Transportation Statistics Annual Report is a summary of the state of the transportation system and its consequences, the quality of statistics used to characterize the transportation system, and planned efforts by the U.S. Department of Transportation's Bureau of Transportation Statistics (BTS) to improve the quality of the statistics. BTS was established by Congress to compile, analyze, and make accessible information on the nation's transportation system; to collect information on intermodal transportation and other related areas as needed; and to enhance the quality and effectiveness of the Department of Transportation's statistical programs through research, the development of guidelines, and the promotion of improvements in data acquisition and use.

The complexity, diversity, and random nature of transportation problems necessitates a broad analytical toolbox. Describing tools commonly used in the field, Statistical and Econometric Methods for Transportation Data Analysis, Second Edition provides an understanding of a broad range of analytical tools required to solve transportation problems. It includes a wide breadth of examples and case studies covering applications in various aspects of transportation planning, engineering, safety, and economics. After a solid refresher on statistical fundamentals, the book focuses on continuous dependent variable models and count and discrete dependent variable models. Along with an entirely new section on other statistical methods, this edition offers a wealth of new material. New to the Second Edition A subsection on Tobit and censored regressions An explicit treatment of frequency domain time series analysis, including Fourier and wavelets analysis methods New chapter that presents logistic regression commonly used to model binary outcomes New chapter on ordered probability models New chapters on random-parameter models and Bayesian statistical modeling New examples and data sets Each chapter clearly presents fundamental concepts and principles and includes numerous references for those seeking additional technical details and applications. To reinforce a practical understanding of the modeling techniques, the data sets used in the text are offered on the book’s CRC Press web page. PowerPoint and Word presentations for each chapter are also available for download.

The Fed. Transit Admin. (FTA) collects and analyzes data from across the country on public transportation (PT) fuel use, vehicles deployed, rides taken, etc. These data provides valuable insight into the impacts of auto, truck, SUV, and PT travel on the production of greenhouse gas emissions. There are significant greenhouse gas emission savings by using PT. This paper presents an analysis of the data and frames it in a broader context. It concludes with a description of FTA actions that address climate change. PT can reduce greenhouse gas emissions by: Providing a low emissions alternative to driving; Facilitating compact land use, reducing the need to travel long distances; and Minimizing the carbon footprint of transit oper.

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