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Computer Research and Modeling, 2021, Volume 13, Issue 2, Pages 295–303
DOI: https://doi.org/10.20537/2076-7633-2021-13-2-295-303
(Mi crm885)
 

This article is cited in 1 scientific paper (total in 1 paper)

SPECIAL ISSUE
MODELING OF TRAFFIC IN INTELLIGENT TRANSPORTATION SYSTEMS

Method of forming multiprogram control of an isolated intersection

A. A. Vlasova, I. A. Pilgeikinaa, I. A. Skorikovab

a Penza State University of Architecture and Construction, 28/1318 Herman Titov st., Penza, 440028, Russia
b RusSoft LLC, 52 Chkalov's st., Penza, 440052, Russia
References:
Abstract: The simplest and most desirable method of traffic signal control is precalculated regulation, when the parameters of the traffic light object operation are calculated in advance and activated in accordance to a schedule. This work proposes a method of forming a signal plan that allows one to calculate the control programs and set the period of their activity. Preparation of initial data for the calculation includes the formation of a time series of daily traffic intensity with an interval of 15 minutes. When carrying out field studies, it is possible that part of the traffic intensity measurements is missing. To fill up the missing traffic intensity measurements, the spline interpolation method is used. The next step of the method is to calculate the daily set of signal plans. The work presents the interdependencies, which allow one to calculate the optimal durations of the control cycle and the permitting phase movement and to set the period of their activity. The present movement control systems have a limit on the number of control programs. To reduce the signal plans' number and to determine their activity period, the clusterization using the $k$-means method in the transport phase space is introduced In the new daily signal plan, the duration of the phases is determined by the coordinates of the received cluster centers, and the activity periods are set by the elements included in the cluster. Testing on a numerical illustration showed that, when the number of clusters is 10, the deviation of the optimal phase duration from the cluster centers does not exceed 2 seconds. To evaluate the effectiveness of the developed methodology, a real intersection with traffic light regulation was considered as an example. Based on field studies of traffic patterns and traffic demand, a microscopic model for the SUMO (Simulation of Urban Mobility) program was developed. The efficiency assessment is based on the transport losses estimated by the time spent on movement. Simulation modeling of the multiprogram control of traffic lights showed a 20% reduction in the delay time at the traffic light object in comparison with the single-program control. The proposed method allows automation of the process of calculating daily signal plans and setting the time of their activity.
Keywords: traffic light regulation, multiprogram control, time series, clustering, k-means.
Funding agency Grant number
Fund for Assistance to Small Innovative Enterprises in the Scientific and Technical Sphere 15361GU/2020
The work was supported by the Innovation Promotion Fund (contract No. 15361GU/2020 dated 20.06.2020).
Received: 14.09.2020
Revised: 25.02.2021
Accepted: 02.03.2021
English version:
Computer Research and Modeling, 2021, Volume 13, Issue 2, Pages e295–e303
DOI: https://doi.org/10.20537/2076-7633-2021-13-2-295-303
Document Type: Article
UDC: 656.13
Language: Russian
Citation: A. A. Vlasov, I. A. Pilgeikina, I. A. Skorikova, “Method of forming multiprogram control of an isolated intersection”, Computer Research and Modeling, 13:2 (2021), 295–303; Computer Research and Modeling, 13:2 (2021), e295–e303
Citation in format AMSBIB
\Bibitem{VlaPilSko21}
\by A.~A.~Vlasov, I.~A.~Pilgeikina, I.~A.~Skorikova
\paper Method of forming multiprogram control of an isolated intersection
\jour Computer Research and Modeling
\yr 2021
\vol 13
\issue 2
\pages 295--303
\mathnet{http://mi.mathnet.ru/crm885}
\crossref{https://doi.org/10.20537/2076-7633-2021-13-2-295-303}
\transl
\jour Computer Research and Modeling
\yr 2021
\vol 13
\issue 2
\pages e295--e303
\crossref{https://doi.org/10.20537/2076-7633-2021-13-2-295-303}
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  • https://www.mathnet.ru/eng/crm/v13/i2/p295
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Research and Modeling
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    Abstract page:93
    Russian version PDF:20
    English version PDF:9
    References:14
     
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