Evaluation of the FHWA Traffic Noise Model (TNM) for Highway Traffic Noise Prediction in the State of Colorado

Details

• Creators:
  Hankard, Michael ; Cerjan, Jeff ; Leasure, Joshua
• Corporate Creators:
  Hankard Environmental Inc.
• Corporate Contributors:
  Colorado. Department of Transportation. Applied Research & Innovations Branch ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  • Traffic noise
  • Mathematical prediction
  • Noise
  • Evaluation
  • Procedures
  • Statistical analysis
  • Pavements
  • Traffic barriers
  • noise levels
• Publication/ Report Number:
  CDOT-2005-21
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States ; Colorado
• Edition:
  Final Report
• Corporate Publisher:
  Colorado Department of Transportation. Applied Research & Innovations Branch
• Description:
  The Federal Highway Administration's Traffic Noise Model (TNM) versions 2.1 and 2.5 were analyzed to determine their functionality and accuracy in Colorado. First, predicted levels were compared to noise levels measured at 42 locations at 13 sites throughout Colorado. In general, TNM predicted within ± 2 dB of the measured noise levels. Second, each of TNM's input parameters was varied through its useful range. The results for the Hard Soil ground type, barrier insertion loss, flow control, and parallel barriers do not completely agree with known acoustical principles and should be studied further. Finally, TNM results were compared to those of the German RLS90, Nordik Statens Planverk, and STAMINA noise models. TNM exhibits a faster decay rate than all of the other models, and predicts higher insertion loss than the other models for low height barriers.
• Format:
  PDF
• Funding:
  03 HTD 00062
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/93078/dot_93078_DS1.pdf
• File Type:
  [PDF - 7.94 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:fccf77780d3e73bbbde042dd0949f4205b2fefd4cd5ff6c1550dfb72cb8170f1fd279074a611166bee610cc4eb82c4e26ab8e3e49bf44f07c58d9dab0c624b56