City and Regional Planning / Şehir ve Bölge Planlama
Permanent URI for this collectionhttps://hdl.handle.net/11147/4274
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Article Casting the Swarms Problem in the Ensembles Context(Çukurova Üniversitesi, 2016) Kok, Çağatay; Çellek, Seven Burçin; Koşun, Çağlar; Özdemir, SerhanSürü robotları yüzlerce farklı şekilde modellenmiştir. Kalabalık olmaları sürülerin bir özelliğidir. Sayılamayacak kadar çok sayıya ulaştıklarında, termo-istatiksel mekanik devreye girebilir. Yazarlar bu avantajı kullanarak sürü robotları için evrensel istatistik oluşturmak istediler. Üç temel topluluk açıklandı ve formüle edildi. Sürüler izole edildiklerinde mikrokanonik uyum ortama hakim olurken, ortama av veya avcı girişi olur ise, duruma bağlı olarak değişimler gözlemlenir. Bu yüzden formulasyonlar ve geçişler şarta bağlıdır. Son olarak gözlemlenen olasılıklar tartışıldıArticle Citation - WoS: 6Citation - Scopus: 7An Entropy-Based Analysis of Lane Changing Behavior: An Interactive Approach(Taylor and Francis Ltd., 2017) Koşun, Çağlar; Özdemir, SerhanObjectives: As a novelty, this article proposes the nonadditive entropy framework for the description of driver behaviors during lane changing. The authors also state that this entropy framework governs the lane changing behavior in traffic flow in accordance with the long-range vehicular interactions and traffic safety. Methods: The nonadditive entropy framework is the new generalized theory of thermostatistical mechanics. Vehicular interactions during lane changing are considered within this framework. The interactive approach for the lane changing behavior of the drivers is presented in the traffic flow scenarios presented in the article. According to the traffic flow scenarios, 4 categories of traffic flow and driver behaviors are obtained. Through the scenarios, comparative analyses of nonadditive and additive entropy domains are also provided. Results: Two quadrants of the categories belong to the nonadditive entropy; the rest are involved in the additive entropy domain. Driving behaviors are extracted and the scenarios depict that nonadditivity matches safe driving well, whereas additivity corresponds to unsafe driving. Furthermore, the cooperative traffic system is considered in nonadditivity where the long-range interactions are present. However, the uncooperative traffic system falls into the additivity domain. The analyses also state that there would be possible traffic flow transitions among the quadrants. This article shows that lane changing behavior could be generalized as nonadditive, with additivity as a special case, based on the given traffic conditions. Conclusions: The nearest and close neighbor models are well within the conventional additive entropy framework. In this article, both the long-range vehicular interactions and safe driving behavior in traffic are handled in the nonadditive entropy domain. It is also inferred that the Tsallis entropy region would correspond to mandatory lane changing behavior, whereas additive and either the extensive or nonextensive entropy region would match discretionary lane changing behavior. This article states that driver behaviors would be in the nonadditive entropy domain to provide a safe traffic stream and hence with vehicle accident prevention in mind.Article Citation - WoS: 3Citation - Scopus: 3Determining the Complexity of Multi-Component Conformal Systems: a Platoon-Based Approach(Elsevier Ltd., 2017) Koşun, Çağlar; Özdemir, SerhanMany systems in nature and engineering are composed of subsystems. These subsystems may be formed in a linear, planar or spatial array. A typical example of these formations is a chain of vehicles known as platoon formation in traffic flow. Platoon formation of vehicles is a linear or planar formation of vehicles where a certain and a constant headway, and sideway if applicable, is provided in between every and each one of them. It is argued in this paper that a well-automated platoon formation of vehicles is an extreme case of conformity. During this transformation from a many degrees of freedom formation to a solid object, Tsallis q value is computed to be ranging from one extreme case of q=3 to the other where q=1, when classified in terms of inverse temperatures of clearance fluctuations. At one extreme of q=3, one observes unbounded fluctuations in clearance fluctuations so that inverse temperature distributions approach a Dirac delta at the origin. At the other extreme of q=1, fluctuations in clearance tend to zero asymptotically, where a solid structure of agents (vehicles) emerges. The transition from q=3 to q=1 is investigated through synthetic and experimental clearance fluctuations between the cars. The results show that during the transition from q=3 to q=1, the platoon loses its many degrees of freedom (dof) of motion until a solid single object emerges. Authors assert that the Tsallis q value of a platoon of vehicles is limited to 3>q<1.Article Citation - WoS: 14Citation - Scopus: 15A Superstatistical Model of Vehicular Traffic Flow(Elsevier Ltd., 2016) Koşun, Çağlar; Özdemir, SerhanIn the analysis of vehicular traffic flow, a myriad of techniques have been implemented. In this study, superstatistics is used in modeling the traffic flow on a highway segment. Traffic variables such as vehicular speeds, volume, and headway were collected for three days. For the superstatistical approach, at least two distinct time scales must exist, so that a superposition of nonequilibrium systems assumption could hold. When the slow dynamics of the vehicle speeds exhibit a Gaussian distribution in between the fluctuations of the system at large, one speaks of a relaxation to a local equilibrium. These Gaussian distributions are found with corresponding standard deviations 1/β. This translates into a series of fluctuating beta values, hence the statistics of statistics, superstatistics. The traffic flow model has generated an inverse temperature parameter (beta) distribution as well as the speed distribution. This beta distribution has shown that the fluctuations in beta are distributed with respect to a chi-square distribution. It must be mentioned that two distinct Tsallis q values are specified: one is time-dependent and the other is independent. A ramification of these q values is that the highway segment and the traffic flow generate separate characteristics. This highway segment in question is not only nonadditive in nature, but a nonequilibrium driven system, with frequent relaxations to a Gaussian.Article Citation - WoS: 2Citation - Scopus: 2Soft Computing and Regression Modelling Approaches for Link-Capacity Functions(Czech Technical University in Prague, 2016) Koşun, Çağlar; Tayfur, Gökmen; Çelik, Hüseyin MuratLink-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, SerhanTraffic 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.