Self Learning Longitudinal Control For On Road Vehicles
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Self Learning Longitudinal Control For On Road Vehicles
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Author : Puccetti, Luca
language : en
Publisher: KIT Scientific Publishing
Release Date : 2023-06-16
Self Learning Longitudinal Control For On Road Vehicles written by Puccetti, Luca and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-16 with categories.
Reinforcement Learning is a promising tool to automate controller tuning. However, significant extensions are required for real-world applications to enable fast and robust learning. This work proposes several additions to the state of the art and proves their capability in a series of real world experiments.
Limited Information Shared Control And Its Applications To Large Vehicle Manipulators
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Author : Varga, Bálint
language : en
Publisher: KIT Scientific Publishing
Release Date : 2024-01-08
Limited Information Shared Control And Its Applications To Large Vehicle Manipulators written by Varga, Bálint and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-08 with categories.
This work focuses on the Limited Information Shared Control and its controller design using potential games. Through the developed systematic controller design, the experiments demonstrate the effectiveness and superiority of this concept compared to traditional manual and non-cooperative control approaches in the application of large vehicle manipulators.
Deep Learning For Autonomous Vehicle Control
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Author : Sampo Kuutti
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Deep Learning For Autonomous Vehicle Control written by Sampo Kuutti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.
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.
2019 Ieee International Conference On Electro Information Technology Eit
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Author :
language : en
Publisher:
Release Date : 2019
2019 Ieee International Conference On Electro Information Technology Eit written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Computer engineering categories.
Reinforcement Learning For Sequential Decision And Optimal Control
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Author : Shengbo Eben Li
language : en
Publisher: Springer Nature
Release Date : 2023-04-05
Reinforcement Learning For Sequential Decision And Optimal Control written by Shengbo Eben Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-05 with Computers categories.
Have you ever wondered how AlphaZero learns to defeat the top human Go players? Do you have any clues about how an autonomous driving system can gradually develop self-driving skills beyond normal drivers? What is the key that enables AlphaStar to make decisions in Starcraft, a notoriously difficult strategy game that has partial information and complex rules? The core mechanism underlying those recent technical breakthroughs is reinforcement learning (RL), a theory that can help an agent to develop the self-evolution ability through continuing environment interactions. In the past few years, the AI community has witnessed phenomenal success of reinforcement learning in various fields, including chess games, computer games and robotic control. RL is also considered to be a promising and powerful tool to create general artificial intelligence in the future. As an interdisciplinary field of trial-and-error learning and optimal control, RL resembles how humans reinforce their intelligence by interacting with the environment and provides a principled solution for sequential decision making and optimal control in large-scale and complex problems. Since RL contains a wide range of new concepts and theories, scholars may be plagued by a number of questions: What is the inherent mechanism of reinforcement learning? What is the internal connection between RL and optimal control? How has RL evolved in the past few decades, and what are the milestones? How do we choose and implement practical and effective RL algorithms for real-world scenarios? What are the key challenges that RL faces today, and how can we solve them? What is the current trend of RL research? You can find answers to all those questions in this book. The purpose of the book is to help researchers and practitioners take a comprehensive view of RL and understand the in-depth connection between RL and optimal control. The book includes not only systematic and thorough explanations of theoretical basics but also methodical guidance of practical algorithm implementations. The book intends to provide a comprehensive coverage of both classic theories and recent achievements, and the content is carefully and logically organized, including basic topics such as the main concepts and terminologies of RL, Markov decision process (MDP), Bellman’s optimality condition, Monte Carlo learning, temporal difference learning, stochastic dynamic programming, function approximation, policy gradient methods, approximate dynamic programming, and deep RL, as well as the latest advances in action and state constraints, safety guarantee, reference harmonization, robust RL, partially observable MDP, multiagent RL, inverse RL, offline RL, and so on.
A System Level Study Of The Longitudinal Control Of A Platoon Of Vehicles
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Author : Shahab Sheikholeslam
language : en
Publisher:
Release Date : 1992
A System Level Study Of The Longitudinal Control Of A Platoon Of Vehicles written by Shahab Sheikholeslam and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with categories.
Real Time Applications Of Machine Learning In Cyber Physical Systems
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Author : Easwaran, Balamurugan
language : en
Publisher: IGI Global
Release Date : 2022-03-11
Real Time Applications Of Machine Learning In Cyber Physical Systems written by Easwaran, Balamurugan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Computers categories.
Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.
Autonomous Road Vehicle Path Planning And Tracking Control
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Author : Levent Guvenc
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-06
Autonomous Road Vehicle Path Planning And Tracking Control written by Levent Guvenc and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-06 with Technology & Engineering categories.
Discover the latest research in path planning and robust path tracking control In Autonomous Road Vehicle Path Planning and Tracking Control, a team of distinguished researchers delivers a practical and insightful exploration of how to design robust path tracking control. The authors include easy to understand concepts that are immediately applicable to the work of practicing control engineers and graduate students working in autonomous driving applications. Controller parameters are presented graphically, and regions of guaranteed performance are simple to visualize and understand. The book discusses the limits of performance, as well as hardware-in-the-loop simulation and experimental results that are implementable in real-time. Concepts of collision and avoidance are explained within the same framework and a strong focus on the robustness of the introduced tracking controllers is maintained throughout. In addition to a continuous treatment of complex planning and control in one relevant application, the Autonomous Road Vehicle Path Planning and Tracking Control includes: A thorough introduction to path planning and robust path tracking control for autonomous road vehicles, as well as a literature review with key papers and recent developments in the area Comprehensive explorations of vehicle, path, and path tracking models, model-in-the-loop simulation models, and hardware-in-the-loop models Practical discussions of path generation and path modeling available in current literature In-depth examinations of collision free path planning and collision avoidance Perfect for advanced undergraduate and graduate students with an interest in autonomous vehicles, Autonomous Road Vehicle Path Planning and Tracking Control is also an indispensable reference for practicing engineers working in autonomous driving technologies and the mobility groups and sections of automotive OEMs.
Roadvehicles Surroundings Supervision On Board Sensors And Communications
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Author : Felipe Jimenez
language : en
Publisher: MDPI
Release Date : 2019-01-29
Roadvehicles Surroundings Supervision On Board Sensors And Communications written by Felipe Jimenez and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Motor vehicles. Aeronautics. Astronautics categories.
This book is a printed edition of the Special Issue "Road Vehicles Surroundings Supervision: On-Board Sensors and Communications" that was published in Applied Sciences
Handbook Of Research On Emerging Trends And Applications Of Machine Learning
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Author : Solanki, Arun
language : en
Publisher: IGI Global
Release Date : 2019-12-13
Handbook Of Research On Emerging Trends And Applications Of Machine Learning written by Solanki, Arun and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-13 with Computers categories.
As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.