Work

Traffic safety, sustainable mobility and human rights: data-driven analysis of traffic accidents in Serbia

Year: 2026

Type: article

Abstract: Objectives This paper presents the application of data mining methods in the analysis of traffic accidents in the Republic of Serbia during the period 2022–2025, based on the open dataset available through the Open Data Portal of the Republic of Serbia. The aim of the study is to examine the extent to which spatial, temporal, and structural attributes enable the differentiation between accidents involving material damage only and accidents involving injured or deceased persons. Material and methods The analysis was conducted in the Weka environment using the J48, Random Forest, Naive Bayes, kNN, and Logistic algorithms, with evaluation based on Accuracy, Precision, Recall, F1-score, and ROC AUC measures. Results The results indicate that the Logistic algorithm achieved the best overall performance, while Naive Bayes demonstrated the highest recall for the class of accidents involving injured or deceased persons. Conclusions The results indicate that the Logistic algorithm achieved the best overall performance, while Naive Bayes demonstrated the highest recall for the class of accidents involving injured or deceased persons.

Source: Journal of Modern Science

DOI: 10.13166/jms/241829

Authors: Dragana Radosavljević, Aleksandra Petrovic, Vladimir Maksimović, Iwona Barbara Florek

Institutions: University of Priština - Kosovska Mitrovica, University of Prishtina, Alcide De Gasperi University of Euroregional Economy in Józefów

Language: English

Topic: Traffic and Road Safety

Subfield: Safety, Risk, Reliability and Quality

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Good health and well-being

Open Access status: gold

Estimated APC paid: $183