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research article

Traffic congestion and noise emissions with detailed vehicle trajectories from UAVs

Espadaler-Clapes, Jasso  
•
Barmpounakis, Emmanouil  
•
Geroliminis, Nikolas  
August 1, 2023
Transportation Research Part D-Transport And Environment

Excessive noise in cities due to road traffic negatively affects human health. We utilize detailed vehicle trajectories collected by a swarm of drones to estimate traffic noise emissions in an urban environment. We use the CNOSSOS model to estimate vehicles' sound power level. Considering each vehicle an individual source point, we compute the noise levels at four bus stops, analyze their noise patterns and quantify their contribution. Using well-known acoustic metrics like the equivalent continuous sound level, we perform a sensitivity analysis of the radius around an evaluation point to compute the noise levels. We show the correlation between noise emissions and congestion at the microscopic level, and we analyze noise levels at the macroscopic level due to better sound propagation integration. The results show clear trends for sound power level and differences across them. Finally, the aggregated equivalent continuous sound levels present a clear pattern with vehicle accumulation.

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Type
research article
DOI
10.1016/j.trd.2023.103822
Web of Science ID

WOS:001147271000001

Author(s)
Espadaler-Clapes, Jasso  
Barmpounakis, Emmanouil  
Geroliminis, Nikolas  
Date Issued

2023-08-01

Publisher

Pergamon-Elsevier Science Ltd

Published in
Transportation Research Part D-Transport And Environment
Volume

121

Article Number

103822

Subjects

Life Sciences & Biomedicine

•

Technology

•

Noise Emissions

•

Swarm Of Drones

•

Traffic Flow

•

Trajectory Data

•

Multimodal Systems

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LUTS  
FunderGrant Number

Swiss National Science Foundation

200021_188590

Available on Infoscience
February 23, 2024
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/205330
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