Driverless cars represent a disruptive technological change in transportation as we know it. These vehicles are capable of sensing, navigating, and communicating with their external surroundings without any human intervention. They leverage various technologies including imaging, radar, laser optics, and GPS to navigate through dynamically changing road environments. In this report, we analyze the Intellectual Property (Patents) landscape of driverless car technology. Our analysis reveals key aspects relating to innovation in this technology, including filing trends, top assignees, their portfolio strength, and geographical coverage.

Autonomous vehicle technology has the potential to significantly improve social welfare. This report addresses the numerous legislative, regulatory, and liability issues this technology will raise.

The subject of this book is artificial intelligence (AI), introducing the fast road sensing algorithm and system based on image pattern recognition for unmanned vehicle, especially for traffic sign recognition and complex road recognition. With rich figures and credible data, this book systematically and comprehensively describes the core technology and industrialization focus of today's unmanned vehicle system, which can be used as a reference for R & D Engineers and industrialization practitioners of unmanned vehicle, and it can also be used as a teaching material for higher grades and postgraduates in colleges and universities.

Automotive industry is going through a technological shock. Multiple intertwined technological advances (autonomous vehicle, connect vehicles and mobility-as-a-Service) are creating new rules for an industry that had not changed its way of doing business for almost a century. Key players from the tech and traditional automobile sectors – although with different incentives – are pooling resources to realize the goal of self-driving cars. AV innovation by auto and tech companies’ innovation is still largely home based, however, there is some shifting geography at the margin. AV and other related technologies are broadening the automotive innovation landscape, with several IT-focused hotspots – which traditionally were not at the center of automotive innovation – gaining prominence.

Automated driving system (ADS) technology and ADS-enabled/operated vehicles - commonly referred to as automated vehicles and autonomous vehicles (AVs) - have the potential to impact the world as significantly as the internal combustion engine. Successful ADS technologies could fundamentally transform the automotive industry, civil planning, the energy sector, and more. Rapid progress is being made in artificial intelligence (AI), which sits at the core of and forms the basis of ADS platforms. Consequently, autonomous capabilities such as those afforded by advanced driver assistance systems (ADAS) and other automation solutions are increasingly becoming available in the marketplace. To achieve highly or fully automated or autonomous capabilities, a major leap forward in the validation of these ADS technologies is required. Without this critical cog, helping to ensure the safety and reliability of these systems and platforms, the full capabilities of ADS technology will not be realized. This paper explores the ADS validation challenge by reviewing existing approaches and examining the effectiveness of those approaches, presenting critical techniques required to bring safe and effective solutions to market, discussing unsettled topics, and suggesting next steps for industry stakeholders to consider as they work to advance the ADS ecosystem. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019001

Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards and future developments of autonomous and connected heavy vehicles. This book provides insights into various issues pertaining to heavy vehicle technology and helps users develop solutions towards autonomous, connected, cognitive solutions through the convergence of Big Data, IoT, cloud computing and cognition analysis. Various physical, cyber-physical and computational key points related to connected vehicles are covered, along with concepts such as edge computing, dynamic resource optimization, engineering process, methodology and future directions. The book also contains a wide range of case studies that help to identify research problems and an analysis of the issues and synthesis solutions. This essential resource for graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics combines both basic concepts and advanced level content from technical experts. - Covers state-of-the-art developments and research in vehicle sensor technology, vehicle communication technology, convergence with emerging technologies, and vehicle software and hardware integration - Addresses challenges such as optimization, real-time control systems for distance and steering mechanism, and cognitive and predictive analysis - Provides complete product development, commercial deployment, technological and performing costs and scaling needs

Blockchain was first conceptualized as a method of building trust in machines and has grown into a vital aspect of many different sectors of the economy. Recently, attention has shifted to the field of autonomous vehicles, and the added value blockchain can provide for the future of this sector by building next generation secure decentralized, distributed, and trusted automated environments and enhancing the productivity of several autonomous applications. Opportunities and Challenges for Blockchain Technology in Autonomous Vehicles is a critical reference source that explores the applications of blockchain in automated industries. Featuring coverage on a wide range of topics including privacy, risk assessment, and performance optimization, this book is ideally designed for design engineers, industry professionals, cryptographers, service designers, entrepreneurs, government officials, consultants, researchers, academicians, and students.

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.

Emerging Library Technologies, is written for librarians/information professionals, teachers, administrators, researchers, undergraduate/graduate students, and others who are interested in learning about some of the most popular emerging technologies in the media today such as artificial intelligence, robotics, drones, driverless vehicles, big data, virtual/augmented reality, 3D printing, and wearable technologies. This valuable resource shows how they can be used in libraries and resource centers, and how to get stakeholder buy in for implementing these technologies. - Covers innovative insights on how these emerging technologies can be used in all types libraries and resource centers. - Discusses how to get key stakeholders on board before implementing emerging technologies including a checklist to complete before presenting your technology proposal to senior management. - Brings unique perspective for assisting people who will be displaced by these emerging technologies. - Includes resources at the end of every chapter on keeping abreast and building expertise on the emerging technology topic. - Contains tips on how professionals can forge strategic relationships to collaborate on emerging technology projects such as preparing students for STEM and STEAM careers. - Poses engaging questions for further discussion after each chapter. - Includes comprehensive glossary at the end of each chapter.