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The Cutting Edge of AI Autonomous Cars

Author: Lance B. Eliot

Publisher: Lbe Press Publishing

Published: 2018-10-26

Total Pages: 276

ISBN-13: 9780578409641

An insightful treatise 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 Autonomous cars (also referred to as self-driving cars and driverless cars). Included too are essential advances about the practical application of Artificial Intelligence (AI) and Machines Learning (ML).

AI-enabled Technologies for Autonomous and Connected Vehicles

Author: Yi Lu Murphey

Publisher: Springer Nature

Published: 2022-09-07

Total Pages: 563

ISBN-13: 3031067800

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This book reports on cutting-edge research and advances in the field of intelligent vehicle systems. It presents a broad range of AI-enabled technologies, with a focus on automated, autonomous and connected vehicle systems. It covers advanced machine learning technologies, including deep and reinforcement learning algorithms, transfer learning and learning from big data, as well as control theory applied to mobility and vehicle systems. Furthermore, it reports on cutting-edge technologies for environmental perception and vehicle-to-everything (V2X), discussing socioeconomic and environmental implications, and aspects related to human factors and energy-efficiency alike, of automated mobility. Gathering chapters written by renowned researchers and professionals, this book offers a good balance of theoretical and practical knowledge. It provides researchers, practitioners and policy makers with a comprehensive and timely guide on the field of autonomous driving technologies.

Human-Like Decision Making and Control for Autonomous Driving

Author: Peng Hang

Publisher: CRC Press

Published: 2022-07-25

Total Pages: 201

ISBN-13: 1000624951

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This book details cutting-edge research into human-like driving technology, utilising game theory to better suit a human and machine hybrid driving environment. Covering feature identification and modelling of human driving behaviours, the book explains how to design an algorithm for decision making and control of autonomous vehicles in complex scenarios. Beginning with a review of current research in the field, the book uses this as a springboard from which to present a new theory of human-like driving framework for autonomous vehicles. Chapters cover system models of decision making and control, driving safety, riding comfort and travel efficiency. Throughout the book, game theory is applied to human-like decision making, enabling the autonomous vehicle and the human driver interaction to be modelled using noncooperative game theory approach. It also uses game theory to model collaborative decision making between connected autonomous vehicles. This framework enables human-like decision making and control of autonomous vehicles, which leads to safer and more efficient driving in complicated traffic scenarios. The book will be of interest to students and professionals alike, in the field of automotive engineering, computer engineering and control engineering.

AI-enabled Technologies for Autonomous and Connected Vehicles

Author: Yi Lu Murphey

Publisher: Springer

Published: 2022-09-27

Total Pages: 0

ISBN-13: 9783031067792

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Artificial Intelligence for Autonomous Vehicles

Author: Sathiyaraj Rajendran

Publisher: John Wiley & Sons

Published: 2024-02-27

Total Pages: 208

ISBN-13: 111984763X

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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.

Robot Ethics 2.0

Author: Patrick Lin

Publisher: Oxford University Press

Published: 2017-09-01

Total Pages: 352

ISBN-13: 0190652969

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The robot population is rising on Earth and other planets. (Mars is inhabited entirely by robots.) As robots slip into more domains of human life--from the operating room to the bedroom--they take on our morally important tasks and decisions, as well as create new risks from psychological to physical. This makes it all the more urgent to study their ethical, legal, and policy impacts. To help the robotics industry and broader society, we need to not only press ahead on a wide range of issues, but also identify new ones emerging as quickly as the field is evolving. For instance, where military robots had received much attention in the past (and are still controversial today), this volume looks toward autonomous cars here as an important case study that cuts across diverse issues, from liability to psychology to trust and more. And because robotics feeds into and is fed by AI, the Internet of Things, and other cognate fields, robot ethics must also reach into those domains, too. Expanding these discussions also means listening to new voices; robot ethics is no longer the concern of a handful of scholars. Experts from different academic disciplines and geographical areas are now playing vital roles in shaping ethical, legal, and policy discussions worldwide. So, for a more complete study, the editors of this volume look beyond the usual suspects for the latest thinking. Many of the views as represented in this cutting-edge volume are provocative--but also what we need to push forward in unfamiliar territory.

Road Terrain Classification Technology for Autonomous Vehicle

Author: Shifeng Wang

Publisher: Springer

Published: 2019-03-15

Total Pages: 97

ISBN-13: 981136155X

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This book provides cutting-edge insights into autonomous vehicles and road terrain classification, and introduces a more rational and practical method for identifying road terrain. It presents the MRF algorithm, which combines the various sensors’ classification results to improve the forward LRF for predicting upcoming road terrain types. The comparison between the predicting LRF and its corresponding MRF show that the MRF multiple-sensor fusion method is extremely robust and effective in terms of classifying road terrain. The book also demonstrates numerous applications of road terrain classification for various environments and types of autonomous vehicle, and includes abundant illustrations and models to make the comparison tables and figures more accessible.

Deep Learning for Autonomous Vehicle Control

Author: Sampo Kuutti

Publisher: Morgan & Claypool Publishers

Published: 2019-08-08

Total Pages: 82

ISBN-13: 168173608X

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The next generation of autonomous vehicles will provide major improvements in traffic flow, fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of autonomous vehicles, one aspect of which is robust and adaptable vehicle control. Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which it may encounter after deployment. However, deep learning methods have shown great promise in not only providing excellent performance for complex and non-linear control problems, but also in generalizing previously learned rules to new scenarios. For these reasons, the use of deep neural networks for vehicle control has gained significant interest. In this book, we introduce relevant deep learning techniques, discuss recent algorithms applied to autonomous vehicle control, identify strengths and limitations of available methods, discuss research challenges in the field, and provide insights into the future trends in this rapidly evolving field.

Leading Edge Trends for AI Driverless Cars

Author: Lance Eliot

Publisher: Lbe Press Publishing

Published: 2018-10-03

Total Pages: 264

ISBN-13: 9780692042403

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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 cars. Included too are keen insights about the practical application of Artificial Intelligence (AI) and Machines Learning (ML).

Autonomous Vehicles

Author: Steven Van Uytsel

Publisher: Springer Nature

Published: 2020-12-21

Total Pages: 229

ISBN-13: 9811592551

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This edited book aims to address challenges facing the deployment of autonomous vehicles. Autonomous vehicles were predicted to hit the road by 2017. Even though a high degree of automation may have been achieved, vehicles that can drive autonomously under all circumstances are not yet commercially available, and the predictions have been adjusted. Now, experts even say that we are still decades away from fully autonomous vehicles. In this volume, the authors form a multidisciplinary team of experts to discuss some of the reasons behind this delay. The focus is on three areas: business, technology, and law. The authors discuss how the traditional car manufacturers have to devote numerous resources to the development of a new business model, in which the sole manufacturing of vehicles may no longer be sufficient. In addition, the book seeks to introduce how technological challenges are creating a shift toward connected autonomous vehicles. Further, it provides insight into how regulators are responding to the insufficiently tested technology and how lawyers try to answer the liability question for accidents with these autonomous vehicles.