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Yayın Improving the calibration time of traffic simulation models using parallel computing technique(Institute of Electrical and Electronics Engineers Inc., 2019-06) Dadashzadeh, Nima; Ergün, Murat; Kesten, Ali Sercan; Zura, MarijanThe calibration procedure for traffic simulation models can be a very time-consuming process in the case of a large-scale and complex network. In the application of Evolutionary Algorithms (EA) such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) for calibration of traffic simulation models, objective function evaluation is the most time-consuming step in such calibration problems, because EA has to run a traffic simulation and calculate its corresponding objective function value once for each set of parameters. The main contribution of this study has been to develop a quick calibration procedure for the parameters of driving behavior models using EA and parallel computing techniques (PCTs). The proposed method was coded and implemented in a microscopic traffic simulation software. Two scenarios with/without PCT were analyzed using the developed methodology. The results of scenario analysis show that using an integrated calibration and PCT can reduce the total computational time of the optimization process significantly-in our experiments by 50%-and improve the optimization algorithm's performance in a complex optimization problem. The proposed method is useful for overcoming the limitation of computational time of the existing calibration methods and can be applied to various EAs and traffic simulation software.Yayın Statistical analysis of bus transportation networks of Istanbul(World Scientific Publishing Co Pte Ltd, 2016) Çoban, Veysel; Atan, Sabri TankutTransportation networks such as railway, airport and bus networks are the real-world networks whose inherent statistical properties characterize and differentiate the networks. In order to understand the network characteristics of bus transportation networks (BTNs) of Istanbul, we analyzed its network properties such as degree distributions, clustering coefficients and assortativity. BTNs of Istanbul is defined into three networks as the existence and nonexistence of the metrobus and existence of third- bridge. They are also graphically represented within C-, L- and P-Space topologies that are defined with the connection of the bus stops or routes. Statistical results obtained from network properties reflected the characteristics of the BTNs of Istanbul and give an information about the effects of the metrobus lines and third bridge on the BTNs in Istanbul.
