Open AccessToll Road Roughness Index Forecasting with Combination Grey Forecasting Model and Similarity Spatial Data
Author(s) -
R. Nurhadiansyah,
Asep Id Hadiana
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/662/2/022065
Subject(s) - international roughness index , unavailability , toll , index (typography) , transport engineering , toll road , computer science , engineering , reliability engineering , surface finish , biology , world wide web , genetics , mechanical engineering
The International Roughness Index (IRI) is used by toll road operators throughout the world as a main standard to quantify road surface roughness. IRI are performed to monitor the pavement conditions to evaluate pavements quality, and is a main supporting factor of safety and driving comfort. In Indonesian toll roads, IRI must be measured by annually with determinate value is ≤ 4 m/km (unit of measurement). The purpose of this research is IRI forecasting on the Pondok Aren - Serpong toll road uses limited data history, testing results in 2013, 2015, 2016 and 2017 with Grey Forecasting Model (GM) method. Because of unavailability of testing results in 2014, this research tried to improve forecasting accuracy using the Similarity Spatial Data (SSD), is the IRI testing result on toll road that have similar characteristics with Pondok Aren - Serpong toll road. The final goal of this research is to determine how much influence the use of SSD in increasing the GM forecasting accuracy.