Basics on Categorizing Travel-Time-Based Degrees of Satisfaction Using Triangular Fuzzy-Membership Functions

Abstract

The travel desires of trip-makers in urban activity centres depend mainly on the location of residential areas, proximity to various activity centres, household characteristics, and socio-economic factors that influence the choice of travel modes. Decision-making with regard to the choice of a particular mode of travel is fuzzy in nature, and seldom follows a rigid rule-based approach. In this context, the fuzzy-logic approach was considered since it could handle inherent randomness in decision-making related to mode-choice. The present study focuses on the application of this technique making use of revealed preference survey data collected through CES and MVA Systra, later compiled and corrected in various stages at NITK. The difference between the actual travel time by a particular mode, and the theoretical travel time based on average vehicular speeds was used as an important indicator in determining the degrees of satisfaction of the trip-maker. This indicator was computed, and fitted using a normal distribution. It was assumed that indicator values between μ-3σ and μ could be considered for the category of satisfied trip-makers according to the three sigma rule where μ is the mean indicator value, and σ represents the standard deviation. The computed values of the indicators were used in classifying the data into 6 categories of degrees of satisfaction that formed the basic framework for modelling using fuzzy-logic technique. This paper aims at understanding the basic mathematical computations involved in defuzzification using the centroid method for triangular membership functions, and provides a comparison with results obtained using MATLAB. © 2020 The Authors. Published by Elsevier B.V.