Based on his popular AI Insider column and reader feedback, this is Dr. Eliot's highly rated introductory coverage on the emergence and advent of autonomous driverless self-driving cars. Readable for everyone, discover the underlying technology that makes self-driving cars achievable. Furthermore, learn about the key business aspects, economics, and politics that will shape the future of self-driving cars. Essential elements of Artificial Intelligence (AI) and Machine Learning are covered, along with blockchain, bitcoins, genetic algorithms, neural networks, and more.

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.

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.

When human drivers let intelligent software take the wheel: the beginning of a new era in personal mobility.

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.

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".

The country's leading transport expert describes how the driverless vehicle revolution will transform highways, cities, workplaces and laws not just here, but across the globe. Our time at the wheel is done. Driving will become illegal, as human drivers will be demonstrably more dangerous than cars that pilot themselves. Is this an impossible future, or a revolution just around the corner? Sam Schwartz, America's most celebrated transportation guru, describes in this book the revolution in self-driving cars. The ramifications will be dramatic, and the transition will be far from seamless. It will overturn the job market for the one in seven Americans who work in the trucking industry. It will cause us to grapple with new ethical dilemmas-if a car will hit a person or a building, endangering the lives of its passengers, who will decide what it does? It will further erode our privacy, since the vehicle can relay our location at any moment. And, like every other computer-controlled device, it can be vulnerable to hacking. Right now, every major car maker here and abroad is working on bringing autonomous vehicles to consumers. The fleets are getting ready to roll and nothing will ever be the same, and this book shows us what the future has in store.

This ground-breaking and insider look at cybernetic self-driving cars provides a state-of-the-art exploration of how advances in AI and machine learning are enabling the advent of self-driving cars.

A computer beats the reigning human champion of Go, a game harder than chess. Another is composing classical music. Labs are creating life-forms from synthetic DNA. A doctor designs an artificial trachea, uses a 3D printer to produce it, and implants it and saves a child's life. Astonishing technological advances like these are arriving in increasing numbers. Scholar and entrepreneur Vivek Wadhwa uses this book to alert us to dozens of them and raise important questions about what they may mean for us. Breakthroughs such as personalized genomics, self-driving vehicles, drones, and artificial intelligence could make our lives healthier, safer, and easier. But the same technologies raise the specter of a frightening, alienating future: eugenics, a jobless economy, complete loss of privacy, and ever-worsening economic inequality. As Wadhwa puts it, our choices will determine if our future is Star Trek or Mad Max. Wadhwa offers us three questions to ask about every emerging technology: Does it have the potential to benefit everyone equally? What are its risks and rewards? And does it promote autonomy or dependence? Looking at a broad array of advances in this light, he emphasizes that the future is up to us to create—that even if our hands are not on the wheel, we will decide the driverless car's destination.

In Autonorama: The Illusory Promise of High-Tech Driving, historian Peter Norton argues that driverless cars cannot be the safe, sustainable, and inclusive "mobility solutions" that tech companies and automakers are promising us. The salesmanship behind the "driverless future" is distracting us from better ways to get around that we can implement now. Unlike autonomous vehicles, these alternatives are inexpensive, safe, sustainable, and inclusive. Norton takes the reader on an engaging ride--from the GM Futurama exhibit to "smart" highways and vehicles--to show how we are once again being sold car dependency in the guise of mobility. Autonorama is hopeful, advocating for wise, proven, humane mobility that we can invest in now, without waiting for technology that is forever just out of reach.