A GIS approach to the development of a segment-level derailment prediction model.

A GIS approach to the development of a segment-level derailment prediction model. Accid Anal Prev. 2021 Jan 22;151:105897 Authors: Chow T, Shah TI, Park PY, Fu L Abstract Train related accidents, particularly derailments, can lead to severe consequences especially when they involve injuries or fatalities or when they involve hazardous materials that might result in environmental impacts. Whereas numerous road safety studies have suggested appropriate approaches to predicting vehicle-to-vehicle collisions, very few railway safety studies have considered predicting the number of derailments on rail tracks in North America. In addition, the existing few rail safety assessment and derailment prediction models have often been constrained by aggregated data limiting the safety assessments by, for example, failing to consider segment-level characteristics. This paper focused on the development of an integrated database for the development of a segment-level derailment prediction model for Canada's rail network. The primary objective of this paper is to report how challenges in the data integration process were overcome and also to develop a network screening tool to identify segments with high derailment risk in Canada's rail network. Negative binomial regression and the Empirical Bayes technique were used to estimate the predicted number of derailments on Canada's rail network at the segment level. A network screening process was then succ...
Source: Accident; Analysis and Prevention. - Category: Accident Prevention Authors: Tags: Accid Anal Prev Source Type: research