Time Horizon for Forecasting the Number of Traffic Accidents

On Polish roads, there are more and more automobiles each year. This results in more people using the roadways. Because of this, the threat posed by traffic accidents, which involve the loss of human life and financial resources, is quickly expanding. The rise of motorization and the quickening expansion of the human population are to blame for this. The tiny amount of the dataset that may be utilized for research in this respect is the major problem in anticipating and evaluating data on road accidents. Despite the fact that road accidents result in millions of lives and injuries worldwide each year, they are not very common. Traffic accidents are still quite common despite the pandemic's reduction. The aim of the essay is to evaluate the temporal horizon of the predicted number of traffic accidents. For this reason, an estimate of the expected number of traffic accidents in the future years was made, and its effect on the average percentage error of the projection was computed. Based on the analysis of the input data on the number of road accidents (annual and monthly), the results show that monthly and annual data can be forecast up to six years in advance. Received: 11 May 2024 | Revised: 20 August 2024 | Accepted: 2 September 2024 Conflicts of Interest The author declares that he has no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Piotr Gorzelańczyk: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration.

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Publication Details

Journal
Archives of Advanced Engineering Science
Published
2024-09-09
DOI
https://doi.org/10.47852/bonviewaaes42023400
Citations
2
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.53
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article

Time Horizon for Forecasting the Number of Traffic Accidents

Piotr Gorzelańczyk
2 citations
Archives of Advanced Engineering Science
Traffic Prediction and Management Techniques
0.53
article

Time Horizon for Forecasting the Number of Traffic Accidents

Piotr Gorzelańczyk
article en
2 citations

Abstract

On Polish roads, there are more and more automobiles each year. This results in more people using the roadways. Because of this, the threat posed by traffic accidents, which involve the loss of human life and financial resources, is quickly expanding. The rise of motorization and the quickening expansion of the human population are to blame for this. The tiny amount of the dataset that may be utilized for research in this respect is the major problem in anticipating and evaluating data on road accidents. Despite the fact that road accidents result in millions of lives and injuries worldwide each year, they are not very common. Traffic accidents are still quite common despite the pandemic's reduction. The aim of the essay is to evaluate the temporal horizon of the predicted number of traffic accidents. For this reason, an estimate of the expected number of traffic accidents in the future years was made, and its effect on the average percentage error of the projection was computed. Based on the analysis of the input data on the number of road accidents (annual and monthly), the results show that monthly and annual data can be forecast up to six years in advance. Received: 11 May 2024 | Revised: 20 August 2024 | Accepted: 2 September 2024 Conflicts of Interest The author declares that he has no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Piotr Gorzelańczyk: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration.

Archives of Advanced Engineering Science
Stanisław Staszic University of Applied Sciences in Piła (PL)
Openalex Percentile: Top 35%
Traffic Prediction and Management Techniques
0.53
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