Программный комплекс поддержки принятия решений для определения факта нарушения ПДД по траектории транспортного средства на видеоизображении
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Decision support system for detecting traffic violations based on vehicle’s trajectory

idMinnikhanov R.N. idAnikin I.V. idDagaeva M.V. idChernyshevskij P.A. idKadyrov A.R.

UDC 004.932
DOI: 10.26102/2310-6018/2023.40.1.016

  • Abstract
  • List of references
  • About authors

The paper proposes the approach for detecting the traffic violations based on illegal vehicle’s trajectory on video streams. As an example of such violations, illegal left turn is considered. This approach was implemented in a decision support system. YOLO neural network was employed as an object detector as part of the approach, LPRNet network for license plate recognition, and Ramer-Douglas-Pecker algorithm for the trajectory thinning. Using the example of the illegal left turn, a number of classifiers was studied: SVM, GaussianNB, KNeighbors, Decision Tree, Random Forest сlassifiers. These classifiers can be utilized to identify trajectories that violate road traffic regulations. Numerical experiments demonstrate that the SVM has about 95 % of classification accuracy among other algorithms. The computational cost also decreased due to the use of the trajectory thinning algorithm and lightweight neural network models. The capabilities of decision support system integration into the Centre for Automated Recording of Traffic Offences were illustrated by the example of left turn detection.

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Minnikhanov Rifkat Nurgalievich
Doctor of Technical Sciences Professor


Road Safety State Company

Kazan, Russian Federation

Anikin Igor Vjacheslavovich
Doctor of Technical Sciences Professor


Kazan National Research Technical University named after A.N. Tupolev-KAI

Kazan, Russian Federation

Dagaeva Maria Vitalievna


Road Safety State Company

Kazan, Russian Federation

Chernyshevskij Pavel Andreevich


Road Safety State Company

Kazan, Russian Federation

Kadyrov Azat Ruslanovich


Road Safety State Company

Kazan, Russian Federation

Keywords: intelligent transport system, decision support system, video image processing, machine learning, neural networks, trajectory classification

For citation: Minnikhanov R.N. Anikin I.V. Dagaeva M.V. Chernyshevskij P.A. Kadyrov A.R. Decision support system for detecting traffic violations based on vehicle’s trajectory. Modeling, Optimization and Information Technology. 2023;11(1). Available from: https://moitvivt.ru/ru/journal/pdf?id=1311 DOI: 10.26102/2310-6018/2023.40.1.016 (In Russ).


Full text in PDF

Received 19.01.2023

Revised 31.01.2023

Accepted 02.03.2023

Published 03.03.2023