Estimation of Average Speed of Road Vehicles by Sound Intensity Analysis.

acoustic vector sensor sound intensity speed estimation traffic analysis

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
07 Aug 2021
Historique:
received: 14 07 2021
revised: 03 08 2021
accepted: 05 08 2021
entrez: 28 8 2021
pubmed: 29 8 2021
medline: 1 9 2021
Statut: epublish

Résumé

Constant monitoring of road traffic is important part of modern smart city systems. The proposed method estimates average speed of road vehicles in the observation period, using a passive acoustic vector sensor. Speed estimation based on sound intensity analysis is a novel approach to the described problem. Sound intensity in two orthogonal axes is measured with a sensor placed alongside the road. Position of the apparent sound source when a vehicle passes by the sensor is estimated by means of sound intensity analysis in three frequency bands: 1 kHz, 2 kHz and 4 kHz. The position signals calculated for each vehicle are averaged in the analysis time frames, and the average speed estimate is calculated using a linear regression. The proposed method was validated in two experiments, one with controlled vehicle speed and another with real, unrestricted traffic. The calculated speed estimates were compared with the reference lidar and radar sensors. Average estimation error from all experiment was 1.4% and the maximum error was 3.2%. The results confirm that the proposed method allow for estimation of time-averaged road traffic speed with accuracy sufficient for gathering traffic statistics, e.g., in a smart city monitoring station.

Identifiants

pubmed: 34450779
pii: s21165337
doi: 10.3390/s21165337
pmc: PMC8398890
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Narodowe Centrum Badań i Rozwoju
ID : POIR.04.01.04/2019

Références

Multimed Tools Appl. 2015;74(12):4235-4251
pubmed: 26321871
Sensors (Basel). 2018 Apr 16;18(4):
pubmed: 29659524

Auteurs

Józef Kotus (J)

Department of Multimedia Systems, Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, Poland.

Grzegorz Szwoch (G)

Department of Multimedia Systems, Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, Poland.

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Classifications MeSH