Sensing discomfort of standing passengers in public rail transportation systems using a smart phone
This addresses the issue of passenger comfort in urban rail transit, but it is incremental as it applies existing logistic regression to new data.
The paper tackled the problem of measuring standing passenger discomfort in public rail systems by analyzing acceleration data and passenger feedback, resulting in a discomfort index for comparing ride comfort across different rail lines and a predictive method based on acceleration values.
This paper aims to investigate the effect of acceleration on the discomfort of standing passengers. The acceleration levels from different public rail transport lines such as the mass rapid transits (MRTs) and light rail transits (LRTs) of Singapore, as well as the associated qualitative data indicating the discomfort of standing passengers were collected and analyzed. Based on a logistic regression model to analyze the data, a discomfort index was introduced, which can be used to compare various rail lines based on ride comfort. A method for predicting the discomfort of passengers based on the acceleration values was proposed for any given train line.