Zaman Serisi Modelleri ile Trafik Kazası Sayılarının Tahmin Edilmesi: Forecasting Traffic Accident Numbers Using Time Series Models

Serhat TOPUZ; Hakan Murat ARSLAN

Authors

Serhat TOPUZ
Hakan Murat ARSLAN düzce üniversitesi

Keywords:

Time Series Models, Traffic Accident Numbers, ARIMA Model

Abstract

This study aims to forecast the number of traffic accidents that may occur in the jurisdiction of the Gendarmerie in the Western Black Sea Region using time series models. Statistical data from April 2019 to December 2023 obtained from the official website of the General Command of Gendarmerie have been utilized. This data includes traffic accidents occurring in the provinces of Bartın, Bolu, Düzce, Karabük, Kastamonu, Sinop, and Zonguldak. The Autoregressive Integrated Moving Average (ARIMA) method has been employed to predict future accident numbers. In this context, data analyses and modeling have been conducted using Minitab and EViews software. The results of the study are supported by trend analysis, seasonality analysis, and forecasting models. According to the findings, predicting the number of traffic accidents will contribute to more informed and effective decision-making by managers in personnel allocation and economic planning. Furthermore, the forecast results obtained will assist in taking necessary measures to prevent traffic accidents, which are significant for public health and the state economy, in future similar studies relevant to academic and public institutions.

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Forecasting Traffic Accident Numbers Using Time Series Models