ArticleScientific reports2025
Estimating railway track curvature using gyroscope and GPS sensors.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The horizontal curvature of railway tracks plays a significant role in vehicle‒track dynamics, and accurate knowledge of the track curvature is essential for vehicle operators to fully understand the running behavior of vehicles. However, it is generally difficult for wagon operators or researchers to obtain track geometry information due to confidential reasons. Using sensors installed on wagons is an alternative to estimate the track curvature. This paper proposes and compares two methods for estimating the track curvature: the gyro method and the GPS method. The gyro method calculates the curvature by analyzing the car body's yaw rate relative to its running velocity, while the GPS method utilizes the two-dimensional (2D) trajectory of the vehicle. First, a multibody system (MBS) simulation including a three-wagon train passing through a curve with a radius of 300 m is conducted, and it aims to study the influence of measured positions on the car-body and longitudinal compressive forces (LCFs) on the gyro method. A theoretical analysis of the GPS method highlights the significance of sampling distance and signal precision on the accuracy of curvature estimation. Secondly, an experimental study by installing a gyroscope sensor, a GPS sensor, and several accelerometers on a wagon is performed to compare the effectiveness of these two methods. The results that both methods can be used to estimate the track curvature and the gyro method has an obvious advantage when estimating the running curvature in complex track sections with many crossovers and parallel lines. Additionally, two applications are demonstrated: one involves utilizing the gyroscope and GPS sensors to determine the real running trajectory of the train, while the other integrates accelerometers to monitor the wheel‒rail interaction during a long journey.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.