Tag: Grey Forecasting Model IRI

  • Toll Road Roughness Index Forecasting with Combination Grey Forecasting Model and Similarity Spatial Data

    Toll Road Roughness Index Forecasting with Combination Grey Forecasting Model and Similarity Spatial Data

    Authors: Nurhadiansyah R. ; Hadiana A.

    DOI: 10.1088/1757-899X/662/2/022065

    Abstract

    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. © Published under licence by IOP Publishing Ltd.

    Indexed keywords

    Engineering controlled terms

    Pavements; Safety factor; Surface roughness; Toll highways

    Engineering uncontrolled terms

    Driving comfort; Forecasting accuracy; Grey forecasting model; International roughness index; Pavement condition; Road roughness; Road surface roughness; Supporting factors

    Engineering main heading

    Forecasting

    This article can be accessed at: https://www.scopus.com/pages/publications/85075867499