Applying neural network techniques to determine traffic flow redirection proportions in road networks

• Autorzy: Nguyen Xuan-Hien , Vu Thi Van Anh , Than Quoc Viet , Pham Viet Thanh , Nguyen The Anh , Ha Muon

Identyfikatory

DOI

10.20858/sjsutst.2025.127.16

• Języki publikacji: EN

Abstrakty

EN

This article explores traffic management strategies for addressing unpredictable events in transportation networks, focusing on situations where road segment capacity is reduced due to factors like traffic accidents or disruptions. The research aims to determine the proportion of traffic flow redistribution needed to maintain network efficiency under such conditions. A novel method is proposed to mitigate congestion by rerouting vehicles from heavily loaded roads, identified by high network load coefficients, to alternative routes. The approach also calculates the optimal volume of redirected traffic to avoid overloading other parts of the network, thereby minimizing the risk of secondary congestion. To achieve this, neural network-based survey and regression analysis techniques are utilized, offering precise and data-driven solutions for traffic redirection. The study highlights the potential of improving urban traffic flow through enhancements to indirect traffic control systems integrated into Intelligent Transportation Systems. By optimizing vehicle rerouting strategies, the proposed method seeks to increase ITS efficiency, especially in scenarios with high congestion risks or traffic accidents. This approach promises a more resilient and adaptive urban transportation network, ensuring smoother traffic operations and reduced congestion impacts.

Słowa kluczowe

EN

traffic management; intelligent transport systems; intelligent neutral network; traffic flows

PL

zarządzanie ruchem drogowym; inteligentne systemy transportowe; inteligentna neutralna sieć; natężenie ruchu drogowego

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Zeszyty Naukowe. Transport / Politechnika Śląska
• Rocznik: 2025
• Tom: z. 127
• Strony: 267--275
• Opis fizyczny: Bibliogr. 10 poz.

Twórcy

autor

Nguyen Xuan-Hien

• Faculty of Automobile Technology, Hanoi University of Industry (HaUI), 298 Cau Dien street, Hanoi, Vietnam

• https://orcid.org/0000-0002-1552-1867

autor

Vu Thi Van Anh

• Faculty of traffic police, People’s s police university, 36 Nguyen Huu Tho street, 7th district, Hochiminh city, Vietnam

• https://orcid.org/0009-0000-4948-1616

autor

Than Quoc Viet

• Faculty of Automobile Technology, Hanoi University of Industry (HaUI), 298 Cau Dien street, Hanoi, Vietnam

• https://orcid.org/0000-0002-2320-4386

autor

Pham Viet Thanh

• Faculty of Automobile Technology, Hanoi University of Industry (HaUI), 298 Cau Dien street, Hanoi, Vietnam

• https://orcid.org/0000-0002-2472-2871

autor

Nguyen The Anh

• Faculty of Automobile Technology, Hanoi University of Industry (HaUI), 298 Cau Dien street, Hanoi, Vietnam

• https://orcid.org/0009-0009-7250-0382

autor

Ha Muon

• Faculty of Information Technology, Telecommunications University, Nha Trang, Vietnam

• https://orcid.org/0000-0003-4385-1916

Bibliografia

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• 6. Efimenko D.B. 2012. „Methodological foundations of building navigation systems of dispatch control of transportation processes on road transport (e.g. urban passenger transport)”. Diss. doctor of technical sciences. 05.22.08. Мoscow. 479 p.
• 7. Kosolapov A.V. 1992. „Increase of efficiency of information support of road traffic participants in the cities”. Diss. candidate of technical sciences. 05.22.10. Мoscow. 178 p.
• 8. Kocherga V.G. 2001. „Estimation and forecasting of the road traffic parameters in the intellectual transportation systems”. Rostov n/D: Rost. State Construction University. 130 p.
• 9. Utkin A.V. 2006. „Modeling of driver behavior and quality assessment of a mixed traffic flow”. "Organization and traffic safety in large cities"”. In: Collection of reports of the 7th International Conference. St.-Petersburg. P. 84-86.
• 10. Xuan Can Vuong, Rui-Fang Mou, Trong Thuat Vu, Hoang Van Nguyen. 2021. „An adaptive method for an isolated intersection under mixed traffic conditions in Hanoi based on ANFIS using VISSIM-MATLAB”. IEEE Access 9: 166328-166338. DOI: 10.1109/ACCESS.2021.3135418