City and Regional Planning / Şehir ve Bölge Planlama

Permanent URI for this collectionhttps://hdl.handle.net/11147/4274

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Author: search.filters.author.Koşun, ÇağlarWoS Q: search.filters.wosQuartile.Q4

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  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Soft Computing and Regression Modelling Approaches for Link-Capacity Functions
    (Czech Technical University in Prague, 2016) Koşun, Çağlar; Tayfur, Gökmen; Çelik, Hüseyin Murat
    Link-capacity functions are the relationships between the fundamental traffic variables like travel time and the flow rate. These relationships are important inputs to the capacity-restrained traffic assignment models. This study investigates the prediction of travel time as a function of several variables V/C (flow rate/capacity), retail activity, parking, number of bus stops and link type. For this purpose, the necessary data collected in Izmir, Turkey are employed by Artificial Neural Networks (ANNs) and Regression-based models of multiple linear regression (MLR) and multiple non-linear regression (MNLR). In ANNs modelling, 70% of the whole dataset is randomly selected for the training, whereas the rest is utilized in testing the model. Similarly, the same training dataset is employed in obtaining the optimal values of the coefficients of the regression-based models. Although all of the variables are used in the input vector of the models to predict the travel time, the most significant independent variables are found to be V/C and retail activity. By considering these two significant input variables, ANNs predicted the travel time with the correlation coefficient R = 0:87 while this value was almost 0.60 for the regression-based models.
  • Article
    An Analysis of Vehicular Traffic Flow Using Langevin Equation
    (Faculty of Transport and Traffic Sciences, University of Zagreb, 2015) Koşun, Çağlar; Çelik, Hüseyin Murat; Özdemir, Serhan
    Traffic flow data are stochastic in nature, and an abundance of literature exists thereof. One way to express stochastic data is the Langevin equation. Langevin equation consists of two parts. The first part is known as the deterministic drift term, the other as the stochastic diffusion term. Langevin equation does not only help derive the deterministic and random terms of the selected portion of the city of Istanbul traffic empirically, but also sheds light on the underlying dynamics of the flow. Drift diagrams have shown that slow lane tends to get congested faster when vehicle speeds attain a value of 25 km/h, and it is 20 km/h for the fast lane. Three or four distinct regimes may be discriminated again from the drift diagrams; congested, intermediate, and free-flow regimes. At places, even the intermediate regime may be divided in two, often with readiness to congestion. This has revealed the fact that for the selected portion of the highway, there are two main states of flow, namely, congestion and free-flow, with an intermediate state where the noise-driven traffic flow forces the flow into either of the distinct regimes. © 2015, Faculty of Transport and Traffic Engineering. All rights reserved.