Virginia Tech Transportation InstituteGagnon, JeffEvans, RobertArulrajah, Arul2015-08-112015-08-112015-06-04Evans, R., & Arulrajah, A. (2015, June). Identifying waveband roughness in highway pavements using power spectral density analysis. Paper presented at the 9th International Conference on Managing Pavement Assets, Alexandria, VA. Presentation retrieved from www.apps.vtti.vt.edu/PDFs/icmpa9/session7/Evans.pdfhttp://hdl.handle.net/10919/56375The international roughness index and the ride number are the most common road profile indices used throughout the world today, which are both based on the response of a simulated passenger car travelling at 80 km per hour. Unfortunately, both of these indices only provide a summary of the road condition (according to a passenger vehicle) and do not provide any information about the likely cause of pavement deterioration or provide any insight into the most effective maintenance strategy to employ to remedy the pavement. As past studies have postulated that there is link between type of waveband roughness present in a pavement and cause of deterioration, a series of new waveband profile indices using Power Spectral Density (PSD) analysis have been developed to quantify the amount of waveband roughness present in a pavement. Moreover, these profile indices have been developed into a series of easy to use templates that can identify pavement sections containing abnormally high concentrations of waveband roughness (particularly long wavelength roughness). By identifying the dominant roughness waveband that contributes most towards pavement deterioration, better future maintenance decisions should naturally result. Although these waveband identification templates have been based on a set of rural highways in north-west Victoria, Australia, the methodology could be applied to other pavement sets throughout the world.22 pagesapplication/pdfen-USIn CopyrightPresentationwww.apps.vtti.vt.edu/PDFs/icmpa9/session7/Evans.pdf