Volume List  / Volume 8 (4)

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)

Marwa Elharoun - Public Works Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt -

Usama Elrawy Shahdah - Public Works Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt -

Sherif M. El-Badawy - 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.


Download Article

Number of downloads: 1418


Acknowledgements:

The authors would like to acknowledge Dr. Alaa Gabr, Associate Professor at Mansoura University, for his help in the data collection process.


References:

Abdulhaq, D.M.N. 2016. Transportation Mode Choice Model for Palestinian Universities Students: A Case Study on An-Najah New Campus, Master of Science thesis, An-Najah National University-Faculty of Graduate Studies.

 

Al-Ahmadi, H.M. 2006. Development of intercity mode choice models for Saudi Arabia, Engineering Sciences 17(1): 3-12.

 

Almasri, E.; Alraee, S. 2013. Factors Affecting Mode Choice of Work Trips in Developing Cities—Gaza as a Case Study, Journal of Transportation Technologies 3(04): 247-259.

 

Amemiya, T. 1981. Qualitative response models: A survey, Journal of Economic Literature 19(4): 1483-1536.

 

Ben-Akiva, M. 1974. Structure of Passenger Travel Demand Models, Transportation Research Record 526: 26-42.

 

Ben-Akiva, M.E.; Lerman, S.R. 1985. Discrete choice analysis: theory and application to travel demand (Vol. 9). MIT press.

 

Bierlaire, M. 2003. BIOGEME: a Free Package for The Estimation of Discrete Choice Models. In Proceedings of the Swiss Transport Research Conference, No. TRANSP-OR-CONF-2006-048.

 

Conrady, S.; Jouffe, L. 2013. Modeling Vehicle Choice and Simulating Market Share with Bayesian Networks: A case study about predicting the U.S. market share of the Porsche Panamera using the Bayesia Market Simulator. Available from internet: https://library.bayesia.com/download/attachments/4882677/choice_modeling_v32.pdf.

 

Egyptian central agency for public mobilization and statistics. 2017. Egyptian Population in 2017 [in Arabic]. Available from internet: http://www.capmas.gov.eg/Admin/Pages%20Files/201871611358gov.pdf.

 

El-Bany, M.E.S.; Shahin, M.M.; Hashim, I.H.; Serag, M.S. 2014. Policy Sensitive Mode Choice Analysis of Port-Said City, Egypt, Alexandria Engineering Journal 53(4): 891-901.

 

El Esawey, M.; Ghareib, A. 2009. Analysis of Mode Choice Behavior in Greater Cairo Region. In Proceeding of the 88th Annual Meeting of Transportation Research Board, No. 09-0168.

 

ELMWorks, Inc. 2008. Easy Logit Modeling (ELM) Software, Version 1.1.10 [Computer Software]. Available from internet: http://elm.newman.me.

 

Fletcher, J.; Ramanathan, T.; Dallaire, S.; Szala, M.; Saini, A.; Levine, R. 2018. POL242 Online Lab Manual, University of Toronto. Available from internet: http://www.chass.utoronto.ca/~josephf/pol242/onlinetutorials.htm.

 

Gensch, D.H. 1980. Choice model calibrated on current behavior predicts public response to new policies, Transportation Research Part A: General 14(2): 137-142.

 

Habib, K.; El-Assi, W. 2016. How Large is too Large? The Issue of Sample Size Requirements of Regional Household Travel Surveys, the Case of the Transportation Tomorrow Survey in the Greater Toronto and Hamilton Area. In Proceeding of the 95th Annual Meeting of Transportation Research Board.

 

IBM Corp. 2017. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. [Computer Software].

 

Koppelman, F.S.; Bhat, C. 2006. A self-instructing course in mode choice modeling: multinomial and nested logit models. U.S. Department of Transport, Federal Transit Administration. Available from internet: http://www.caee.utexas.edu.

 

Ortuzar, J.; Willumsen, L.G. 2011. Modelling transport. John Wiley & Sons. 607 p.

 

Richardson, A.J. 2003. Creative Thinking About Transportation Planning. In Proceeding of the 82nd Annual Meeting of the Transportation Research Board.