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Rahayu, Rahayu Sulistyorini (2009) PENGEMBANGAN MODEL KOMBINASI GRAVITY, MULTINOMIAL LOGIT DAN EQUILIBRIUM ASSIGNMENT. In: Simposium XII FSTPT, 13 Nov - 14 Nov 1999, Universitas Kristen Petra Surabaya. (Submitted)

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    Abstract Generally, transportation cases requires O-D matrices as main input which present traveling patern in a certain region plan. One of effective and economist method to define O-D matrices is estimation method based on traffic flow data which is included in Non-Convensional Methods. In previous research (Tamin,2000) concluded that the accuration level of O-D matrices that estimated from traffic flow information mostly influenced by several factors as followed; the choice of transport demand model and estimation method that used for calibrate parameter of transportation model. Model that developed in this research is model that combine trip distribution stage, mode choice and trip assignment, hence this model could be used for estimate O-D matrices for several different mode. However, the previous research still in a burden condition of “All or Nothing” which is not realistic for some congested road networks in urban area. So, the main objective of this research is the application of a combined trip distribution-mode choice model estimated from traffic count under equilibrium condition (congested road network). In this research, we use gravity as trip distribution model, multinomial logit as mode choice model and equilibrium assignment condition as trip assignment model. Estimation method have been developed using linear-least-squares to calibrate the unknown parameters of the postulated model. Further this development model applied by using software emme/3. Kata kunci: gravity, multinomial logit, equilibrium assignment

    Item Type: Conference or Workshop Item (Lecture)
    Subjects: T Technology > TA Engineering (General). Civil engineering (General)
    Divisions: Fakultas Teknik
    Depositing User: Admin Fakultas Teknik
    Date Deposited: 25 Apr 2016 18:18
    Last Modified: 25 Apr 2016 18:18

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