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Deep Learning for Autonomous Vehicle Control

- Algorithms, State-of-the-Art, and Future Prospects
Af: Sampo Kuutti, Phil Barber, Saber Fallah, Richard Bowden Engelsk Paperback

Deep Learning for Autonomous Vehicle Control

- Algorithms, State-of-the-Art, and Future Prospects
Af: Sampo Kuutti, Phil Barber, Saber Fallah, Richard Bowden Engelsk Paperback
Tjek vores konkurrenters priser

The next generation of autonomous vehicles will provide major improvements in traffic flow, fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of autonomous vehicles, one aspect of which is robust and adaptable vehicle control. Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which it may encounter after deployment. However, deep learning methods have shown great promise in not only providing excellent performance for complex and non-linear control problems, but also in generalizing previously learned rules to new scenarios. For these reasons, the use of deep neural networks for vehicle control has gained significant interest.

In this book, we introduce relevant deep learning techniques, discuss recent algorithms applied to autonomous vehicle control, identify strengths and limitations of available methods, discuss research challenges in the field, and provide insights into the future trends in this rapidly evolving field.

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The next generation of autonomous vehicles will provide major improvements in traffic flow, fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of autonomous vehicles, one aspect of which is robust and adaptable vehicle control. Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which it may encounter after deployment. However, deep learning methods have shown great promise in not only providing excellent performance for complex and non-linear control problems, but also in generalizing previously learned rules to new scenarios. For these reasons, the use of deep neural networks for vehicle control has gained significant interest.

In this book, we introduce relevant deep learning techniques, discuss recent algorithms applied to autonomous vehicle control, identify strengths and limitations of available methods, discuss research challenges in the field, and provide insights into the future trends in this rapidly evolving field.

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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 70
ISBN-13: 9783031003745
Indbinding: Paperback
Udgave:
ISBN-10: 3031003748
Kategori: Maskinteknik
Udg. Dato: 8 aug 2019
Længde: 0mm
Bredde: 191mm
Højde: 235mm
Forlag: Springer International Publishing AG
Oplagsdato: 8 aug 2019
Forfatter(e): Sampo Kuutti, Phil Barber, Saber Fallah, Richard Bowden
Forfatter(e) Sampo Kuutti, Phil Barber, Saber Fallah, Richard Bowden

Kategori Maskinteknik

ISBN-13 9783031003745

Sprog Engelsk

Indbinding Paperback

Sider 70

Udgave

Længde 0mm

Bredde 191mm

Højde 235mm

Udg. Dato 8 aug 2019

Oplagsdato 8 aug 2019

Forlag Springer International Publishing AG

Kategori sammenhænge