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Time-series analysis as tool for evaluation of traffic safety
Krivec, David ; Bensa, Bruno ; Pavčič, Tomaž
In this research project modelling of traffic accident consequences was performed. The goal of the research project was to establish a model for forecasting of road accident injuries and fatalities ...by use of available data basis. ARIMA models were identified as the most appropriate for the accomplishment of the set goals. These models represent advanced and fine tuned analytical tools for time series analysis. Monthly data showing the number of fatalities and severe injuries in road traffic accidents in Slovenia for the years from 1994 to 2004 were used. The data structure shows a strong seasonal component with a period of twelve months that stressed the importance of implementing seasonal ARIMA modelling. The model was constructed to provide all relevant information about the analyzed time series. The process of modelling includes identification of the model, its estimation, diagnosis and a short-term forecast. New traffic legislation entered into force during the observed period. That event represents a strong and unique external influence - a change in the system. The influence was accurately analyzed with intervention analysis and included in the model. This model was then used to produce a short-term aggregate forecast for fatalities and severely injured persons involved in traffic accidents. The elaborated model gives us the possibility to follow the actual course of events and to evaluate discrepancies with predicted values. In case of substantial discrepancies a search for reasons can be promptly triggered. It is expected that time-series analysis as tool for continuous evaluation of traffic safety will eventually enable extraction of the three E's (Education, Engineering, and Enforcement) impact in the road safety development in Slovenia.
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