Publication detail

Neural Network-Based Train Identification in Railway Switches and Crossings Using Accelerometer Data

KRČ, R. PODROUŽEK, J. KRATOCHVÍLOVÁ, M. VUKUŠIČ, I. PLÁŠEK, O.

Original Title

Neural Network-Based Train Identification in Railway Switches and Crossings Using Accelerometer Data

Type

journal article in Web of Science

Language

English

Original Abstract

This paper aims to analyse possibilities of train type identification in railway switches and crossings (S&C) based on accelerometer data by using contemporary machine learning methods such as neural networks. That is a unique approach since trains have been only identified in a straight track. Accelerometer sensors placed around the S&C structure were the source of input data for subsequent models. Data from four S&C at different locations were considered and various neural network architectures evaluated. The research indicated the feasibility to identify trains in S&C using neural networks from accelerometer data. Models trained at one location are generally transferable to another location despite differences in geometrical parameters, substructure, and direction of passing trains. Other challenges include small dataset and speed variation of the trains that must be considered for accurate identification. Results are obtained using statistical bootstrapping and are presented in a form of confusion matrices.

Keywords

Neural Network-Based Train Identification; Railway Switches and Crossings; Accelerometer Data

Authors

KRČ, R.; PODROUŽEK, J.; KRATOCHVÍLOVÁ, M.; VUKUŠIČ, I.; PLÁŠEK, O.

Released

24. 11. 2020

Publisher

Hindawi

ISBN

0197-6729

Periodical

JOURNAL OF ADVANCED TRANSPORTATION

Year of study

2020

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

1

Pages to

10

Pages count

10

URL

https://www.hindawi.com/journals/jat/2020/8841810/

Full text in the Digital Library

http://hdl.handle.net/11012/196564

BibTex

@article{BUT168007,
  author="Rostislav {Krč} and Jan {Podroužek} and Martina {Floriánová} and Ivan {Vukušič} and Otto {Plášek}",
  title="Neural Network-Based Train Identification in Railway Switches and Crossings Using Accelerometer Data",
  journal="JOURNAL OF ADVANCED TRANSPORTATION",
  year="2020",
  volume="2020",
  number="1",
  pages="1--10",
  doi="10.1155/2020/8841810",
  issn="0197-6729",
  url="https://www.hindawi.com/journals/jat/2020/8841810/"
}