Development of a Decision Support System for Road Maintenance Scheduling
Akindele Opeyemi Areegbe, Abiodun Alani Ogunseye, Naheem Olakunle Adesina, Thomas Kokumo Yesufu "Development of a Decision Support System for Road Maintenance Scheduling", International Journal of Engineering Trends and Technology (IJETT), V50(3),150-154 August 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The work developed and evaluated the performance of a vehicle vibration monitoring system for road maintenance scheduling. The developed system consist of an ADXL335 three-axis accelerometer to detect vehicle vibration; an Arduino Uno microcontroller board for data conditioning and storage; and a GPSMAP 78s Global Positioning System (GPS) receiver for obtaining the geographical coordinates of the location and the vehicle velocity. The developed system, attached to a test vehicle, samples the vehicle vibration signal, conditions, stores and sends the sampled data to a personal computer (PC) via a USB connection. The International Roughness Index (IRI) and Road Quality Index (RQI) of the test road sections were calculated from the standard deviation of the acquired vehicle vibration data with a MATLAB program running on the PC. The RQI result showed that the roads can be classified into excellent, smooth and rough road sections per selected road. For a selected road with five (5) classified sections having an overall “smooth” outlook, the highest and lowest value of RQIs were 1.691 and 1.436 respectively; for another selected road having an overall “rough” outlook with ten (10) classified sections, the highest and lowest RQIs were 1.940 and 0.000 respectively. The study concluded by developing a system that can be used to prioritize the maintenance of failing road sections. This can aid road maintenance agencies to schedule road maintenance work appropriately.
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Road Surface Roughness, Scheduling, Road Quality Index, Roughness index, microcontroller.