Relationship analysis between deterioration of switch support and railway passenger comfort using machine learning

Aug 2, 2026

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Passenger comfort is a critical performance factor for railway transportation, affecting satisfaction, health and well-being, economics, competitiveness, and safety. Railway switches and their associated support components can degrade due to geometry changes, operational functions, and applied loads, producing vibration, noise, and instability that passengers perceive as discomfort. This study investigates the relationship between switch support deterioration and passenger comfort using machine learning, training a convolutional neural network on axle box accelerations generated from verified multi-body simulations. Model accuracy exceeds 80%, supporting data-driven maintenance and comfort evaluation.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages5

Reading Time13 min

AccessFree to download

Introduction

Literature review

Relationship analysis between deterioration of switch support and railway passenger comfort using machine learning Jessada Sresakoolchai 1*, Ni-Asri Cheputeh 2 1Department of Civil and Environmental Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla, Thailand 2Department of Mechanical and Mechatronics Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla, Thailand Abstract. Passenger comfort is one of the critical factors in the railway system. Passenger comfort plays an important role in the success and effectiveness of railway transportation systems in terms of passenger satisfaction, health and well-being, economy, competition capability, and safety. For the railway infrastructure, one of the important components is a switch. Switches in the railway system have the function of guiding rolling stocks or trains to the preferred directions and tracks. However, switches are the components of the railway infrastructure that can negatively affect railway passenger comfort due to their geometry and the functions that are used to change the direction of rolling stocks. This study aims to study the relationship between the deterioration of railway switch support and railway passenger comfort by using machine learning. The data used in the study are axle box accelerations that are numerically simulated from verified multi-body simulation models. The machine learning technique used in the study is the convolutional neural network. The indicator used to evaluate the machine learning model's performance is the accuracy. From the machine learning model development and training, the accuracy of the machine learning model is higher than 80% which is satisfied. Railway operators can benefit from the study’s findings by applying the developed machine learning model to collect data to evaluate the deterioration of railway switch support and the effect on railway passenger comfort. Keywords: public transportation, railway transportation, railway switch, passenger comfort, machine learning 1 Introduction The railway transportation system plays an important role in urban and interurban mobility due to its advantages such as reliability, efficiency, sustainability, safety, and environmental friendly. One of the factors that make passengers choose to travel using railway transportation is passenger comfort which is relatively high compared to other modes of transportation. In this case, one of the key factors influencing passenger comfort is the condition of railway infrastructure, particularly the railway switches. As other components of railway infrastructure, railway switches deteriorate along the usage of the railway infrastructure especially railway switches that are applied by high loads because switches are used to guide rolling stocks. Besides the switches themselves, the supports of switches also deteriorate along the usage of the railway infrastructure. The deterioration of switch support can significantly affect the smoothness of the ride, causing vibrations, noise, and instability that passengers can perceive as discomfort [1] . Railway switches have a critical influence on the smooth transition of trains between tracks. However, over time, railway switches will wear and tear due to stress and environmental factors. In addition, switch support can deteriorate due to the loads applied to the railway infrastructure. The switch support deterioration can result in a settlement or lower stiffness that affects the stability of the railway infrastructure. The deterioration of switch support not only impacts the operational efficiency and safety of railway systems but also directly influences passenger comfort. Passengers experiencing vibrations due to the instability of the switch support may experience an uncomfortable journey. The discomfort can lead to dissatisfaction and spoiled well-being of passengers. This study aims to analyze the relationship between the deterioration

FAQs

Why is passenger comfort important in railway transportation?

Passenger comfort strongly influences passenger satisfaction, health and well-being, and overall effectiveness of railway transportation, including safety and economy.

How does switch support deterioration affect passenger experience?

Deterioration can reduce stiffness or cause settlement, leading to vibrations, noise, and instability that passengers perceive as discomfort.

What machine learning approach and data are used in this study?

A convolutional neural network is trained using axle box accelerations generated from verified multi-body simulation models, with varying parameters such as vehicle speed, weight, and support stiffness.

Aug 2, 2026

Upload by Rowan