Reinforcement Learning In Eco Driving For Connected And Automated Vehicles
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| Author | : Yi Lu Murphey |
| Publisher | : Springer Nature |
| Total Pages | : 563 |
| Release | : 2022-09-07 |
| Genre | : Technology & Engineering |
| ISBN | : 3031067800 |
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.
| Author | : Fei Hu |
| Publisher | : CRC Press |
| Total Pages | : 608 |
| Release | : 2023-05-12 |
| Genre | : Computers |
| ISBN | : 1000877256 |
Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.
| Author | : Biao Luo |
| Publisher | : Springer Nature |
| Total Pages | : 532 |
| Release | : 2024 |
| Genre | : Neural computers |
| ISBN | : 9819981840 |
The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
| Author | : Hao Dong |
| Publisher | : Springer Nature |
| Total Pages | : 526 |
| Release | : 2020-06-29 |
| Genre | : Computers |
| ISBN | : 9811540950 |
Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance. Divided into three main parts, this book provides a comprehensive and self-contained introduction to DRL. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation. The second part covers selected DRL research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, with detailed explanations. The book is intended for computer science students, both undergraduate and postgraduate, who would like to learn DRL from scratch, practice its implementation, and explore the research topics. It also appeals to engineers and practitioners who do not have strong machine learning background, but want to quickly understand how DRL works and use the techniques in their applications.
| Author | : Vipin Kumar Kukkala |
| Publisher | : Springer Nature |
| Total Pages | : 782 |
| Release | : 2023-10-03 |
| Genre | : Technology & Engineering |
| ISBN | : 3031280164 |
This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.
| Author | : Xinhang Li |
| Publisher | : OAE Publishing Inc. |
| Total Pages | : 17 |
| Release | : 2023-09-13 |
| Genre | : Computers |
| ISBN | : |
Multi-vehicle pursuit (MVP) is one of the most challenging problems for intelligent traffic management systems due to multi-source heterogeneous data and its mission nature. While many reinforcement learning (RL) algorithms have shown promising abilities for MVP in structured grid-pattern roads, their lack of dynamic and effective traffic awareness limits pursuing efficiency. The sparse reward of pursuing tasks still hinders the optimization of these RL algorithms. Therefore, this paper proposes a distributed generative multi-adversarial RL for MVP (DGMARL-MVP) in urban traffic scenes. In DGMARL-MVP, a generative multi-adversarial network is designed to improve the Bellman equation by generating the potential dense reward, thereby properly guiding strategy optimization of distributed multi-agent RL. Moreover, a graph neural network-based intersecting cognition is proposed to extract integrated features of traffic situations and relationships among agents from multi-source heterogeneous data. These integrated and comprehensive traffic features are used to assist RL decision-making and improve pursuing efficiency. Extensive experimental results show that the DGMARL-MVP can reduce the pursuit time by 5.47% compared with proximal policy optimization and improve the pursuing average success rate up to 85.67%. Codes are open-sourced in Github.
| Author | : UMAR ZAKIR ABDUL HAMID |
| Publisher | : SAE International |
| Total Pages | : 213 |
| Release | : 2022-10-28 |
| Genre | : Technology & Engineering |
| ISBN | : 1468603485 |
We are at the beginning of the next major disruptive cycle caused by computing. In transportation, the term Autonomous, Connected, Electric, and Shared (ACES) has been coined to represent the enormous innovations enabled by underlying electronics technology. The benefits of ACES vehicles range from improved safety, reduced congestion, and lower stress for car occupants to social inclusion, lower emissions, and better road utilization due to optimal integration of private and public transport. ACES is creating a new automotive and industrial ecosystem that will disrupt not only the technical development of transportation but also the management and supply chain of the industry. Disruptions caused by ACES are prompted by not only technology but also by a shift from a traditional to a software-based mindset, embodied by the arrival of a new generation of automotive industry workforce. In Autonomous, Connected, Electric and Shared Vehicles: Disrupting the Automotive and Mobility Sectors, Umar Zakir Abdul Hamid provides an overview of ACES technology for cross-disciplinary audiences, including researchers, academics, and automotive professionals. Hamid bridges the gap among the book’s varied audiences, exploring the development and deployment of ACES vehicles and the disruptions, challenges, and potential benefits of this new technology. Topics covered include: • Recent trends and progress stimulating ACES growth and development • ACES vehicle overview • Automotive and mobility industry disruptions caused by ACES • Challenges of ACES implementation • Potential benefits of the ACES ecosystem While market introduction of ACES vehicles that are fully automated and capable of unsupervised driving in an unstructured environment is still a long-term goal, the future of mobility will be ACES, and the transportation industry must prepare for this transition. Autonomous, Connected, Electric and Shared Vehicles is a necessary resource for anyone interested in the successful and reliable implementation of ACES. “ACES are destined to be a game changers on the roads, altering the face of mobility.” Daniel Watzenig, Professor Graz University of Technology, Austria
| Author | : Wuhong Wang |
| Publisher | : Springer Nature |
| Total Pages | : 841 |
| Release | : 2021-12-13 |
| Genre | : Technology & Engineering |
| ISBN | : 9811654298 |
These proceedings gather selected papers from the 11th International Conference on Green Intelligent Transportation Systems and Safety, held in Beijing, China on October 17-19, 2020. The book features cutting-edge studies on Green Intelligent Mobility Systems, the guiding motto being to achieve “green, intelligent, and safe transportation systems”. The contributions presented here can help promote the development of green mobility and intelligent transportation technologies to improve interconnectivity, resource sharing, flexibility and efficiency. Given its scope, the book will benefit researchers and engineers in the fields of Transportation Technology and Traffic Engineering, Automotive and Mechanical Engineering, Industrial and System Engineering, and Electrical Engineering alike. The readers will be able to find out the Advances in Green Intelligent Transportation System and Safety.
| Author | : Hussein T. Mouftah |
| Publisher | : CRC Press |
| Total Pages | : 517 |
| Release | : 2020-12-17 |
| Genre | : Science |
| ISBN | : 1000258971 |
This book presents a comprehensive coverage of the five fundamental yet intertwined pillars paving the road towards the future of connected autonomous electric vehicles and smart cities. The connectivity pillar covers all the latest advancements and various technologies on vehicle-to-everything (V2X) communications/networking and vehicular cloud computing, with special emphasis on their role towards vehicle autonomy and smart cities applications. On the other hand, the autonomy track focuses on the different efforts to improve vehicle spatiotemporal perception of its surroundings using multiple sensors and different perception technologies. Since most of CAVs are expected to run on electric power, studies on their electrification technologies, satisfaction of their charging demands, interactions with the grid, and the reliance of these components on their connectivity and autonomy, is the third pillar that this book covers. On the smart services side, the book highlights the game-changing roles CAV will play in future mobility services and intelligent transportation systems. The book also details the ground-breaking directions exploiting CAVs in broad spectrum of smart cities applications. Example of such revolutionary applications are autonomous mobility on-demand services with integration to public transit, smart homes, and buildings. The fifth and final pillar involves the illustration of security mechanisms, innovative business models, market opportunities, and societal/economic impacts resulting from the soon-to-be-deployed CAVs. This book contains an archival collection of top quality, cutting-edge and multidisciplinary research on connected autonomous electric vehicles and smart cities. The book is an authoritative reference for smart city decision makers, automotive manufacturers, utility operators, smart-mobility service providers, telecom operators, communications engineers, power engineers, vehicle charging providers, university professors, researchers, and students who would like to learn more about the advances in CAEVs connectivity, autonomy, electrification, security, and integration into smart cities and intelligent transportation systems.
| Author | : Kundan Meshram |
| Publisher | : John Wiley & Sons |
| Total Pages | : 420 |
| Release | : 2024-09-27 |
| Genre | : Technology & Engineering |
| ISBN | : 1394228449 |
This exciting new volume covers the most up-to-date advances, theories, and practical applications for non-motorized transportation (NMT) systems, geographic information system-based transportation systems, and signal processing for urban transportation systems. This book will allow readers to readers to identify traffic and transport problems in cities and to study mass transportation systems, and modes of transportation and their characteristics, focusing on transportation infrastructure which includes green bays, control stations, mitigation buildings, separator lanes, and safety islands. From this, readers will be able to study urban public transport systems and gain some background into intelligent transportation and telemetric systems, including techniques for designing transport telemetric systems and applying them to urban transportation. Applications include advanced traffic management systems, advanced traveler information systems, advanced vehicle control systems, commercial vehicle operational management, advanced public transportation systems, electronic payment systems, advanced urban transportation, security and safety systems, and urban traffic control. From this, an artificial Intelligence-based transportation system design using genetic algorithms and neural networks is discussed, to show applications in designs. These models and their studies are further extended in signal processing systems and geographic information systems (GIS) to improve transportation system design, and to apply this to the design of non-motorized transportation models, while ensuring pedestrian safety. All these models are further analyzed for environmental impact assessment, which include structural audits, analysis of site selection procedure, baseline conditions and major concerns, green building and its advantages, the description of potential environmental effects, and many more interesting topics.
