Model of the intelligent system for prediction of road traffic accidents

Oleksandr Byzkrovnyi, Kirill Smelyakov, Anastasiya Chupryna

Abstract


This study aims to determine the prerequisites for the occurrence of road traffic accidents, analyze the most dangerous maneuvers of motor vehicles that can lead to hazardous situations, and develop the most effective method for promptly informing the driver about potential danger. The goal of this study is to develop an information system that ensures timely notification of drivers about possible road traffic accidents in designated hazardous areas. The tasks include: investigating existing computer vision models for classification and object tracking tasks and determining the most suitable ones for deployment on a single-board computer Nvidia Jetson, while examining their performance and technical limitations; developing an optimized solution for the prompt notification of drivers about danger; creating an algorithm for detecting potential vehicle collisions that integrates computer vision methods and mathematical modeling; developing a comprehensive danger warning system based on the obtained results and testing its functionality. The following methods were applied in this study: a process-based approach to investigate the mechanisms of road traffic accident occurrence, statistical analysis of hazardous areas and maneuvers, and performance analysis of computer vision models for real-time object detection and tracking and driver notification. Additionally, road situations were simulated and modeled using the BeamNG.tech environment. The results include the development of a methodology based on computer vision and mathematical models for identifying hazardous situations on the road and the creation of an approach for prompt notification of road users using cloud technologies, IoT devices, and the GeoHash algorithm. An information system that allows drivers to receive warnings about potential hazards along their route has been proposed. Conclusions: this study confirms the successful development of a software system for forecasting and notifying drivers about the risk of road traffic accidents. The conducted studies have demonstrated the effectiveness of the proposed algorithm for detecting hazardous situations and technological solutions for road infrastructure integration. Experiments conducted using BeamNG.tech have confirmed the functionality of the developed system, which can be applied to minimize the risk of road traffic accidents in designated hazardous areas.

Keywords


Information Technologies Development; Intelligent software system; model for vehicles crash prediction; Machine Learning; Computer Vision; Nvidia Jetson; Messages routing optimization; GeoHash; Internet of Things

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References


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DOI: https://doi.org/10.32620/reks.2025.4.09

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