International Roughness Index
The International Roughness Index (IRI) is the roughness index most commonly obtained from measured longitudinal road profiles. It is calculated using a quarter-car vehicle math model, whose response is accumulated to yield a roughness index with units of slope (in/mi, m/km, etc.). Since its introduction in 1986, IRI has become the road roughness index most commonly used worldwide for evaluating and managing road systems.
The measurement of IRI is required for data provided to the United States Federal Highway Administration, and is covered in several standards from ASTM International: ASTM E1926 - 08, ASTM E1364 - 95(2005), and others. IRI is also used to evaluate new pavement construction, to determine penalties or bonus payments based on smoothness.
In the early 1980s the highway engineering community identified road roughness as the primary indicator of the utility of a highway network to road users. However, existing methods used to characterize roughness were not reproducible by different agencies using different measuring equipment and methods. Even with a given agency, the methods were not necessarily repeatable. Nor were they stable with time.
The United States National Cooperative Highway Research Program (NCHRP) initiated a research project to help state agencies improve their use of roughness measuring equipment. The work was continued by The World Bank to determine how to compare or convert data obtained from different countries (mostly developing countries) involved in World Bank projects. Findings from the World Bank testing showed that most equipment in use could produce useful roughness measures on a single scale if methods were standardized. The roughness scale that was defined and tested was eventually named the International Roughness Index.
The IRI was defined as a mathematical property of a two-dimensional road profile (a longitudinal slice of the road showing elevation as it varies with longitudinal distance along a travelled track on the road). As such, it can be calculated from profiles obtained with any valid measurement method, ranging from static rod and level surveying equipment to high-speed inertial profiling systems.
The quarter-car math model replicates roughness measurements that were in use by highway agencies in the 1970s and 1980s. The IRI is statistically equivalent to the methods that were in use, in the sense that correlation of IRI with a typical instrumented vehicle (called a "response type road roughness measuring system", RTRRMS) was as good as the correlation between the measures from any two RTRRMS's. As a profile-based statistic, the IRI had the advantage of being repeatable, reproducible, and stable with time. The IRI is based on the concept of a 'golden car' whose suspension properties are known. The IRI is calculated by simulating the response of this 'golden car' to the road profile. In the simulation, the simulated vehicle speed is 80 km/h (49.7 mi/h). The properties of the 'golden car' were selected in earlier research to provide high correlation with the ride response of a wide range of automobiles that might be instrumented to measure a slope statistic (m/km). The damping in the IRI is higher than most vehicles, to prevent the math model from "tuning in" to specific wavelengths and producing a sensitivity not shared by the vehicle population at large.
The slope statistic of the IRI was chosen for backward compatibility with roughness measures in use. It is the average absolute (rectified) relative velocity of the suspension, divided by vehicle speed to convert from rate (e.g. m/s) to slope (m/km). The frequency content of the suspension movement rate is similar to the frequency content of chassis vertical acceleration and also tire/road vertical loading. Thus, IRI is highly correlated to the overall ride vibration level and to the overall pavement loading vibration level. Although it is not optimized to match any particular vehicle with full fidelity, it is so strongly correlated with ride quality and road loading that most research projects that have tested alternate statistics have not found significant improvements in correlation.
The IRI is measured using profilometers, which measure the road profile, or by correlating the measurements of RTRRMS to an IRI calculated from a profile. Using World Bank terminology, these are respectively called Information Quality Level (IQL) 1 and IQL-3 devices, representing the relative accuracy of the measurements. A common misconception is that the 80 km/h used in the simulation must also be used when physically measuring roughness with an instrumented vehicle. IQL-1 systems measure the profile direction, independent of speed, and IQL-3 systems typically have correlation equations for different speeds to relate the actual measurements to IRI.
IQL-1 systems typically report the roughness at 10–20 m intervals; IQL-3 at 100m+ intervals. The data can be presented using a moving average to provide a "roughness profile". These IRI profiles are sometimes used to evaluate new construction to determine bonus/penalty payments for contractors, and to identify specific locations where repairs or improvements (e.g., grinding) are recommended. The IRI is also a key determinant of vehicle operating costs which are used to determine the economic viability of road improvement projects.
The Dipstick Profiler, with a reported accuracy of .01 mm ( 0.0004 inches), is the most widely used and accepted Class 1 profiler for the purposes of calibrating profilometers that measure IRI.
- Sayers, M.W., and Karamihas, S.M. (1998). "Little Book of Profiling". University of Michigan Transportation Research Institute. Retrieved 2010-03-07.
- Sayers, M.W., Gillespie, T. D., and Paterson, W.D. Guidelines for the Conduct and Calibration of Road Roughness Measurements, World Bank Technical Paper No. 46, The World Bank, Washington DC, 1986.
- ASTM E1926 - 08 Standard Practice for Computing International Roughness Index of Roads from Longitudinal Profile Measurements
- ASTM E1364 - 95(2005) Standard Test Method for Measuring Road Roughness by Static Level Method
- Gillespie, T.D., Sayers, M.W., and Segel, L., “Calibration of Response-Type Road Roughness Measuring Systems.” NCHRP Rept. No. 228, December 1980
- Data Collection Technologies for Road Management
- Sayers, M.W., Profiles of Roughness. Transportation Research Record 1260, Transportation Research Board, National Research Council, Washington, D.C. 1990
- Modelling Road User and Environmental Costs in HDM-4
- Face® Dipstick® website home page
- Comparison of Roughness Calibration Equipment - with a View to Increased Confidence in Network Level Data; G. Morrow, A. Francis, S.B. Costello, R.C.M. Dunn, 2006
- "Relating Road Roughness and Vehicle Speeds to Human Whole Body Vibration and Exposure Limits" by Ahlin and Granlund in International Journal of Pavement Engineering, volume 3, issue 4, December 2002, pages 207–216.