A data-driven study of road traffic accidents in Albania: Nonlinear regression applications in the transportation system

A significant unanticipated issue for the study of transport systems is the occurrence of road traffic accidents, resulting in the number of cases, injuries, and fatalities. The Albanian transport system has suffered from negligence and a lack of investment. Consequently, road traffic accidents have increased while current efforts to improve road safety remain minimal compared to the growing traffic volume. The research aims to provide an overview of road traffic accident statistics in Albania using data from 2015 to 2024, offering insights into the current situation and future projections. Furthermore, three key attributes—road traffic accidents, population projections, and the number of registered vehicles during the study period—have been considered in developing a nonlinear road accident prediction model. The data on road traffic accidents, in terms of the total number of road traffic cases (C), road traffic fatalities (F), and road traffic injuries (I), were used from road traffic accidents in Albania as dependent variables. The Andreassen model has been adapted to develop a regression model suitable for Albania's data, where population projections and the number of registered vehicles are taken as independent variables. Moreover, this paper aims to model the evolution of road safety as a function of the level of motorization and population projections, emphasizing that the increase in the number of vehicles leads to a decrease in the number of traffic fatalities, and an increase in the number of accident cases, as well as in the number of injured per vehicle. The study results allow planners to estimate future road traffic accidents in the country.

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Publication Details

Journal
Edelweiss Applied Science and Technology
Published
2025-05-15
DOI
https://doi.org/10.55214/25768484.v9i5.7215
Citations
1
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.11
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article

A data-driven study of road traffic accidents in Albania: Nonlinear regression applications in the transportation system

Homan Emadifar, Raimonda Dervishi, Zhifka Muka Meco, Agbata Benedict Celestine et al.
1 citations
Edelweiss Applied Science and Technology
Forecasting Techniques and Applications
2.11
article

A data-driven study of road traffic accidents in Albania: Nonlinear regression applications in the transportation system

Homan Emadifar, Raimonda Dervishi, Zhifka Muka Meco, Agbata Benedict Celestine, Sander Kovaci, Marin Malotaj
article en
1 citations

Abstract

A significant unanticipated issue for the study of transport systems is the occurrence of road traffic accidents, resulting in the number of cases, injuries, and fatalities. The Albanian transport system has suffered from negligence and a lack of investment. Consequently, road traffic accidents have increased while current efforts to improve road safety remain minimal compared to the growing traffic volume. The research aims to provide an overview of road traffic accident statistics in Albania using data from 2015 to 2024, offering insights into the current situation and future projections. Furthermore, three key attributes—road traffic accidents, population projections, and the number of registered vehicles during the study period—have been considered in developing a nonlinear road accident prediction model. The data on road traffic accidents, in terms of the total number of road traffic cases (C), road traffic fatalities (F), and road traffic injuries (I), were used from road traffic accidents in Albania as dependent variables. The Andreassen model has been adapted to develop a regression model suitable for Albania's data, where population projections and the number of registered vehicles are taken as independent variables. Moreover, this paper aims to model the evolution of road safety as a function of the level of motorization and population projections, emphasizing that the increase in the number of vehicles leads to a decrease in the number of traffic fatalities, and an increase in the number of accident cases, as well as in the number of injured per vehicle. The study results allow planners to estimate future road traffic accidents in the country.

Edelweiss Applied Science and TechnologyVol. 9(5)
Polytechnic University of Tirana (AL)
Openalex Percentile: Top 14%
Forecasting Techniques and Applications
2.11
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