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The purpose of this Special Issue is to create an an academic platform whereby high-quality research papers are published on the applications of innovative AI algorithms to transportation planning and operation. The authors present their original research articles related to the applications of AI or machine-learning techniques to transportation planning and operation. The topics of the articles encompass traffic surveillance, traffic safety, vehicle emission reduction, congestion management, traffic speed forecasting, and ride sharing strategy.
Cities are the next frontier for artificial intelligence to permeate. As smart urban environments become possible, probable, and even preferred, artificial intelligence offers the chance for even further advancement through infrastructure and industry boosting. Opportunity overflows, but without thorough research to guide a complicated development and implementation process, urban environments can become disorganized and outright dangerous for citizens. AI-Based Services for Smart Cities and Urban Infrastructure is a collection of innovative research that explores artificial intelligence (AI) applications in urban planning. In addition, the book looks at how the internet of things and AI can work together to enable a real smart city and discusses state-of-the-art techniques in urban infrastructure design, construction, operation, maintenance, and management. While highlighting a broad range of topics including construction management, public transportation, and smart agriculture, this book is ideally designed for engineers, entrepreneurs, urban planners, architects, policymakers, researchers, academicians, and students.
Addresses the Challenges Facing Public Transport Policy Makers and OperatorsPublic Transit Planning and Operation: Modeling, Practice and Behavior, Second Edition offers new solutions for delivering both better services and greater efficiency, solutions which have been developed and tested by the author in over thirty years of research work with ma
This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
This edited book comprises papers about the impacts, benefits and challenges of connected and automated cars. It is the third volume of the LNMOB series dealing with Road Vehicle Automation. The book comprises contributions from researchers, industry practitioners and policy makers, covering perspectives from the U.S., Europe and Japan. It is based on the Automated Vehicles Symposium 2015 which was jointly organized by the Association of Unmanned Vehicle Systems International (AUVSI) and the Transportation Research Board (TRB) in Ann Arbor, Michigan, in July 2015. The topical spectrum includes, but is not limited to, public sector activities, human factors, ethical and business aspects, energy and technological perspectives, vehicle systems and transportation infrastructure. This book is an indispensable source of information for academic researchers, industrial engineers and policy makers interested in the topic of road vehicle automation.
A multi-disciplinary approach to transportation planning fundamentals The Transportation Planning Handbook is a comprehensive, practice-oriented reference that presents the fundamental concepts of transportation planning alongside proven techniques. This new fourth edition is more strongly focused on serving the needs of all users, the role of safety in the planning process, and transportation planning in the context of societal concerns, including the development of more sustainable transportation solutions. The content structure has been redesigned with a new format that promotes a more functionally driven multimodal approach to planning, design, and implementation, including guidance toward the latest tools and technology. The material has been updated to reflect the latest changes to major transportation resources such as the HCM, MUTCD, HSM, and more, including the most current ADA accessibility regulations. Transportation planning has historically followed the rational planning model of defining objectives, identifying problems, generating and evaluating alternatives, and developing plans. Planners are increasingly expected to adopt a more multi-disciplinary approach, especially in light of the rising importance of sustainability and environmental concerns. This book presents the fundamentals of transportation planning in a multidisciplinary context, giving readers a practical reference for day-to-day answers. Serve the needs of all users Incorporate safety into the planning process Examine the latest transportation planning software packages Get up to date on the latest standards, recommendations, and codes Developed by The Institute of Transportation Engineers, this book is the culmination of over seventy years of transportation planning solutions, fully updated to reflect the needs of a changing society. For a comprehensive guide with practical answers, The Transportation Planning Handbook is an essential reference.
Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices. Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.
This volume thoroughly explores the perceptions and ethical considerations surrounding urban artificial intelligence (AI). Tan Yigitcanlar delves into the complex public and professional views on AI, offering invaluable insights for policymakers, urban planners, and developers. As the world rapidly advances technologically, the role of AI has become increasingly significant. AI’s transformative power spans various sectors, revolutionising how we operate and innovate in fields such as healthcare, finance, agriculture, and space exploration. Despite its wide‐reaching impact, the integration of AI into urban planning and development remains relatively underexplored. This is surprising given AI’s immense potential to revolutionise urban design, management, and experience. Comprising eight comprehensive and insightful chapters, this book examines AI’s role in urban contexts, including its applications, public perceptions, and ethical implications. The first part of the guidebook delves into varied perceptions of AI within different urban sectors, presenting detailed perception analyses on AI’s role in urban planning, local government services, disaster management, and the construction industry. The second part shifts focus to the ethical implications and responsible implementation of AI in urban settings. It provides frameworks and strategies to ensure AI technologies contribute positively to urban development while mitigating potential risks and ethical concerns. This volume, alongside its companion Urban Artificial Intelligence: A Guidebook for Understanding Concepts and Technologies, offers a holistic view of Urban Artificial Intelligence. Together, these books provide essential insights for urban planners, policymakers, researchers, and anyone interested in AI and urban development, guiding responsible AI integration to foster smarter, more sustainable, and equitable urban environments.
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.