Разработка алгоритмического аппарата по обеспечению безопасности дорожного движения
Работая с нашим сайтом, вы даете свое согласие на использование файлов cookie. Это необходимо для нормального функционирования сайта, показа целевой рекламы и анализа трафика. Статистика использования сайта отправляется в «Яндекс» и «Google»
Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Development of an algorithmic apparatus for ensuring road safety

idArutiunian M.A.

UDC 656
DOI: 10.26102/2310-6018/2023.42.3.013

  • Abstract
  • List of references
  • About authors

This article presents one of the scientific results obtained by the author in the course of the dissertation research. The problem considered in the study, namely the problem of ensuring the safety of road users, is raised. It was demonstrated that in megacities the installation of the “necessary minimum set of means” is not observed in all areas, which, in turn, causes violations by road users. Existing methods for assessing and improving the safety of road users are considered, limitations are highlighted. A possible tool for solving the analyzed problem with the aid of the identified restrictions is proposed which is the rational placement of technical means of traffic organization. An algorithmic apparatus has been developed that allows predicting and recommending suitable places for installing technical means of organizing traffic on those streets where they are located either irrationally or not at all based on the Decision Tree machine learning algorithm. A proprietary method for preparing input data with a description of the stages is proposed. The use of the semantic differential method to determine the weights / importance of attributes is proposed. Testing of the developed algorithmic apparatus was carried out both using the example of the “model” and using the example of a real site. It is noted that the proposed algorithm is able to generate a large amount of input data, which will further expand the algorithm and take into account even more various factors. It is expected that the developed algorithmic apparatus will significantly minimize the number of traffic accidents. It is assumed that the scientific results obtained in the research will allow a comprehensive assessment of the problems of organizing traffic in existing built-up areas or areas planned for development.

1. Arutiunian M.A. Metody ocenki i povyshenija peshehodnoj bezopasnosti. Al'manah nauchnyh rabot molodyh uchenyh Universiteta ITMO. 2020; 5: 23-26. (In Russ.).

2. Fujitsu Global. What is SPATIOWL? URL: http://www.fujitsu.com/global/solutions/business-technology/intelligent-society/smart-mobility/spatiowl/ (accessed on 18.10.2022).

3. Siemens. Sitraffic Vehicle2x. URL: https://assets.new.siemens.com/siemens/assets/api/uuid:9c7f02efa4cd2e1b0f6ea0eadeb5db658837d86e/siemens-vehicle-to-x-communication-technology-infographic.pdf (accessed on 18.10.2022).

4. Qualcomm. Cellular V2X. URL: https://www.qualcomm.com/invention/5g/cellular-v2x (accessed on 10.12.2019).

5. Lawniczak A.T., Di Stefano B.N., Ernst J.B. Stochastic model of cognitive agents learning. Stochastic Models, Statistics and Their Applications. 2015:319326.

6. Daganzo C.F., Knoop V.L. Traffic flow on pedestrianized streets. Transportation Research Part B: Methodological. 2016:86:211222.

7. Wang L., Ye S., Cheong K.H., Xie N. Pedestrian group-crossing behavior modeling and simulation based on multidimensional dirty faces game. Complexity. 2017.

8. Yang J., Deng W., Wang J., Li Q., Wang Z. Modeling pedestrians’ road crossing behavior in traffic system micro-simulation in China. Transportation Research Part A. 2006;40:280290.

9. Zeng W., Chen P., Nakamura H., Iryo-Asano M. Application of social force model to pedestrian behavior analysis at signalized crosswalk. Transportation Research Part C. 2014;40:143159.

10. Feliciani C., Crociani L., Gorrini A., Vizzari G., Bandini S., Nishinari K. A simulation model for non-signalized pedestrian crosswalks based on evidence from on field observation. Intelligenza Artificiale. 2017;11:117138.

Arutiunian Melania Andranikovna


Admiral Makarov State University of Maritime and Inland Shipping

Saint Petersburg, the Russian Federation

Keywords: technical means of traffic management, algorithmic apparatus, method, semantic differential, decision tree machine learning algorithm

For citation: Arutiunian M.A. Development of an algorithmic apparatus for ensuring road safety. Modeling, Optimization and Information Technology. 2023;11(3). Available from: https://moitvivt.ru/ru/journal/pdf?id=1411 DOI: 10.26102/2310-6018/2023.42.3.013 (In Russ).


Full text in PDF

Received 19.06.2023

Revised 25.07.2023

Accepted 10.08.2023

Published 11.08.2023