Its-pro-flow: a new enhanced short-term traffic flow prediction for intelligent transportation systems

• Autorzy: Kozici Halil Ibrahim , Kosunalp Selahattin , Arucu Muhammet

Identyfikatory

DOI

10.20858/sjsutst.2023.120.8

• Języki publikacji: EN

Abstrakty

EN

Short-term traffic flow prediction plays a significant role in various applications of intelligent transportation systems (ITS), such as road traffic control and route guidance. This requires the development of intelligent prediction approaches for accurate and timely traffic flow information. To handle this issue, this paper emphasizes the potential of a new idea to propose a high-quality and intelligent prediction of short-term traffic flow in ITS. The proposed model, referred to as ITS-Pro-Flow, takes the benefits of the well-known Profile-Energy (Pro-Energy) as a landmark solution, relying on past observations and current conditions to forecast future short-term traffic flow volume. ITS-Pro-Flow has an effective prediction mechanism due to its unique enhancements over Pro-Energy. The distinctive feature of ITS-Pro-Flow is that it dynamically adjusts the contributions of past predictions and current observations for a particular prediction, which is equally performed in Pro-Energy. We prove the performance of ITS-Pro-Flow through extensive simulations with 2 datasets, in comparison to Pro-Energy and IPro-Energy. Performance results clearly indicate that ITS-Pro-Flow provides more accurate predictions than other schemes.

Słowa kluczowe

EN

traffic flow; intelligent transportation; prediction; Pro-Energy

PL

przepływ ruchu; inteligentny transport; przewidywanie; Pro-Energy

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Zeszyty Naukowe. Transport / Politechnika Śląska
• Rocznik: 2023
• Tom: z. 120
• Strony: 117--136
• Opis fizyczny: Bibliogr. 27 poz.

Twórcy

autor

Kozici Halil Ibrahim

• Department of Intelligent Transportation Systems and Technologies, Institute of Science, University of Bandirma Onyedi Eylul, Bandirma, Balikesir

• https://orcid.org/0000-0001-7544-3656

autor

Kosunalp Selahattin

• Department of Computer Technologies, Gonen Vocational School, University of Bandirma Onyedi Eylul, Bandirma, Balikesir

• https://orcid.org/0000-0003-2899-4679

autor

Arucu Muhammet

• Department of Computer Technologies, Gonen Vocational School, University of Bandirma Onyedi Eylul, Bandirma, Balikesir

• https://orcid.org/0000-0001-7620-9044

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