Acoustic vehicle speed estimation from single sensor measurements

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00351743" target="_blank" >RIV/68407700:21230/21:00351743 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/JSEN.2021.3110009" target="_blank" >https://doi.org/10.1109/JSEN.2021.3110009</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/JSEN.2021.3110009" target="_blank" >10.1109/JSEN.2021.3110009</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Acoustic vehicle speed estimation from single sensor measurements

Popis výsledku v původním jazyce

The paper addresses acoustic vehicle speed estimation using single sensor measurements. We introduce a new speed-dependent feature based on the attenuation of the sound amplitude. The feature is predicted from the audio signal and used as input to a regression model for speed estimation. For this research, we have collected, annotated, and published a dataset of audio-video recordings of single vehicles passing by the camera at a known constant speed. The dataset contains 304 urban-environment real-field recordings of ten different vehicles. The proposed method is trained and tested on the collected dataset. Experiments show that it is able to accurately predict the pass-by instant of a vehicle and to estimate its speed with an average error of 7.39 km/h. When the speed is discretized into intervals of 10 km/h, the proposed method achieves the average accuracy of 53.2% for correct interval prediction and 93.4% when misclassification of one interval is allowed. Experiments also show that sound disturbances, such as wind, severely affect acoustic speed estimation.

Název v anglickém jazyce

Acoustic vehicle speed estimation from single sensor measurements

Popis výsledku anglicky

The paper addresses acoustic vehicle speed estimation using single sensor measurements. We introduce a new speed-dependent feature based on the attenuation of the sound amplitude. The feature is predicted from the audio signal and used as input to a regression model for speed estimation. For this research, we have collected, annotated, and published a dataset of audio-video recordings of single vehicles passing by the camera at a known constant speed. The dataset contains 304 urban-environment real-field recordings of ten different vehicles. The proposed method is trained and tested on the collected dataset. Experiments show that it is able to accurately predict the pass-by instant of a vehicle and to estimate its speed with an average error of 7.39 km/h. When the speed is discretized into intervals of 10 km/h, the proposed method achieves the average accuracy of 53.2% for correct interval prediction and 93.4% when misclassification of one interval is allowed. Experiments also show that sound disturbances, such as wind, severely affect acoustic speed estimation.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF19_074%2F0016255" target="_blank" >EF19_074/0016255: Mezinárodní mobility výzkumných pracovníků MSCA IF III na ČVUT v Praze</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Sensors Journal

ISSN

1530-437X

e-ISSN

1558-1748

Svazek periodika

21

Číslo periodika v rámci svazku

20

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

8

Strana od-do

23317-23324

Kód UT WoS článku

000709128900120

EID výsledku v databázi Scopus

2-s2.0-85114714611