Train Performance Analysis Using Heterogeneous Statistical Models

This study investigated the effect of a harsh winter climate on the performance of high-speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance to take time-varying risks of train delays into consideration...

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Bibliographic Details
Published in:Atmosphere
Main Authors: Jianfeng Wang, Jun Yu
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2021
Subjects:
stratified Cox model
heterogeneous Markov chain model
likelihood ratio test
primary delay
arrival delay
Meteorology. Climatology
QC851-999
Northern Sweden
Online Access:https://doi.org/10.3390/atmos12091115
https://doaj.org/article/8c4f7e8d86ab4a0b84766bac91a36b15
Description
Summary:This study investigated the effect of a harsh winter climate on the performance of high-speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance to take time-varying risks of train delays into consideration. Specifically, the stratified Cox model and heterogeneous Markov chain model were used to model primary delays and arrival delays, respectively. Our results showed that weather variables including temperature, humidity, snow depth, and ice/snow precipitation have a significant impact on train performance.

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