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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
In New Mobilities: Smart Planning for Emerging Transportation Technologies, transportation expert Todd Litman examines 12 emerging transportation modes and services that are likely to significantly affect our lives: bike- and carsharing, micro-mobilities, ridehailing and micro-transit, public transit innovations, telework, autonomous and electric vehicles, air taxis, mobility prioritization, and logistics management. Public policies around New Mobilities can either help create heaven, a well-planned transportation system that uses new technologies intelligently, or hell, a poorly planned transportation system that is overwhelmed by conflicting and costly, unhealthy, and inequitable modes. His expert analysis will help planners, local policymakers, and concerned citizens to make informed choices about the New Mobility revolution.
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.
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".
This research topic centers on the practical application of game theory and optimization methods to address complex challenges in real-world contexts. At its core, game theory provides a framework for analyzing strategic interactions among rational decision-makers, while optimization techniques are designed to seek the most favorable outcomes. These tools have proven to be powerful assets across a wide range of domains, from economics and computer science to social sciences and engineering. The following objectives guide this exploration: (i) Understanding Game Theory and Optimization in Real-world Contexts: This objective involves investigating how these mathematical constructs are applied to model and resolve problems across various fields. (ii) Analyzing the Effectiveness of Game Theory and Optimization Techniques: This involves studying real-world case studies and practical applications with the goal of evaluating the performance and efficiency of these methods in practice. (iii) Identifying Potential Areas for Effective Application of Game Theory and Optimization: This objective aims to pinpoint sectors or disciplines that may significantly benefit from the application of these mathematical techniques. The goal of this Research Topic in Frontiers in Physics aims to produce a comprehensive understanding of the real-world applications of game theory and optimization, highlighting their practical impact and potential for future use. It will provide valuable insights for professionals and researchers working in the fields where these techniques can be applied and contribute to the body of knowledge in game theory and optimization. Potential topics include but are not limited to the following: 1. Economics and Business: How are game theory and optimization used to make strategic business decisions and to understand economic phenomena? 2. Computer Science: How do these techniques contribute to areas like network design, machine learning, and algorithm development? 3. Social Sciences: How can game theory and optimization help in understanding social dynamics, designing policies, and resolving conflicts? 4. Engineering and Operations Research: How are these techniques utilized in system design, process optimization, and decision-making?
The DARPA Grand Challenge was a landmark in the field of robotics: a race by autonomous vehicles through 132 miles of rough Nevada terrain. It showcased exciting and unprecedented capabilities in robotic perception, navigation, and control. The event took place in October 2005 and drew teams of competitors from academia and industry, as well as many garage hobbyists. This book presents fifteen technical papers that describe each team's driverless vehicle, race strategy, and insights. As a whole, they present the state of the art in autonomous vehicle technology and offer a glimpse of future technology for tomorrow’s driverless cars.
Business Models for Transforming Customer Relationships What if there were a way to turn occasional, sporadic transactions with customers into long-term, continuous relationships--while simultaneously driving dramatic improvements in operational efficiency? What if you could break your existing trade-offs between superior customer experience and low cost? This is the promise of a connected strategy. New forms of connectivity--involving frequent, low-friction, customized interactions--mean that companies can now anticipate customer needs as they arise, or even before. Simultaneously, enabled by these technologies, companies can create new business models that deliver more value to customers. Connected strategies are win-win: Customers get a dramatically improved experience, while companies boost operational efficiency. In this book, strategy and operations experts Nicolaj Siggelkow and Christian Terwiesch reveal the emergence of connected strategies as a new source of competitive advantage. With in-depth examples from companies operating in industries such as healthcare, financial services, mobility, retail, entertainment, nonprofit, and education, Connected Strategy identifies the four pathways--respond-to-desire, curated offering, coach behavior, and automatic execution--for turning episodic interactions into continuous relationships. The authors show how each pathway creates a competitive advantage, then guide you through the critical decisions for creating and implementing your own connected strategies. Whether you're trying to revitalize strategy in an established company or disrupt an industry as a startup, this book will help you: Reshape your connections with your customers Find new ways to connect with existing suppliers while also activating new sources of capacity Create the right revenue model Make the best technology choices to support your strategy Integrating rich examples, how-to advice, and practical tools in the form of "workshop chapters" throughout, this book is the ultimate resource for creating competitive advantage through connected relationships with your customers and redefined connections in your industry.
Front Cover -- About Island Press -- Subscribe -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- 1. Will the Transportation Revolutions Improve Our Lives-- or Make Them Worse? -- 2. Electric Vehicles: Approaching the Tipping Point -- 3. Shared Mobility: The Potential of Ridehailing and Pooling -- 4. Vehicle Automation: Our Best Shot at a Transportation Do-Over? -- 5. Upgrading Transit for the Twenty-First Century -- 6. Bridging the Gap between Mobility Haves and Have-Nots -- 7. Remaking the Auto Industry -- 8. The Dark Horse: Will China Win the Electric, Automated, Shared Mobility Race? -- Epilogue -- Notes -- About the Contributors -- Index -- IP Board of Directors