Detecting Patterns in Train Position Data of Trains in Shunting Yards

Analysis of Arrival Time Distributions and Delays

Bachelor Thesis (2024)
Author(s)

A.C. Krudde (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

MM De Weerdt – Mentor (TU Delft - Algorithmics)

Issa K. Hanou – Mentor (TU Delft - Algorithmics)

J. Sun – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2024
Language
English
Graduation Date
27-06-2024
Awarding Institution
Delft University of Technology
Project
CSE3000 Research Project
Programme
Computer Science and Engineering
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Shunting yards are locations next to train stations that serve as parking places for trains when they are not in operation and often contain facilities for maintenance and cleaning for passenger trains. Planning of the tasks regarding shunting trains involves routing, assignment of tracks, and scheduling tasks. This is done manually and requires a lot of effort, making it inefficient. Identifying patterns specific in the arrival times of trains at shunting yards can help to predict future train arrivals and potential delays throughout the year more accurately. This enables the alignment of staff and equipment with train arrivals, minimizing idle time and optimizing cost efficiency.
This research focuses on extracting and analyzing the arrival times of trains at shunting yards using a dataset consisting of GPS data. It conducts two algorithms to cluster the given data for each train unit within and across days to identify the same train across different days. Distributions and heatmaps of the arrival times and delays are created based on the identified train series. They are analyzed to identify patterns in train arrival times and delays across different months.

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