PEDESTRIAN RED LIGHT TRAFFIC RECOGNITION MODEL BASED ON YOLOV8 ALGORITHM

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Published: Apr 30, 2025
DOI: https://doi.org/10.20998/2522-9052.2025.2.10
Keywords:
deep learning network, YOLOv8 model, pedestrian red light traffic detection, road safety, intelligent transport system, object detection, performance evaluation

Main Article Content

Svitlana Gavrylenko
National Technical University "Kharkiv Polytechnic Institute", Kharkiv
Wang Zhihao
Chongqing Telecommunication Polytechnic College, Chongqing

Abstract

The object of the study is the process recognition of pedestrian red light traffic. The subject of the study are the methods of process recognition of pedestrian red light traffic. The purpose of the paper is to improve the efficiency of real-time pedestrian red light traffic recognition model. The results obtained. The pedestrian red light traffic recognition model based on real-time object detection architecture YOLOv8 was proposed. The architecture and characteristics of YOLOv8 model, including its improved network structure, multi-scale detection ability, and adaptive anchor adjustment were introduced in detail. To demonstrate the efficiency and benefits of applying the YOLOv8 model, its performance was evaluated in various scenarios. Conclusions. Experiments have confirmed the efficiency of the proposed method. The use of the developed method based on the YOLOv8 architecture allowed to increase precision up to 0.935. Overall, the average performance across all categories is 0.851, which means that the model has a relatively high detection accuracy. In addition, model has a high-speed index.

Article Details

How to Cite
Gavrylenko , S. ., & Zhihao, W. . (2025). PEDESTRIAN RED LIGHT TRAFFIC RECOGNITION MODEL BASED ON YOLOV8 ALGORITHM. Advanced Information Systems, 9(2), 75–83. https://doi.org/10.20998/2522-9052.2025.2.10
Issue
Vol. 9 No. 2 (2025): Advanced Information Systems
Section
Intelligent information systems
Author Biographies

Svitlana Gavrylenko , National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Doctor of Technical Science, Professor, Professor of Department of "Computer Engineering and Programming"

Wang Zhihao, Chongqing Telecommunication Polytechnic College, Chongqing

Master of Computer Engineering, Lecturer of Department of "Communication Engineering and Industrial Internet"

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