STATISTICAL ESTIMATION OF ROAD TRAFFIC NOISE IN AN ARBITRARY SOUND PROPAGATION ENVIRONMENT BY USE OF STRATONOVICH'S THEORY FOR A RANDOM POINTS SYSTEM

To date, many methods for estimating the statistics of road traffic noise have been proposed involving the introduction of particular vehicle distribution models, such as an equally spaced model, an exponentially distributed model, or an Erlang distribution type model, in a simplified sound propagation environment such as a free sound field. In certain more generalized studies based particularly on the latest Erlang distribution type model (i.e, a gamma distribution model), only the first and second order moments of the sound intensity fluctuation, which can be derived from statistical information on the location of only one and/or two vehicles (e.g, the distributions of the positions of the vehicles and of the distance between two arbitrary vehicles, moving in the same direction) have been taken into consideration. The higher order statistical properties of traffic noise are important, however, if one wishes to take into account the form of the noise distribution, from which any noise evaluation index must be derived. Thus, this paper is devoted to considering the relationships between the multi-dimensional correlation properties of the sound intensity and the higher order information on the flow of vehicles by use of stratonovich's stochastic theory for A random points system. The relationships between the theoretical results and those of well-known previous studies are discussed for several lower order moments.(a) (TRRL)

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0022460X
• Corporate Authors:

  Academic Press Incorporated

  24-28 Oval Road
  London NW1 7DX,   England 
• Authors:
  • Ohta, M
  • Yamaguchi, S
  • Ikuta, A
• Publication Date: 1980-3-22

Media Info

• Features: Figures; References;
• Pagination: p. 275-284
• Serial:
  • Journal of Sound and Vibration
  • Volume: 69
  • Issue Number: 2
  • Publisher: Elsevier
  • ISSN: 0022-460X
  • EISSN: 1095-8568
  • Serial URL: http://www.sciencedirect.com/science/journal/0022460X

Subject/Index Terms

• TRT Terms: Correlation analysis; Distributions (Statistics); Estimating; Estimation theory; Length; Location; Mathematical models; Noise; Physical distribution; Statistical analysis; Statistics; Stochastic processes; Traffic noise
• ITRD Terms: 6572: Distribution (stat); 132: Forecast; 6488: Length; 9061: Location; 6473: Mathematical model; 6748: Sound; 6555: Statistics
• Subject Areas: Data and Information Technology; Environment; Freight Transportation; Highways;

Filing Info

• Accession Number: 00319557
• Record Type: Publication
• Source Agency: Transport Research Laboratory
• Files: ITRD, TRIS
• Created Date: Feb 6 1981 12:00AM