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|Title||Development of A Trip Generation Model for Gaza City|
|Title in Arabic||تطوير نموذج لتولد الرحلات في مدينة غزة|
Travel demand forecasting is essential for the design of transportation facilities and services, and also for planning, investment, and policy development. Trip generation is the first step of travel demand forecasting process. Developing countries including Gaza Strip often use trip generation models that are developed by the developed countries. These models are not suitable to be used in its original form because of the different conditions and circumstances in developing countries. Therefore, there is a need to develop a trip generation model for Gaza in order to help in predicting the future demand and adopting the suitable transport policies to solve the transportation problem. Given this context, the aim of the research is to develop a trip generation model for Gaza City using an appropriate technique to determine the household travel characteristics pattern in the study area. It aims also to compare trip rates modeled by way of Conventional cross classification (CCA) and that of Multiple cross classification (MCA) in Gaza city. Furthermore, it aims to develop a trip attraction model using multiple linear regression technique (MLR). Household interview surveys were conducted to determine the method used for traveling. A number of 425 household surveys were distributed in different districts of Gaza city. MCA and MLR models were calibrated using the root mean squared error (RMSE) between the observed and the predicted data. For the process of validation, a combination of sensitivity analysis and statistical tests were used for MCA models. Cross and split validation methods were used to validate trip attraction models. The findings of the research show that vehicle ownership, household size, income level and total number of licensed drivers are the strong factors that affect trip production in Gaza City. Also, it shows that MCA models are more effective in expressing trip rates for trip production than CCA models. An increase in sample size will leads to an increase of the performance of both MCA and CCA matrices in predicting trip rates. School trips are the best model among other models obtained in trip attraction with the best coefficient of determination (R2), followed by college trips in ranking. Home based other trips was the least significant model in expressing trip attraction. The study recommended that the results of trip generation in Gaza City is useful for the further study on trip distribution, mode choice and trip assignment models in order to forecast the travel demand for Gaza City in the future time period.
|Publisher||الجامعة الإسلامية - غزة|
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