الفهرس 
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Abstract
Mansoura city is considered one of the most crowded cities in Egypt. The absence of effective application of urban transportation planning process in the city results in deficiencies in choosing the suitable transport policies to reduce the transportation related problems resulting from urban development and fast population increase. Mansoura does not have a transportation model; hence, developing a mode choice model for the city is considered very crucial for predicting the use of each mode, and the factors that affect selecting a specific mode. Thus, the aim of this study is to develop a mode choice (MC) behavioral model for individuals’ trips in Mansoura City. A survey of primary information on mode choice was conducted through online questionnaire. Around 10,000 online questionnaires were collected in 2015 using Google Forms. These questionnaires represent around 30,000 individual trips. In this study, only persons older than 13-years old were considered (i.e., 15,265 records). Two-thirds of the data were randomly selected and used in developing the MC model and the remaining one-third was used in validating the developed model. The developed model covers the five main modes of transportation currently employed in the city, the first mode is “Private car”, the second mode is “taxi”, the third mode is “microbus Bus”, which is the most used mode among all other modes of transportation, the fourth mode is walking, and fifth mode is other modes which are fairly used. These other modes are important for future policy considerations, in order to encourage their use to assist in solving the mounting traffic problems. The developed model shows that the factors that significantly affect the choice of transport modes are the total travel time, total cost, ownership of transport means, driving license ownership, occupational status, residence status, gender, and personal income. The results indicate that the proposed model exhibits a good fit for the data with a prediction accuracy of about 85%. Furthermore, the prediction accuracy of the model that was calibrated using the 2015 data was rechecked using data from 2017 and 2018 and the model prediction ability was still good. To assess the effect of sample size on the mode choice model prediction accuracy, the mode choice models were calibrated with different sample sizes randomly selected from the data and the prediction ratio was then estimated. Using sample sizes larger than 2000 observations were found to slightly improve the prediction accuracy. In addition, to achieve at least 80% prediction accuracy, only 870 observations are required. The sensitivity analysis for different level of service attributes was performed to determine their relative elasticity for each trip mode by increasing or decreasing the attribute value by different rates given that all other variables were held constant. This was conducted in order to observe the varying percentage modal split for all travelling modes with a change in the value of the attribute. This study can be used by transportation planners to expect people’s behavior and travel demand analysis and to study the feasibility and possibility of introducing new transportation modes to the transport system in Mansoura city such as the bus service. Finally, the developed models can be used to forecast the future modal choice by entering forecasted future value of exploratory variables.