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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]