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A Statistical Analysis of Factors Associated with Driver-Perceived Road Roughness on Urban Highways

Description: This study linked physical quantitative roadway measures with subjective, driver-perceived measures of roughness on urban highways. 56 participants from the general public were placed in normal traffic conditions and asked their opinions about pavement roughness on 40 predetermined highway test segments. Driver evaluations were collected with other data, such as speed and in-vehicle noise, and matched with driver-specific socio-demographic data and pavement-specific data from the Washington State Department of Transportation and its pavement management system.
 
Results from an ordered logit model indicated that the international roughness index (IRI) is the single best predictor of driver-perceived road roughness and driver acceptability. Pavements with low IRI values generally corresponded with low roughness rankings and high levels of user acceptability. Other factors statistically associated with driver-perceived measures of road roughness included measured IRI, the presence of pavement maintenance, the presence of joints or bridge abutments, the age of the pavement surface, the vehicle type, levels of in-vehicle noise, the speed of vehicle, and the gender and income of the driver.
 
This study also provided empirical data that can be used to both support or challenge the federal IRI acceptability threshold of 170 in./mi (2.7 m/km) recommended by the Federal Highway Administration.

  • Date Published: June, 2002
  • Publication Number: WA-RD 538.1
  • Last Modified: May 1, 2007
  • Authors: Kevan Shafizadeh, Fred Mannering, Linda Pierce.
  • Originator: Washington State Transportation Center (TRAC)
  • # of Pages: 138 p., 1,068 KB (PDF)
  • Subject: Drivers, Evaluation, Logits, Pavement management systems, Roughness, Statistical analysis, Urban highways.
  • Keywords: Pavement preservation, roughness, international roughness index, ride quality, roadways, pavement management systems, probability, statistics.
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This abstract was last modified April 29, 2008