Author: Mashrur Chowdhury Publisher: Elsevier ISBN: 0443138796 Category : Computers Languages : en Pages : 572
Book Description
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
Author: Ennio Cascetta Publisher: Springer Science & Business Media ISBN: 0387758577 Category : Business & Economics Languages : en Pages : 753
Book Description
"This book provides a rigorous and comprehensive coverage of transportation models and planning methods and is a must-have to anyone in the transportation community, including students, teachers, and practitioners." Moshe Ben-Akiva, Massachusetts Institute of Technology.
Author: Yinhai Wang Publisher: Elsevier ISBN: 9780128170267 Category : Transportation Languages : en Pages : 0
Book Description
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.
Author: Paolo Pagano Publisher: CRC Press ISBN: 1315353725 Category : Science Languages : en Pages : 156
Book Description
Intelligent Transport Systems (ITS) are the way forward for sustainable growth of mobility at all levels (local, regional, national, transnational). The book reviews the current status of Research & Development. It includes connected (and autonomous) cars and buses, real-world large-scale field trials, data analysis and assessment of technological solutions. Standards and normative aspects in the domain of Electronic Fee Collection and Cooperative Systems oriented to probe data collection, safety and non-safety critical applications in vehicular networks, are studied. The book provides the rational, perspectives, and technical issues for the implementation of ITS solutions in a genuine inter-modal scenario, taking the example of a Mediterranean seaport, actively involved in testing and validation of ITS standards. The novelty of this book is that it covers R&D, standards, and pilots, all under one cover. Rather than stressing the novelty in ICT, the authors have presented the need for system-level integration, assessment of existing (standard) solutions, and piloting experiments in real-world industrial scenarios.
Author: Constantinos Antoniou Publisher: Elsevier ISBN: 0128150181 Category : Business & Economics Languages : en Pages : 312
Book Description
Demand for Emerging Transportation Systems: Modeling Adoption, Satisfaction, and Mobility Patterns comprehensively examines the concepts and factors affecting user quality-of-service satisfaction. The book provides an introduction to the latest trends in transportation, followed by a critical review of factors affecting traditional and emerging transportation system adoption rates and user retention. This collection includes a rigorous introduction to the tools necessary for analyzing these factors, as well as Big Data collection methodologies, such as smartphone and social media analysis. Researchers will be guided through the nuances of transport and mobility services adoption, closing with an outlook of, and recommendations for, future research on the topic. This resource will appeal to practitioners and graduate students.
Author: Lawrence A. Klein Publisher: SPIE-International Society for Optical Engineering ISBN: 9781510627642 Category : Algorithms Languages : en Pages : 235
Book Description
"Sensor and Data Fusion for Intelligent Transportation Systems introduces readers to the roles of the data fusion processes defined by the Joint Directors of Laboratories (JDL) data fusion model, data fusion algorithms, and noteworthy applications of data fusion to ITS. Additionally, the monograph offers detailed descriptions of three of the widely applied data fusion techniques and their relevance to ITS (namely, Bayesian inference, Dempster-Shafer evidential reasoning, and Kalman filtering), and indicates directions for future research in the area of data fusion. The focus is on data fusion algorithms rather than on sensor and data fusion architectures, although the book does summarize factors that influence the selection of a fusion architecture and several architecture frameworks"--
Author: Michael Dalgleish Publisher: Artech House Publishers ISBN: 9781580537155 Category : Technology & Engineering Languages : en Pages : 233
Book Description
"The first-of-its-kind book presents state-of-the-art traffic monitoring and analysis methods, helping professionals make the most of their data collection and assessment efforts. This unique resource offers a hands-on understanding of the latest sensors, processors, and communication links for everything from vehicle counts to urban congestion measurement. Moreover, practitioners learn statistical techniques for quantifying data accuracy and reducing uncertainly in both current system state assessments and future system slate forecasts."--BOOK JACKET.
Author: Satish V. Ukkusuri Publisher: Springer ISBN: 3319758624 Category : Business & Economics Languages : en Pages : 240
Book Description
This book presents papers based on the presentations and discussions at the international workshop on Big Data Smart Transportation Analytics held July 16 and 17, 2016 at Tongji University in Shanghai and chaired by Professors Ukkusuri and Yang. The book is intended to explore a multidisciplinary perspective to big data science in urban transportation, motivated by three critical observations: The rapid advances in the observability of assets, platforms for matching supply and demand, thereby allowing sharing networks previously unimaginable. The nearly universal agreement that data from multiple sources, such as cell phones, social media, taxis and transit systems can allow an understanding of infrastructure systems that is critically important to both quality of life and successful economic competition at the global, national, regional, and local levels. There is presently a lack of unifying principles and methodologies that approach big data urban systems. The workshop brought together varied perspectives from engineering, computational scientists, state and central government, social scientists, physicists, and network science experts to develop a unifying set of research challenges and methodologies that are likely to impact infrastructure systems with a particular focus on transportation issues. The book deals with the emerging topic of data science for cities, a central topic in the last five years that is expected to become critical in academia, industry, and the government in the future. There is currently limited literature for researchers to know the opportunities and state of the art in this emerging area, so this book fills a gap by synthesizing the state of the art from various scholars and help identify new research directions for further study.
Author: Lawrence A. Klein Publisher: SPIE Press ISBN: 9780819454355 Category : Technology & Engineering Languages : en Pages : 346
Book Description
This book illustrates the benefits of sensor fusion by considering the characteristics of infrared, microwave, and millimeter-wave sensors, including the influence of the atmosphere on their performance. Applications that benefit from this technology include: vehicular traffic management, remote sensing, target classification and tracking- weather forecasting- military and homeland defense. Covering data fusion algorithms in detail, Klein includes a summary of the information required to implement each of the algorithms discussed, and outlines system application scenarios that may limit sensor size but that require high resolution data.
Author: Mashrur Chowdhury
Author: 
Author: Ennio Cascetta
Author: Yinhai Wang
Author: Paolo Pagano
Author: Constantinos Antoniou
Author: Lawrence A. Klein
Author: Michael Dalgleish
Author: Satish V. Ukkusuri
Author: Lawrence A. Klein