Statistical requirements for noise mapping based on mobile measurements using bikes

Autor: Jordi Romeu, Arnaud Can, Pierre Aumond, G. Quintero, A. Balastegui
Přispěvatelé: Universitat Politècnica de Catalunya. Departament d'Enginyeria Mecànica, Universitat Politècnica de Catalunya. LEAM - Laboratori d'Enginyeria Acústica i Mecànica, Laboratorio de Ingeniería Acústica y Mecánica, parent, Unité Mixte de Recherche en Acoustique Environnementale (UMRAE ), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema)-Université Gustave Eiffel, Polytechnic University of Catalonia
Rok vydání: 2019
Předmět:
Soroll -- Mesurament
BICYCLETTE
Acoustics and Ultrasonics
Mean squared error
Computer science
MOBILE SAMPLING
Interval (mathematics)
010501 environmental sciences
NOISE MAPPING
01 natural sciences
Soroll urbà
[SPI]Engineering Sciences [physics]
Circulació urbana -- Soroll -- Aspectes ambientals
Noise--Measurement
0103 physical sciences
City traffic--Environmental aspects
Reference noise
DYNAMIC NOISE MODELING
Sampling (Statistics)
010301 acoustics
CARTOGRAPHIE
0105 earth and related environmental sciences
[SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph]
Desenvolupament humà i sostenible [Àrees temàtiques de la UPC]
Sampling (statistics)
Function (mathematics)
Traffic flow
Grid
EXPOSURE ASSESSMENT
MODELISATION
BRUIT
Noise
Noise mapping
City noise
Exposure assessment
Mostreig (Estadística)
Algorithm
Mobile sampling
Dynamic noise modeling
Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Recercat. Dipósit de la Recerca de Catalunya
instname
Applied Acoustics
Applied Acoustics, Elsevier, 2019, pp.271-278. ⟨10.1016/j.apacoust.2019.07.020⟩
ISSN: 0003-682X
DOI: 10.1016/j.apacoust.2019.07.020
Popis: This research presents a modeling framework that allows checking the statistical requirements for producing noise maps based on mobile measurements. First, a sound field of reference is created based on a micro-simulation traffic modeling coupled with acoustic modeling, which outputs sound levels each second on a grid of receivers. The aggregated indicators ( L Aeq ) calculated from this sound field serve then as reference. Mobile targets performing measurements evolve within the simulation, aiming to estimate these indicators. The difference between the reference noise map and the one generated by the moving receivers, characterized by the Root Mean Square Error (RMSE), is computed for different aggregation radius of mobile receivers, and as a function of the number of passes-by and to the distance to its nearest cross street. It is observed that the mobile sampling is actually possible and the RMSE can be reduced by setting an optimal aggregation radius and a minimum number of passes-by. With the optimal parameters, 95% of the mobile samples fall within an estimation error interval of [−3.0, 2.2] dBA from the reference. It is also shown that the distance to the nearest cross street affects the estimation error depending on the traffic flow, producing a RMSE greater than 2 dB for distances lower than 30 m.
Databáze: OpenAIRE
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