Traffic analysis based on bluetooth passive scanning

Safa Boudabous; Julian Garbiso; Bertrand Leroy; Stephan Clemencon; Houda Labiod

doi:10.1109/VTCSpring.2019.8746452

Traffic analysis based on bluetooth passive scanning

Safa Boudabous, Julian Garbiso, Bertrand Leroy, Stephan Clemencon, Houda Labiod

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

During the last decade, Bluetooth has become a widespread feature in the automobile industry, meaning that its signal activity can be correlated with road traffic. Using this technology as a means for assessing traffic is very cost-effective and has a low impact on the infrastructure. Nevertheless, unlike other techniques, it does not provide direct sensing of vehicles only. Statistical analysis methods need to be applied to the collected data. In this paper, we first propose a machine learning method for traffic flow estimation using Bluetooth sensors. We also propose a method for estimating the mean travel speed between two sensors. The performance of the proposed methods is evaluated through eight weeks of experimentation. Finally, we envision a potential solution for building real-time Origin- Destination matrices.

Original language	English
Title of host publication	2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728112176
DOIs	https://doi.org/10.1109/VTCSpring.2019.8746452
Publication status	Published - 1 Apr 2019
Externally published	Yes
Event	89th IEEE Vehicular Technology Conference, VTC Spring 2019 - Kuala Lumpur, Malaysia Duration: 28 Apr 2019 → 1 May 2019

Publication series

Name	IEEE Vehicular Technology Conference
Volume	2019-April
ISSN (Print)	1550-2252

Conference

Conference	89th IEEE Vehicular Technology Conference, VTC Spring 2019
Country/Territory	Malaysia
City	Kuala Lumpur
Period	28/04/19 → 1/05/19

Access to Document

10.1109/VTCSpring.2019.8746452

Cite this

Boudabous, S., Garbiso, J., Leroy, B., Clemencon, S., & Labiod, H. (2019). Traffic analysis based on bluetooth passive scanning. In 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings Article 8746452 (IEEE Vehicular Technology Conference; Vol. 2019-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCSpring.2019.8746452

@inproceedings{2e0338cb798443c99ed53c95e510c4a1,

title = "Traffic analysis based on bluetooth passive scanning",

abstract = "During the last decade, Bluetooth has become a widespread feature in the automobile industry, meaning that its signal activity can be correlated with road traffic. Using this technology as a means for assessing traffic is very cost-effective and has a low impact on the infrastructure. Nevertheless, unlike other techniques, it does not provide direct sensing of vehicles only. Statistical analysis methods need to be applied to the collected data. In this paper, we first propose a machine learning method for traffic flow estimation using Bluetooth sensors. We also propose a method for estimating the mean travel speed between two sensors. The performance of the proposed methods is evaluated through eight weeks of experimentation. Finally, we envision a potential solution for building real-time Origin- Destination matrices.",

author = "Safa Boudabous and Julian Garbiso and Bertrand Leroy and Stephan Clemencon and Houda Labiod",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 89th IEEE Vehicular Technology Conference, VTC Spring 2019 ; Conference date: 28-04-2019 Through 01-05-2019",

year = "2019",

month = apr,

day = "1",

doi = "10.1109/VTCSpring.2019.8746452",

language = "English",

series = "IEEE Vehicular Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings",

}

Boudabous, S, Garbiso, J, Leroy, B, Clemencon, S & Labiod, H 2019, Traffic analysis based on bluetooth passive scanning. in 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings., 8746452, IEEE Vehicular Technology Conference, vol. 2019-April, Institute of Electrical and Electronics Engineers Inc., 89th IEEE Vehicular Technology Conference, VTC Spring 2019, Kuala Lumpur, Malaysia, 28/04/19. https://doi.org/10.1109/VTCSpring.2019.8746452

Traffic analysis based on bluetooth passive scanning. / Boudabous, Safa; Garbiso, Julian; Leroy, Bertrand et al.
2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8746452 (IEEE Vehicular Technology Conference; Vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Traffic analysis based on bluetooth passive scanning

AU - Boudabous, Safa

AU - Garbiso, Julian

AU - Leroy, Bertrand

AU - Clemencon, Stephan

AU - Labiod, Houda

PY - 2019/4/1

Y1 - 2019/4/1

N2 - During the last decade, Bluetooth has become a widespread feature in the automobile industry, meaning that its signal activity can be correlated with road traffic. Using this technology as a means for assessing traffic is very cost-effective and has a low impact on the infrastructure. Nevertheless, unlike other techniques, it does not provide direct sensing of vehicles only. Statistical analysis methods need to be applied to the collected data. In this paper, we first propose a machine learning method for traffic flow estimation using Bluetooth sensors. We also propose a method for estimating the mean travel speed between two sensors. The performance of the proposed methods is evaluated through eight weeks of experimentation. Finally, we envision a potential solution for building real-time Origin- Destination matrices.

AB - During the last decade, Bluetooth has become a widespread feature in the automobile industry, meaning that its signal activity can be correlated with road traffic. Using this technology as a means for assessing traffic is very cost-effective and has a low impact on the infrastructure. Nevertheless, unlike other techniques, it does not provide direct sensing of vehicles only. Statistical analysis methods need to be applied to the collected data. In this paper, we first propose a machine learning method for traffic flow estimation using Bluetooth sensors. We also propose a method for estimating the mean travel speed between two sensors. The performance of the proposed methods is evaluated through eight weeks of experimentation. Finally, we envision a potential solution for building real-time Origin- Destination matrices.

U2 - 10.1109/VTCSpring.2019.8746452

DO - 10.1109/VTCSpring.2019.8746452

M3 - Conference contribution

AN - SCOPUS:85068963145

T3 - IEEE Vehicular Technology Conference

BT - 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 89th IEEE Vehicular Technology Conference, VTC Spring 2019

Y2 - 28 April 2019 through 1 May 2019

ER -

Traffic analysis based on bluetooth passive scanning

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