Development of empirical models for ground-borne vibration from road traffic

Ground-borne vibration produced from road traffic has become an area of interest in recent years due to environmental concern. Most countries have encountered the ground-borne vibration problems when the buildings and structures are near the roadway system. The ground-borne vibration may cause annoyance to the people and also can affect buildings and equipment near the roadway system. Many developed countries have designed their own approach on how to overcome the ground-borne vibration problem. In Malaysia, guidelines have been developed to describe the ground vibration threshold. However, no specific technique has been introduced on how to measure the ground vibration level. Furthermore, important parameter such as the soil dynamics factor were not considered in the current ground-borne vibration model. Therefore, the goal of this study was to develop an empirical model that can predict the ground borne-vibration from road traffic towards the surrounding area that would incorporate soil dynamics, pavement characteristics, and traffic parameters. Additionally, this study was undertaken to complement the established Malaysian guidelines using a model developed from empirical multiple regression analysis. The research study involved at eight different sites within Selangor and with single carriageway. Several important parameters such as soil shear wave velocity, international roughness index (IRI), distance from vibration source, vehicles flow rate and speed were collected from site study. Current models were tested with field data to evaluate the reliability. The results indicated inaccurate prediction when it used with local field data. Multiple linear regression analysis with a systematic methodological procedures were used to develop the models. Three empirical models that are reliable to estimate ground vibration were developed in the study. These models are meant for estimating hard ground vibration, soft ground vibration and general ground vibration surrounding the highway area. Several significant parameters were found from the multiple regression analysis for each model. All models had been tested using new dataset and the verification results showed that there is a good agreement between the model predictions and the empirical measurement for all models. The sensitivity analysis has shown that the vehicle flow rate is highly sensitive when predicting soft ground vibration. The distance from the source of vibration is a highly sensitive parameter for predicting hard ground vibration. Finally, the findings of this study can serve as a starting point towards developing national guidelines, for a more sustainable road development and environmental safety.

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