Train Performance Analysis Using Heterogeneous Statistical Models

Abstract

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.

Keywords

• stratified Cox model
• heterogeneous Markov chain model
• likelihood ratio test
• primary delay
• arrival delay