As Apollo 11's Lunar Module descended toward the moon under automatic control, a program alarm in the guidance computer's software nearly caused a mission abort. Neil Armstrong responded by switching off the automatic mode and taking direct control. He stopped monitoring the computer and began flying the spacecraft, relying on skill to land it and earning praise for a triumph of human over machine. In Digital Apollo, engineer-historian David Mindell takes this famous moment as a starting point for an exploration of the relationship between humans and computers in the Apollo program. In each of the six Apollo landings, the astronaut in command seized control from the computer and landed with his hand on the stick. Mindell recounts the story of astronauts' desire to control their spacecraft in parallel with the history of the Apollo Guidance Computer. From the early days of aviation through the birth of spaceflight, test pilots and astronauts sought to be more than "spam in a can" despite the automatic controls, digital computers, and software developed by engineers. Digital Apollo examines the design and execution of each of the six Apollo moon landings, drawing on transcripts and data telemetry from the flights, astronaut interviews, and NASA's extensive archives. Mindell's exploration of how human pilots and automated systems worked together to achieve the ultimate in flight--a lunar landing--traces and reframes the debate over the future of humans and automation in space. The results have implications for any venture in which human roles seem threatened by automated systems, whether it is the work at our desktops or the future of exploration.David A. Mindell is Dibner Professor of the History of Engineering and Manufacturing, Professor of Engineering Systems, and Director of the Program in Science, Technology, and Society at MIT. He is the author of Between Human and Machine: Feedback, Control, and Computing before Cybernetics and War, Technology, and Experience aboard the USS Monitor.

Designed for those involved with intelligent transportation systems (ITS), this volume guides the reader through the fundamentals that are essential for planning and operations. This reference focuses on traffic flow fundamentals and application areas, issues and principles. It includes discussion of security concerns in transportation systems, seeking to allow a greater degree of confidence in the success of your projects before actual implementation.

Here's a complete, up-to-date survey of modern transportation systems. It provides the 30-point framework underlying most major transportation systems, and it closely examines current and emergent activity to improve both freight and passenger transportation.

Using the 30-point framework as a guide, transportation professionals can more effectively analyze existing and proposed systems. Plus, the book clearly explains ITS concepts and gives some perspectives of ITS' future. Featuring an extensive explanation of common transportation systems, this book helps you understand the needs of the customer of transportation services, how those needs shape decision-making, and the complex relationships among transportation technologies, systems, and institutions. Using this guide helps you design transportation systems and programs based on a strong fundamental understanding of how current systems work and the key issues impacting them.

During the last decade, developments in smart cars, mobile devices, internet of things and vehicular communications are revolutionizing the future of smart cities. With the rapid integration of these smart devices into our surroundings, we are heading to a new era of a highly connected and environmentally friendly ecosystem.This book offers a unique opportunity for the reader to explore state-of-the-art developments in applications, technologies (e.g., Big Data and artificial intelligence), services and research trends in smart mobility for smart cities. It also provides a reference for professionals and researchers in the areas of smart mobility (e.g., autonomous valet parking, passenger trajectory data, smart traffic control systems) and recent technical trends on their enabling technologies. The materials have been carefully selected to reflect the latest developments in the field with many novel contributions from academics and industry experts from around the world.

In the modern world, further development of society is impossible without environmentally friendly modes of transport and their effective interaction within the framework of Smart Energy and ECO-driving concepts. Written at a time of rapid development of information technologies in various fields, this book serves as a kind of bridge for the introduction of artificial intelligence into the electric transport power supply systems.The calculation models and methods proposed make it possible to choose the most efficient modern equipment for electric power supply of electric vehicles, which, as a result, saves investment costs and reduces time to make decisions for designing complex objects. Insight is also given into building and adjusting Smart Energy class equipment to achieve optimal and economical modes.

This collection of chapters on the latest methods and tools for applied research in aviation psychology guides the diverse range of professionals working within aviation on how to adapt flexibly to the continuously evolving requirements of the aeronautical landscape. Experts from the industry and academia explore selected applications, ranging from aviation system engineering to bridging the gap between research and industrialization, safety culture, training and examination. Psychological tools are explored, including designing biocybernetic adaptive systems, predictive automation, and support for designing the human role in future human-machine teaming concepts. Special chapters are dedicated to spatial disorientation, reactivity, stress, eye-tracking, electrodermal and cardiac assessment under the influence of G forces. This is essential reading for aviation psychologists, human factors practitioners, engineers, designers, operational specialists, students and researchers in academia, industry, and government. The practitioners and researchers working in other safety critical domains (e.g., medicine, automotive) will also find the handbook valuable.

This book lays a new foundation toward achieving artificial self-intelligence by future machines such as intelligent vehicles. Its chapters provide a broad coverage to the three key modules behind the design and development of intelligent vehicles for the ultimate purpose of actively ensuring driving safety as well as preventing accidents from all possible causes. Self-contained and unified in presentation, the book explains in details the fundamental solutions of vehicle's perception, vehicle's decision-making, and vehicle's action-taking in a pedagogic order.Besides the fundamental knowledge and concepts of intelligent vehicle's perception, decision and action, this book includes a comprehensive set of real-life application scenarios in which intelligent vehicles will play a major role or contribution. These case studies of real-life applications will help motivate students to learn this exciting subject. With concise and simple explanations, and boasting a rich set of graphical illustrations, the book is an invaluable source for both undergraduate and postgraduate courses, on artificial intelligence, intelligent vehicle, and robotics, which are offered in automotive engineering, computer engineering, electronic engineering, and mechanical engineering. In addition, the book will help strengthen the knowledge and skills of young researchers who want to venture into the research and development of artificial self-intelligence for intelligent vehicles of the future.Related Link(s)

Although the concept of a fully automated driving system as envisioned under the Automated Highway System program has yet to be realised, technological advancements over the past decade have led to the emergence of advanced driver assistance systems and features such as Adaptive Cruise Control (ACC), collision warning, automatic braking, and lane-keeping assist systems. To date, deployed systems and features have largely been designed to support safe operations rather than to relieve the driver of direct vehicle control. Advancements in driver assistance systems (eg: ACC and lane-keeping assist) may provide some of the early building blocks for future automated driving systems that assume either partial or full authority from the driver. Although automated systems offer the promise of increased safety and reduced human error, substantive human factors challenges need to be addressed before these forms of automated systems become a practical reality. These challenges include the potential for negative adaptations occurring through misunderstanding of, misuse of, or overreliance on the system, or changes in attention and distraction from the driving task. Another concern is how an automated system will impact drivers' information-processing capabilities and level of workload, including their willingness to engage in non-driving-related secondary tasks. Automation may also impact a driver's situational awareness -- including the ability to perceive critical factors in the environment or to detect system state changes (system failures) -- as the driver's role shifts from active vehicle control to passive monitoring of the automated system and environment, and path planning down the road. This book assesses the research, the technology and the concepts behind automated driving.

While many transportation and city planners, researchers, students, practitioners, and political leaders are familiar with the technical nature and promise of vehicle automation, consensus is not yet often seen on the impact that will result, or the policies and actions that those responsible for transportation systems should take. The End of Driving: Transportation Systems and Public Policy Planning for Autonomous Vehicles explores both the potential of vehicle automation technology and the barriers it faces when considering coherent urban deployment. The book evaluates the case for deliberate development of automated public transportation and mobility-as-a-service as paths towards sustainable mobility, describing critical approaches to the planning and management of vehicle automation technology. It serves as a reference for understanding the full life cycle of the multi-year transportation systems planning processes, including novel regulation, planning, and acquisition tools for regional transportation. Application-oriented, research-based, and solution-oriented rather than predict-and-warn, The End of Driving concludes with a detailed discussion of the systems design needed for accomplishing this shift. From the Foreword by Susan Shaheen: The authors ... extend potential solutions through a set of open-ended exercises after each chapter. Their approach is both strategic and deliberate. They lead the reader from definitions and context setting to the transition toward automation, employing a range of creative strategies and policies. While our quest to understand how to deploy automated vehicles is just beginning, this book provides a thoughtful introduction to inform this evolution.

A number of wireless technologies have been developed in recent years to meet the increasing needs of high-speed wireless communications in civil and military applications. The advances include WiFi (IEEE 802.11), WiMAX (IEEE 802.16), sensor networks, wireless Mesh/Ad hoc networks, mobile IP, smart antenna, cognitive radio, and so on. These emerging technologies will significantly impact the design and operation of Intelligent Transportation Systems, which aims to effectively provide higher vehicles safety, traffic management, and communications among vehicles and transport infrastructure. Organised into three parts, 'Wireless Technologies for Intelligent Transportation Systems' provides readers a thorough technical guide covering various wireless technologies developed in the most recent years for Intelligent Transportation Systems applications. It presents key technologies of circuits and physical layer, network protocols, system designs and applications. The broad content covers topics of radar sensor, radio channel modelling, smart antenna, medium access control, routing protocol, data dissemination, hand-over, security, mesh networking, road traffic estimation and monitoring, and location-based services. This comprehensive book is a collection of basic concepts, major issues, design approaches, application examples, and future research directions of various advanced technologies developed for Intelligent Transportation Systems. With its broad coverage allowing cross reference, it serves as an essential reference for engineers, researchers, students, scientists, professors, designers and planners of Intelligent Transportation Systems.

This book deals with the estimation of travel time in a very comprehensive and exhaustive way. Travel time information is and will continue to be one key indicator of the quality of service of a road network and a highly valued knowledge for drivers. Moreover, travel times are key inputs for comprehensive traffic management systems. All the above-mentioned aspects are covered in this book. The first chapters expound on the different types of travel time information that traffic management centers work with, their estimation, their utility and their dissemination. They also remark those aspects in which this information should be improved, especially considering future cooperative driving environments.Next, the book introduces and validates two new methodologies designed to improve current travel time information systems, which additionally have a high degree of applicability: since they use data from widely disseminated sources, they could be immediately implemented by many administrations without the need for large investments. Finally, travel times are addressed in the context of dynamic traffic management systems. The evolution of these systems in parallel with technological and communication advancements is thoroughly discussed. Special attention is paid to data analytics and models, including data-driven approaches, aimed at understanding and predicting travel patterns in urban scenarios. Additionally, the role of dynamic origin-to-destination matrices in these schemes is analyzed in detail.

The first edited volume addressing analysis for unmanned vehicles, with focus on operations research rather than engineering The editors have a unique combination of extensive operational experience and technical expertise Chapters address a wide-ranging set of examples, domains and applications Accessible to a general readership and also informative for experts

This book introduces readers to the key provisions of the URRAN-based technical asset management system - a methodology for managing resources and risks by analyzing and ensuring the required levels of reliability and safety in Russia's railway transport facilities. It describes the architecture of the URRAN information system's unified corporate platform (UCP URRAN) and its subsystems for infrastructure facilities and rolling stock complexes. It also highlights the UCP URRAN's prospects for development, especially in the application of artificial intelligence to predict dangerous events in railway transport operation. The book is chiefly intended for specialists engaged in practical work on the technical maintenance of railway transport facilities. It can also be used as a reference guide for students and researchers at railway universities or professionals who are dealing with problems in technical asset management in other industries.

Logistics and supply chain management deal with managing the ?ow of goods or services within a company, from suppliers to customers, and along a supply chain where companies act as suppliers as well as customers. As transportation is at the heart of logistics, the design of tra?c and transportation networks combined with the routing of vehicles and goods on the networks are important and demanding planning tasks. The in?uence of transport, logistics, and s- ply chain management on the modern economy and society has been growing steadily over the last few decades. The worldwide division of labor, the conn- tion of distributed production centers, and the increased mobility of individuals lead to an increased demand for e?cient solutions to logistics and supply chain management problems. On the company level, e?cient and e?ective logistics and supply chain management are of critical importance for a company's s- cessanditscompetitiveadvantage. Properperformanceofthelogisticsfunctions can contribute both to lower costs and to enhanced customer service. Computational Intelligence (CI) describes a set of methods and tools that often mimic biological or physical principles to solve problems that have been di?cult to solve by classical mathematics. CI embodies neural networks, fuzzy logic, evolutionary computation, local search, and machine learning approaches. Researchersthat workinthis areaoften comefromcomputer science, operations research, or mathematics, as well as from many di?erent engineering disciplines. Popular and successful CI methods for optimization and planning problems are heuristic optimization approaches such as evolutionary algorithms, local search methods, and other types of guided search methods.

With a focus on cargo transportation, this book addresses the development of approaches intended to secure an infrastructure of smart services to support the adaptive implementation of online multi-modal freight transport management processes. It discusses the development of multi-criteria decision-making components and their integration into the multi-layered computer-based information management of intelligent systems. Through detailed descriptions of various components of intelligent transport management systems, the book demonstrates how to develop the services needed in the right place and at the right time, and how to properly adapt to user needs, making necessary interventions to ensure the safety of the transportation process. Further, it describes the main ways to increase the autonomy and efficiency of user-vehicle interaction and shows how Information and Communications Technology (ICT) structural support for current and past situations in AI-based systems can help to anticipate future developments in freight transportation.

This book provides readers with expert knowledge on the design of fast charging infrastructures and their planning in smart cities and communities to support autonomous transportation. The recent development of fast charging infrastructures using hybrid energy systems is examined, along with aspects of connected and autonomous vehicles (CAV) and their integration within transportation networks and city infrastructures. The book looks at challenges and opportunities for autonomous transportation, including connected and autonomous vehicles, shuttles, and their technology development and deployment within smart communities. Intelligent control strategies, architectures, and systems are also covered, along with intelligent data centers that ensure effective transportation networks during normal and emergency situations. Planning strategies are presented to demonstrate the resilient transportation infrastructures, and optimized performance is discussed in view of performance indicators and requirements specifications, as well as regulations and standards.

This book establishes the models of the electric motor, the hydraulic compound brake system, and the electromagnetic and friction integrated brake system. Considering the two principles on safety and energy saving, it proposes a hybrid brake-by-wire system optimization design method and proposes the optimization method of braking force distribution in different braking modes. The methodology of the book is by using the common Lyapunov function to analyze the stability of the braking mode switching process and designs the braking mode switching controller of the hybrid braking system. The selection of materials provides readers with some guidance in the future design and control of hybrid drive-by-wire systems for autonomous vehicles

This book constitutes the proceedings of the 5th International Conference on Intelligent Transport Systems, INTSYS 2021, which was held in November 2021. Due to COVID-19 pandemic the conference was held virtually. With the globalization of trade and transportation and the consequent multi-modal solutions used, additional challenges are faced by organizations and countries. Intelligent Transport Systems make transport safer, more efficient, and more sustainable by applying information and communication technologies to all transportation modes. The 15 revised full papers in this book were selected from 31 submissions and are organized in three thematic sessions on mobility; blockchain and disaster management; and data analytics.

This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence. Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.

This book focuses on cellular Vehicle-to-Everything (C-V2X), currently the most promising wireless communication technology for Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Pedestrian (V2P), Vehicle-to-Network (V2N) and Vehicle-to-Cloud (V2C) communications. Because of its low latency and high reliability, C-V2X has become an essential enabling technology for Intelligent Transportation Systems (ITSs) and autonomous driving. This book begins by introducing readers to the research background and status quo of global development. Then, after analyzing the performance requirements of various V2X applications, the system architecture and technical standards are presented. The two evolving stages of C-V2X, i.e., LTE-V2X and NR-V2X, are introduced in detail. In addition, related technologies such as mobile edge computing, network slicing and high-precision positioning, C-V2X security, C-V2X spectrum requirements and planning, and industrial development and applications are introduced. In closing, the book discusses future applications of and technical challenges for C-V2X. This book is the first monograph dedicated to C-V2X, offering experts, researchers and engineers from the areas of IT/CT, intelligent transportation, intelligent and connected vehicles (ICVs) an in-depth understanding of C-V2X technology and standards, while also outlining related interdisciplinary research. The book can also be used as a reference resource for both undergraduate and graduate studies.

This monograph explores the design of controllers that suppress oscillations and instabilities in congested traffic flow using PDE backstepping methods. The first part of the text is concerned with basic backstepping control of freeway traffic using the Aw-Rascle-Zhang (ARZ) second-order PDE model. It begins by illustrating a basic control problem - suppressing traffic with stop-and-go oscillations downstream of ramp metering - before turning to the more challenging case for traffic upstream of ramp metering. The authors demonstrate how to design state observers for the purpose of stabilization using output-feedback control. Experimental traffic data are then used to calibrate the ARZ model and validate the boundary observer design. Because large uncertainties may arise in traffic models, adaptive control and reinforcement learning methods are also explored in detail. Part II then extends the conventional ARZ model utilized until this point in order to address more complex traffic conditions: multi-lane traffic, multi-class traffic, networks of freeway segments, and driver use of routing apps. The final chapters demonstrate the use of the Lighthill-Whitham-Richards (LWR) first-order PDE model to regulate congestion in traffic flows and to optimize flow through a bottleneck. In order to make the text self-contained, an introduction to the PDE backstepping method for systems of coupled first-order hyperbolic PDEs is included. Traffic Congestion Control by PDE Backstepping is ideal for control theorists working on control of systems modeled by PDEs and for traffic engineers and applied scientists working on unsteady traffic flows. It will also be a valuable resource for researchers interested in boundary control of coupled systems of first-order hyperbolic PDEs.

This book constitutes the refereed proceedings of the 16th International Workshop on Communication Technologies for Vehicles, Nets4Cars/Nets4Trains/Nets4Aircraft 2021, held in Madrid, Spain, in November 2021. The 6 full and 2 short papers were carefully reviewed and selected from numerous submissions. The selected papers present original research results in areas related to the physical layer, communication protocols and standards, mobility and traffic models, experimental and field operational testing, and performance analysis

Unmanned Aerial Vehicle (UAV) has extended the freedom to operate and monitor the activities from remote locations. It has advantages of flying at low altitude, small size, high resolution, lightweight, and portability. UAV and artificial intelligence have started gaining attentions of academic and industrial research. UAV along with machine learning has immense scope in scientific research and has resulted in fast and reliable outputs. Deep learning-based UAV has helped in real time monitoring, data collection and processing, and prediction in the computer/wireless networks, smart cities, military, agriculture and mining. This book covers artificial techniques, pattern recognition, machine and deep learning - based methods and techniques applied to different real time applications of UAV. The main aim is to synthesize the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems and numerous application areas. This book is ideal for researchers, scientists, engineers and designers in academia and industry working in the fields of computer science, computer vision, pattern recognition, machine learning, imaging, feature engineering, UAV and sensing.

This book is intended for engineer's in automotive industry and in research community of electrical machines. This book systematically focus on all the major aspects of switched reluctance motor for intelligent electric vehicle applications, including optimization design, drive system control, regenerative braking control, and motor-suspension system control, which is particularly suited for readers who are interested to learn the theory of the motor used for intelligent electric vehicles.The comprehensive and systematic treatment of practical issues around switched reluctance motor considering vehicle requirments is one of the major features of the book. The book can benefit researchers, engineers, and graduate students in fields of switched reluctance motor, electric vehicle drive system, regenerative braking system, motor-suspension system, etc.