Author:
KOLISKOVA PETRA,NEUBAUER JIRI
Abstract
Traffic accidents remain a topical safety issue. The aim of this article is to use the statistical apparatus to describe a random variable, the daily number of accidents, and to model it. The data on traffic accidents for the period 2012–2021, including time and location information, came from the database of the Fire Rescue Service of the Czech Republic. The study utilised an analysis of variance for statistical analysis with a count variable, following a Poisson distribution. One-factor and two-factor analyses are used to describe the dependence of the daily number of accidents involving the deployment of the fire rescue service on the day of the week, and month. The use of generalised linear model for count data to analyse the number of traffic accidents is unique in the Czech Republic.
Reference15 articles.
1. Bačkalić, S.: Temporal analysis of the traffic accidents occurrence in province of Vojvodina. Transport Problems. 2013. 8. 87-93.
2. Cerna Ñahuis, S., Guyeux, C., H. Arcolezi, H., Couturier, R., Royer, G., Lotufo, A.: Long Short-Term Memory for Predicting Firemen Interventions. 2019. 1132-1137. 10.1109/CoDIT.201 9.882067
3. Cerna Ñahuis, S., Guyeux, C., H. Arcolezi, H., Couturier, R., Royer, G.: A Comparison of LSTM and XGBoost for Predicting Firemen Interventions. 2020. 10.1007/978-3-030-45691-7\_39.
4. Devore, J. L.: Probability and Statistics for Engineering and the Sciences. 8th ed. Boston: Brooks/Cole. 2012.
5. Dobson, A.: An Introduction to Generalized Linear Models. London: Chapman & Hall. 2008.