P.K. Nikolyuk, O.V. Zelinska
Èlektron. model. 2025, 47(1):40-52
https://doi.org/10.15407/emodel.47.01.040
ABSTRACT
The fundamental issue of urban traffic is the time of vehicle travel along the chosen route. It is clear that this time should be minimized for each driver. In a large city, there may be more than a million such drivers. The basic element and at the same time the basic problem of traffic control in a metropolis is a single intersection. It is this object where city roads intersect that is both the main cause and source of traffic jams. Therefore, the first priority is to implement intelligent regulation of vehicle traffic through a single intersection. By organizing efficient traffic through such an object, we will achieve high traffic efficiency throughout the city. There is a whole range of approaches to solving the problem of traffic control through intersections. An important direction is the use of computer modeling based on artificial intelligence (AI) methods. An intersection model and an AI-based algorithm for implementing the passage of cars through such an object are proposed, which allows optimizing traffic. The second important aspect of optimizing the traffic process is proposed, which is based on modeling the urban transport network using an oriented nonplanar weighted multigraph. Graph theory algorithms are used to optimize the passage of each vehicle along the selected route.
KEYWORDS
urban traffic, artificial intelligence (AI), vehicle, graph theory
REFERENCES
- Yao,, Li, X., Li Q. andYu C. (2024), “Safety aware neural network for connected and automated vehicle operations”, Transportation Research Part E: Logistics and Transportation Review, Vol. 192, article 103780.
https://doi.org/10.1016/j.tre.2024.103780 - Bharadiya, J. (2023), “Artificial Intelligence in Transportation Systems a Critical Review”, American Journal of Computing and Engineering, Vol. 6, no. 1, pp. 35-45.
https://doi.org/10.47672/ajce.1487 - Liang, X., Guler, S., Gayan, V. (2020), “An equtable traffic signal control scheme at isolated intersections using Connected Vehicle technology”, Research Part C, Vol. 110, pp. 81-97.
https://doi.org/10.1016/j.trc.2019.11.005 - Majid, H., Lu, C., Karim, H. (2018), “An integrated approach for dynamic traffic routing and ramp metering using sliding mode control”, of Traffic and Transportation Engineering (English Edition), Vol. 5, Is. 2, pp. 116-128.
https://doi.org/10.1016/j.jtte.2017.08.002 - Boguto, D.G., Kadomskiy, K.K., Nikolyuk, P.K., Pidgurska, A.I. (2019), “Algorithm of intelligent urban traffic”, Bulletin of V.Karazin Kharkiv National University, Series Mathematical Modeling. Information Technology. Automated Control System, Vol. 42, pp. 12-25. URL: https://cutt.ly/uPR3J6w.
- Porwal, S., Khamesra, J., Gupta R., Chhetri, V., Chhetri, B. (2021), “Density based smart traffic control and management system”, Journal of Emerging Technologies and Innovative Research, Vol. 8, Is. 10, pp. 416-420. DOI: 10.1729/Journal.28283.
- Tao, T., Qian, S. (2024), “Do Smart Loading Zones help reduce traffic congestion? A causal analysis in Pittsburgh” // Transportation Research Part E, Vol. 192, article 103796.
https://doi.org/10.1016/j.tre.2024.103796 - Rahimipour, S., Moeinfar, R., Hashemi S. (2019), “Traffic prediction using a self-adjusted evolutionary neural network”, Mod. Transportation, Vol. 27, pp. 306-316.
https://doi.org/10.1007/s40534-018-0179-5 - Zargiannaki, E., Tzouras, P., Antoniou, E. et. al. (2024), “Assessing the impacts of traffic calming at network level: A multimodal agent-based simulation”, Journal of traffic and transportation engineering (English edition), 11, No 1, pp. 41-54.
https://doi.org/10.1016/j.jtte.2023.01.003 - Chetan, G., Tushar, N., Vinit, P. et. al. (2021), “Applying Advanced Technology For Traffic Management System”, IOSR Journal of Mechanical and Civil Engineering, 18, Is. 4, pp. 8-12. DOI: 10.9790/1684-1804030812
- Ganga, B., Nagamani, K. (2020), “Implementation of intelligent traffic management system using IoT”, International Journal of Electrical Engineering and Technology, Vol. 11, Is. 5, pp. 22-30.
https://doi.org/10.34218/IJEET.11.5.2020.003 - Godson, S., Monday, O., Oluwaseun, E. et. al. (2020), “Smart Transportation System for Solving Urban Traffic Congestion”, Review of Computer Engineering Studies, 7, No. 3, pp. 55-59.
https://doi.org/10.18280/rces.070302 - Olayode, , Du, B., Severino, A. et. al. (2023), “Systematic literature review on the applications, impacts, and public perceptions of autonomous vehicles in road transportation system”, Journal of traffic and transportation engineering (English edition), Vol. 10, No. 6, pp. 1037-1060.
https://doi.org/10.1016/j.jtte.2023.07.006 - Hoang, A., Walton, N., Hai, L. (2024), “Optimal decentralized signal control for platooning in connected vehicle networks”, Transportation Research Part C, 167, article 104832.
https://doi.org/10.1016/j.trc.2024.104832 - Nikolyuk P., Neskorodieva T., Fedorov E. et. al. (2021), “Intellectual algorithm implementation for megacity traffic management”, CEUR Workshop proceedings, Information Technology and Interactions, V. 2845, pp. 400-408. URL: https://ceurspt.wikidata.dbis.rwth-aachen.de/Vol-2845/Paper_37.html.