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Read the Reviews
"This book provides a knowledgeable application of statistical and econometric methods to
transportation data used in ongoing research. It gives priority to applied processes and describes
how these methods can be successfully used and interpreted. It also provides awareness into the
variety of data collection sources used in statistical analysis, interprets results, and analyzes the implication of those results. It is worth reading this book for a better understanding of transportation data analysis using statistical techniques that are specifically applicable to transportation."
—Bhuiyan Monwar Alam and Mohammad Abdulkaleem, Journal of the Transportation Research Forum, Vol. 49, No. 3 (Fall 2010) |
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About the Item
In recent years, transportation systems have been judged on performance-based outcomes, thus, quantitative methods have become increasingly important to such assessments. Transportation Statistics brings together the work of outstanding experts on the latest methods and the applications of those methods to the many modes of transportation statistics at the international level. It details applications of the appropriate statistical methods and other quantitative methods such as operations research and performance measurement. You'll find examples and explications of the techniques used in transportation modeling such as travel demand, travel demand forecasting, freight analysis, the environment and much more. This one-of-a-kind, definitive technical reference will equip practitioners, policy-makers, and academic researchers with state-of-the-art statistical tools used in transportation modeling, how to interpret results and how to analyze the implications of those results. |
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Key Features
Presents up-to-date applications of statistical and econometric methods to transportation data rather than statistical theory
Offers transportation statistical applications that reflect current international research
Emphasizes applied processes and illustrates how these methods can be successfully used and interpreted
Provides insight into the variety of data collection sources used in statistical analysis
Draws on the many advances in statistical analysis of transportation data as a result of increasing computing power
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About the Editor
Brian W. Sloboda was a former economist at the Bureau of Transportation Statistics in the U.S. Department of Transportation and the Bureau of Economic Analysis in the U.S. Department of Commerce. While at the Bureau of Transportation Statistics, he did research in examining the relationship of transportation and the economy, productivity in the various modes of transportation; and tourism and transportation. Currently, he is a pricing economist at the US Postal Service. He is also teaching economics and statistics as an adjunct faculty for the University of Phoenix, University of Maryland, Park University, and the USDA Graduate School. |
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Table of Contents
Preface
Chapter 1: Macroscopic Road Safety Modeling: A State Space Approach Applied to Three Belgium Regions
Filip A. M. Van den Bossche, Koen Vanhoof, Geert Wets, and Tom Brijs
Chapter 2: Traffic Safety Study: Empirical Bayes or Full Bayes
Luis F. Miranda-Moreno and Liping Fu
Chapter 3: Utilizing Data Warehouse to Develop Freeway Travel Time Reliability Stochastic Models
Emam B. Emam and Haitham M. Al-Deek
Chapter 4: Mixed Logit Modeling of Parking Type Choice Behavior
Stephane Hess and John W. Polak
Chapter 5: Modeling Daily Traffic Counts: Analyzing the Effects of Holidays
Mario Cools, Elke Moons, and Geert Wets
Chapter 6: Issues with Small Samples in Trip-Generation Estimation
Paul Metaxatos
Chapter 7: Recent Progress on Activity-Based Microsimulation Models of Travel Demand and Future Prospects
Abolfazl Mohammadian, Joshua Auld and Sadayuki Yagi
Chapter 8: Maximum Simulated Likelihood Estimation with Spatially Correlated Observations: A Comparison of Simulation Techniques
Xiaokun Wang and Kara M. Kockelman
Chapter 9: Analyzing the Impact of Land Transportation on Regional Tourism: The Case of the Closure of the Glion Tunnel in the Valais, Switzerland
Miriam Scaglione
Chapter 10: Quasi-Likelihood Generalized Linear Regression Analysis of Fatality Risk Data
C. Craig Morris
Chapter 11: Developing Statewide Weekend Travel Demand Forecast and Mode
Choice Models for New Jersey
Rongfang Liu and Yi Deng
Chapter 12: Transferability of Time-of-Day Choice Modeling for Long-Distance Trips
Xia Jin and Alan Horowitz
Chapter 13: Univariate Sensitivity and Uncertainty Analysis of Statewide
Travel Demand and Land Use Models for Indiana
Li Jin and Jon D. Fricker
Index
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