LAPSE:2023.17359
Published Article

LAPSE:2023.17359
Traffic Intersection Lane Control Using Radio Frequency Identification and 5G Communication
March 6, 2023
Abstract
This article deals with automated urban traffic management, and proposes a new comprehensive infrastructure solution for dynamic traffic direction switching at intersection lines. It was assumed that the currently used solutions based on video monitoring are unreliable. Therefore, the Radio Frequency IDentification (RFID) technique was introduced, in which vehicles are counted and, if necessary, identified in order to estimate the flows on individual lanes. The data is acquired in real time using fifth-generation wireless communications (5G). The Pots and Ising models derived from the theory of statistical physics were used in a novel way to determine the state of direction traffic lights. The models were verified by simulations using data collected from real traffic observations. The results were presented for two exemplary intersections.
This article deals with automated urban traffic management, and proposes a new comprehensive infrastructure solution for dynamic traffic direction switching at intersection lines. It was assumed that the currently used solutions based on video monitoring are unreliable. Therefore, the Radio Frequency IDentification (RFID) technique was introduced, in which vehicles are counted and, if necessary, identified in order to estimate the flows on individual lanes. The data is acquired in real time using fifth-generation wireless communications (5G). The Pots and Ising models derived from the theory of statistical physics were used in a novel way to determine the state of direction traffic lights. The models were verified by simulations using data collected from real traffic observations. The results were presented for two exemplary intersections.
Record ID
Keywords
5G, RFID, Smart City, traffic management
Subject
Suggested Citation
Paszkiewicz A, Pawłowicz B, Trybus B, Salach M. Traffic Intersection Lane Control Using Radio Frequency Identification and 5G Communication. (2023). LAPSE:2023.17359
Author Affiliations
Paszkiewicz A: Department of Complex Systems, The Faculty of Electrical and Computer Engineering, Rzeszów University of Technology, Wincentego Pola 2, 35-959 Rzeszów, Poland [ORCID]
Pawłowicz B: Department of Electronic and Telecommunications Systems, Rzeszów University of Technology, Wincentego Pola 2, 35-959 Rzeszów, Poland [ORCID]
Trybus B: Department of Computer and Control Engineering, Rzeszów University of Technology, Wincentego Pola 2, 35-959 Rzeszów, Poland [ORCID]
Salach M: Department of Complex Systems, The Faculty of Electrical and Computer Engineering, Rzeszów University of Technology, Wincentego Pola 2, 35-959 Rzeszów, Poland [ORCID]
Pawłowicz B: Department of Electronic and Telecommunications Systems, Rzeszów University of Technology, Wincentego Pola 2, 35-959 Rzeszów, Poland [ORCID]
Trybus B: Department of Computer and Control Engineering, Rzeszów University of Technology, Wincentego Pola 2, 35-959 Rzeszów, Poland [ORCID]
Salach M: Department of Complex Systems, The Faculty of Electrical and Computer Engineering, Rzeszów University of Technology, Wincentego Pola 2, 35-959 Rzeszów, Poland [ORCID]
Journal Name
Energies
Volume
14
Issue
23
First Page
8066
Year
2021
Publication Date
2021-12-02
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14238066, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.17359
This Record
External Link

https://doi.org/10.3390/en14238066
Publisher Version
Download
Meta
Record Statistics
Record Views
320
Version History
[v1] (Original Submission)
Mar 6, 2023
Verified by curator on
Mar 6, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.17359
Record Owner
Auto Uploader for LAPSE
Links to Related Works
