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Hands On Vision And Behavior For Self Driving Cars
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Book Synopsis Hands-On Vision and Behavior for Self-Driving Cars by : Luca Venturi
Download or read book Hands-On Vision and Behavior for Self-Driving Cars written by Luca Venturi and published by Packt Publishing Ltd. This book was released on 2020-10-23 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to learning visual perception for self-driving cars for computer vision and autonomous system engineers Key FeaturesExplore the building blocks of the visual perception system in self-driving carsIdentify objects and lanes to define the boundary of driving surfaces using open-source tools like OpenCV and PythonImprove the object detection and classification capabilities of systems with the help of neural networksBook Description The visual perception capabilities of a self-driving car are powered by computer vision. The work relating to self-driving cars can be broadly classified into three components - robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field. You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real self-driving car is a huge cross-functional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You’ll even be able to tackle core challenges in self-driving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller. By the end of this book, you’ll be equipped with the skills you need to write code for a self-driving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers. What you will learnUnderstand how to perform camera calibrationBecome well-versed with how lane detection works in self-driving cars using OpenCVExplore behavioral cloning by self-driving in a video-game simulatorGet to grips with using lidarsDiscover how to configure the controls for autonomous vehiclesUse object detection and semantic segmentation to locate lanes, cars, and pedestriansWrite a PID controller to control a self-driving car running in a simulatorWho this book is for This book is for software engineers who are interested in learning about technologies that drive the autonomous car revolution. Although basic knowledge of computer vision and Python programming is required, prior knowledge of advanced deep learning and how to use sensors (lidar) is not needed.
Book Synopsis Applied Deep Learning and Computer Vision for Self-Driving Cars by : Sumit Ranjan
Download or read book Applied Deep Learning and Computer Vision for Self-Driving Cars written by Sumit Ranjan and published by Packt Publishing Ltd. This book was released on 2020-08-14 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Self Driving Car written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2024-05-06 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is Self Driving Car A self-driving car, also known as an autonomous car (AC), driverless car, robotaxi, robotic car or robo-car, is a car that is capable of operating with reduced or no human input. Self-driving cars are responsible for all driving activities, such as perceiving the environment, monitoring important systems, and controlling the vehicle, which includes navigating from origin to destination. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Self-driving car Chapter 2: Advanced driver-assistance system Chapter 3: Vehicular automation Chapter 4: Automatic parking Chapter 5: Waymo Chapter 6: Mobileye Chapter 7: History of self-driving cars Chapter 8: Tesla Autopilot Chapter 9: Cruise (autonomous vehicle) Chapter 10: Regulation of self-driving cars (II) Answering the public top questions about self driving car. (III) Real world examples for the usage of self driving car in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Self Driving Car.
Book Synopsis Autonomous Driving by : Markus Maurer
Download or read book Autonomous Driving written by Markus Maurer and published by Springer. This book was released on 2016-05-21 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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".
Book Synopsis Learning to Drive by : David Michael Stavens
Download or read book Learning to Drive written by David Michael Stavens and published by Stanford University. This book was released on 2011 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every year, 1.2 million people die in automobile accidents and up to 50 million are injured. Many of these deaths are due to driver error and other preventable causes. Autonomous or highly aware cars have the potential to positively impact tens of millions of people. Building an autonomous car is not easy. Although the absolute number of traffic fatalities is tragically large, the failure rate of human driving is actually very small. A human driver makes a fatal mistake once in about 88 million miles. As a co-founding member of the Stanford Racing Team, we have built several relevant prototypes of autonomous cars. These include Stanley, the winner of the 2005 DARPA Grand Challenge and Junior, the car that took second place in the 2007 Urban Challenge. These prototypes demonstrate that autonomous vehicles can be successful in challenging environments. Nevertheless, reliable, cost-effective perception under uncertainty is a major challenge to the deployment of robotic cars in practice. This dissertation presents selected perception technologies for autonomous driving in the context of Stanford's autonomous cars. We consider speed selection in response to terrain conditions, smooth road finding, improved visual feature optimization, and cost effective car detection. Our work does not rely on manual engineering or even supervised machine learning. Rather, the car learns on its own, training itself without human teaching or labeling. We show this "self-supervised" learning often meets or exceeds traditional methods. Furthermore, we feel self-supervised learning is the only approach with the potential to provide the very low failure rates necessary to improve on human driving performance.
Book Synopsis Computer Vision for Autonomous Vehicles by : Joel Janai
Download or read book Computer Vision for Autonomous Vehicles written by Joel Janai and published by . This book was released on 2020 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several survey papers on particular sub-problems have appeared, no comprehensive survey on problems, datasets, and methods in computer vision for autonomous vehicles has been published. This monograph attempts to narrow this gap by providing a survey on the state-of-the-art datasets and techniques. Our survey includes both the historically most relevant literature as well as the current state of the art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding, and end-to-end learning for autonomous driving. Towards this goal, we analyze the performance of the state of the art on several challenging benchmarking datasets, including KITTI, MOT, and Cityscapes. Besides, we discuss open problems and current research challenges. To ease accessibility and accommodate missing references, we also provide a website that allows navigating topics as well as methods and provides additional information.
Book Synopsis Creating Autonomous Vehicle Systems by : Shaoshan Liu
Download or read book Creating Autonomous Vehicle Systems written by Shaoshan Liu and published by Morgan & Claypool Publishers. This book was released on 2017-10-25 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Autonomous Vehicle Technology by : James M. Anderson
Download or read book Autonomous Vehicle Technology written by James M. Anderson and published by Rand Corporation. This book was released on 2014-01-10 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author :Committee on Commerce, Science, and Transportation United States Senate Publisher :Createspace Independent Publishing Platform ISBN 13 :9781546641728 Total Pages :92 pages Book Rating :4.6/5 (417 download)
Book Synopsis Hands Off by : Committee on Commerce, Science, and Transportation United States Senate
Download or read book Hands Off written by Committee on Commerce, Science, and Transportation United States Senate and published by Createspace Independent Publishing Platform. This book was released on 2017-05-13 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the automobile first rolled off the assembly line in River Rouge, Michigan, cars in America have offered independence, mobility, and adventure. Now, profound changes are coming to our roads. Technological advancements are progressing at a rapid pace and fully self-driving cars will be here sooner than we think. We are facing an opportunity to expand the options for transportation by car while also making it smarter and safer. Technological challenges remain, but perhaps the greatest hurdle to the deployment of these vehicles may be a regulatory environment, a patchwork of state and Federal laws unable to keep pace with these evolving technologies. Everything from driver assist functions like lane departure warnings to completely autonomous vehicles will transform transportation and mobility, profoundly affecting safety issues that have confronted society since the invention of the car. In 2014, 32,675 Americans lost their lives due to car accidents. More than 90 percent of these tragedies are linked to human error, driver choices, intoxication, and distraction. Automated vehicles have the potential to reduce that number dramatically. Unlike human drivers, automated vehicles don't get tired, drunk, or distracted. In addition to helping reduce accidents on American roads, autonomous vehicles promise to improve the quality of life for older Americans and members of the disabled community.
Book Synopsis Autonomous Driving by : Andreas Herrmann
Download or read book Autonomous Driving written by Andreas Herrmann and published by Emerald Group Publishing. This book was released on 2018-03-26 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Self-Driving Vehicles and Enabling Technologies by :
Download or read book Self-Driving Vehicles and Enabling Technologies written by and published by BoD – Books on Demand. This book was released on 2021-09-22 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the development and technical progress of self-driving vehicles in the context of the Vision Zero project from the European Union, which aims to eliminate highway system fatalities and serious accidents by 2050. It presents the concept of Autonomous Driving (AD) and discusses its applications in transportation, logistics, space, agriculture, and industrial and home automation.
Download or read book Self-Driving Cars written by Haydn Sonnad and published by Cherry Lake. This book was released on 2019-08-01 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cars have come a long way thanks to technology, from Model T cars to cars that drive themselves. In Self-Driving Cars in the Disruptors in Tech series, readers will discover how autonomous driving technology has and continues to disrupt industries from car manufacturers to city infrastructures. Series includes a table of contents, tech-forward sidebars, a timeline, glossary, index, and author biography.
Author :United States. Congress Publisher :Createspace Independent Publishing Platform ISBN 13 :9781976192500 Total Pages :92 pages Book Rating :4.1/5 (925 download)
Book Synopsis Hands Off by : United States. Congress
Download or read book Hands Off written by United States. Congress and published by Createspace Independent Publishing Platform. This book was released on 2017-09-08 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands off : the future of self-driving cars : hearing before the Committee on Commerce, Science, and Transportation, United States Senate, One Hundred Fourteenth Congress, second session, March 15, 2016.
Book Synopsis Theories and Practices of Self-Driving Vehicles by : Qingguo Zhou
Download or read book Theories and Practices of Self-Driving Vehicles written by Qingguo Zhou and published by Elsevier. This book was released on 2022-07-03 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Self-driving vehicles are a rapidly growing area of research and expertise. Theories and Practice of Self-Driving Vehicles presents a comprehensive introduction to the technology of self driving vehicles across the three domains of perception, planning and control. The title systematically introduces vehicle systems from principles to practice, including basic knowledge of ROS programming, machine and deep learning, as well as basic modules such as environmental perception and sensor fusion. The book introduces advanced control algorithms as well as important areas of new research. This title offers engineers, technicians and students an accessible handbook to the entire stack of technology in a self-driving vehicle. Theories and Practice of Self-Driving Vehicles presents an introduction to self-driving vehicle technology from principles to practice. Ten chapters cover the full stack of driverless technology for a self-driving vehicle. Written by two authors experienced in both industry and research, this book offers an accessible and systematic introduction to self-driving vehicle technology. Provides a comprehensive introduction to the technology stack of a self-driving vehicle Covers the three domains of perception, planning and control Offers foundational theory and best practices Introduces advanced control algorithms and high-potential areas of new research Gives engineers, technicians and students an accessible handbook to self-driving vehicle technology and applications
Book Synopsis Self-driving Cars by : Michael Fallon
Download or read book Self-driving Cars written by Michael Fallon and published by Twenty-First Century Books (Tm). This book was released on 2018-08 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Author Fallon presents a history of how the technology used in self-driving cars has developed, identifies recent technological gains, and surveys recent controversies surrounding the potential mass adoption of self-driving cars."--Provided by publisher.
Book Synopsis Autonomous Driving and Advanced Driver-Assistance Systems (ADAS) by : Lentin Joseph
Download or read book Autonomous Driving and Advanced Driver-Assistance Systems (ADAS) written by Lentin Joseph and published by CRC Press. This book was released on 2021-12-16 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous Driving and Advanced Driver-Assistance Systems (ADAS): Applications, Development, Legal Issues, and Testing outlines the latest research related to autonomous cars and advanced driver-assistance systems, including the development, testing, and verification for real-time situations of sensor fusion, sensor placement, control algorithms, and computer vision. Features: Co-edited by an experienced roboticist and author and an experienced academic Addresses the legal aspect of autonomous driving and ADAS Presents the application of ADAS in autonomous vehicle parking systems With an infinite number of real-time possibilities that need to be addressed, the methods and the examples included in this book are a valuable source of information for academic and industrial researchers, automotive companies, and suppliers.
Download or read book Driverless written by Hod Lipson and published by MIT Press. This book was released on 2017-09-15 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: When human drivers let intelligent software take the wheel: the beginning of a new era in personal mobility. “Smart, wide-ranging, [and] nontechnical.” —Los Angeles Times “Anyone who wants to understand what's coming must read this fascinating book.” —Martin Ford, New York Times bestselling author of Rise of the Robots In the year 2014, Google fired a shot heard all the way to Detroit. Google's newest driverless car had no steering wheel and no brakes. The message was clear: cars of the future will be born fully autonomous, with no human driver needed. In the coming decade, self-driving cars will hit the streets, rearranging established industries and reshaping cities, giving us new choices in where we live and how we work and play. In this book, Hod Lipson and Melba Kurman offer readers insight into the risks and benefits of driverless cars and a lucid and engaging explanation of the enabling technology. Recent advances in software and robotics are toppling long-standing technological barriers that for decades have confined self-driving cars to the realm of fantasy. A new kind of artificial intelligence software called deep learning gives cars rapid and accurate visual perception. Human drivers can relax and take their eyes off the road. When human drivers let intelligent software take the wheel, driverless cars will offer billions of people all over the world a safer, cleaner, and more convenient mode of transportation. Although the technology is nearly ready, car companies and policy makers may not be. The authors make a compelling case for why government, industry, and consumers need to work together to make the development of driverless cars our society's next “Apollo moment.”
