PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

Train-induced ground-borne vibration has a negative effect on residential areas near railway tracks. Residents who are regularly exposed to ground-borne vibration can experience sleep disturbances and more serious health problems in the long run. In addition, it concerns the mental health of those who live nearby. Residents’ productivity and quality of life can be harmed as a result of direct exposure to train-induced ground-borne vibration. The relevant authorities must record a few precise measurements using technically sophisticated instruments and equipment to research further the impact of ground-borne vibrations induced by train traffic. However, the equipment is usually costly, and it has become one of the main stumbling blocks to achieving the desired results. This paper aimed to propose an alternative to the authority’s current guidelines and standards for vibration limits and environmental control. This research established a regression prediction model to forecast the peak particle velocity of commuter train ground-borne vibration. The established model considered a few parameters obtained from site surveys with limited or no tools at all. The data collected was measured along the ground rail tracks involving human-operated trains. Residents living in landed residential areas near railway tracks were selected as the recipients. Finally, the peak particle velocity models were established, validated, and a sensitivity analysis was carried out.

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