Cluster-based analysis and time-series prediction model for reducing the number of traffic accidents
Traffic is a complex system, in terms of functioning as well as organization. Traffic stop, i.e. failure to perform the required transport function from point A into point B, can be caused by variety of circumstances, and one of them is the occurrence of traffic accident. Therefore, it is of a great importance to pay attention to increasing the traffic safety level throughout the implementation of various measures. Traffic safety is one of the most important links of the traffic system. This paper analyzes in details the impact of the road and its environment, vehicles and drivers on traffic accidents. The model of classification of traffic accidents causes has been implemented on the basis of similarities of drivers, vehicles and road characteristics. k-means clustering algorithm has been used for this purpose. According to data available, time-series prediction model has been implemented in the second part of the work, for prediction of traffic accidents in analyzes regions. Results in both implemented cases are more than satisfactory.