This package provides tools to compute...
- noise (emission) levels on network links (based on traffic volume, share of heavy goods vehicles, speed level)
- noise (immission) levels at receiver points (based on the surrounding links' emissions and distances)
- population units (= population densities) at receiver points (mapping agents to the nearest receiver point)
- noise damages (= noise exposure costs) at receiver points (based on population units and noise levels)
The computation of noise levels is based on the German RLS 90 approach (Richtlinien fuer den Laermschutz and Strassen, Forschungsgesellschaft fuer Strassen- und Verkehrswesen), but applies some simplifications and minor modifications. Thus, noise levels should be considered as estimates rather than exact values. The conversion of noise exposures into monetary costs follows a slightly modified version of the German EWS approach (Empfehlungen fuer Wirtschaftlichkeitsuntersuchungen an Strassen, Forschungsgesellschaft fuer Strassen- und Verkehrswesen). A more detailed description of the computation methodology and the model limitations is provided in the related publications.
For examples see the examples package.
All relevant parameters such as the temporal and spatial resolution are specified in the NoiseConfigGroup.
Related publications (list not regularly updated):
- I. Kaddoura, L. Kroeger, and K. Nagel. User-specific and dynamic internalization of road traffic noise exposures. Networks and Spatial Economics, 2016. DOI: 10.1007/s11067-016-9321-2. Preprint available here.
- I. Kaddoura and K. Nagel. Activity-based computation of marginal noise exposure costs: Implications for traffic management. Transportation Research Record 2597, 2016. DOI: 10.3141/2597-15. Preprint available here.
- N. Kuehnel, I. Kaddoura and R. Moeckel. Noise Shielding in an Agent-Based Transport Model Using Volunteered Geographic Data. Procedia Computer Science Volume 151, 2019. Pages 808-813 DOI: 10.1016/j.procs.2019.04.110. Available from here.