Research Methodology

Data triangulation and market breakdown

Research assumptions Research data including primary and secondary data

Primary data includes breakdown of primaries and key industry insights

Secondary data includes key data from secondary sources

The Artificial Intelligence in Transportation report highlights set of information related to pricing and the category of customers who are more than willing to pay for certain products and services. The information on opportunities as well as product features, determine which offerings or benefits command sale and identify the communications channels used by the  market leaders to create premium positioning strategies  as well as attract broadest share.

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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. Growing demand for growing medicinal application

                    4.2.2.2. Rising legalization of Artificial Intelligence in Transportation

                    4.2.2.3. Technological advancement in product invention

          4.2.3. Market restraints analysis

                    4.2.3.1. The complex regulatory framework for the usage of Artificial Intelligence in Transportation

    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

Continued…

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