عنوان مقاله [English]
These days, traffic is one of the biggest problems in metropolitan life. The heavy traffic, besides many problems for citizens, causes waste of resources such as energy and fuel. Many factors affect traffic in Tehran. Identification of these factors and their impact on traffic flow can help urban managers to prioritize and allocate resources to address their effects. The purpose of this study is to investigate the effect of two factors of driving accidents and atmospheric conditions on traffic congestion in the metropolitan Tehran and to model and predict the traffic length caused by these factors in different situations. The data of this research has been collected through the investigation of the database of the traffic control center of Tehran. For this purpose, firstly, statistical analysis and pre-processing operations have been performed on the data. Then, by using data mining methods such as clustering, classification, and categorization through the decision tree, two models for the effect of accidents and atmospheric conditions in different regions of Tehran have been obtained. Finally, the rules for each model are extracted. The results show that about 4% of traffic was caused by accidents and 1% due to atmospheric conditions. According to statistical analysis of linear regression, it is determined that the traffic length due to accident is a function of the accident severity, the area of the municipality of the accident site, and the
number of involved equipment, while it doesn't have the effect of a typical day or holiday. Also, the traffic length caused by atmospheric conditions depends on the area of the municipality, the atmospheric conditions, and the day type of typical day or the holiday. The results show that the maximum length of traffic is related to the crashes with two vehicles involved in the accident or in rainy weather. It is also found that according to the results and extracted rules, the maximum traffic length in both models is 200-500 meters.