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Dünya’da ve Türkiye’de trafiğe çıkan araç sayısı gün geçtikçe artmaktadır. Bu durum doğal olarak trafikte oluşan araç yoğunluğunun giderek artmasına ve yolculuklarda önemli gecikmelere sebebiyet verebilmektedir. Birçok insanın günlük hayatını etkileyen bu sorun, özellikle nüfus yoğunluğunun fazla olduğu şehirlerde kendini daha net göstermektedir. Şehiriçi trafikte oluşan yoğunluğun çeşitli sebeplerinin olmasının yanı sıra, trafikte araç sürücülerinin şerit seçim ve kullanım tercihleri de oluşan yoğunluk üzerinde önemli olumsuz bir etkiye sahip olabilmektedir. Sürücülerin yollarda en sol şerit daha hızlı hareket eder düşüncesi ile o şeridi daha çok kullanma arzusu içerisinde olması, tek bir şeritte yığılma oluşmasına neden olabilmektedir. Çalışmada, akıllı ulaşım sistemleri yardımıyla çok şeritli şehiriçi yollarda şerit kullanım yoğunluklarının tespitinin yapılmasını amaçlayan yenilikçi bir akıllı sistem öneri tasarımı sunulmuştur. Önerilen sistem üzerinde etkili olan faktörlerin belirlenmesi amacıyla SWOT analizi yapılmıştır. SWOT analizi ile belirlenen faktörler, beş kişilik bir uzman ekibin değerlendirmeleri ile analitik hiyerarşi prosesi (AHP) yöntemi kullanılarak ağırlıklandırılmıştır. Uygulanan A’WOT analizinden elde edilen sonuçlara göre sistemin en güçlü yönünün önerilen bu sistemden arzulanan doğru şerit kullanımı ile trafikte tıkanıklığın azaltılması olduğu görülmüştür. Önerilen sistemin çıkış noktası olan bu faktörün ön plana çıkması, çalışmanın temel amacını desteklemiş ve bu tür yenilikçi sistemlere ihtiyaç olduğunu net şekilde ortaya koymuştur.

In the current literature, it is clearly seen that most of the traffic chaos is generally observed at intersections of the urban roads in cities. On the other hand, many current traffic studies and research prove that fixed-time signalized intersections cannot have a good ability to control and manage current traffic flow at signalized intersection legs. For this aim, intelligent intersections were developed and started to be used in many cities all over the world in the last decade. These new intelligent intersection systems suggest dynamic signal times for all intersection legs by using real-time measured traffic data. These systems generally use cameras or loop detectors, which are located in the proper places on a signalized intersection leg and record vehicle movements. Within the scope of this study, a performance comparison was made for before and after the camera-based intelligent intersection applications at three isolated pilot signalized intersections within the scope of the "Smart City Traffic Safety" project, which is one of the largest Intelligent Transportation System projects in Turkey. After the system was activated, it was observed that the drivers had impatient behaviors in the beginning and had difficulty getting used to these new systems. After the signal cycle was regulated with the learning of artificial intelligence, it was seen that the drivers had more patience and more observant behaviors. It was also obtained from the analysis results that these new intelligent systems resulted in an average 16% decrease in control delays and a 20% decrease in vehicle speeds.

Current capacity manuals do not allow comprehensively evaluating negative effects on lane capacity caused by undisciplined vehicle movements and lane utilization, such as failure to obey distance rules, lane blockage caused by roadside parking effect, formation of an extra lane using in the emergency lane, etc., which are mostly observed in undeveloped and developing countries. Irregularities of the traffic flow caused by undisciplined movements and lane utilization result in decreased capacity or traffic change on the urban lanes. To overcome this problem, a lane-based study was carried out to determine the relation among effective parameters and their effect on lane capacity. In order to model the impact of these parameters, a comprehensive study was conducted in two cities in Turkey. Two different methods (statistical analysis and metaheuristic search algorithm) were used for this purpose and new more reasonable lane capacity estimation models (ALLCEM-1 and ALLCEM-2) were developed by examining all local conditions. The results proved that both examined methods are effective in modelling lane capacity of signalized intersections. It was also found that such parameters as the type of intersection (either a roundabout or not), effective green time, saturation flow rate, traffic volume, heavy vehicle ratio, and the number of actively used lanes have a major impact on the accuracy of prediction of road capacity.

In undeveloped and developing countries, maternal mortality is an important problem in public health. High maternal deaths observed in some regions of Turkey are related to inequities in reaching health services (low transport facilities). To prevent maternal mortality, pregnant women should have access to health services for professional care before, during, and after childbirth. In Turkey, most maternal deaths are related to socio-economic factors, equity issues, health services and transportation facilities. Especially, transportation facilities to health centers play an important role in preventing maternal deaths. Thus, to prevent the negative effect of the winter season and adverse transportation facilities on maternal mortality, the Turkey Ministry of Health (MoH), aiming to reduce the maternal mortality ratio (MMR) in rural areas, initiated the “Guest Motherhood Project (GMP)” to cover all of its urban and rural areas. In this project, health services for pregnant women in risky regions were restructured. In the scope of the project, access problems to health centers were eliminated and rapid access to rural areas and challenging territories of Turkey were provided. Current maternal mortality statistics show that GMP is yielding good results and high quality delivery services at all health centers in every region of the country despite the regional disparities.

Pavement surface deformations have a significant effect on speed profile of vehicles and traffic flow conditions. These deformations limit driving properties and increase vehicle operation and maintenance costs. Additionally, they cause many problems such as accidents, slower movement speeds, capacity loss and severe discomfort states. There are many factors having an effect on road capacities and they vary according to different road and traffic flow conditions. In this study, it is aimed to investigate and develop models to estimate shockwave and bottleneck forming, capacity loss and speed reduction, which occurred on examined road links caused by pavement deformations. For the prediction of road capacity, flow–density (q–k) relationship, bottleneck and shockwave analysis methods were used. In the scope this study, deformed road links were divided into three sections; Section A – before deformation zone, Section B – deformation zone, and Section C – after deformation zone. All three sections were investigated and empirical results were obtained. According to analysis results, it was found that pavement surface deformations have a negative effect on the level of road service capability. Obtained results also showed that there are significant reductions in capacity relatively by up to 44 and 26% would result from surface deformations on deformed lanes and non-deformed adjacent lanes.

Accident prevention is relatively a complex issue considering the effectiveness of the injury prevention technologies as well as more detailed assessment of the complex interactions between the road condition, vehicle and human factor. For many years, highway agencies and vehicle manufacturers showed great efforts to reduce the injuries resulting from the vehicle crashes. Many researchers used a broad range of methods to evaluate the impact of several factors on traffic accidents and injuries. Recent developments lead up to capable for determining the effects of these factors. According to World Health Organization (WHO), cyclists and pedestrians comprise respectively 1.6% and 16.3% in traffic crash fatalities in 2013. Also in Turkey crash fatalities for pedestrian and cyclists are respectively 20.6% and 3% according to Turkish Statistical Instıtute data in 2013. The relationship between cycling and pedestrian rates and injury rates over time is also unknown. This paper aims to predict the crash severity with the traffic injury data of the Konya City in Turkey by implementing the Artificial Neural Networks (ANN), Regression Trees (RT) and Multiple Linear Regression modelling (MLRM) method.

Container traffic forecasting is important for the operations and the design steps of a seaport facility. In this study, performances of the novel soft computing models were compared for the container traffic forecasting of principal Turkish seaports (Istanbul, Izmir, and Mersin seaports) with excessive container traffic. Four forecasting models were implemented based on Artificial Neural Network with Artificial Bee Colony and Levenberg-Marquardt Algorithms (ANN-ABC and ANN-LM), Multiple Nonlinear Regression with Genetic Algorithm (MNR-GA), and Least Square Support Vector Machine (LSSVM). Forecasts were carried out by using the past records of the gross domestic product, exports, and population of the Turkey as indicators of socioeconomic and demographic status. Performances of the forecasting models were evaluated with several performance metrics. Considering the testing period, the LSSVM, ANN-ABC, and ANN-LM models performed better than the MNR-GA model considering overall fitting and prediction performances of the extreme values in the testing data. The LSSVM model was found to be more reliable compared to the ANN models. Forecasting part of the study suggested that container traffic of the seaports will be increased up to 60%, 67%, and 95% at the 2023 for the Izmir, Mersin, and Istanbul seaports considering official growth scenarios of Turkey.

Various road surface deformations generally occur on urban and rural roads due to infrastructure, superstructure deficiencies and excessive heavy vehicle loads. In addition to driver-based errors, many accidents happen due to these mentioned surface deformations. This study aims to present lateral lane utilization and longitudinal driving behaviours on a two-lane deformed road. The effect of deformation on the tendency of drivers’ lane selection, lane utilization, and the movement in traffic flow will also be determined. For this purpose, parameters such as lateral position, speed, acceleration/deceleration and location data of vehicles travelling through four different deformation zones on a two-lane road in Izmir (Turkey), were collected. Based on the fact that in ideal conditions, distribution of lateral positions of vehicles in a lane is similar to normal distribution. The collected data was evaluated with chi-square (χ2) goodness of fit test to see if they are fit to normal distribution or not. This study concluded that if a deformation zone has wider area and less depth, it will be less effective on lateral lane utilization of vehicles. It was also obtained from the results that variation in other parameters such as deformation type, depth and height are associated with the lateral lane utilization of drivers. Additionally, the drivers’ characteristics such as perception and aggressiveness are seen as the most important factors influencing the longitudinal vehicle behaviours while passing through the deformation zones.

Urban and rural roads are opened to service after the application of road surface markings in Turkey. However, visibility of these roads reduce or disappear caused by the disrepair in a short time after the construction. These road surface markings have a mission to be a visual guide on behavior of lane utilization of drivers. For this reason, it has crucial importance to prevent traffic accidents. Unfortunately, the necessary importance to road surface markings are not given by the authorities in urban and rural roads of Turkey. Generally, standard road marking paint are used in all roads because of its low price and it loses retroreflectivity performance after short time. As a result of this situation chaos, lane indiscipline and many traffic accidents occur in urban and rural roads. Whereas, many different road painting materials are used such as Epoxy, Methyl Methacrylate, Polyester, Thermoplastic, Polyurea etc. to obtain higher performance and resistance according to different road characteristics and environmental conditions. In the scope of this study, a general information were given about the utilization of different surface marking materials which is used in developed countries effectively. Additionally, a number of recommendations and guidance notes have been provided for road makers and decision authorities wishing to use these materials in Turkey.