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1 This Thesis (Trip Attraction Model for Private Schools in Amman) was successfully defended and approved on (.) Examination Committee Signature Dr. Mohammed Al-Tarawneh, Chairman... Assoc. Prof. of Civil Engineering / Transportation The University of Jordan Prof. Yousef Siam, Member... Prof. of Civil Engineering / Transportation The University of Jordan Prof. Adly balbisi, Member... Prof. of Civil Engineering / Transportation The University of Jordan Dr. Khalied Ramadn, Member... Assoc. Prof. of Civil Engineering / Transportation Applied Science University

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4 III DEDICATION To My Mother, For Every Thing And to the Soul of My Father may His Soul Rest in Peace

5 IV ACKNOWLEDGMENTS From the First step to the final stage I owe gratitude to my supervisor Dr. Mohammad Tarawnah, for his continuous support, encouragement, and his sound advice and careful guidance. I would also like to express my deepest sense of appreciation to Prof. Adly Balbasy.

6 V CONTENTS Page COMMITTEE DECISION...II DEDICATION...III ACKNOWLEDGMENTS...IV CONTENTS...V LIST OF FIGURES...IX LIST OF TABLES... XII LIST OF APPENDICES...XIII ABSTRACT...XIV Chapter ONE INTRODUCTION GENERAL TRAVEL DEMAND FORECASTING Factors Influencing Travel Demand Sequential Steps For Travel Forecasting PROBLEM DEFINITION Study Objective..5

7 VI Chapter Two LITERATURE REVIEW...2 Chapter Three METHODOLOGY...11 DATA COLLECTION...14 Chapter Four 3.1 TYPES OF DATA COLLECTED DATA COLLECTION CRITERIA DATA COLLECTED Counts of Vehicles CHALLENGES IN DATA COLLECTION...28 MODEL DEVELOPMENT SIGNIFICANCE WITHIN And BETWEEN GROUPS of the PRIVATES SCHOOLS SINGLE VARIABLE MODELS Attracted Demand vs. Gross Floor Area of the Private School Attracted Demand vs. Number of Students in the Private School Attracted Demand vs. Number of Employees in the

8 VII Private School Attracted Demand vs. Number of Buses in the Private School...46 Chapter Five Attracted Demand vs. Tuitions in the Private School MULTI-VARIABLE MODELS...54 TRIP RATES TRIP RATES BASED ON DATA COLLECTED FROM FIELD TRIP RATES BASED ON MODELS DEVELOPED WITHOUT CONSTANT Attracted Demand vs. Private School Gross Floor Area Attracted Demand vs. Number of Students at Private schools Attracted Demand vs. Number of Employees at Private schools Attracted Demand vs. Number of Buses at Private schools...66

9 VIII Attracted Demand vs. Tuitions at Private schools COMPARISONS WITH OTHER MANUALS...68 CONCLUSIONS...69 RECOMMENDATIONS...70 REFERENCES...71 APPENDICES...72

10 IX LIST OF FIGURES PAGE Figure (3.1) Average Attracted and Generated Vehicles to Each Private School Surveyed...23 Figure (4.1) One-Way ANOVA test...30 Figure (4.2) Calibration of the Best Three Models to Correlate Between Demand Attracted and (GFA)...32 Figure (4.3) Comparisons between Observed and Theoretical Demand Based on the Model of (GFA)...35 Figure (4.4) Unstandardized Residuals (ei) based on The Model Developed with Respect to (GFA)...35 Figure (4.5) Calibration of the Best Three Models to Correlate Between Demand Attracted and (NS)...36 Figure (4.6) Comparisons between Observed and Theoretical Demand Based on the Model of (NS)...39 Figure (4.7) Unstandardized Residuals (ei) based on The Model Developed with Respect to (NS)...39 Figure (4.8) Calibration of the Best Three Models to Correlate Between Demand Attracted and (NE)...40 Figure (4.9) Comparisons between Observed and Theoretical Demand Based on the Model of (NE)...43 Figure (4.10) Unstandardized Residuals (ei) based on The Model Developed with Respect to (NE)...43

11 X Figure (4.11) Calibration of the Best Three Models to Correlate Between Demand Attracted and (NB)...44 Figure (4.12) Comparisons between Observed and Theoretical Demand Based on the Model of (NB)...47 Figure (4.13) Unstandardized Residuals (ei) based on The Model Developed with Respect to (NB)...47 Figure (4.14) Calibration of the Best Three Models To Correlate Between Demand Attracted and (T)...48 Figure (4.15) Comparisons between Observed and Theoretical Demand Based on the Model of (T)...51 Figure (4.16) Unstandardized Residuals (ei) based on The Model Developed with Respect to (T)...51 Figure (4.17) Results of Stepwise Method...54 Figure (4.18) Comparisons between Observed and Theoretical Demand Based on The Model of (GFA) Based on Stepwise Method...56 Figure (4.19) Unstandardized Residuals (ei) based on The Model Developed with Respect to (GFA) Based on Stepwise Method...56 Figure (5.1) Trip Rates Based on Data Collected From Field...58

12 XI LIST OF TABLES PAGE Table (3.1): Data Collection Date for Each Private school...16 Table (3.2): Peak Hour of Operation on Each surveyed Private School...17 Table (3.3): The Number of Trips Generated and Attracted to the 15 Private schools (1 st Day)...18 Table (3.4): The Number of Trips Generated and Attracted to Private schools (2nd Day)...19 Table (3.5): The Number of Trips Generated and Attracted to Private Schools (3rd Day)...20 Table (3.6): Average Number of Trips Generated and Attracted to Surveyed Private Schools...21 Table (3.7): Number of Vehicle-Trips Attracted and Generated Among All Days for Surveyed Private School...22 Table (3.8) Data Collected for Each Private School...25 Table (3.9) Data Collected to Initiate Modeling Processes...26 Table (4.1) Private Schools Groups...29 Table (4.2) The Result of the Model Calibration Process Between (VA) and (GFA)...32 Table (4.3) Residual Analysis Data Sheet (ei) vs. (GFA)...34 Table (4.4) the Result of the Model Calibration Process Between (VA) and (NS)...37 Table (4.5) Residual Analysis Data Sheet (ei) vs. (NS)...38 Table (4.6) the Result of The Model Calibration Process Between (Va) and (NE)...41 Table (4.7) Residual Analysis Data Sheet (ei) vs. (NE)...42

13 XII Table (4.8) the Result of the Model Calibration Process Between (VA) and (NB)...45 Table (4.9) Residual Analysis Data Sheet (ei) vs. (NB)...46 Table (4.10) The Result of the Model Calibration Process Between (VA) and (T)...49 Table (4.11) Residual Analysis Data Sheet (ei) vs. (T)...50 Table (4.12) Residual Analysis Data Sheet (ei) vs. (GFA) (Stepwise Method)...55 Table (5.1): Trip Attraction Rates for the Private Schools Based on Field Data...58 Table (5.2): General Summery of the Trip Rates Resulted From Field Data...60 Table (5.3): Comparison between Trip Attraction Rates Resulted With Different Manuals...64 Conclusions.66 Recommendations...67 References...68

14 XIII LIST OF APPENDICES PAGE Appendix A: Traffic Counts... Appendix B: Modeling Types...115

15 XIV TRIP ATTRACTION MODEL FOR PRIVATE SCHOOLS IN AMMAN BY Hazem Mohammed Al-Nawaiseh SUPERVISOR Dr. Mohammad Al-Trawneh ABSTRACT Fifteen randomly distributed private schools in the city of Amman were surveyed for the purpose of developing models that represents the demand attracted to private school. The survey takes place between March & April 2009 the data collection had two activities: the first activity was counting the number of vehicle trips attracted to private schools. This count included all vehicles that either enters the school from the gate or park on the adjacent streets the count was conducted during the peak periods 7- am and 1-3 pm. The second activity included the collection of physical information about each school. Regression analysis was used for modeling. Variables included in the modeling were gross floor area, number of students, number of busses, number of employee and tuition. For testing the suitability of the model "R" and ANOVA tests were conducted. Stepwise analysis was also performed to generate the most representative multivariable model. Analysis should that gross floor area among other variables was the most significant variable that affect the demand attracted to private school.

16 III. Linear-Without Constant Model of The Attracted Demand vs., (NE). Variables Entered/Removed(b) Model Variables Entered Variables Removed Method 1 NE(a). Enter a. All requested variables entered. b. Dependent Variable: Va Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate a. Predictors: (NE) ANOVA(b) Sum of Mean Model Squares Df Square F Sig. 1 Regression 932, , Residual 44, , Total 976, Coefficients(a) Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 NEP

17 IV. Linear-Without Constant Model of The Attracted Demand vs., (NB). Variables Entered/Removed(b) Model Variables Entered Variables Removed Method 1 NB(a). Enter a. All requested variables entered. b. Dependent Variable: Va Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate a. Predictors: (NB) ANOVA(b) Sum of Mean Model Squares Df Square F Sig. 1 Regression 869, , Residual 106, , Total 976, Coefficients(a) Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 NB

18 V. Linear-Without Constant Model of The Attracted Demand vs., (T). Variables Entered/Removed(b) Model Variables Entered Variables Removed Method 1 T(a). Enter a. All requested variables entered. b. Dependent Variable: Va Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate a. Predictors: (T) ANOVA(b) Sum of Mean Model Squares Df Square F Sig. 1 Regression 49, , Residual 100, , Total 150, Coefficients(a) Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) T