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10. TRANSPORTATION MODELING AND ANALYSIS FOR URBAN TRIP DISTRIBUTION USING INTERVAL TYPE-2 FUZZY LOGIC by Umoh U. A, Asuquo D. E, Eyoh I. J. and Isuekpe E. C. Volume 55 (February 2020 Issue)
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TRANSPORTATION MODELING AND ANALYSIS FOR URBAN TRIP DISTRIBUTION USING INTERVAL TYPE-2 FUZZY LOGIC

Umoh U. A, Asuquo D. E, Eyoh I. J. and Isuekpe E. C.

Department of Computer Science, Faculty of Science, University of Uyo, Uyo

Abstract

This paper explores the potential capabilities of Interval Type-2 Fuzzy Logic (IT2FL) in urban trip distribution modeling (TDM) to estimate the volume of trip interaction between selected zones. Some objectives and constraints of transport processes are often difficult to be measured by crisp values because of the inherent imprecision and uncertainties of transportation data. An IT2FL model is designed and applied to model inter-city passenger flow. Six (6) urban centers in Akwa Ibom State, Nigeria, were selected for the study, which includes; Uyo, Eket, Oron, Ikot Ekpene, Abak and Ikot Abasi. The data on passengers’ trips generated, passengers trips attracted and the distance used in the study were obtained from travel survey.  The IT2FL model for trip distribution  involves the operation of fuzzification which Gaussian membership function is employed, knowledge base which comprises rules and data base built to support the fuzzy inference using Mandani inference mechanism, K-Mendel algorithm is explored for type reduction process and defuzzification.. The study investigates gravity model as applied in urban trip distribution for the purpose of comparison. For the purpose of performance measure and model evaluation in this analysis, four goodness-of-fit statistics are used to compare the model performance. The four performance metrics - mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE) and mean absolute percentage error (MAPE) - are applied and the results indicate that IT2FL model gives a better performance with lower error values of 10.2, 1.18, 0.14 and 0.22 for MAE, MSE, RMSE and MAPE, respectively compared to 11.66, 2.25, 0.18 and 0.32, respectively given by the gravity model. Thus, IT2FLS serves as a better model in managing transportation problem by aiding good decision for both travelers and transport planners. 

Keywords: IntervalFuzzy-2 Logic, Transportation Planning, Trip Generation, Trip distribution, Trip attraction

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