{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T18:21:47Z","timestamp":1762453307107,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T00:00:00Z","timestamp":1762387200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Informatics"],"abstract":"<jats:p>This article describes a model for optimizing traffic flow control and generating traffic signal phases based on the stochastic dynamics of traffic and the percolation properties of transport networks. As input data (in SUMO), we use lane-level vehicle flow rates, treating them as random processes with unknown distributions. It is shown that the percolation threshold of the transport network can serve as a reliability criterion in a stochastic model of lane blockage and can be used to determine the control interval. To calculate the durations of permissive control signals and their sequence for different directions, vehicle queues are considered and the time required for them to reach the network\u2019s percolation threshold is estimated. Subsequently, the lane with the largest queue (i.e., the shortest time to reach blockage) is selected, and a phase is formed for its signal control, as well as for other lanes that can be opened simultaneously. Simulation results show that when dynamic traffic signal control is used and a percolation-dynamic model for balancing road traffic is applied, lane occupancy indicators such as \u201ccongestion\u201d decrease by 19\u201351% compared to a model with statically specified traffic signal phase cycles. The characteristics of flow dynamics obtained in the simulation make it possible to construct an overall control quality function and to assess, from the standpoint of traffic network management organization, an acceptable density of traffic signals and unsignalized intersections.<\/jats:p>","DOI":"10.3390\/informatics12040122","type":"journal-article","created":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T17:51:43Z","timestamp":1762451503000},"page":"122","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Percolation\u2013Stochastic Model for Traffic Management in Transport Networks"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2190-700X","authenticated-orcid":false,"given":"Anton","family":"Aleshkin","sequence":"first","affiliation":[{"name":"Institute of Cybersecurity and Digital Technologies, MIREA-Russian Technological University, 78 Vernadsky Avenue, 119454 Moscow, Russia"}]},{"given":"Dmitry","family":"Zhukov","sequence":"additional","affiliation":[{"name":"Institute of Radio Electronics and Informatics, MIREA-Russian Technological University, 78 Vernadsky Avenue, 119454 Moscow, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1708-9211","authenticated-orcid":false,"given":"Vadim","family":"Zhmud","sequence":"additional","affiliation":[{"name":"Institute of Laser Physics SB RAS, Prosp. Lavrentieva 15b, 630090 Novosibirsk, Russia"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,6]]},"reference":[{"key":"ref_1","first-page":"436","article-title":"Intelligent traffic light design and control in smart cities: A survey on techniques and methodologies","volume":"5","author":"Paulus","year":"2020","journal-title":"Int. J. Veh. Inf. Commun. Syst."},{"key":"ref_2","first-page":"2549","article-title":"The Efficiency of Smart Traffic Light in the \u201cSmart City\u201d Concept Based on Neural Networks for Object and Image Recognition","volume":"20","author":"Nurmukhanbetov","year":"2023","journal-title":"Sci. Aspect"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Alvarez Lopez, P., Behrisch, M., Bieker-Walz, L., Erdmann, J., Fl\u00f6tter\u00f6d, Y.-P., Hilbrich, R., L\u00fccken, L., Rummel, J., Wagner, P., and Wie\u00dfner, E. (2018, January 4\u20137). Microscopic Traffic Simulation using SUMO. 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