Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Artificial Intelligence (AI) in Transportation Market 

5.1. COVID-19 Landscape: Artificial Intelligence (AI) in Transportation Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Artificial Intelligence (AI) in Transportation Market, By Offering

8.1. Artificial Intelligence (AI) in Transportation Market, by Offering, 2023-2032

8.1.1. Hardware

8.1.1.1. Market Revenue and Forecast (2020-2032)

8.1.2. Software

8.1.2.1. Market Revenue and Forecast (2020-2032)

Chapter 9. Global Artificial Intelligence (AI) in Transportation Market, By Machine Learning Technology

9.1. Artificial Intelligence (AI) in Transportation Market, by Machine Learning Technology e, 2023-2032

9.1.1. Deep Learning

9.1.1.1. Market Revenue and Forecast (2020-2032)

9.1.2. Deep Learning

9.1.2.1. Market Revenue and Forecast (2020-2032)

9.1.3. Context Awareness

9.1.3.1. Market Revenue and Forecast (2020-2032)

9.1.4. Context Awareness

9.1.4.1. Market Revenue and Forecast (2020-2032)

Chapter 10. Global Artificial Intelligence (AI) in Transportation Market, By Process 

10.1. Artificial Intelligence (AI) in Transportation Market, by Process, 2023-2032

10.1.1. Signal Recognition

10.1.1.1. Market Revenue and Forecast (2020-2032)

10.1.2. Object Recognition

10.1.2.1. Market Revenue and Forecast (2020-2032)

10.1.3. Data Mining

10.1.3.1. Market Revenue and Forecast (2020-2032)

Chapter 11. Global Artificial Intelligence (AI) in Transportation Market, By Application 

11.1. Artificial Intelligence (AI) in Transportation Market, by Application, 2023-2032

11.1.1. Semi Autonomous Truck

11.1.1.1. Market Revenue and Forecast (2020-2032)

11.1.2. Truck platooning

11.1.2.1. Market Revenue and Forecast (2020-2032)

11.1.3. Predictive maintenance

11.1.3.1. Market Revenue and Forecast (2020-2032)

11.1.4. Precision and mapping

11.1.4.1. Market Revenue and Forecast (2020-2032)

11.1.5. Autonomous truck

11.1.5.1. Market Revenue and Forecast (2020-2032)

11.1.6. Machine human interface

11.1.6.1. Market Revenue and Forecast (2020-2032)

11.1.7. Others

11.1.7.1. Market Revenue and Forecast (2020-2032)

Chapter 12. Global Artificial Intelligence (AI) in Transportation Market, Regional Estimates and Trend Forecast

12.1. North America

12.1.1. Market Revenue and Forecast, by Offering (2020-2032)

12.1.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.1.3. Market Revenue and Forecast, by Process (2020-2032)

12.1.4. Market Revenue and Forecast, by Application (2020-2032)

12.1.5. U.S.

12.1.5.1. Market Revenue and Forecast, by Offering (2020-2032)

12.1.5.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.1.5.3. Market Revenue and Forecast, by Process (2020-2032)

12.1.5.4. Market Revenue and Forecast, by Application (2020-2032)

12.1.6. Rest of North America

12.1.6.1. Market Revenue and Forecast, by Offering (2020-2032)

12.1.6.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.1.6.3. Market Revenue and Forecast, by Process (2020-2032)

12.1.6.4. Market Revenue and Forecast, by Application (2020-2032)

12.2. Europe

12.2.1. Market Revenue and Forecast, by Offering (2020-2032)

12.2.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.2.3. Market Revenue and Forecast, by Process (2020-2032)

12.2.4. Market Revenue and Forecast, by Application (2020-2032)

12.2.5. UK

12.2.5.1. Market Revenue and Forecast, by Offering (2020-2032)

12.2.5.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.2.5.3. Market Revenue and Forecast, by Process (2020-2032)

12.2.5.4. Market Revenue and Forecast, by Application (2020-2032)

12.2.6. Germany

12.2.6.1. Market Revenue and Forecast, by Offering (2020-2032)

12.2.6.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.2.6.3. Market Revenue and Forecast, by Process (2020-2032)

12.2.6.4. Market Revenue and Forecast, by Application (2020-2032)

12.2.7. France

12.2.7.1. Market Revenue and Forecast, by Offering (2020-2032)

12.2.7.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.2.7.3. Market Revenue and Forecast, by Process (2020-2032)

12.2.7.4. Market Revenue and Forecast, by Application (2020-2032)

12.2.8. Rest of Europe

12.2.8.1. Market Revenue and Forecast, by Offering (2020-2032)

12.2.8.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.2.8.3. Market Revenue and Forecast, by Process (2020-2032)

12.2.8.4. Market Revenue and Forecast, by Application (2020-2032)

12.3. APAC

12.3.1. Market Revenue and Forecast, by Offering (2020-2032)

12.3.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.3.3. Market Revenue and Forecast, by Process (2020-2032)

12.3.4. Market Revenue and Forecast, by Application (2020-2032)

12.3.5. India

12.3.5.1. Market Revenue and Forecast, by Offering (2020-2032)

12.3.5.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.3.5.3. Market Revenue and Forecast, by Process (2020-2032)

12.3.5.4. Market Revenue and Forecast, by Application (2020-2032)

12.3.6. China

12.3.6.1. Market Revenue and Forecast, by Offering (2020-2032)

12.3.6.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.3.6.3. Market Revenue and Forecast, by Process (2020-2032)

12.3.6.4. Market Revenue and Forecast, by Application (2020-2032)

12.3.7. Japan

12.3.7.1. Market Revenue and Forecast, by Offering (2020-2032)

12.3.7.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.3.7.3. Market Revenue and Forecast, by Process (2020-2032)

12.3.7.4. Market Revenue and Forecast, by Application (2020-2032)

12.3.8. Rest of APAC

12.3.8.1. Market Revenue and Forecast, by Offering (2020-2032)

12.3.8.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.3.8.3. Market Revenue and Forecast, by Process (2020-2032)

12.3.8.4. Market Revenue and Forecast, by Application (2020-2032)

12.4. MEA

12.4.1. Market Revenue and Forecast, by Offering (2020-2032)

12.4.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.4.3. Market Revenue and Forecast, by Process (2020-2032)

12.4.4. Market Revenue and Forecast, by Application (2020-2032)

12.4.5. GCC

12.4.5.1. Market Revenue and Forecast, by Offering (2020-2032)

12.4.5.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.4.5.3. Market Revenue and Forecast, by Process (2020-2032)

12.4.5.4. Market Revenue and Forecast, by Application (2020-2032)

12.4.6. North Africa

12.4.6.1. Market Revenue and Forecast, by Offering (2020-2032)

12.4.6.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.4.6.3. Market Revenue and Forecast, by Process (2020-2032)

12.4.6.4. Market Revenue and Forecast, by Application (2020-2032)

12.4.7. South Africa

12.4.7.1. Market Revenue and Forecast, by Offering (2020-2032)

12.4.7.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.4.7.3. Market Revenue and Forecast, by Process (2020-2032)

12.4.7.4. Market Revenue and Forecast, by Application (2020-2032)

12.4.8. Rest of MEA

12.4.8.1. Market Revenue and Forecast, by Offering (2020-2032)

12.4.8.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.4.8.3. Market Revenue and Forecast, by Process (2020-2032)

12.4.8.4. Market Revenue and Forecast, by Application (2020-2032)

12.5. Latin America

12.5.1. Market Revenue and Forecast, by Offering (2020-2032)

12.5.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.5.3. Market Revenue and Forecast, by Process (2020-2032)

12.5.4. Market Revenue and Forecast, by Application (2020-2032)

12.5.5. Brazil

12.5.5.1. Market Revenue and Forecast, by Offering (2020-2032)

12.5.5.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.5.5.3. Market Revenue and Forecast, by Process (2020-2032)

12.5.5.4. Market Revenue and Forecast, by Application (2020-2032)

12.5.6. Rest of LATAM

12.5.6.1. Market Revenue and Forecast, by Offering (2020-2032)

12.5.6.2. Market Revenue and Forecast, by Machine Learning Technology (2020-2032)

12.5.6.3. Market Revenue and Forecast, by Process (2020-2032)

12.5.6.4. Market Revenue and Forecast, by Application (2020-2032)

Chapter 13. Company Profiles

13.1. Volvo

13.1.1. Company Overview

13.1.2. Product Offerings

13.1.3. Financial Performance

13.1.4. Recent Initiatives

13.2. Daimler

13.2.1. Company Overview

13.2.2. Product Offerings

13.2.3. Financial Performance

13.2.4. Recent Initiatives

13.3. Scania

13.3.1. Company Overview

13.3.2. Product Offerings

13.3.3. Financial Performance

13.3.4. Recent Initiatives

13.4. Paccar

13.4.1. Company Overview

13.4.2. Product Offerings

13.4.3. Financial Performance

13.4.4. Recent Initiatives

13.5. Peloton

13.5.1. Company Overview

13.5.2. Product Offerings

13.5.3. Financial Performance

13.5.4. Recent Initiatives

13.6. Valeo

13.6.1. Company Overview

13.6.2. Product Offerings

13.6.3. Financial Performance

13.6.4. Recent Initiatives

13.7. Xevo

13.7.1. Company Overview

13.7.2. Product Offerings

13.7.3. Financial Performance

13.7.4. Recent Initiatives

13.8. ZF

13.8.1. Company Overview

13.8.2. Product Offerings

13.8.3. Financial Performance

13.8.4. Recent Initiatives

13.9. Zonar

13.9.1. Company Overview

13.9.2. Product Offerings

13.9.3. Financial Performance

13.9.4. Recent Initiatives

13.10. Tier-I Suppliers

13.10.1. Company Overview

13.10.2. Product Offerings

13.10.3. Financial Performance

13.10.4. Recent Initiatives

Chapter 14. Research Methodology

14.1. Primary Research

14.2. Secondary Research

14.3. Assumptions

Chapter 15. Appendix

15.1. About Us

15.2. Glossary of Terms