Brown coal areas as attactive living areas using road noise simulation based on existing traffic data for noise minimisation

Traffic noise is an important factor for the design of pleasant living spaces. Perception-based prediction of noise exposure in urban, development and traffic planning offers great potential, but is not available nowadays. Though, approaches for simulation-based prediction of sound propagation already exist. A realistic representation of the vehicle noise sources including the vehicle movement, the consideration of the environment and noise reduction measures as well as the auralization of the noise, however, remains to be developed.

Thus, in BaLSaM, a validated tool for the auralization of road traffic noise in transportation scenarios is to be implemented. For this purpose, source, transmission and receiver characteristics as well as motion patterns from traffic data and possible noise reduction measures will be considered. Simulation methods and concepts as well as human perception will be addressed. The potential to utilise available data from traffic and planning will be demonstrated and published using example scenarios. In the future, the generated tool will be used for both new and re-planning of vehicular traffic routes as well as for the development of urban planning concepts in order to offer cyclists, pedestrians and residents a quieter and more pleasant environment.

The Institute for Automotive Engineering (ika) is responsible for the overall project description as well as for the source description task. The objective is to model the noise characteristics of vehicles based on available traffic data. In order to provide the input data for the sound propagation simulation, time-domain source models are developed that include both tire rolling and AVAS (Acoustic Vehicle Alerting System) noise. For verification of the source-transfer path-receiver model, the developed method will be verified by measurements on the vehicle in its entirety and suitable scenarios, which will be investigated simulatively, will be replicated.

About the BMDV's mFUND funding program:

As part of the mFUND innovation initiative, the BMDV has been funding data-based research and development projects for the digital and connected mobility of the future since 2016. Project funding is complemented by active professional networking between stakeholders from politics, business, administration and research. Open data is made available via the Mobilithek. For more information, visit



Carolin Schliephake M.Sc.
+49 241 80 25660

Project duration

11/2023 – 10/2025

Project partner

Institute for Hearing Technology and Acoustics incl. the PAAD research group of the RWTH Aachen University, HEAD acoustics GmbH, REICHER HAASE ASSOZIIERTE GMBH

Supported by

[Logo: BM Digitales und Verkehr][Logo: mFUND]Förderung erfolgt durch das BMDV im Rahmen der Innovationsinitiative mFUND


Institute for Automotive Engineering
RWTH Aachen University
Steinbachstraße 7
52074 Aachen · Germany
+49 241 80 25600

We use cookies on our website. Some of them are essential for the operation of the site, while others help us to improve this site and the user experience (tracking cookies). You can decide for yourself whether you want to allow cookies or not. Please note that if you reject them, you may not be able to use all the functionalities of the site.