Article
DEVELOPING A MODE CHOICE MODEL FOR MANSOURA CITY IN EGYPT
DOI: 10.7708/ijtte.2018.8(4).10
8 / 4 / 528 - 542 Pages
Author(s)
Usama Elrawy Shahdah - Public Works Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt -
Abstract
This study presents a mode choice (MC) behavioural model for individuals’ trips in Mansoura City in Egypt. Mansoura city lies in the delta region and considered as 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. 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, which are Private car, Taxi, Microbus, Walking, and others. The results indicate that the developed model exhibits a good fit for the data with prediction accuracy of about 85%. Moreover, the model shows that total travel time, total cost, ownership of transport means, driving license ownership, occupational status, residence status, gender, and personal income are the main factors that significantly affect the choice of transport modes.
Number of downloads: 1348
Keywords:
choice;
urban transportation planning;
multinomial logit models;
easy logit modeler (ELM);
Mansoura;
Acknowledgements:
The authors would like to acknowledge Dr. Alaa Gabr, Associate Professor at Mansoura University, for his help in the data collection process.
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