Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more.
This Handbook presents a comprehensive and rigorous overview of the state-of-the-art on Smart Cities. It provides the reader with an authoritative, exhaustive one-stop reference on how the field has evolved and where the current and future challenges lie. From the foundations to the many overlapping dimensions (human, energy, technology, data, institutions, ethics etc.), each chapter is written by international experts and amply illustrated with figures and tables with an emphasis on current research. The Handbook is an invaluable desk reference for researchers in a wide variety of fields, not only smart cities specialists but also by scientists and policy-makers in related disciplines that are deeply influenced by the emergence of intelligent cities. It should also serve as a key resource for graduate students and young researchers entering the area, and for instructors who teach courses on these subjects. The handbook is also of interest to industry and business innovators.
The Intelligent Systems Series encompasses theoretical studies, design methods, and real-world implementations and applications. It publishes titles in three core sub-topic areas: Intelligent Automation, Intelligent Transportation Systems, and Intelligent Computing. Titles focus on professional and academic reference works and handbooks. This volume, Advances in Artificial Transportation Systems and Simulation, covers hot topics including driver assistance systems; cooperative vehicle-highway systems; collision avoidance; pedestrian protection; image, radar and lidar signal processing; and V2V and V2I communications. The readership for the series is broad, reflecting the wide range of intelligent systems interest and application, but focuses on engineering (in particular automation, control, mechatronics, robotics, transportation, automotive, aerospace), electronics and electronic design, and computer science. - Provides researchers and engineers with up to date research results and state-of-the art technologies in the area of intelligent vehicles and transportation systems - Includes case studies plus surveys of the latest research - Covers hot topics including driver assistance systems; cooperative vehicle-highway systems; collision avoidance; pedestrian protection; image, radar and lidar signal processing; V2V and V2I communications
The book presents the select proceedings of the 8th International Conference on Transportation Systems Engineering and Management (CTSEM 2021). The book covers topics pertaining to three broad areas of transportation engineering, namely Transportation Planning, Traffic Engineering and Pavement Technology. The topics covered include transportation and land use, urban and regional transportation planning, travel behavior modeling, travel demand analysis, forecasting and management, transportation and ICT, public transport planning and management, freight transport, traffic flow modeling and management, highway design and maintenance, capacity and level of service, traffic crashes and safety, ITS and applications, non-motorized transportation, transportation economics and policy, road and parking pricing, pedestrian facilities and safety, road asset management, pavement materials and characterization, pavement design and construction, pavement evaluation and management, transportation infrastructure financing, innovative trends in transportation systems, sustainable transportation, smart cities, resilience of transportation systems and environmental and ecological aspects. This book will be useful for the students, researchers and the professionals in the area of civil engineering, especially transportation and traffic engineering.
Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. It presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. They will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners. - Utilizes real ITS examples to facilitate a quicker grasp of materials presented - Contains contributors from both leading academic and commercial domains - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications - Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques - New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics
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.
Proceedings of the 15th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences, Nice, France, 24-27 July 2024.
Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems examines the combined impact of buildings and transportation systems on energy demand and use. With a strong focus on AI and machine learning approaches, the book comprehensively discusses each part of the energy life cycle, considering source, grid, demand, storage, and usage. Opening with an introduction to smart buildings and intelligent transportation systems, the book presents the fundamentals of AI and its application in renewable energy sources, alongside the latest technological advances. Other topics presented include building occupants' behavior and vehicle driving schedule with demand prediction and analysis, hybrid energy storages in buildings with AI, smart grid with energy digitalization, and prosumer-based P2P energy trading. The book concludes with discussions on blockchain technologies, IoT in smart grid operation, and the application of big data and cloud computing in integrated smart building-transportation energy systems. A smart and flexible energy system is essential for reaching Net Zero whilst keeping energy bills affordable. This title provides critical information to students, researchers and engineers wanting to understand, design, and implement flexible energy systems to meet the rising demand in electricity. - Introduces spatiotemporal energy sharing with new energy vehicles and human-machine interactions - Discusses the potential for electrification and hydrogenation in integrated building-transportation systems for sustainable development - Highlights key topics related to traditional energy consumers, including peer-to-peer energy trading and cost-benefit business models
