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ITS-PRO-FLOW: A NEW ENHANCED SHORT-TERM TRAFFIC FLOW PREDICTION FOR INTELLIGENT TRANSPORTATION SYSTEMS.

Authors :
KAZICI, Halil Ibrahim
KOSUNALP, Selahattin
ARUCU, Muhammet
Source :
Scientific Journal of Silesian University of Technology. Series Transport / Zeszyty Naukowe Politechniki Slaskiej. Seria Transport; 2023, Vol. 120, p117-136, 20p
Publication Year :
2023

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02093324
Volume :
120
Database :
Complementary Index
Journal :
Scientific Journal of Silesian University of Technology. Series Transport / Zeszyty Naukowe Politechniki Slaskiej. Seria Transport
Publication Type :
Academic Journal
Accession number :
164885998
Full Text :
https://doi.org/10.20858/sjsutst.2023.120.8