KNOWLEDGE-BASED PREPROCESSOR FOR TRAFFIC NOISE PREDICTION

A knowledge-based preprocessor system has been developed to assist the engineer in creating data input files for the STAMINA 2.0 traffic noise prediction program. The preprocessor used rule-based heuristic knowledge for certain decisions, algorithmic routines to provide data to the rules and to help automate the file creation process, and linkages to editing routines for manual manipulation. The system is used as the engineer works with a design project's plans. The system requests certain data from the user, and ultimately creates two STAMINA input files. The first file contains the baseline noise barriers as starting points for final barrier design with a companion program called OPTIMA, and the second file contains only the ground-line elevations for accurate assessment of no-barrier levels. System performance was tested on two major analysis areas on each of two design projects previously done by human experts. In all cases, the system created syntactically correct STAMINA input files that resembled those of the experts and produced meaningful sound level results when run. In some cases, these STAMINA files resulted in barrier insertion loss predictions very similar to those produced by the experts using the OPTIMA program. Although it was not the intent of this work to replace use of OPTIMA, the files produced by the system should reduce time spent using OPTIMA, as well as time typically spent making modifications to the STAMINA files. Although fully functioning, the system should be considered an operational prototype until further testing and refinement.

Media Info

  • Features: Figures; References; Tables;
  • Pagination: p. 36-48
  • Monograph Title: Energy and environment 1990: transportation-induced noise and air pollution
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00497404
  • Record Type: Publication
  • ISBN: 030905009X
  • Files: TRIS, TRB, ATRI
  • Created Date: Sep 30 1990 12:00AM