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Öğe A hybrid traffic controller system based on flower pollination algorithm and type-2 fuzzy logic optimized with crow search algorithm for signalized intersections(Springer, 2024) Korkmaz, Ersin; Akgüngör, Ali PayidarIn this study, a hybrid traffic signal control (HTSC) system based on phase and time optimization was developed. The Flower Pollination Algorithm (FPA) approach was used for phase optimization, while Type-2 Fuzzy Logic, optimized with the Crow Search Algorithm (CSA), was utilized for time optimization. The hybrid system's performance was investigated using nine different traffic conditions and four different intersection geometries. The hybrid system was compared with three controller systems which are a fixed-time signal controller, a signal controller based on the FPA approach (FPA_TSC), and the optimized Type-1 fuzzy logic signal controller (Type-1 FL-TSC). The HTSC approach achieved the best performance with about 32% improvement over the fixed-time traffic controller and it showed 5% and 6% better performance than the FPA_TSC and Type-1 FL-TSC, respectively. Considering the performance of the new hybrid system, it is effective in minimizing delays and driver dissatisfaction occurring from signalization. It also contributes to the reduction of emissions and fuel consumption. The HTSC approach can be used as an alternative signal control method in the control of intersections with high traffic volume due to its fast and effective performance.Öğe Bezier Search Differential Evolution algorithm based estimation models of delay parameter k for signalized intersections(Wiley, 2022) Akgüngör, Ali Payidar; Korkmaz, ErsinThis article presents a new methodology for estimating delay parameter k, and proposes analytical models which are used artificial intelligence technique for signalized intersections that considers the variation in traffic flow with under-saturated and over-saturated conditions. The delay parameter k has been expressed as a function of the degree of saturation in the proposed analytical models. Using the Bezier Search Differential Evolution algorithm (BeSD) algorithm, four different model forms were developed separately for under-saturated conditions (x <1) and over-saturated conditions (x > =1). Among the model forms developed as linear, quadratic, power, and logarithmic, the quadratic model presented the best results in both traffic conditions. In the validation of the models, a total of 140 different traffic conditions were determined, 56 of which cover the under-saturated and 84 the over-saturated traffic conditions. According to the statistical results, using k values depending on the proposed model instead of using a constant k value (0.5) provides 1.5 and 4.3 improvements for RMSE and MAPE values in under-saturated traffic conditions respectively, while these improvements in over-saturated traffic conditions have reached 9.5 and 6, respectively. As a result, using k values depending on the proposed model will be effective in obtaining a more accurate delay value. This effect is more evident, especially in over-saturated traffic conditions.Öğe Comparison of artificial bee colony and flower pollination algorithms in vehicle delay models at signalized intersections(SPRINGER LONDON LTD, 2020) Korkmaz, Ersin; Akgungor, Ali PayidarDelay is a significant research topic since it includes indicators such as travel quality, lost time and fuel consumption. Furthermore, the delay is used for optimization of traffic control systems and determination of the level of service at signalized intersections. Therefore, researchers have focused on accurate estimation of delay. The objective of this study is to simply and accurately estimate the delay and evaluate the performance of the proposed approaches which are artificial bee colony (ABC) and flower pollination algorithms (FPA). In this study, ABC and FPA have been used to develop different delay models which are linear, semi-quadratic, quadratic and power forms. Analysis period (T), the green ratio (g/C; effective green to cycle length) and the degree of saturation (x = v/c; volume to capacity) are used as input parameters while developing the models. The results of present models are compared to estimations obtained from analytical models which are Highway Capacity Manual and Australian (Akcelik) delay models. Semi-quadratic form yielded to best results in terms of coefficient of determination (R-2), mean square error and mean absolute error. Additionally, FPA approach showed better performance than ABC approach finding the optimal solution in the lower number of iterations.Öğe Comparison Of Different Approaches In Traffic Forecasting Models For The D-200 Highway In Turkey(Fac Transport Silesian Univ Technology, 2018) Dogan, Erdem; Korkmaz, Ersin; Akgungor, Ali PayidarShort-term traffic estimations have a significant influence in terms of effectively controlling vehicle traffic. In this study, short-term traffic forecasting models have been developed based on different approaches. Seasonal autoregressive integrated moving average (SARIMA), artificial bee colony (ABC) and differential evolution (DE) algorithms are the techniques used in the optimization of models, which have been developed by using observation data for the D-200 highway in Turkey. 80% of the data were used for training, with the remaining data used for testing. The performances of the models were illustrated with mean absolute errors (MAEs), mean absolute percentage errors (MAPEs), the coefficient of determination (R2) and the root-mean-square errors (RMSEs). It is understood that all the models provided consistent and useful results when the developed models were compared with the statistical results. In the models created separately for two lanes, the R2 values of the models were calculated to be approximately 92% for the right lane, which is generally used by heavy vehicles, and 88% for the left lane, which is used by less traffic. Based on the MAE and RMSE values, the model developed by the ABC algorithm gave the lowest error and showed more effective performance than the other approaches. Thus, the ABC model showed that it is appropriate for use on other highways in Turkey.Öğe COVID-19 Salgın Sürecinin Toplu Taşıma Sistemlerine Etkisinin Anket Yöntemiyle İstanbul-Ankara İçin İncelenmesi(2022) Korkmaz, ErsinCOVID-19 virüsü, dünyada olduğu gibi Türkiye’de de hızlı bir şekilde yayılmıştır. Meydana gelen salgın, tüm yaşam alanlarını olumsuz etkilemiştir. Bu alanların başlıcaları arasında şehir içi ve şehir dışı ulaşım gösterilebilir. Bu çalışmada, salgının toplu taşımayı ne şekilde etkilediği ve toplu taşıma üzerindeki kişisel algı değişiminin nasıl gerçekleştiğinin incelenmesi amaçlanmıştır. Çalışma kapsamında, İstanbul ve Ankara ilindeki salgın öncesi ve sonrası dönemlere ait verilerle birlikte, kullanıcıların toplu taşımaya karşı algılarını gösteren anket verisi kullanılmıştır. 1,5 yıllık salgın sürecinde toplu taşımada taşınan yolcunun %45 azaldığı gözlemlenmiştir. Vaka sayılarının artmasıyla hükümetin sıkı tedbirler aldığı dönemlerde ise %80’den fazla azalma olduğu görülmüştür. Kullanıcı anketlerine göre, COVID-19 salgın sürecince maske kullanımı, ulaşım araçlarının dezenfekte edilmesi, ayakta yolcu alınmaması ve taşıma kapasitesinin azaltılması gibi tedbirler alınmasına rağmen toplu ulaşımın salgın öncesine göre daha az tercih edildiği ve %20’lik bir azalma olduğu tespit edilmiştir. Virüse yakalanma durumu toplu taşıma araçlarına olan güven ve seçim etkisinde belirleyici olmaktadır. Özellikle virüse birden fazla kez yakalananların daha rahat hareket ettikleri ve toplu taşımaya yönelik daha az endişe duydukları görülmüştür. Ayrıca, özel araç kullanımının artış gösterdiği, şehir içi ulaşımda dolmuşların ve şehirlerarası ulaşımda otobüslerin en güvensiz araçlar olarak algılandığı görülmüştür.Öğe Delay estimation models for signalized intersections using differential evolution algorithm(Academic Publication Council, 2017) Korkmaz, Ersin; Akgungor, Ali PayidarDelay is an important parameter in the optimization of traffic signals and the determination of the level of service (LOS) of a signalized intersection since it directly reflects the lost travel time and fuel consumption. The accurate estimation of delay is, therefore, an important issue. The purpose of this study is to develop new delay models with less input parameters by using one of the artificial intelligent techniques. In this research, three types of differential evolution delay estimation models (DEDEM), i.e. linear, exponential and quadratic, were developed using differential evolution (DE) approach. In developing of the delay models, the green ratio (g/C effective green to cycle length) and the degree of saturation (x=v/c; volume to capacity) were considered. The first one changed from 0.35 to 0.60, the second one varied between 0.7 and 1.4. The model outputs were compared analytically to the HCM and Australian (Akcelik) delay models. The study results illustrated that R2, Mean Square Error (MSE) and Mean Absolute Error (MAE) values of DEDEMquadratic, which are 0.97, 207.98, 12.12 respectively, were better than analytical delay models and other types models. As a result, the quadratic form of DEDEM model can be used as an alternative estimation model for delay, and DE approach can be utilized as a model-fitting algorithm as well.Öğe Energy demand estimation in Turkey according to modes of transportation: Bezier search differential evolution and black widow optimization algorithms-based model development and application(Springer London Ltd, 2023) Korkmaz, ErsinIn this study, Bezier search differential evolution (BeSD) and black widow optimization (BWO) algorithms-based estimation models in different forms have been developed to estimate the transportation energy consumption in Turkey. In order to examine the effect of demand distribution in modes of transportation on energy consumption, parameters in modes of transportation which are Passenger-km and Freight-km, Carbon dioxide emissions, Gross Domestic Product and Infrastructure Investment parameters are used as model parameters. Model performances are evaluated within different error criteria, and their performances are revealed. The BeSD algorithm performed better than the BWO algorithm and revealed that it is the most appropriate method for transportation energy demand (TED) estimation. Although each model developed using two different approaches is usable, BeSD-based quadratic model has shown the highest performance with a 0.95% MAPE value, and TED's predictions for the future have been put forth based on this model. According to two different scenarios, TED projections until 2040 are presented for cases in which the current distribution of demand in modes of transportation and there is a demand shift from highway to other modes of transportation. The projections of the parameters have been determined by the least squares method. In the first scenario, it has been predicted that there will be 63 MTOE energy demand in 2040, and the projection values are consistent with the Ministry of Energy and Natural Resources values. In the second scenario, when demand shifts from the highway to other modes of transportation, it is predicted that energy consumption will decrease and there will be 42 MTOE in 2040.Öğe Energy Demand Estimation in Turkey According to Road and Rail Transportation: Walrus Optimizer and White Shark Optimizer Algorithm-Based Model Development and Application(Mdpi, 2024) Korkmaz, Ersin; Dogan, Erdem; Akgungor, Ali PayidarTransport energy demand (TED) forecasting is a crucial issue for countries like Turkey that are dependent on external resources. The accuracy and effectiveness of these forecasts are extremely important, especially for the strategies and plans to be developed. With this in mind, different forms of forecasting models were developed in the present study using the Walrus Optimizer (WO) and White Shark Optimizer (WSO) algorithms to estimate Turkey's energy consumption related to road and railway transportation modes. Additionally, another objective of this study was to examine the impacts of different transport modes on energy demand. To investigate the effect of demand distribution among transport modes on energy consumption, model parameters such as passenger-kilometers (P-km), freight-kilometers (F-km), carbon dioxide emissions (CO2), gross domestic product (GDP), and population (POP) were utilized in the development of the models. It was found that the WO algorithm outperformed the WSO algorithm and was the most suitable method for energy demand forecasting. All the developed models demonstrated a better performance level than those reported in previous studies, with the best performance achieved by the semi-quadratic model developed with the WO, showing a 0.95% MAPE value. Projections for energy demand up to the year 2035 were established based on two different scenarios: the current demand distribution among transport modes, and a demand shift from road to rail transportation. It is anticipated that the proposed energy demand models will serve as an important guide for effective planning and strategy development. Moreover, the findings suggest that a balanced distribution among transport modes will have a positive impact on transport energy and will result in lower energy requirements.Öğe Estimating The Number Of Traffic Accidents, Injuries And Fatalities In Turkey Using Adaptive Neuro-Fuzzy Inference System(Scientific Research Center Ltd Belgrade, 2016) Akgungor, Ali Payidar; Korkmaz, Ersin; Dogan, ErdemThis study proposes Adaptive Neuro-Fuzzy Inference System (ANFIS) models to estimate the number of accidents, injuries and fatalities in Turkey. In the model development, population (P) and the number of vehicles (N) are selected as model parameters. Three different ANFIS structure models are developed using the data covering from 2000 to 2014. Developed models' results are statistically compared to observed values for training and test data in terms of root mean square errors (RMSE), mean absolute percentage errors (MAPE) and coefficient of determination (R-2). The results of the ANFIS models showed that they was suitable to estimate the number of accidents, injuries and fatalities. To investigate the performance of ANFIS models for future estimations, a ten-year period from 2015 to 2024 is considered. Thus, future values of population was obtained from the projection of Turkish Statistical Institute (TSI) and the vehicle ownership rate is expected to reach 0.4 by 2024. Therefore, population and the number of vehicles are considered to reach approximately 85 and 34 million, respectively. The results obtained from future estimations reveal the suitability of ANFIS approach for road safety applications.Öğe Estimation Of Car Ownership In Turkey Using Artificial Bee Colony Algorithm(Scientific Research Center Ltd Belgrade, 2016) Korkmaz, Ersin; Dogan, Erdem; Akgungor, Ali PayidarThis study proposes Artificial Bee Colony (ABC) models to estimate the number of cars in Turkey. In other words, car ownership is defined the number of cars per 1000 people. In the models development, population (P), per capita Gross Domestic Product (GDP) as dollars and fuel prices as Petrol, Diesel and Lpg were selected as model parameters. Two different ABC models were developed using the data covering from 2004 to 2015. According to fuel type, the coefficients of models were determined for each fuel type. Therefore, the sum of number of cars for each fuel type presented car ownership in Turkey. Developed models' results were statistically compared to observed values in terms of root mean square errors (RMSE), mean absolute percentage errors (MAPE) and coefficient of determination (R-2). The results of the ABC models showed that they were suitable to estimate the number of cars. To investigate the performance of ABC models for future estimations, a ten-year period from 2016 to 2025 was considered. Thus, future values of population were obtained from the projection of Turkish Statistical Institute (TSI) and the projections of other parameters, per capita GDP and fuel price, were executed according to current growth curve. The results obtained from future estimations reveal the suitability of ABC approach for determination of car ownership.Öğe Estimation Of Passenger-Kilometer And Tonne-Kilometer Values For Highway Transportation In Turkey Using The Flower Pollination Algorithm(Fac Transport Silesian Univ Technology, 2018) Korkmaz, Ersin; Akgungor, Ali PayidarWithin the scope of this study, intercity passenger and freight movements in Turkey are estimated by using the flower pollination algorithm (FPA), while demand forecasts are performed on transport systems considering possible future scenarios. Since the passenger and freight transport system in Turkey mainly involves road transport, passenger-kilometer and tonne-kilometer values of this system are estimated. By relying on three independent parameters, models were developed in three different forms: linear, force and semi-quadratic. Population (P) between 1990 and 2016, gross domestic product per capita (GDPperC) in US dollars and the number of vehicles were used as input parameters for the development of the models. When the passenger-kilometer models were created, the number of cars, buses and minibuses that are predominantly used for passenger transportation was preferred for the number of vehicles, while the number of trucks and vans used for cargo transportation were taken into consideration in the tonne-kilometer models. The coefficients of the models were determined by FPA optimization, with models developed to estimate passenger-kilometer and tonne-kilometer values. The model results were compared with the observation values and their performance was evaluated. Two different scenarios were created to estimate passenger-kilometer and tonne-kilometer in 2030. Parallel to the increase in population and welfare level, it is predicted that demand for passenger and freight transport will increase. In particular, the higher input parameter values in Scenario 1 significantly affect the increase in demand, leading to a demand increase of around 50%. In addition, the FPA has demonstrated effective performance in predicting the demand for passenger and freight transport and that it can be used in many different areas.Öğe Estimation of the soil liquefaction potential through the Krill Herd algorithm(Techno-Press, 2023) Sonmezer, Yetis Bulent; Korkmaz, ErsinLooking from the past to the present, the earthquakes can be said to be type of disaster with most casualties among natural disasters. Soil liquefaction, which occurs under repeated loads such as earthquakes, plays a major role in these casualties. In this study, analytical equation models were developed to predict the probability of occurrence of soil liquefaction. In this context, the parameters effective in liquefaction were determined out of 170 data sets taken from the real field conditions of past earthquakes, using WEKA decision tree. Linear, Exponential, Power and Quadratic models have been developed based on the identified earthquake and ground parameters using Krill Herd algorithm. The Exponential model, among the models including the magnitude of the earthquake, fine grain ratio, effective stress, standard penetration test impact number and maximum ground acceleration parameters, gave the most successful results in predicting the fields with and without the occurrence of liquefaction. This proposed model enables the researchers to predict the liquefaction potential of the soil in advance according to different earthquake scenarios. In this context, measures can be realized in regions with the high potential of liquefaction and these measures can significantly reduce the casualties in the event of a new earthquake.Öğe Flower pollination algorithm approach for the transportation energy demand estimation in Turkey: model development and application(Taylor & Francis Inc, 2018) Korkmaz, Ersin; Akgungor, Ali PayidarThis study proposes a new optimization technique to estimate the Transportation Energy Demand (TED) employing the Flower Pollination Algorithm (FPA). The TED estimation models were developed based on three parameters, which are Annual Vehicle-Km (AVK), Gross Domestic Product per Capita (GDPperC), and Carbon-dioxide (CO2) emission according to the linear, power and quadratic forms. These three parameters were determined by the WEKA data mining software program among nine parameters. Randomly selected 80% of historical data for 47 years, from 1970 to 2016, were used for the training of the algorithm, and the remains were used in the testing stage of the models. The performances of the models were evaluated according to six different statistical criteria. Transportation energy demand forecasts by 2035 were carried out using three different scenarios using the TED estimation models. According to the scenarios, it is predicted that the transportation energy demand in Turkey will have doubled by 2035 in comparison with 2016. The FPA approach has been successfully applied in the development of the TED estimation models. The most important impact of this study is to help the creation of strategic action plans for energy policies in the transport sector and to contribute to the more efficient use of limited energy resources in the country.Öğe Investigating Parameter Interactions with the Factorial Design Method: Webster's Optimal Cycle Length Model(Univ Osijek, Tech Fac, 2018) Akgungor, Ali Payidar; Korkmaz, ErsinAccurate estimation of cycle length is an important factor in the performance of a signalized intersection. Cycle length is determined by employing some parameters such as arrival flow, number of phase, lost time etc., but each parameter has different effects on a cycle length model. If the effects of parameters and their interactions in the cycle length model are known, the performance of the model can be effectively increased. In this study, the sensitivity of optimal cycle length model proposed by Webster and its parameters were analysed with the factorial design method. The reason for selecting this model is that the model has still been used in signal timing practice and has lead many studies of researchers over 50 years. The evaluation of sensitivity analysis shows that while arrival flow as single parameter has a major effect on the optimal cycle length model, the remaining single parameters of the model (i.e., the number of phase in a cycle length, saturation flow and lost time) have secondary importance. Additionally, two parameter interactions of arrival flow-saturation flow have major effect on the model results. For three parameter interactions, the number of phase-arrival flow-saturation flow interaction has a slightly larger effect than the other three-parameter interactions. As a result, the factorial design method is an effective tool to determine the importance of the model parameters for researchers, and it can be employed to other traffic engineering applications.Öğe İzole Sinyalize Kavşaklar için Çiçek Tozlaşma Algoritması Kullanılarak Devre Süresi Modellerinin Geliştirilmesi(2020) Akgüngör, Ali Payıdar; Yavuz, Sevim; Korkmaz, Ersin; Doğan, ErdemSon zamanlarda nüfus ve ekonomideki büyüme karayollarında araç kullanımını arttırmakta, buna bağlı olarak da kavşakların kapasitesi yetersiz kalmaktadır. Kavşakların verimsiz çalışmasından dolayı gecikme, yakıt tüketimi, emisyon salınımı artarken sürücü davranışları da olumsuz etkilenmektedir. Kavşak geometrilerinin iyileştirilmesinin yanı sıra, optimum devre süresinin doğru tespiti ve sinyal sürelerinin düzenlenmesi ile de bu sorunların minimuma indirilebilmesi mümkün olmaktadır. Bu çalışmada Çiçek Tozlaşma Algoritması (ÇTA) kullanılarak optimum devre süresi modelleri geliştirilmiştir. Ayrıca en düşük gecikmeye sahip olan devre sürelerinin belirlenmesinde Diferansiyel Gelişim Algoritmasından (DGA) yararlanılmıştır. Kalibre edilen Webster modeline ilave olarak sabit eklenmiş Webster model formu ve üstel formda devre süresi modelleri geliştirilmiştir. VISSIM simülasyon programı ile elde edilen gecikme değerlerine göre geliştirilen bütün modeller Webster modeli ve VISTRO optimizasyon programı ile karşılaştırılmış ve önerilen modellerin istatistiksel olarak daha iyi performansa sahip olduğu görülmüştür. Bu modellerin özellikle yüksek trafik hacmine sahip trafik durumlarında yetersiz kalan Webster modelindeki eksiklikleri kapatarak alternatif bir devre süresi tahmin modeli olarak kullanılabileceği ön görülmektedir.Öğe İzole sinyalize kavşaklarda yapay zekâ teknikleri ile trafik sinyal kontrolü ve optimizasyonu(Kırıkkale Üniversitesi, 2019) Korkmaz, Ersin; Akgüngör, Ali Payıdaroptimizasyonuna dayalı Hibrid Trafik Kontrol Sistemi (HTKS) geliştirilmiştir. Geliştirilen sistemde Çiçek Tozlaşma Algoritması (ÇTA), Karga Arama Algoritması (KAA) ve Tip-2 Bulanık Mantık (Tip-2 BM) yaklaşımları kullanılmış olup, gecikmenin minimize edilmesi amaçlanmıştır. İki ana modülden oluşan sistemde, birinci modül ile ÇTA kullanılarak faz plan optimizasyonu yapılmakta, ikinci modülde ise KAA ile optimize edilen Tip-2 BM yaklaşımı ile süre optimizasyonu gerçekleştirilmektedir. Faz optimizasyonuna ilaveten faz seçimi de sağlanmış ve belirlenen faz düzeninde hangi faza öncelik verileceği tayin edilmiştir. Geliştirilen sistemlerin simülasyonları KU-Trsim mikroskobik simülasyon programında gerçekleştirilmiştir. KU-Trsim simülasyon programı kuyruk uzunluklarını ve araç sayılarını verecek şekilde revize edilmiş, ayrıca farklı trafik kontrol sistemleri ile uyumlu hale getirilmiştir. Simülasyon programının kullanım kolaylığı ve çıktı parametrelerinin görselliği için girdi ve çıktı ara yüzleri kontrol sistemlerine uygun olarak oluşturulmuştur. HTKS 4 farklı kavşak geometrisi ve 15 farklı trafik hacim senaryosuna göre farklı kontrol sistemleri ile karşılaştırılarak sistemin performansı ve uygulanabilirliği ortaya konulmuştur. Sabit zamanlı sistem, Diferansiyel Gelişim Algoritması (DGA) ile optimize edilen sabit zamanlı optimum devre süresi (DGA-ODS) sistemi, sadece faz optimizasyon modülünün kullanıldığı ÇTA-TKS sistemi ve Tip-1 BM-TKS sistemi performans karşılaştırılmasında kullanılan farklı kontrol sistemleridir. Kontrol sistemlerinden elde edilen gecikme değerlerine göre, HTKS'nın sabit zamanlı sisteme göre % 17 ile % 33 arasında, DGA-ODS sistemine göre % 9 ile % 19, ÇTA-TKS sistemine göre % 1,5 ile % 5 ve Tip-1 BM-TKS sistemine göre % 3 ile % 6 arasında iyileştirme sağladığı görülmüştür.Öğe Meta-Sezgisel Yöntemlerle Sabit Zamanlı Sinyalize Kavşaklar için Optimum Devre Süresi Modeli(2019) Akgüngör, Ali Payıdar; Turna, Özge Yılmaz; Korkmaz, Ersin; Doğan, ErdemSon zamanlarda nüfus ve ekonomideki büyüme karayollarında araç kullanımını arttırmaktadır. Buna bağlı olarak kavşakların kapasitesi giderek yetersiz kalmaktadır. Kavşakların verimsiz çalışmasından dolayı gecikme, yakıt tüketimi, emisyon salınımı artarken sürücü davranışları da olumsuz etkilenmektedir. Optimum devre süresinin doğru tespiti ve sinyal sürelerinin düzenlenmesi ile bu sorunların minimuma indirilebilmesi mümkün olmaktadır. Bu çalışmada Yapay Arı Kolonisi Algoritması (YAKA) kullanılarak optimum devre süresi modelleri geliştirilmiştir. Ayrıca en düşük gecikmeye sahip olan devre sürelerinin belirlenmesinde Diferansiyel Gelişim Algoritmasından (DGA) yararlanılmıştır. Kalibre edilen Webster modeline ilave olarak üstel ve kuadratik formda modeller geliştirilmiştir. Geliştirilen bütün modeller Webster modelinden istatistiksel olarak daha iyi performansa sahip olurken, en iyi performansı da üstel model vermiştir. Bu modellerin özellikle yüksek trafik hacmine sahip trafik durumlarında yetersiz kalan Webster modelinin eksikliğini kapatarak alternatif bir devre süresi tahmin modeli olarak kullanılabileceği görülmüştür.Öğe Modelling Weekend Traffic With Weather Conditions Using Various Equation Type And Differential Evolution Algorithm(Scientific Research Center Ltd Belgrade, 2016) Dogan, Erdem; Akgungor, Ali Payidar; Korkmaz, ErsinIn weekends, amount of passenger car traffic is usually higher than weekday because of the activity-based traveling on some highways. Forecasting of this traffic, might help to local authorities to take safety precautions decisions on a road segments. This study aims to compose models to forecast weekend traffics using weather conditions and average weekday traffic variables. For this aim, two main models were composed: The Saturday traffic model and the Sunday traffic model. The Saturday traffic model variables are mean weekday daily traffic, maximum temperatures of Saturday and precipitations. The Sunday model is a linear model with only one variable: the predicted traffic values from the Saturday traffic model. In the modeling Saturday traffics, six-month (from January to June) data, which belongs to year 2015 and Ankara Kinkkale highway in Turkey, were used and 2014-March data were used for testing the models. The used temperatures were normalized and the precipitations data were involved as logical (0 or 1) inputs in models. To find best equation type for Saturday traffic model, four various equation forms were selected: (1) Linear, (2) polynomial-1, (3) polynomial-2, (4) multiplicative equation from. The linear and polynomial-1 have three, multiplicative has four, and polynomial -2 equation has five coefficients need to be determinate. Differential evolution algorithm was utilized to determinate best fitted values for these coefficients. Performance of the models were calculated using mean square error and coefficient of determination. The model with the polynomial-2 equation has minimum errors for the modelling stage and R-2 value is around 0.80. The model with the polynomial-2 showed the best performance on testing stage (R-2=0.96). These results show that the weekend traffic is related to weather conditions and it can be modeled convenient equation form and differential evolution algorithm.Öğe Optimizing of phase plan, sequence and signal timing based on flower pollination algorithm for signalized intersections(SPRINGER, 2020) Korkmaz, Ersin; Akgungor, Ali PayidarThe purpose of this study is to develop a control system that optimizes the phase plan, sequence and signal timing using the flower pollination algorithm (FPA). At the same time, it is aimed to improve the fixed-time control system with the optimum cycle length search approach based on the differential evolution algorithm. The applicability and performances of these two control systems were examined in 15 different traffic situations according to 4 different intersection geometries. Fixed-time and optimized fuzzy logic traffic controller (FLC) developed by Dogan were used as the reference control systems in performance comparison. The optimum cycle length search system can achieve approximately 18% improvement over the fixed-time system, but showed lower performance than the FPA and FLC control systems. The FPA system has proven its applicability by achieving the best performance with about a 30% improvement compared to the fixed-time system and about 3% improvement compared to the FLC system. The FPA approach, which has a fast and effective performance, has been found to be an alternative method for intersection control, and it is foreseen that it can increase the intersection capacity and reduce the negative effects such as delay and fuel consumption.Öğe Optimum cycle length models using atom search optimization and grasshopper optimization algorithms(Wiley, 2022) Korkmaz, Ersin; Akgungor, Ali PayidarA fixed-time traffic control system is widely used to manage the traffic flow at intersections. Cycle length has an important effect on the performance of the fixed-time control system and the Webster model is widely used in the literature to determine the cycle length. However, when the traffic flow ratio (Y) approaches 1, the Webster model loses its effectiveness and cannot determine the cycle length when Y is above 1. In the scope of this study, it is aimed to develop models that can predict cycle length for all traffic conditions in which are Y <= 1 and Y >= 1. Two different heuristic algorithms, atom search optimization (ASO) and grasshopper optimization algorithm (GOA) were used in the development of models and the performances of these algorithms were demonstrated. The efficiency of the developed models has been demonstrated by comparing them with both Webster's model and VISTRO optimization program. Models developed in exponential, power, and quadratic forms have been able to predict cycle lengths with lower delay values by showing better performance than Webster and VISTRO. In addition, statistical results show that the ASO approach is more successful than the GOA approach.
