Analisis Fungsi Distribusi Panjang Perjalanan Berdasarkan Maksud dan Waktu Perjalanan

Abstract

Trip Length Distribution (TLD) analysis is needed to determine the form or parameter coefficients of the impedance function that is useful for estimating trip distribution. Using the right function as a constraint on the trip distribution allow us to reduce the ambiguity of the Origin-Destination (O-D) Matrix. The type of function that represents the real TLD conditions needs to be formulated correctly so that it can be used to accurately calibrate the O-D Matrix as a basis for predicting future trip volumes. Research related to TLD patterns as part of student travel behavior has not been widely studied. Understanding the characteristics of campus community travel behavior is an important element in transportation studies to determine mobility factors on campus and encourage a sustainable transportation system. The initial stage, it is necessary to describe the prevailing travel trends based on the characteristics of trips. Based on the background description above, the research problem formulation is: how do trip characteristics, namely the purpose and time of travel, influence the form of the travel impedance function among students? The research data collection method used a home interview survey. Meanwhile, data analysis used nonlinear regression to find the form of the function that fits the statistical criteria. The analysis results show that the purpose and time of travel do not affect the form of the impedance function, which is represented by the trip length distribution shape graph. However, based on the results of the regression analysis, it shows that the purpose and travel time influence the parameter values of the impedance function. The smallest influence occurs with the exponential function type, followed by the power function, Tanner, and Gamma. The Gamma function is generally more representative and more consistent in explaining the form of the travel impedance function of students in various travel time intervals.