
- 424 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Decision-Making Techniques for Autonomous Vehicles
About this book
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.
- Provides a complete overview of decision-making and control techniques for autonomous vehicles
- Includes technical, physical, and mathematical explanations to provide knowledge for implementation of tools
- Features machine learning to improve performance of decision-making algorithms
- Shows how regulations and ethics influence the development and implementation of these algorithms in real scenarios
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Decision-Making Techniques for Autonomous Vehicles by Jorge Villagra,Felipe Jiménez in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Automotive Transportation & Engineering. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Decision-making Techniques for Autonomous Vehicles
- Cover
- Title Page
- Copyright Page
- Table of Contents
- Contributors
- About the editors
- Chapter 1 Overview
- Chapter 2 Embodied decision architectures
- Chapter 3 Behavior planning
- Chapter 4 Motion prediction and risk assessment
- Chapter 5 Motion search space
- Chapter 6 Motion planning
- Chapter 7 End-to-end architectures
- Chapter 8 Interplay between decision and control
- Chapter 9 Traffic data analysis and route planning
- Chapter 10 Cooperative driving
- Chapter 11 Infrastructure impact
- Chapter 12 Driver behavior
- Chapter 13 Human-machine interaction
- Chapter 14 Algorithms validation
- Chapter 15 Legal and social aspects
- Index