Creating Autonomous Vehicle Systems

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Creating Autonomous Vehicle Systems, Second Edition

Liu Shaoshan,Li Liyun,Tang Jie,Wu Shuang,Gaudiot Jean-Luc
Creating Autonomous Vehicle Systems Second Edition Book PDF

Author : Liu Shaoshan,Li Liyun,Tang Jie,Wu Shuang,Gaudiot Jean-Luc
Publisher : Springer Nature
Page : 221 pages
File Size : 46,9 Mb
Release : 2022-05-31
Category : Mathematics
ISBN : 9783031018053

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Creating Autonomous Vehicle Systems, Second Edition by Liu Shaoshan,Li Liyun,Tang Jie,Wu Shuang,Gaudiot Jean-Luc Pdf

This book is one of the first technical overviews of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions as to its future actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map—in addition to training better recognition, tracking, and decision models. Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the authors received many helpful comments and feedback from readers. Based on this, the second edition was improved by extending and rewriting multiple chapters and adding two commercial test case studies. In addition, a new section entitled “Teaching and Learning from this Book” was added to help instructors better utilize this book in their classes. The second edition captures the latest advances in autonomous driving and that it also presents usable real-world case studies to help readers better understand how to utilize their lessons in commercial autonomous driving projects. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find extensive references for an effective, deeper exploration of the various technologies.

Creating Autonomous Vehicle Systems

Liu Shaoshan,Li Liyun,Tang Jie,Wu Shuang,Gaudiot Jean-Luc
Creating Autonomous Vehicle Systems Book PDF

Author : Liu Shaoshan,Li Liyun,Tang Jie,Wu Shuang,Gaudiot Jean-Luc
Publisher : Springer Nature
Page : 192 pages
File Size : 40,6 Mb
Release : 2017-10-25
Category : Mathematics
ISBN : 9783031018022

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Creating Autonomous Vehicle Systems by Liu Shaoshan,Li Liyun,Tang Jie,Wu Shuang,Gaudiot Jean-Luc Pdf

This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.

Creating Autonomous Vehicle Systems

Shaoshan Liu,Liyun Li,Jie Tang,Shuang Wu,Jean-Luc Gaudiot
Creating Autonomous Vehicle Systems Book PDF

Author : Shaoshan Liu,Liyun Li,Jie Tang,Shuang Wu,Jean-Luc Gaudiot
Publisher : Morgan & Claypool Publishers
Page : 198 pages
File Size : 42,5 Mb
Release : 2017-10-25
Category : Computers
ISBN : 9781681730080

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Creating Autonomous Vehicle Systems by Shaoshan Liu,Liyun Li,Jie Tang,Shuang Wu,Jean-Luc Gaudiot Pdf

This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.

Vehicle Systems from an Artificial Intelligence Perspective

Pavel Nedoma,Zdeněk Herda,Andrei Aksjonov
Vehicle Systems from an Artificial Intelligence Perspective Book PDF

Author : Pavel Nedoma,Zdeněk Herda,Andrei Aksjonov
Publisher : Eliva Press
Page : 0 pages
File Size : 51,6 Mb
Release : 2022-11-11
Category : Electronic
ISBN : 9994983989

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Vehicle Systems from an Artificial Intelligence Perspective by Pavel Nedoma,Zdeněk Herda,Andrei Aksjonov Pdf

This book is devoted to various forms of autonomous driving (AD) that will drastically transform the transportation of people and goods and enable urban areas to be redesigned, creating more livable and enjoyable spaces, thus meeting several demands simultaneously. Artificial intelligence (AI) takes a prominent position among the technological contributions making automated and connected driving safe, comfortable, efficient, and affordable. AI has found applications in various domains, from safety systems and simulation to monitoring the status of the driver and passengers. Some of these innovative aspects are discussed in this work. The as-yet unresolved technical challenges and constant endeavours around the world to advance this exciting technology have motivated the creation of this book. The book is structured into eight consequential chapters. It highlights the importance of control engineering, recent advances in environment sensing and perception, in-vehicle architectures, and reliable power computing as well as active and functional safety in AD. There is also a strong focus on validating and testing AD functions. The work concludes with a sample of relevant industry-driven research projects and industrial initiatives. The authors firmly believe that this book on the application of AI in autonomous vehicles (AV) provides a comprehensive overview of current and emerging technical challenges in the field and gives invaluable insights into industrial demands. The authors also hope the reader will be inspired by the collection of technical articles, selected project summaries, and introductions to renowned national and international initiatives.

Autonomous Vehicle Technology

James M. Anderson,Kalra Nidhi,Karlyn D. Stanley,Paul Sorensen,Constantine Samaras,Oluwatobi A. Oluwatola
Autonomous Vehicle Technology Book PDF

Author : James M. Anderson,Kalra Nidhi,Karlyn D. Stanley,Paul Sorensen,Constantine Samaras,Oluwatobi A. Oluwatola
Publisher : Rand Corporation
Page : 214 pages
File Size : 55,5 Mb
Release : 2014-01-10
Category : Transportation
ISBN : 9780833084378

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Autonomous Vehicle Technology by James M. Anderson,Kalra Nidhi,Karlyn D. Stanley,Paul Sorensen,Constantine Samaras,Oluwatobi A. Oluwatola Pdf

The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.

Human-Like Decision Making and Control for Autonomous Driving

Peng Hang,Chen Lv,Xinbo Chen
Human Like Decision Making and Control for Autonomous Driving Book PDF

Author : Peng Hang,Chen Lv,Xinbo Chen
Publisher : CRC Press
Page : 237 pages
File Size : 50,7 Mb
Release : 2022-07-25
Category : Mathematics
ISBN : 9781000625028

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Human-Like Decision Making and Control for Autonomous Driving by Peng Hang,Chen Lv,Xinbo Chen Pdf

This book details cutting-edge research into human-like driving technology, utilising game theory to better suit a human and machine hybrid driving environment. Covering feature identification and modelling of human driving behaviours, the book explains how to design an algorithm for decision making and control of autonomous vehicles in complex scenarios. Beginning with a review of current research in the field, the book uses this as a springboard from which to present a new theory of human-like driving framework for autonomous vehicles. Chapters cover system models of decision making and control, driving safety, riding comfort and travel efficiency. Throughout the book, game theory is applied to human-like decision making, enabling the autonomous vehicle and the human driver interaction to be modelled using noncooperative game theory approach. It also uses game theory to model collaborative decision making between connected autonomous vehicles. This framework enables human-like decision making and control of autonomous vehicles, which leads to safer and more efficient driving in complicated traffic scenarios. The book will be of interest to students and professionals alike, in the field of automotive engineering, computer engineering and control engineering.

Autonomous Driving

Andreas Herrmann,Walter Brenner,Rupert Stadler
Autonomous Driving Book PDF

Author : Andreas Herrmann,Walter Brenner,Rupert Stadler
Publisher : Emerald Group Publishing
Page : 460 pages
File Size : 48,7 Mb
Release : 2018-03-26
Category : Business & Economics
ISBN : 9781787148345

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Autonomous Driving by Andreas Herrmann,Walter Brenner,Rupert Stadler Pdf

The technology and engineering behind autonomous driving is advancing at pace. This book presents the latest technical advances and the economic, environmental and social impact driverless cars will have on individuals and the automotive industry.

Autonomous Ground Vehicles

Ümit Özgüner,Tankut Acarman,Keith Alan Redmill
Autonomous Ground Vehicles Book PDF

Author : Ümit Özgüner,Tankut Acarman,Keith Alan Redmill
Publisher : Artech House
Page : 289 pages
File Size : 45,8 Mb
Release : 2011
Category : Technology & Engineering
ISBN : 9781608071937

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Autonomous Ground Vehicles by Ümit Özgüner,Tankut Acarman,Keith Alan Redmill Pdf

In the near future, we will witness vehicles with the ability to provide drivers with several advanced safety and performance assistance features. Autonomous technology in ground vehicles will afford us capabilities like intersection collision warning, lane change warning, backup parking, parallel parking aids, and bus precision parking. Providing you with a practical understanding of this technology area, this innovative resource focuses on basic autonomous control and feedback for stopping and steering ground vehicles.Covering sensors, estimation, and sensor fusion to percept the vehicle motion and surrounding objects, this unique book explains the key aspects that makes autonomous vehicle behavior possible. Moreover, you find detailed examples of fusion and Kalman filtering. From maps, path planning, and obstacle avoidance scenarios...to cooperative mobility among autonomous vehicles, vehicle-to-vehicle communication, and vehicle-to-infrastructure communication, this forward-looking book presents the most critical topics in the field today.

Canonical Instabilities of Autonomous Vehicle Systems

Rodrick Wallace
Canonical Instabilities of Autonomous Vehicle Systems Book PDF

Author : Rodrick Wallace
Publisher : Springer
Page : 45 pages
File Size : 55,5 Mb
Release : 2017-10-31
Category : Technology & Engineering
ISBN : 9783319699356

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Canonical Instabilities of Autonomous Vehicle Systems by Rodrick Wallace Pdf

The asymptotic limit theorems of control and information theories make it possible to explore the dynamics of collapse likely to afflict large-scale systems of autonomous ground vehicles that communicate with each other and with an embedding intelligent roadway. Any vehicle/road system is inherently unstable in the control theory sense as a consequence of the basic irregularities of the traffic stream, the road network, and their interactions, placing it in the realm of the Data Rate Theorem that mandates a minimum necessary rate of control information for stability. It appears that large-scale V2V/V2I systems will experience correspondingly large-scale failures analogous to the vast, propagating fronts of power network blackouts, and possibly less benign but more subtle patterns of individual vehicle, platoon, and mesoscale dysfunction. The central matter is the synergism between poorly-understood traffic flow dynamics and similarly cryptic multisource information network dynamics, leading to highly punctuated phase transition analogs.

Engineering Autonomous Vehicles and Robots

Shaoshan Liu
Engineering Autonomous Vehicles and Robots Book PDF

Author : Shaoshan Liu
Publisher : John Wiley & Sons
Page : 216 pages
File Size : 47,5 Mb
Release : 2020-03-02
Category : Computers
ISBN : 9781119570554

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Engineering Autonomous Vehicles and Robots by Shaoshan Liu Pdf

Offers a step-by-step guide to building autonomous vehicles and robots, with source code and accompanying videos The first book of its kind on the detailed steps for creating an autonomous vehicle or robot, this book provides an overview of the technology and introduction of the key elements involved in developing autonomous vehicles, and offers an excellent introduction to the basics for someone new to the topic of autonomous vehicles and the innovative, modular-based engineering approach called DragonFly. Engineering Autonomous Vehicles and Robots: The DragonFly Modular-based Approach covers everything that technical professionals need to know about: CAN bus, chassis, sonars, radars, GNSS, computer vision, localization, perception, motion planning, and more. Particularly, it covers Computer Vision for active perception and localization, as well as mapping and motion planning. The book offers several case studies on the building of an autonomous passenger pod, bus, and vending robot. It features a large amount of supplementary material, including the standard protocol and sample codes for chassis, sonar, and radar. GPSD protocol/NMEA protocol and GPS deployment methods are also provided. Most importantly, readers will learn the philosophy behind the DragonFly modular-based design approach, which empowers readers to design and build their own autonomous vehicles and robots with flexibility and affordability. Offers progressive guidance on building autonomous vehicles and robots Provides detailed steps and codes to create an autonomous machine, at affordable cost, and with a modular approach Written by one of the pioneers in the field building autonomous vehicles Includes case studies, source code, and state-of-the art research results Accompanied by a website with supplementary material, including sample code for chassis/sonar/radar; GPS deployment methods; Vision Calibration methods Engineering Autonomous Vehicles and Robots is an excellent book for students, researchers, and practitioners in the field of autonomous vehicles and robots.

Autonomous Driving

Markus Maurer,J. Christian Gerdes,Barbara Lenz,Hermann Winner
Autonomous Driving Book PDF

Author : Markus Maurer,J. Christian Gerdes,Barbara Lenz,Hermann Winner
Publisher : Springer
Page : 706 pages
File Size : 46,8 Mb
Release : 2016-05-21
Category : Technology & Engineering
ISBN : 9783662488478

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Autonomous Driving by Markus Maurer,J. Christian Gerdes,Barbara Lenz,Hermann Winner Pdf

This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies? Experts from Germany and the United States define key societal, engineering, and mobility issues related to the automation of vehicles. They discuss the decisions programmers of automated vehicles must make to enable vehicles to perceive their environment, interact with other road users, and choose actions that may have ethical consequences. The authors further identify expectations and concerns that will form the basis for individual and societal acceptance of autonomous driving. While the safety benefits of such vehicles are tremendous, the authors demonstrate that these benefits will only be achieved if vehicles have an appropriate safety concept at the heart of their design. Realizing the potential of automated vehicles to reorganize traffic and transform mobility of people and goods requires similar care in the design of vehicles and networks. By covering all of these topics, the book aims to provide a current, comprehensive, and scientifically sound treatment of the emerging field of “autonomous driving".

Computing Systems for Autonomous Driving

Weisong Shi,Liangkai Liu
Computing Systems for Autonomous Driving Book PDF

Author : Weisong Shi,Liangkai Liu
Publisher : Springer Nature
Page : 239 pages
File Size : 54,9 Mb
Release : 2021-11-15
Category : Computers
ISBN : 9783030815646

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Computing Systems for Autonomous Driving by Weisong Shi,Liangkai Liu Pdf

This book on computing systems for autonomous driving takes a comprehensive look at the state-of-the-art computing technologies, including computing frameworks, algorithm deployment optimizations, systems runtime optimizations, dataset and benchmarking, simulators, hardware platforms, and smart infrastructures. The objectives of level 4 and level 5 autonomous driving require colossal improvement in the computing for this cyber-physical system. Beginning with a definition of computing systems for autonomous driving, this book introduces promising research topics and serves as a useful starting point for those interested in starting in the field. In addition to the current landscape, the authors examine the remaining open challenges to achieve L4/L5 autonomous driving. Computing Systems for Autonomous Driving provides a good introduction for researchers and prospective practitioners in the field. The book can also serve as a useful reference for university courses on autonomous vehicle technologies.This book on computing systems for autonomous driving takes a comprehensive look at the state-of-the-art computing technologies, including computing frameworks, algorithm deployment optimizations, systems runtime optimizations, dataset and benchmarking, simulators, hardware platforms, and smart infrastructures. The objectives of level 4 and level 5 autonomous driving require colossal improvement in the computing for this cyber-physical system. Beginning with a definition of computing systems for autonomous driving, this book introduces promising research topics and serves as a useful starting point for those interested in starting in the field. In addition to the current landscape, the authors examine the remaining open challenges to achieve L4/L5 autonomous driving. Computing Systems for Autonomous Driving provides a good introduction for researchers and prospective practitioners in the field. The book can also serve as a useful reference for university courses on autonomous vehicle technologies.

Collaborative Fleet Maneuvering for Multiple Autonomous Vehicle Systems

Yuanzhe Wang,Danwei Wang
Collaborative Fleet Maneuvering for Multiple Autonomous Vehicle Systems Book PDF

Author : Yuanzhe Wang,Danwei Wang
Publisher : Springer Nature
Page : 160 pages
File Size : 41,7 Mb
Release : 2022-09-21
Category : Technology & Engineering
ISBN : 9789811957987

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Collaborative Fleet Maneuvering for Multiple Autonomous Vehicle Systems by Yuanzhe Wang,Danwei Wang Pdf

This book presents theoretical foundations and technical implementation guidelines for multi-vehicle fleet maneuvering, which can be implemented by readers and can also be a basis for future research. As a research monograph, this book presents fundamental concepts, theories, and technologies for localization, motion planning, and control of multi-vehicle systems, which can be a reference book for researchers and graduate students from different levels. As a technical guide, this book provides implementation guidelines, pseudocode, and flow diagrams for practitioners to develop their own systems. Readers should have a preliminary knowledge of mobile robotics, state estimation and automatic control to fully understand the contents in this book. To make this book more readable and understandable, extensive experimental results are presented to support each chapter.

How to Build Self-Driving Cars From Scratch, Part 1

Bolakale Aremu
How to Build Self Driving Cars From Scratch Part 1 Book PDF

Author : Bolakale Aremu
Publisher : AB Publisher LLC
Page : 46 pages
File Size : 51,6 Mb
Release : 2024-03-29
Category : Computers
ISBN : 8210379456XXX

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How to Build Self-Driving Cars From Scratch, Part 1 by Bolakale Aremu Pdf

This is part 1 of my 3-part training guide on how to build self-driving cars from scratch. This guide is bundled with a repository containing simulations, python scripts, graphics, and other useful assets. In this step-by-step guide, I’ll teach you how to make an app that you can use to create a simulation where cars learn how to drive autonomously over racing tracks. Here’s a break down of the contents of this guide. Part 1: Car mechanics. In this part, you’ll learn how to draw the car and control it with the keyboard. You will use a multimedia library for Python called Pyglet. This is the only library you will use in this guide. This is a cross-platform windowing and multimedia library for Python. It’s a powerful yet easy-to-use Python library for building games and other visually rich applications on Windows, macOS, and Linux. Part 2: Neural network and genetic algorithm. You’ll learn how to create the AI where you combine a neural network and genetic algorithm. You’ll learn how to add sensors to the car and get output from them. To prevent the untrained network from car crashes, a genetic algorithm will be used to train the cars. This will help the cars to drive simple tracks. Part 3: Challenges. You’ll add some challenges to the system. Tracks get more complicated and will take advantage from the previous track training by storing and retrieving the car brains. By the end of this training, you will have created self-driving cars that are capable of driving on unknown tracks by understanding how to steer, accelerate, and brake based on what cars see in front of them. Since autonomous cars need a brain of some kind, you know we need some AI (artificial intelligence). AI comes in many forms, but in this guide, you’ll use a neural network where the weights are adjusted by a genetic algorithm. Employment opportunities often come from work samples and concrete skills, rather than a college degree. So, you need to learn the practical aspect well enough. This guide will not only help you learn well and build a stunning portfolio, it will also provide you continuous help and support. With this book and my dedicated 24/7 help and support team, there’s nothing for you to fear. I have helped many Python developers update their automation development skills, launch successful careers and get hired for remote jobs. I notice that even the most ambitious beginners can run into problems, such as unable to decide where to begin. Sometimes they get completely lost on the way and therefore need further help. In Chapter 3, I explain how to download my repository which contains all updates of the Python scripts (codes) and simulations used in this guide. Although I explain all the codes used in this guide clearly, if you need further help, just use my support link at the end of the Chapter. The truth is everyone needs help at one point or the other to learn and build automation in their development journey. I can give you more challenges and their solutions in my subsequent trainings.

Decision-Making Techniques for Autonomous Vehicles

Jorge Villagra,Felipe Jimenez
Decision Making Techniques for Autonomous Vehicles Book PDF

Author : Jorge Villagra,Felipe Jimenez
Publisher : Elsevier
Page : 426 pages
File Size : 47,5 Mb
Release : 2023-03-03
Category : Technology & Engineering
ISBN : 9780323985499

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Decision-Making Techniques for Autonomous Vehicles by Jorge Villagra,Felipe Jimenez Pdf

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