A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain

摘要

In this paper, we present a prototype model based on logistic regression analysis, with the aim to understand better the impact of temperature on heat-related incidents on the rail network in Britain. The work draws support from climatic, geographical, and vegetation data resources, and investigates ways in which these data may be used to predict when and where heat-related incidents will most likely occur, thus enabling us to gain a deeper understanding of the conditions that prevail in sites at risk of heat-related disruption events on the rail network in Great Britain. The method is demonstrated using historical records of heat-related incidents within the Anglia area between 2006/07 and 2014/15. By considering a selection of variables, the initial results show that the prototype has good overall performance in terms of both understanding as well as prediction of heat-related incident occurrence.