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Öğe An application of modified Smeed, adapted Andreassen and artificial neural network accident models to three metropolitan cities of Turkey(Academic Journals, 2009) Akgüngör, Ali Payidar; Doğan, ErdemTraffic accident prediction models are used for transportation safety studies. This study proposes 2 analytical models and an artificial neural network (ANN) model to estimate the number of deaths resulted from traffic accidents in 3 metropolitan cities of Turkey utilizing historical data between 1986 and 2005. The first analytical model is a modified form of the Smeed accident prediction model and the second one is an adapted form of the Andreassen model. In the model development, population (P) and the number of vehicles (N) were taken as independent variables. In the ANN approach, the sigmoid and pureline functions were used as activation functions with feed forward-back propagation algorithm. The model estimations were compared against the observations and it was seen that the ANN model performed better than the other 2 analytical models.Öğe An artificial intelligent approach to traffic accident estimation: Model development and application(Vilnius Gediminas Tech Univ, 2009) Akgüngör, Ali Payidar; Doğan, ErdemThis study proposes an Artificial Neural Network (ANN) model and a Genetic Algorithm (GA) model to estimate the number of accidents (A), fatalities (F) and injuries (I) in Ankara, Turkey, utilizing the data obtained between 1986 and 2005. For model development, the number of vehicles (N), fatalities, injuries, accidents and population (P) were selected as model parameters. In the ANN model, the sigmoid and linear functions were used as activation functions with the feed forward-back propagation algorithm. In the GA approach, two forms of genetic algorithm models including a linear and an exponential form of mathematical expressions were developed. The results of the GA model showed that the exponential model form was suitable to estimate the number of accidents and fatalities while the linear form was the most appropriate for predicting the number of injuries. The best fit model with the lowest mean absolute errors (MAE) between the observed and estimated values is selected for future estimations. The comparison of the model results indicated that the performance of the ANN model was better than that of the GA model. To investigate the performance of the ANN model for future estimations, a fifteen year period from 2006 to 2020 with two possible scenarios was employed. In the first scenario, the annual average growth rates of population and the number of vehicles are assumed to be 2.0 % and 7.5%, respectively. In the second scenario, the average number of vehicles per capita is assumed to reach 0.60, which represents approximately two and a half-fold increase in fifteen years. The results obtained from both scenarios reveal the suitability of the current methods for road safety applications.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 Estimating road accidents of Turkey based on regression analysis and artificial neural network approach(2008) Akgüngör, Ali Payidar; Doğan, ErdemThis study proposes two new analytical models and an Artificial Neural Network (ANN) model to estimate the number of accidents, injuries and fatalities in Turkey utilizing historical data between 1986 and 2005. The data between the years 1986 and 2000 were used to develop the models and the rest of data (i.e., 2001-2005) were utilized for testing the developed models. The first of the analytical models is a modified form of the Smeed accident prediction model. The second one is an adapted form of the Andreassen model to Turkey. In the model development, the number of vehicles (N), fatalities (D), injuries (I), accidents (C), and population (P) were taken as model parameters. In the ANN model, the sigmoid and linear functions were used as activation functions with feed forward-back proportion algorithm. The model results were compared against the observations and it was found that the ANN model performed better than the other two analytical models. In order to investigate the performance of the models for future estimations, a fifteen year period from 2006 to 2020 was employed. Considering the fact that Turkey is likely to enter the European Union by 2020, road safety strategies were evaluated with two possible scenarios. In the first scenario, the annual average growth rates of the population and the number of vehicles are assumed to be 1.7% and 7.5% (average growth rates between 1986 and 2005) respectively. In the second scenario, the average number of vehicles per capita is assumed to reach 0.45 which represents a three-fold increase in fifteen years. The results obtained from both scenarios reveal the suitability of the current methods for the road safety applications.Öğe Evaluation of Ankara-Istanbul high speed train project(Vilnius Gediminas Tech Univ, 2007) Akgüngör, Ali Payidar; Demirel, AbdulmuttalipMany countries have been carrying out some changes in their transportation policies for the sake of environmental and economical considerations. These circumstances have also affected Turkey to change the national transportation policies. In this study, transportation policies of Turkey have been investigated and, in this context, an important railway project of Ankara - Istanbul line has been analyzed. In evaluation, the present condition of the rail line, high speed train project is compared in terms of market study, technological and economical point of views. Finally, conclusions and suggestions are presented.Öğe Farklı Yöntemler Kullanılarak Geli?tirilen Trafik Kaza Tahmin Modelleri ve Analizi(Kırıkkale Üniversitesi, 2010) Akgüngör, Ali Payidar; Doğan, ErdemBu çalışmada, regresyon analizi, yapay sinir ağları (YSA) ve genetik algoritma (GA) yöntemleri kullanılarak İzmir ili için trafik kaza tahmin modelleri geliştirilmiştir Modeller geliştirilirken nüfus, araç sayısı ve kaza sayısı model parametreleri olarak kullanılmış ve bu parametrelere ait 1986-2005 yılları arasındaki verilerden faydalanılmıştır. Regresyon analizi kullanılarak geliştirilen kaza modellerinde Smeed ve Andreassen kaza model formları kullanılmıştır. YSA modelinde 2-5-1 ağ mimarisi en uygun mimari olarak belirlenmiş, ağların gizli katmanında sigmoid, çıkış katmanında da doğrusal fonksiyon kullanılmıştır. Ağın eğitiminde ise ileri beslemeli geri yayılım algoritmasından yararlanılmıştır. GA tekniği ile modeller oluşturulurken farklı formdaki modeller denenmiş ancak bu çalışma için en başarılı modelin üstel model olduğu görülmüştür. Geliştirilen bütün modellerin performansları ortalama mutlak yüzde hata (OMYH) ortalama mutlak hata (OMH) ve ortalama karesel hataların karekökü (OKHK) ölçütleri içinde değerlendirilmiştir.Öğe Forecasting highway casualties under the effect of railway development policy in Turkey using artificial neural networks(Springer, 2013) Doğan, Erdem; Akgüngör, Ali PayidarThis study presents forecast of highway casualties in Turkey using nonlinear multiple regression (NLMR) and artificial neural network (ANN) approaches. Also, the effect of railway development on highway safety using ANN models was evaluated. Two separate NLMR and ANN models for forecasting the number of accidents (A) and injuries (I) were developed using 27 years of historical data (1980-2006). The first 23 years data were used for training, while the remaining data were utilized for testing. The model parameters include gross national product per capita (GNP-C), numbers of vehicles per thousand people (V-TP), and percentage of highways, railways, and airways usages (TSUP-H, TSUP-R, and TSUP-A, respectively). In the ANN models development, the sigmoid and linear activation functions were employed with feed-forward back propagation algorithm. The performances of the developed NLMR and ANN models were evaluated by means of error measurements including mean absolute percentage error (MAPE), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R (2)). ANN models were used for future estimates because NLMR models produced unreasonably decreasing projections. The number of road accidents and as well as injuries was forecasted until 2020 via different possible scenarios based on (1) taking TSUPs at their current trends with no change in the national transport policy at present, and (2) shifting passenger traffic from highway to railway at given percentages but leaving airway traffic with its current trend. The model results indicate that shifting passenger traffic from the highway system to railway system resulted in a significant decrease on highway casualties in Turkey.Öğe Investigating urban traffic based noise pollution in the city of Kirikkale, Turkey(Vilnius Gediminas Tech Univ, 2008) Akgüngör, Ali Payidar; Demirel, AbdulmuttalipThe study presents an investigation into traffic based noise pollution in the city of Kinkkale, Turkey. For this purpose, traffic noise levels were measured at 15 intersections across the city during three peak times - morning (08:00-09:00), noon (12:30-13:30) and evening (17:00-18:00) hours. The comparison of L-eq values against the limit values of the Turkish Noise and Control Regulations for Settlement Zones showed that L-eq values exceeded the limits at all stations. A linear regression analysis performed between the L-eq and logarithm of total traffic volume (log Q) produced a coefficient of determination of 0.52. A multi regression analysis carried out between the L-eq and four different vehicle types resulted in a correlation coefficient of 0.74. The correlation matrix indicated that the highest correlation was found for trucks/buses with r = 0.92. The spatial maps of traffic noise created by the Kriging method under ArcView GIS displayed that there seemed to be significant differences in the spatial variation of traffic noise across the city. In order to reduce traffic based noise levels within the city some useful suggestions were presented.Öğe A new delay parameter dependent on variable analysis periods at signalized intersections. Part 1: Model development(Vilnius Gediminas Tech Univ, 2008) Akgüngör, Ali PayidarDelay is an important factor in the optimization of traffic signals and the determination of the level of service of a signalized intersection. This paper proposes a methodology and a new formulation to identify the delay parameter in signalized intersection delay models. In this study, the delay parameter is modeled as a function of analysis period instead of a fixed value used by the existing delay models. Therefore, the proposed delay model including new delay parameter can produce more reasonable delay estimations at signalized intersections for variable time periods. A comparative study of the proposed time-dependent model against the existing four different models was performed to present the improvements in this model.Öğe A new delay parameter dependent on variable analysis periods at signalized intersections. Part 2: Validation and application(Vilnius Gediminas Tech Univ, 2008) Akgüngör, Ali PayidarThe main objective of the present study is to investigate the performance of the proposed model in Part I for variable demand, time and oversaturated conditions. To accomplish this objective and test the proposed model, an experimental study was performed. The proposed delay model for oversaturated traffic conditions was calibrated and verified by the TRAF-NETSIM microscopic simulation program. In the calibration and verification of the proposed model, the simulation study was performed to produce various traffic and time conditions using 48 different scenarios. The delays obtained from the simulations and the proposed model were statistically compared using linear regression analysis. The results indicated that there was a good relationship R-2 = 0.989 at 95% confidence level between the delays generated by the simulations and the delays estimated by the proposed model.Öğe Road traffic accidents and safety programme in Turkey(2007) Akgüngör, Ali Payidar[No abstract available]
