422,00 €
468,89 €
-10% with code: EXTRA
Decision-Making Techniques for Autonomous Vehicles
422,00 € 
- We will send in 10–14 business days.
Decision-Making Techniques for Autonomous Vehicles provides a general overview of control and decision-making tools that could be used in autonomous vehicles. Motion prediction and planning tools are presented, along with the use of machine learning and adaptability to improve performance of algorithms in real scenarios. The book then examines how driver monitoring and behavior analysis are used produce comprehensive and predictable reactions in automated vehicles. The book ultimately covers re…
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- Publisher: Elsevier
- ISBN-10: 0323983391
- ISBN-13: 9780323983396
- Format: 15.2 x 22.9 x 2.2 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Decision-Making Techniques for Autonomous Vehicles (e-book) (used book) | bookbook.eu
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Decision-Making Techniques for Autonomous Vehicles provides a general overview of control and decision-making tools that could be used in autonomous vehicles. Motion prediction and planning tools are presented, along with the use of machine learning and adaptability to improve performance of algorithms in real scenarios. The book then examines how driver monitoring and behavior analysis are used produce comprehensive and predictable reactions in automated vehicles. The book ultimately covers regulatory and ethical issues to consider for implementing correct and robust decision-making. This book is for researchers as well as Masters and PhD students working with autonomous vehicles and decision algorithms.EXTRA 10 % discount with code: EXTRA
422,00 €
468,89 €
We will send in 10–14 business days.
The promotion ends in 16d.00:26:47
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Publisher: Elsevier
- ISBN-10: 0323983391
- ISBN-13: 9780323983396
- Format: 15.2 x 22.9 x 2.2 cm, softcover
- Language: English English
Decision-Making Techniques for Autonomous Vehicles provides a general overview of control and decision-making tools that could be used in autonomous vehicles. Motion prediction and planning tools are presented, along with the use of machine learning and adaptability to improve performance of algorithms in real scenarios. The book then examines how driver monitoring and behavior analysis are used produce comprehensive and predictable reactions in automated vehicles. The book ultimately covers regulatory and ethical issues to consider for implementing correct and robust decision-making. This book is for researchers as well as Masters and PhD students working with autonomous vehicles and decision algorithms.
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