Ontological model for managing waiting time for traffic light signals by road users in a pedestrian crossing zone

Purpose of research. Development of an ontological model for managing the waiting time for traffic light signals by road users in a pedestrian crossing zone, with the capability to count the number of pedestrians and vehicles at the intersection and regulate the timing intervals of traffic light signals based on their quantity. Methods. The database for the ontological model is collected using a computer vision system. A cognitive decision-making model is used to determine object boundaries. Object classification is performed using the YOLO algorithm. The counting of pedestrians and vehicles is carried out within a mathematical model for counting detectable objects in an image. The calculation of time for regulating the duration of traffic light signals is achieved through a mathematical model of intelligent traffic light control. The proposed ontological model includes several stages: data collection, image preprocessing, object boundary detection, classification of road users into classes and subclasses, counting the number of pedestrians and vehicles, and calculating the time required to adjust the duration of intelligent traffic light signals. Results. A specialized software model has been developed, which enables the detection of object classes and the calculation of delay times for traffic light signals to regulate an intelligent traffic light. The state registration certificate for the computer program "Program for Detecting Objects at a Pedestrian Crossing and Determining Traffic Light Signal Delay Times" is numbered 2024662790. Additionally, a patent for the invention "Traffic Light Control Device Based on Fuzzy Logic" (No. 2827781) has been obtained, allowing for the generation of control signals for an intelligent traffic light. Conclusion. The results of experimental studies have demonstrated the high efficiency of the developed ontological model for managing the waiting time for traffic light signals by road users in a pedestrian crossing zone.

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Publication Details

Journal
Proceedings of Southwest State University
Published
2025-04-07
DOI
https://doi.org/10.21869/2223-1560-2024-28-4-124-137
Citations
1
Primary Topic
Cognitive Computing and Networks
Type
article
Field-Weighted Citation Impact
2.48
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article

Ontological model for managing waiting time for traffic light signals by road users in a pedestrian crossing zone

M. V. Bobyr, S. G. Emelianov, N. I. Khrapova
1 citations
Proceedings of Southwest State University
Cognitive Computing and Networks
2.48
article

Ontological model for managing waiting time for traffic light signals by road users in a pedestrian crossing zone

M. V. Bobyr, S. G. Emelianov, N. I. Khrapova
article en
1 citations

Abstract

Purpose of research. Development of an ontological model for managing the waiting time for traffic light signals by road users in a pedestrian crossing zone, with the capability to count the number of pedestrians and vehicles at the intersection and regulate the timing intervals of traffic light signals based on their quantity. Methods. The database for the ontological model is collected using a computer vision system. A cognitive decision-making model is used to determine object boundaries. Object classification is performed using the YOLO algorithm. The counting of pedestrians and vehicles is carried out within a mathematical model for counting detectable objects in an image. The calculation of time for regulating the duration of traffic light signals is achieved through a mathematical model of intelligent traffic light control. The proposed ontological model includes several stages: data collection, image preprocessing, object boundary detection, classification of road users into classes and subclasses, counting the number of pedestrians and vehicles, and calculating the time required to adjust the duration of intelligent traffic light signals. Results. A specialized software model has been developed, which enables the detection of object classes and the calculation of delay times for traffic light signals to regulate an intelligent traffic light. The state registration certificate for the computer program "Program for Detecting Objects at a Pedestrian Crossing and Determining Traffic Light Signal Delay Times" is numbered 2024662790. Additionally, a patent for the invention "Traffic Light Control Device Based on Fuzzy Logic" (No. 2827781) has been obtained, allowing for the generation of control signals for an intelligent traffic light. Conclusion. The results of experimental studies have demonstrated the high efficiency of the developed ontological model for managing the waiting time for traffic light signals by road users in a pedestrian crossing zone.

Proceedings of Southwest State UniversityVol. 28(4)
Southwest Minnesota State University (US)
Sustainable cities and communities
Openalex Percentile: Top 11%
Cognitive Computing and Networks
2.48
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