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Abstract-Roughness is good evaluator of performance of road. This paper presents a case study of IRI (International Roughness Index) estimation at NH 67 during four laning of Trichy - Tanjavur section. An attempt has been made to evaluate the IRI of construction work zones using Levenberg- Marquardt back-propagation training algorithm. A MATLAB based model is developed, and the data from the case study are used to train and test the developed model to predict IRI. The models' performances are evaluated through Correlation coefficient (R2) and Mean Square Error (MSE).
In d exTe rms-Ro u g h n e s s , In t e rn a t i o n a lRo u g h n e s s IndexConstruction Work Zones.
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I. INTRODUCTION
Roughness is defined as the deviation of a surface from a true planar surface with characteristics dimensions that affect vehicle dynamics and ride quality (ASTM Specification E867- 2A). Many indices are developed for quantification of road roughness. Some widely used indices include International Roughness Index (IRI), Ride Number (RN), Profile Index (PI) etc. The International Roughness Index (IRI) was established in 1986 by the World Bank.
It was first introduced in the International Road Roughness Experiment (IRRE) that was held in Brazil. The IRI is internationally accepted standard for calibration of roughness measuring instruments. The IRI is based on simulation of the roughness response of a car travelling at 80 km/h which expresses a ratio of the accumulated suspension motion of a vehicle, divided by the distance travelled during the test IRI and RN are commonly used because of their stability and reproducibility [2].
Artificial neural networks, Genetic programming and Fuzzy techniques have great variety of applications in Transportation engineering and are capable of modeling uncertain relationships. Numerous researches have been conducted to evaluate pavement condition. Rada [1] proposed a life cycle cost model and a cost effectiveness method for project level pavement management. Mactutis [4] et al had done investigations on the relationship between IRI, rutting and cracking using large database.
Dewan and Smith [5] had derived a linear relationship between IRI and pavement condition based on 39 observations. Lin et al [6] had analyzed the relationships between IRI and pavement distress based...