Results of accelerometer measurements in rail passenger transport vehicles

As part of the project, field research was done to better understand how unbalanced accelerations affect passenger comfort in rail transport and to compare this with passengers’ actual, subjective feelings. Data were collected from different types of rail vehicles, like trains and trams, using common mobile devices with MEMS accelerometer sensors.
The research included measuring unbalanced accelerations inside Electric Multiple Units (EMU), Diesel Multiple Units (DMU), and trams. Measurements were taken in cities like Bydgoszcz, Toruń, Olsztyn, and Gdańsk, and on various railway lines, such as lines no. 9, 353, 131, 18, 248, 21, 214, 229, 202, 213, and 250. During the research, the speed of the vehicle, geographical coordinates, unbalanced accelerations in a three-axis reference system, and passengers’ comfort feelings were recorded according to the NMV ISO PN-EN 12299 scale.
The final result was a large dataset with over 19 GB of uncompressed data and metadata. These data were processed and saved in .csv, .txt, and .xlsx formats. They were organized into folders by type of transport, measurement name, and file format. Summary data sets were also created, including information like measurement location, track gauges, dates and times of measurements, line and vehicle numbers, measurement station numbers, raw data file names, and the model of the measuring device.
Preliminary analysis showed that the travel comfort index calculated according to the PN-EN 12299:2009 standard might differ from passengers’ feelings. Comfort indicators should be adjusted to specific conditions and types of vehicles. Using mobile devices for research might have affected the accuracy of the results. Further research should use calibrated equipment, compare results, and introduce correction factors. It is also worth considering developing a custom Android app for such measurements, based on the experience gained from this project.
The research was funded by the MINIATURA_7 grant awarded by the National Science Centre (NCN).