Estimation of the vibrational ride quality of local buses using the international roughness index (Construction of the estimate equation using big data)

Abstract

As a road pavement assessment tool, this paper presents an equation to estimate the vibrational ride comfort of local fixed-route buses from the international roughness index (IRI) and the bus speed. Before construction of the equation, all the needed data was collected as big data: The bus data such as acceleration, speed and position have been collected with the built-in accelerometer and GPS sensor of a smartphone for about 100 days on three national routes. After the measurement, according to ISO2631-1, the ride comfort was quantified as a running r.m.s of the frequency-weighted acceleration on a passenger seat. The IRI was measured every 10 meters with the Class 3 method. It was observed that the ride comfort was weakly correlated with the speed and moderately correlated with the IRI. For the large and the medium buses, two estimate equations were constructed in the form of a function with arguments of the bus speed and the IRI. Their parameters were determined by applying the data fitting technique to the collected big data. The estimate equations give the correlation coefficients of 0.70 to 0.79 and the root mean squared errors of 0.08 to 0.13 m/s2 between the mean values of the measured ride comfort and their estimates on the 10-meter road segments.

Keywords

• vibrational ride comfort
• estimation
• local bus
• big data
• data fitting
• road repair