A statistical analysis of factors associated with driver-perceived road roughness on urban highways.

摘要

This study linked the driving public's perception of road roughness and quantifiable measures of road roughness, along with individual and vehicle characteristics. 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. Subjective driver evaluations were collected along 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 (WDOT) and its pavement management system.; Results from a series of statistical analyses and econometric models (including, but not limited to, analysis of variance, regression, ordered and binary probability models with random and fixed effects) 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. The findings indicate that, while measured IRI levels provide the strongest indication of rankings and acceptability, other factors were also statistically significant. 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 examine the federal IRI acceptability threshold of 170 in/mi (2.7 m/km) recommended by the Federal Highway Administration.