Decision-Making Techniques for Autonomous Vehicles

Häftad, Engelska, 2023

1 666 kr

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Beskrivning

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

Produktinformation

Utgivningsdatum:2023-03-09
Mått:152 x 229 x 33 mm
Vikt:680 g
Format:Häftad
Språk:Engelska
Antal sidor:424
Förlag:Elsevier Science
ISBN:9780323983396

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Mer om författaren

Jorge Villagra graduated in Industrial Engineering at the Technical University of Madrid (UPM) in 2002. He received his PhD in Real-Time Computer Science, Robotics and Automatic Control at the École des Mines de Paris (France) in 2006. From 2007 to 2009 he held a position of Visiting Professor at the University Carlos III (Spain). He then received a 3-year JAE Doc fellowship at the AUTOPIA Program in the Centre for Automation and Robotics, UPM-CSIC (Spain). From 2013 until 2016 he led the Department of ADAS and Autonomous Driving Systems at Ixion Industry & Aerospace SL. He is leading AUTOPIA Program at CSIC since October 2016. He has participated in over 40 R&D), being the principal investigator in half of them. He is a regular speaker in various specialised forums, participates as an independent expert for the European Commission and has published more than 100 articles in international journals and conferences on connected and automated driving. Felipe Jiménez obtained his Master Degree in Industrial Engineering (Mechanics) from the Technical University of Madrid (UPM), his Master Degree in Automotive Engineering from the UPM, his Master Degree in Physical Science (Electronics and Automation) from the National University of Distance Education of Spain and his PhD in Mechanical Engineering from the UPM in 2001, 2002, 2005 and 2006, respectively. Currently, he is Full Professor at the UPM and Research Deputy Director and Head of the Intelligent Systems Unit of the University Institute for Automobile Research of the UPM. His fields of interest are the automotive industry, vehicle safety, mechanical design, driver assistance systems and intelligent transport systems, mainly connected and automated driving. He has been involved in more than 40 R&D projects in the last 10 years and has developed engineering studies for relevant national firms. Furthermore, he is the leader of the Spanish Thematic Network on Intelligent Vehicles.

Innehållsförteckning

1. OverviewPART I: EMBEDDED DECISION COMPONENTS2. Embodied decision architectures3. Behavior planning4. Motion prediction and risk assessment5. Motion search space6. Motion planning7. End-to-end architectures8. Interplay between decision and controlPART II: INFRASTRUCTURE-ORIENTED DECISION-MAKING9. Traffic data analysis and route planning10. Cooperative driving11. Infrastructure impactPART III: USER INFLUENCE12. Driver behavior13. Human-machine interactionPART IV: DEPLOYMENT ISSUES14. Algorithms validation15. Legal and social aspects