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Impact of Artificial Intelligence on Autonomous Driving Development - Research and Markets

DUBLIN — (BUSINESS WIRE) — December 20, 2017 — The "Impact of Artificial Intelligence on Autonomous Driving Development" report has been added to Research and Markets' offering.

With the autonomous vehicle industry racing from zero to warp speed, every aspect of the driving world is set for innovation and transformation, and Artificial Intelligence (AI) development in autonomous driving is to bring that transformation, as it is capable of achieving more than what can be imagined.

For true enablement of Level 4 and Level 5 automated driving, the system should be functional in all weather and driving conditions. Deep learning is expected to be the most adopted approach to develop AI as it learns and starts to think by itself without the need of regular human intervention. This means that the AI will be capable of dealing with the several use cases displaying advanced levels of thinking which is required for autonomous vehicle to function in the real world.

This is what is happening in AI development for robotics, which is briskly percolating for AD development. Using deep neural networks, the system can make decisions that provide a clear understanding of the driving scenarios and can make justified decisions when driving in the autonomous mode.

Besides safety and autonomous driving, AI would be present in several aspects in the automotive industry such as speech recognition, computer vision, connected cars, and virtual assistants. OEMs in the market would like to partner with skilled startups to develop their capabilities to a broader sense.

Advantages of using the AI approach include low lead time for development, ease of testing, addition of a wider range of use cases for autonomous driving, and reduced cost of development as compared to the traditional approach. Object detection, classification, and subsequent learning for decision making based on an internally learnt algorithm to help fasten development.

Key Topics Covered:

1. Executive Summary

2. Research Scope and Segmentation

3. Automated Driving Artificial Intelligence versus Traditional Approach

4. Deep Learning in AI

5. Innovation Through Partnerships

6. Major OEM Activities

7. Growth Opportunities and Companies to Action

8. Conclusions and Future Outlook

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/research/cn3q9g/impact_of?w=4


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Related Topics: Automotive, Artificial Intelligence