A vital book by industry thought leader and global AI expert, Dr. Lance Eliot, and based on his popular AI Insider series and podcasts, this fascinating book provides pioneering advances for the advent of AI self-driving driverless autonomous cars. Included too are keen insights about the practical application of Artificial Intelligence (AI) and Machines Learning (ML).
With the advent of advanced technologies in AI, driverless vehicles have elevated curiosity among various sectors of society. The automotive industry is in a technological boom with autonomous vehicle concepts. Autonomous driving is one of the crucial application areas of Artificial Intelligence (AI). Autonomous vehicles are armed with sensors, radars, and cameras. This made driverless technology possible in many parts of the world. In short, our traditional vehicle driving may swing to driverless technology. Many researchers are trying to come out with novel AI algorithms that are capable of handling driverless technology. The current existing algorithms are not able to support and elevate the concept of autonomous vehicles. This addresses the necessity of novel methods and tools focused to design and develop frameworks for autonomous vehicles. There is a great demand for energy-efficient solutions for managing the data collected with the help of sensors. These operations are exclusively focused on non-traditional programming approaches and depend on machine learning techniques, which are part of AI. There are multiple issues that AI needs to resolve for us to achieve a reliable and safe driverless technology. The purpose of this book is to find effective solutions to make autonomous vehicles a reality, presenting their challenges and endeavors. The major contribution of this book is to provide a bundle of AI solutions for driverless technology that can offer a safe, clean, and more convenient riskless mode of transportation.
Autonomous vehicles have attracted a great deal of attention in the media, however there are some inconsistencies between the perception of autonomous vehicles’ capabilities and their actual functions. This book provides an accessible explanation of how autonomous vehicles function, suggesting appropriate regulatory responses to the existing and emerging technology.
Top expert Dr. Lance B. Eliot provides the latest new insights about AI Autonomous Vehicles (AV) that are emerging as driverless self-driving cars and are progressively appearing on our roadways and byways. Vital issues he addresses include present and future technological advances, societal readiness, business aspects, economic considerations, and other ramifications about how this disruptive innovation will transform the world. Referred to as the "AI Insider" and currently serving as the Executive Director of the Cybernetic Self-Driving Car Institute for Techbrium Inc., he provides a no-holds-barred analysis of how Artificial Intelligence and Machine Learning are both a strength and a potential weakness in the effort toward developing true SAE Level 5 self-driving cars.
Explainable AI for Autonomous Vehicles: Concepts, Challenges, and Applications is a comprehensive guide to developing and applying explainable artificial intelligence (XAI) in the context of autonomous vehicles. It begins with an introduction to XAI and its importance in developing autonomous vehicles. It also provides an overview of the challenges and limitations of traditional black-box AI models and how XAI can help address these challenges by providing transparency and interpretability in the decision-making process of autonomous vehicles. The book then covers the state-of-the-art techniques and methods for XAI in autonomous vehicles, including model-agnostic approaches, post-hoc explanations, and local and global interpretability techniques. It also discusses the challenges and applications of XAI in autonomous vehicles, such as enhancing safety and reliability, improving user trust and acceptance, and enhancing overall system performance. Ethical and social considerations are also addressed in the book, such as the impact of XAI on user privacy and autonomy and the potential for bias and discrimination in XAI-based systems. Furthermore, the book provides insights into future directions and emerging trends in XAI for autonomous vehicles, such as integrating XAI with other advanced technologies like machine learning and blockchain and the potential for XAI to enable new applications and services in the autonomous vehicle industry. Overall, the book aims to provide a comprehensive understanding of XAI and its applications in autonomous vehicles to help readers develop effective XAI solutions that can enhance autonomous vehicle systems' safety, reliability, and performance while improving user trust and acceptance. This book: Discusses authentication mechanisms for camera access, encryption protocols for data protection, and access control measures for camera systems. Showcases challenges such as integration with existing systems, privacy, and security concerns while implementing explainable artificial intelligence in autonomous vehicles. Covers explainable artificial intelligence for resource management, optimization, adaptive control, and decision-making. Explains important topics such as vehicle-to-vehicle (V2V) communication, vehicle-to-infrastructure (V2I) communication, remote monitoring, and control. Emphasizes enhancing safety, reliability, overall system performance, and improving user trust in autonomous vehicles. The book is intended to provide researchers, engineers, and practitioners with a comprehensive understanding of XAI's key concepts, challenges, and applications in the context of autonomous vehicles. It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, information technology, and automotive engineering.
A vital book by industry thought leader and global AI expert, Dr. Lance Eliot, and based on his popular AI Insider series and podcasts, this fascinating book provides pioneering advances for the advent of AI self-driving driverless autonomous cars. Included too are keen insights about the practical application of Artificial Intelligence (AI) and Machines Learning (ML).
Experience the Future of Driving: A Glimpse into the World of Autonomous Vehicles Imagine a world where commuting no longer requires your hands on the wheel or your eyes on the road. AI at the Wheel: The Revolution of Autonomous Driving takes you on an engrossing journey through the transformative technology behind self-driving cars, showcasing a future that is closer than you think. Discover the milestones that have shaped autonomous driving, from the inception of early self-driving prototypes to the breakthroughs in AI and machine learning that enable vehicles to think and react like human drivers. Delve into the stories of the innovators and companies at the forefront of this groundbreaking industry. Uncover the profound impact autonomous vehicles will have on our lives. Learn how these marvels of technology will restructure urban landscapes, shift job markets, and create new economic opportunities. Explore the ethical considerations and legal debates that accompany this technological revolution, as well as the rigorous safety protocols that ensure the reliability of self-driving cars. Feel the pulse of a rapidly evolving industry as the author examines the role of big data, cybersecurity, and the expansive ecosystem supporting autonomous vehicles. From the complexities of V2X communication and energy efficiency to the future of ride-sharing and public transportation, each chapter offers a compelling look at the various dimensions of this technological marvel. Empower yourself with the knowledge to navigate an autonomous future. Whether you're a tech enthusiast, a business professional, or simply curious about what lies ahead, this book equips you with the insights to understand and embrace the coming changes. AI at the Wheel: The Revolution of Autonomous Driving is not just a book–it's your guide to the future.
Based on their systems expertise and their state-of-the-art research, the authors of this outstanding book explore practical and forward-thinking aspects about the emergence of driverless self-driving cars. Artificial Intelligence (AI) and Machine Learning are explored as a key to breakthroughs for self-driving car high-tech innovations. In addition, the authors cover the business, economic, and societal considerations about these autonomous vehicles. This duo has combined their key talents into a vital book packed with new insights and transformational ideas.
A vital book by industry thought leader and global AI expert, Dr. Lance Eliot, and based on his popular AI Insider series and podcasts, this fascinating book provides pioneering advances for the advent of AI self-driving driverless autonomous cars. Included too are keen insights about the practical application of Artificial Intelligence (AI) and Machines Learning (ML).
What Is Self Driving Car A car that incorporates vehicular automation is referred to as a self-driving car, autonomous vehicle (AV), autonomous car, driver-less car, or robotic car (robo-car). This refers to a ground vehicle that is capable of sensing its surroundings and moving safely with little or no input from a human driver. Other names for a self-driving car include driver-less car, robotic car (robo-car), and autonomous vehicle (AV). How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Self-driving car Chapter 2: Vehicular automation Chapter 3: Velodyne Lidar Chapter 4: Waymo Chapter 5: Mobileye Chapter 6: History of self-driving cars Chapter 7: Apple electric car project Chapter 8: Robotaxi Chapter 9: Tesla Autopilot Chapter 10: Ottomotto Chapter 11: Anthony Levandowski Chapter 12: Self-driving car liability Chapter 13: kar-go Chapter 14: Cruise (autonomous vehicle) Chapter 15: Lane centering Chapter 16: Self-driving truck Chapter 17: Yandex self-driving car Chapter 18: Criticism of Tesla, Inc. Chapter 19: Aurora Innovation Chapter 20: Impact of self-driving cars Chapter 21: Woven Planet Holdings (II) Answering the public top questions about self driving car. (III) Real world examples for the usage of self driving car in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of self driving car' technologies. 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.
