Ai Self Driving Cars Vicissitude

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.

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.”

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).

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.

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.

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.

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.

Global expert on AI and self-driving driverless cars, Dr. Lance Eliot provides an indication of the crucial high-tech advances both needed and that are underway. He brings together his deep insights into the rise of Autonomous Vehicles (AV) and covers the high-tech, business, governmental, and societal impacts. For access to his podcasts, see his web site: www.ai-selfdriving-cars.guru

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).