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Double parking has many negative effects on traffic indicators such as traffic congestion, traffic flow conditions, and traffic safety. Double parking includes parameters that affect drivers' behavioral and traffic habits. Various inspection activities and penal sanctions are implemented to prevent parking violations. Within the scope of this study, it is aimed to detect double parking with the YOLOv8 model, one of the deep learning algorithms. In this direction, a data set consisting of a total of 891 images was created, taking into account the streets with high traffic density in İzmit and Erzurum. As a result of the YOLO model, the measurement parameter F1 score value was obtained as 0.83. The mAP@0.5 values of the model for double parking, normal parking and the entire data set were obtained as 0.851, 0.922 and 0.886, respectively. When other performance parameters were examined, it was concluded that the model successfully detected the double parking situation. According to the model performance results, 89% of double and normal parking situations were detected correctly. A data set infrastructure has been created for studies on the detection of double parking. With this study, the initial work of the systems for automatic detection of parking violations and instant warning of drivers was carried out. [ABSTRACT FROM AUTHOR]

The increase in the number of vehicles brings parking needs in city centers. Many studies are being carried out to solve the problem and new parking lots are constructed. With the developing technology, smart systems are effectively used to increase the capacity of existing car parks. Unfortunately, both putting new car parks into service and equipping existing car parks with technological facilities cannot solve the problem. This highlights that public transportation is used effectively instead of vehicles. On the other hand, the idea of enabling people to reduce parking time is a partial solution. Thus, new smart parking mobile application called “Let's Share a Single Vehicle Park-TAPP was developed conceptually. In the system, utilization period must be specified by the user. Users who specify the duration of utilization are rewarded as a fee when they comply. If they do not, they are faced with overpayment and parking utilization restriction. The parking capacity will be planned instantly and an effective operating performance will be achieved. The factors affecting the proposed system were determined by SWOT analysis and the weighting of each factor using the AHP method was obtained by pairwise comparisons. With the A'WOT analysis, it has been determined that the increase in the need for parking spaces with the increase in the number of vehicles. The need for parking, which is the most important factor due to the increasing number of vehicles, shows the need for such innovative systems when all general factor weights of factors are evaluated together. [ABSTRACT FROM AUTHOR]

Topological structure and waiting times of vehicles at the intersection are shown as common causes of traffic congestion. Since the improvements in the topological structure can be realized as a result of long and costly projects, intersection signaling applications become an indispensable application area of smart cities. In intersection signaling applications, phase sequence and duration are calculated to ensure the maximum flow of vehicles per unit time, on the basis of intersection or throughout the network. Junction signaling optimization is a real-time realworld problem that is affected by many variable data. Therefore, many studies are still being carried out to develop the most efficient signaling method. In this study, an approach that optimizes the order and duration of the green phase is proposed to reduce the waiting times at the junction points across the network. This approach has been developed by transferring real-time vehicle data to the SUMO simulator according to the exact scale of city intersections on the real-world map. A new signaling approach named GDRL is proposed by combining graphbased phase duration and Deep Reinforcement Learning-based phase sequence estimation. In this approach, the phase sequence is calculated by the DRL method. The phase duration is calculated based on the maximum flowfinding method of the Ford-Fulkerson algorithm. The GDRL approach has been tested in the SUMO simulator by running parallel on consecutive intersections on the real map and using real data. It has been observed that the GDRL approach efficiently solves traffic congestion by reducing the queue length at intersections by 44%. [ABSTRACT FROM AUTHOR]

One of the problems that emerged in rapidly growing cities is urban transport. Besides traffic congestion, this problem is a threat to the sustainability of the environment and urban mobility. Due to the incapability of traditional urban transport plans, they started to be replaced by Sustainable Urban Mobility Plans (SUMP). This study mentions the new emerging planning approach, reveals the theoretical framework of the subject; then, discusses the current situation of urban transport planning in Turkey. The study analyses the objectives of the Istanbul SUMP, the first plan implemented in Turkey, through MAXQDA software in terms of essential features of the SUMP approach. As a result of the study, indications about level of meeting the requirements of the SUMP approach of Istanbul SUMP were obtained. [ABSTRACT FROM AUTHOR]

Micromobility systems became very popular in Turkey as well as in many parts of the world in recent years. The main reasons for the increase in the popularity of micromobility systems are the increasing vehicle sharing systems, being an economical alternative especially in short distances defined as the last kilometer or last mile, being adversely affected by traffic jams at the lowest level and the perception of these systems being environmentally friendly. However, the extent to which these thoughts or perceptions reflect reality is an issue that should be carefully considered. Micromobility systems are modes of transportation that have become very popular, largely among youngsters as they have an enjoyable use. However, ther are alternatives that have low security, can not offer solutions to traffic jams, and have adverse effects on the environment, contrary to the general public perception. However, they offer an important and positive transportation alternative when used as a complementary mode of transportation in the last kilometer instead of motor vehicles. On the other hand, comprehensive studies such as social benefit/cost analyzes should be carried out to determine the effectiveness of micromobility systems, and important legal regulations should be made regarding the use of these systems. [ABSTRACT FROM AUTHOR]

While the industries grow and develop, people are starting to move from rural to city. Due to this, cities also grew significantly and caused the developments of labor cities. When this happened, laborers started living in a concrete pile, and started to ask for a relaxing and a safe environment in the city but away from the traffic jam. In order to be able to create a liveable environment, firstly some social and economic conditions must be provided, such as; safety, comfort, publicity and heritability. That is why pedestrianization has been started in the residential areas and downtowns. The first samples can be seen in Europe during the 1940s, North America during the 1960s and we can see the first tries of this system in our country in 1978 in Ankara. With Holland's and West Germany's lead, other developed countries like France, USA, England, Switzerland, Australia, and Italy started using this system in their streets. The only reason for this system is to protect the historical city shapes, after a day long engine traffic, and even the businesses are closed, people will still be able to have a place to walk at night in peace. Even though Cambridge dictionary defines pedestrianization as "turning the place to somewhere that cars cannot enter", places cannot be pedestrianized by purifying it. Although complete pedestrianization is not possible in the real world, public transportation is crossed with adequate and effective growth of pedestrian infrastructure and nonengine infrastructure. [ABSTRACT FROM AUTHOR]

Today traffic congestion is one of the most important problems that adversely affect human life in many aspects. Traffic congestion is experienced during the morning and evening peak hours which have the highest traffic intensity. The main reason of the traffic congestion during the peak hours is that the work start and finish times of the firms in both private and public sectors are very close. Spreading the travel demand during peak hours for longer time period is a means to reduce the traffic congestion during the peak hours. The staggered working hours is one of the methods used for this purpose. In this study, a mathematical model is proposed to reduce the traffic congestion by using the staggered working hours strategy. The aim of the model is to find the working hours of the each destination node by considering the travel demands between origin-destination nodes, the paths and the capacities of the roads. A 0-1 integer goal programming model is developed for this purpose. The developed model is solved for different sized data sets. The results show that the staggered working hours strategy will significantly reduce the peak hours traffic congestion. [ABSTRACT FROM AUTHOR]

The traffic congestion has been reach to a critical level in the metropolitan cities, however; the local governments have developed various solution methods against this problem. The most effective solution among these methods is traffic congestion pricing. The local governments of the cities of London, Stockholm and Milan have successfully implemented the congestion pricing method. In this study, the solution of the congestion pricing solution in Erzurum Cumhuriyet Street, which is not applied before, has been examined for this problem. According to both the model created and the survey carried out, in the along the cordon route determined at Cumhuriyet Street, account of theoretical congestion pricing has been made. In the modeling study; car ownership, travel time, fuel consumption and emission costs have been used. As a result, it is foreseen that traffic congestion will decrease in the city center and a significant financial income will be obtained with the application of pricing. [ABSTRACT FROM AUTHOR]

Traffic accidents cause fatality, injury and property damage, as well as traffic congestion, road safety, noise, air pollution, and so on. According to Global Status Report on Road Safety published by World Health Organization (WHO) in 2015, deaths after traffic injuries are predicted to become the seventh leading cause of death by 2030. Besides, economic losses are occurred in large quantities in the developing economies like our country, due to traffic accidents. Various precautions are taken to reduce traffic accidents, such as increasing the number of traffic controls, eliminating road-related defects, increasing the frequency of vehicle inspections, and developing accident prevention mechanisms. In order to reduce the severity and the number of accidents, it has importance to identify and improve the zones called accident black spots where traffic accidents have occurred frequently. In this study, it is aimed to determine accident black spots by using Geographical Information Systems (GIS) and network screening methods and reveal the positive and negative aspects of these methods. For this purpose, the intersections and road segments at İstanbul D100 highway were sorted separately using simple ranking, sliding window and peak searching methods and accident black spots are determined using the K-means clustering method. [ABSTRACT FROM AUTHOR]

Congestion is one of the major problems of metropolitan cities. This problem arises when the increase in demand for travelling with private vehicles surpasses the capacity of the road network. Travel demand management strategies are developed to restrict the excessive demand without making expensive infrastructure investments. Demand management strategies can be classified in two main groups: Fiscal and non-fiscal strategies. Fiscal strategies are implemented to regulate the demand by arranging taxes or tariffs collected for the usage of the transportation infrastructure or facilities. Non-fiscal strategies aim to adjust the demand for private vehicle usage without imposing any financial measures on individuals. Congestion pricing is one of the most powerful fiscal strategies. By definition, congestion pricing is collecting fixed or variable amount of tolls from private vehicle users for the usage of a road or a road network. For variable toll implementations, the amount can be determined according to units such as distance covered or congestion level of the facility. Any driver considering entering a congested road will base his/her decision solely on the costs he/she is going to bear. However, entering an already congested road will impose external costs on other drivers currently on the road, as well. The last vehicle entering an already congested road will increase not only the travel times but also the fuel consumption and emissions of all other vehicles. In the case when natural equilibrium occurs, although abovementioned costs already exist, none of the users are paying the price of creating them. In order to make the users pay the price of the external costs they create, marginal cost pricing is implemented. The price collected by marginal cost pricing implementations is named the optimum price and its value is equal to the external costs that users create. Congestion pricing can be modelled by using two different modelling approaches: Timeindependent static models and time-dependent dynamic models. Time-independent static models deliberately ignore the hourly changes in the traffic parameters and accept an unchanged relationship between parameters of traffic throughout the analysis. On the contrary, time-dependent dynamic models include the time dimension to the analysis and model the implementation with regard to departure time, as well as route choice. The origins of dynamic models is the bottleneck model which is originally developed by Nobel Prize winner researcher William Vickrey. In this study, a congestion pricing scheme is modelled for Eminonu, in order to evaluate the applicability of congestion pricing to Istanbul. Among all the districts of Istanbul, Eminonu have unique properties. First of all, the district which is a peninsula has clearly defined borders, easing the access control issues. Moreover, due to the small surface area of Eminonu, the road network is relatively small and less complicated. As the host of many historic, recreational and governmental areas, severe congestion is routinely experienced on the road network of the district. The focal point of the modelling studies for Eminonu is the determination of optimum price which is calculated according to the principles of the static models of congestion pricing. Analysis of the equilibrium conditions is made possible by obtaining, average cost, marginal cost and demand curves representing the whole district. In practice, marginal cost pricing may sometimes be ignored or not preferred to be implemented by decision makers. Thus, an evaluation of other pricing regimes different than optimum price is also included in the study. Furthermore, the gains, losses and related measurable economic quantities for the individuals are also calculated. The optimum price is calculated as 0.58 TL/km. It is expected to record a decrease close to 16% in the usage of private vehicles by collecting this toll. Maximum revenue can be generated by collecting a toll of 5.042 TL/km which reduces the number of private vehicle users more than 76%.Futhermore by deploying the average travelling distance of 5.32 km in Eminonu road network, per km prices can be converted into constant prices. Consequently, the optimum price is equal to 3.09 TL in constant values. This study provides valuable information for the applicability of congestion pricing to Istanbul. Obviously, when a congestion pricing scheme is introduced significant amount of individuals will start to travel without their private vehicles and considerable amount of money will be collected In order to secure sustainability and acceptability of the scheme, the revenue collected from the individuals must be returned to the system in favour of users who are worse-off by congestion pricing. [ABSTRACT FROM AUTHOR]