Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and
forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers
assess the validity and accuracy of demand forecasts.
Forecasting and evaluating transport demand is an essential task of transport professionals and researchers
that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand
forecasts are necessary for companies and government entities when planning future fleet size, human resource
needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport
Demand help readers solve the problems they face on a daily basis.
Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students
at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative
models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on
statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most
suitable solution for all types of transport applications.
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Copyright - p. iv 5. Dedication - p. v 6. Preface - p. xxi 7. Chapter 1. Transport Demand and Factors Affecting It - p. 1 8. Chapter 2. Evolution and Trends of Transport Demand - p. 47 9. Chapter 3. Methods of Modeling Transport Demand - p. 89 10. Chapter 4. Executive Judgment, Delphi, Scenario Writing, and Survey Methods - p. 125 11. Chapter 5. Statistical Methods for Transport Demand Modeling - p. 163 12. 5.1. An Overview of the Minimum Statistical Background for Transport Demand Modeling - p. 163 13. 5.2. Correlation Between Two Variables and Regression Analysis - p. 168 14. 5.3. Simple Linear Regression Analysis - p. 169 15. 5.4. Multiple Linear Regression Analysis - p. 173 16. 5.5. Evaluation of the Significance of the Parameters of a Regression Analysis - p. 176 17. 5.6. Pearson Correlation Coefficient - p. 186 18. 5.7. Coefficient of Determination - p. 188 19. 5.8. Test of Correlation Between Independent Variables—Multicollinearity, Detection, and Removal - p. 190 20. 5.9. Residuals of Linear Regression - p. 193 21. 5.10. Homoscedasticity and Heteroscedasticity - p. 207 22. 5.11. Evaluation of the Forecasting Accuracy of Models - p. 211 23. 5.12. An Application of Multiple Linear Regression Analysis for Transport Demand - p. 214 24. Chapter 6. Trend Projection and Time Series Methods - p. 225 25. Chapter 7. Econometric, Gravity, and the 4-Step Methods - p. 271 26. 7.1. Methodology and Successive Steps for the Construction of an Econometric Model - p. 271 27. 7.2. Statistical Tests of an Econometric Model - p. 276 28. 7.3. Distinction of Causality From Correlation in Econometric Models - p. 284 29. 7.4. Econometric Models for Air Transport Demand - p. 286 30. 7.5. Econometric Models for Rail Transport Demand - p. 302 31. 7.6. Econometric Models for Public Transport Demand - p. 305 32. 7.7. Econometric Models for Road Transport Demand - p. 308 33. 7.8. Econometric Models for the Forecast of Demand for Taxi Services - p. 309 34. 7.9. Econometric Models for the Simulation of Road Safety - p. 311 35. 7.10. Forecast of Transport Demand at Urban Level—The 4-Step Model - p. 314 36. 7.11. Modeling of Freight Transport Demand - p. 346 37. Chapter 8. Artificial Intelligence—Neural Network Methods - p. 353 38. Chapter 9. Fuzzy Methods - p. 383 39. References - p. 419 40. Abbreviations - p. 447 41. Index - p. 449
Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and
forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers
assess the validity and accuracy of demand forecasts.
Forecasting and evaluating transport demand is an essential task of transport professionals and researchers
that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand
forecasts are necessary for companies and government entities when planning future fleet size, human resource
needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport
Demand help readers solve the problems they face on a daily basis.
Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students
at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative
models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on
statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most
suitable solution for all types of transport applications.
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Copyright - p. iv 5. Dedication - p. v 6. Preface - p. xxi 7. Chapter 1. Transport Demand and Factors Affecting It - p. 1 8. Chapter 2. Evolution and Trends of Transport Demand - p. 47 9. Chapter 3. Methods of Modeling Transport Demand - p. 89 10. Chapter 4. Executive Judgment, Delphi, Scenario Writing, and Survey Methods - p. 125 11. Chapter 5. Statistical Methods for Transport Demand Modeling - p. 163 12. 5.1. An Overview of the Minimum Statistical Background for Transport Demand Modeling - p. 163 13. 5.2. Correlation Between Two Variables and Regression Analysis - p. 168 14. 5.3. Simple Linear Regression Analysis - p. 169 15. 5.4. Multiple Linear Regression Analysis - p. 173 16. 5.5. Evaluation of the Significance of the Parameters of a Regression Analysis - p. 176 17. 5.6. Pearson Correlation Coefficient - p. 186 18. 5.7. Coefficient of Determination - p. 188 19. 5.8. Test of Correlation Between Independent Variables—Multicollinearity, Detection, and Removal - p. 190 20. 5.9. Residuals of Linear Regression - p. 193 21. 5.10. Homoscedasticity and Heteroscedasticity - p. 207 22. 5.11. Evaluation of the Forecasting Accuracy of Models - p. 211 23. 5.12. An Application of Multiple Linear Regression Analysis for Transport Demand - p. 214 24. Chapter 6. Trend Projection and Time Series Methods - p. 225 25. Chapter 7. Econometric, Gravity, and the 4-Step Methods - p. 271 26. 7.1. Methodology and Successive Steps for the Construction of an Econometric Model - p. 271 27. 7.2. Statistical Tests of an Econometric Model - p. 276 28. 7.3. Distinction of Causality From Correlation in Econometric Models - p. 284 29. 7.4. Econometric Models for Air Transport Demand - p. 286 30. 7.5. Econometric Models for Rail Transport Demand - p. 302 31. 7.6. Econometric Models for Public Transport Demand - p. 305 32. 7.7. Econometric Models for Road Transport Demand - p. 308 33. 7.8. Econometric Models for the Forecast of Demand for Taxi Services - p. 309 34. 7.9. Econometric Models for the Simulation of Road Safety - p. 311 35. 7.10. Forecast of Transport Demand at Urban Level—The 4-Step Model - p. 314 36. 7.11. Modeling of Freight Transport Demand - p. 346 37. Chapter 8. Artificial Intelligence—Neural Network Methods - p. 353 38. Chapter 9. Fuzzy Methods - p. 383 39. References - p. 419 40. Abbreviations - p. 447 41. Index - p. 449
