Autonomous Driving Network


Autonomous Driving Network
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Autonomous Driving Network


Autonomous Driving Network
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Author : Wenshuan Dang
language : en
Publisher: CRC Press
Release Date : 2024-01-17

Autonomous Driving Network written by Wenshuan Dang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-17 with Computers categories.


Aiming to outline the vision of realizing automated and intelligent communication networks in the era of intelligence, this book describes the development history, application scenarios, theories, architectures, and key technologies of Huawei's Autonomous Driving Network (ADN) solution. In the book, the authors explain the design of the top-level architecture, hierarchical architecture (ANE, NetGraph, and AI Native NE), and key feature architecture (distributed AI and endogenous security) that underpin Huawei's ADN solution. The book delves into various key technologies, including trustworthy AI, distributed AI, digital twin, network simulation, digitization of knowledge and expertise, human-machine symbiosis, NE endogenous intelligence, and endogenous security. It also provides an overview of the standards and level evaluation methods defined by industry and standards organizations, and uses Huawei's ADN solution as an example to illustrate how to implement AN. This book is an essential reference for professionals and researchers who want to gain a deeper understanding of automated and intelligent communication networks and their applications.



Autonomous And Connected Vehicles


Autonomous And Connected Vehicles
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Author : Dominique Paret
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-28

Autonomous And Connected Vehicles written by Dominique Paret and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-28 with Technology & Engineering categories.


AUTONOMOUS AND CONNECTED VEHICLES Discover the latest developments in autonomous vehicles and what the future holds for this exciting technology In Autonomous and Connected Vehicles, networking experts Dominique Paret and Hassina Rebaine deliver a robust exploration of the major technological changes taking place in the field, and describe the different levels of autonomy possible with current technologies and the legal and regulatory contexts in which new autonomous vehicles will circulate. The book also includes discussions of the sensors, including infrared, ultrasound, cameras, lidar, and radar, used by modern autonomous vehicles. Readers will enjoy the intuitive descriptions of Advanced Driver Assistance Systems (ADAS), network architectures (CAN-FD, FlexRay, and Backbone Ethernet), and software that power current and future autonomous vehicles. The authors also discuss how ADAS can be fused with data flowing over newer and faster network architectures and artificial intelligence to create greater levels of autonomy. The book also includes: A thorough introduction to the buzz and hype surrounding autonomous and connected vehicles, including a brief history of the autonomous vehicle Comprehensive explorations of common issues affecting autonomous and connected vehicles, including regulatory guidelines, legislation, relevant norms and standards, and insurance issues Practical discussions of autonomous vehicle sensors, from DAS to ADAS and HADAS, and VA L3 to L5 In-depth examinations of networks and architecture, including discussions of data fusion, artificial intelligence, and hardware architecture in vehicles Perfect for graduate and undergraduate students in programs dealing with the intersection of wireless communication technologies and vehicles, Autonomous and Connected Vehicles is also a must-read reference for industry professionals and researchers seeking a one-stop reference for the latest developments in vehicle communications technology.



Internet Of Vehicles And Its Applications In Autonomous Driving


Internet Of Vehicles And Its Applications In Autonomous Driving
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Author : Nishu Gupta
language : en
Publisher: Springer Nature
Release Date : 2020-09-18

Internet Of Vehicles And Its Applications In Autonomous Driving written by Nishu Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-18 with Technology & Engineering categories.


This book provides an insight on the importance that Internet of Vehicles (IoV) solutions can have in taking care of vehicular safety through internetworking and automation. Key features of the book are the inclusion and elaboration of recent and emerging developments in various specializations of intelligent transportation systems and their solutions by incorporating IoT (Internet of Things) and IoV. This book presents to its readers useful IoV applications and architectures that cater to their improved driving requirements and lead towards autonomous driving. The application domains have a large range in which vehicular networking, communication technology, sensor devices, computing materials and devices, IoT communication, vehicular and on-road safety, data security and other topics are included.



Networking Vehicles To Everything


Networking Vehicles To Everything
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Author : Markus Mueck
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2018-01-09

Networking Vehicles To Everything written by Markus Mueck and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-09 with Computers categories.


Intro -- Acknowledgments -- Contents -- Preface -- Chapter 1. Introduction -- Chapter 2. Applications and Use Cases -- Chapter 3. V2X Requirements, Standards, and Regulations -- Chapter 4. Technologies -- Chapter 5. V2X networking and connectivity -- Chapter 6. Infotainment -- Chapter 7. Software Reconfiguration -- Chapter 8. Outlook -- Appendix A -- Index



Applied Deep Learning And Computer Vision For Self Driving Cars


Applied Deep Learning And Computer Vision For Self Driving Cars
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Author : Sumit Ranjan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-14

Applied Deep Learning And Computer Vision For Self Driving Cars written by Sumit Ranjan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-14 with Computers categories.


Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV Key FeaturesBuild and train powerful neural network models to build an autonomous carImplement computer vision, deep learning, and AI techniques to create automotive algorithmsOvercome the challenges faced while automating different aspects of driving using modern Python libraries and architecturesBook Description Thanks to a number of recent breakthroughs, self-driving car technology is now an emerging subject in the field of artificial intelligence and has shifted data scientists' focus to building autonomous cars that will transform the automotive industry. This book is a comprehensive guide to use deep learning and computer vision techniques to develop autonomous cars. Starting with the basics of self-driving cars (SDCs), this book will take you through the deep neural network techniques required to get up and running with building your autonomous vehicle. Once you are comfortable with the basics, you'll delve into advanced computer vision techniques and learn how to use deep learning methods to perform a variety of computer vision tasks such as finding lane lines, improving image classification, and so on. You will explore the basic structure and working of a semantic segmentation model and get to grips with detecting cars using semantic segmentation. The book also covers advanced applications such as behavior-cloning and vehicle detection using OpenCV, transfer learning, and deep learning methodologies to train SDCs to mimic human driving. By the end of this book, you'll have learned how to implement a variety of neural networks to develop your own autonomous vehicle using modern Python libraries. What you will learnImplement deep neural network from scratch using the Keras libraryUnderstand the importance of deep learning in self-driving carsGet to grips with feature extraction techniques in image processing using the OpenCV libraryDesign a software pipeline that detects lane lines in videosImplement a convolutional neural network (CNN) image classifier for traffic signal signsTrain and test neural networks for behavioral-cloning by driving a car in a virtual simulatorDiscover various state-of-the-art semantic segmentation and object detection architecturesWho this book is for If you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.



Deep Neural Networks And Data For Automated Driving


Deep Neural Networks And Data For Automated Driving
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Author : Tim Fingscheidt
language : en
Publisher: Springer Nature
Release Date : 2022-07-19

Deep Neural Networks And Data For Automated Driving written by Tim Fingscheidt and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-19 with Technology & Engineering categories.


This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence. Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.



The Next Generation Vehicular Networks Modeling Algorithm And Applications


The Next Generation Vehicular Networks Modeling Algorithm And Applications
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Author : Zhou Su
language : en
Publisher: Springer Nature
Release Date : 2020-11-12

The Next Generation Vehicular Networks Modeling Algorithm And Applications written by Zhou Su and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.


This book proposes the novel network envisions and framework design principles, in order to systematically expound the next generation vehicular networks, including the modelling, algorithms and practical applications. It focuses on the key enabling technologies to design the next generation vehicular networks with various vehicular services to realize the safe, convenient and comfortable driving. The next generation vehicular networks has emerged to provide services with a high quality of experience (QoE) to vehicles, where both better network maintainability and sustainability can be obtained than before. The framework design principles and related network architecture are also covered in this book. Then, the series of research topics are discussed including the reputation based content centric delivery, the contract based mobile edge caching, the Stackelberg game model based computation offloading, the auction game based secure computation offloading, the bargain game based security protection and the deep learning based autonomous driving. Finally, the investigation, development and future works are also introduced for designing the next generation vehicular networks. The primary audience for this book are researchers, who work in computer science and electronic engineering. Professionals working in the field of mobile networks and communications, as well as engineers and technical staff who work on the development or the standard of computer networks will also find this book useful as a reference.



Autonomous Vehicles Volume 2


Autonomous Vehicles Volume 2
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Author : Romil Rawat
language : en
Publisher: John Wiley & Sons
Release Date : 2022-11-30

Autonomous Vehicles Volume 2 written by Romil Rawat and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Technology & Engineering categories.


AUTONOMOUS VEHICLES The companion to Autonomous Vehicles Volume 1: Using Machine Intelligence, this second volume in the two-volume set covers intelligent techniques utilized for designing, controlling, and managing vehicular systems based on advanced algorithms of computing like machine learning, artificial intelligence, data analytics, and Internet of Things (IoT) with prediction approaches to avoid accidental damages, security threats, and theft. Besides communicating with other vehicles, self-driving cars connected to a 5G network will also be able to communicate with different infrastructure elements that make up our roads and other transportation and communication systems. Similarly, an unmanned aerial vehicle (UAV), an aircraft without any human pilot, crew, or passengers on board, can operate under remote control by a human operator, as a remotely-piloted aircraft (RPA), or with various degrees of autonomy. These include autopilot assistance and fully autonomous aircraft that have no provision for human intervention. Transportation is a necessary, but often painful process. With fully autonomous driving, passengers will be freed to accomplish their own goals, turning the dead hours of driving into fruitful hours of learning, working, engaging, and relaxing. Similarly, UAVs can perform functions that human-operated aircraft cannot, whether because of the environment or high-risk situations. The purpose of the book is to present the needs, designs, and applications of autonomous vehicles. The topics covered range from mechanical engineering to computer science engineering, both areas playing vital roles in programming, managing, generating alerts, and GPS position, artificial intelligence-based prediction of path and events, as well as other high-tech tools, are covered in this book, as well. Whether for the student, veteran engineer, or another industry professional, this book, and its companion volume, are must-haves for any library.



Construction Methods For An Autonomous Driving Map In An Intelligent Network Environment


Construction Methods For An Autonomous Driving Map In An Intelligent Network Environment
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Author : Zhijun Chen
language : en
Publisher: Elsevier
Release Date : 2024-04-19

Construction Methods For An Autonomous Driving Map In An Intelligent Network Environment written by Zhijun Chen and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-19 with Technology & Engineering categories.


This book provides an overview of constructing advanced Autonomous Driving Maps. It includes coverage of such methods as: fusion target perception (based on vehicle vision and millimeter wave radar), cross-field of view object perception, vehicle motion recognition (based on vehicle road fusion information), vehicle trajectory prediction (based on improved hybrid neural network) and the driving map construction method driven by road perception fusion. An Autonomous Driving Map is used for optimization of not only for a single vehicle, but also for the entire traffic system.



Introduction To Self Driving Vehicle Technology


Introduction To Self Driving Vehicle Technology
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Author : Hanky Sjafrie
language : en
Publisher: CRC Press
Release Date : 2019-11-21

Introduction To Self Driving Vehicle Technology written by Hanky Sjafrie and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-21 with Computers categories.


This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible. It is aimed at people who want to get their teeth into self-driving vehicle technology, by providing genuine technical insights where other books just skim the surface. The book tackles everything from sensors and perception to functional safety and cybersecurity. It also passes on some practical know-how and discusses concrete SDV applications, along with a discussion of where this technology is heading. It will serve as a good starting point for software developers or professional engineers who are eager to pursue a career in this exciting field and want to learn more about the basics of SDV algorithms. Likewise, academic researchers, technology enthusiasts, and journalists will also find the book useful. Key Features: Offers a comprehensive technological walk-through of what really matters in SDV development: from hardware, software, to functional safety and cybersecurity Written by an active practitioner with extensive experience in series development and research in the fields of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Covers theoretical fundamentals of state-of-the-art SLAM, multi-sensor data fusion, and other SDV algorithms. Includes practical information and hands-on material with Robot Operating System (ROS) and Open Source Car Control (OSCC). Provides an overview of the strategies, trends, and applications which companies are pursuing in this field at present as well as other technical insights from the industry.