|
Abstract
|
|
|---|---|
| The principal risks in the railway industry are mainly associated with collisions, derailments and level crossing accidents. An understanding of the nature of previous accidents on the railway network is required to identify potential causes and develop safety systems and deploy safety procedures. Risk assessment is a process for determining the risk magnitude to assist with decision-making. We propose a three-step methodology to predict the mean number of fatalities in railway accidents. The first is to predict the mean number of accidents by analyzing generalized linear models and selecting the one that best fits to the available historical data on the basis of goodness-offit statistics. The second is to compute the mean number of fatalities per accident and the third is to estimate the mean number of fatalities. The methodology is illustrated on the Spanish railway system. Statistical models accounting for annual and grouped data for the 1992-2009 time period have been analyzed. After identifying the models for broad and narrow gauges, we predicted mean number of accidents and the number of fatalities for the 2010-18 time period. | |
|
International
|
Si |
|
|
10.1142/9789814417747_0176 |
|
Book Edition
|
|
|
Book Publishing
|
World Scientific |
|
ISBN
|
978-981-4417-73-0 |
|
Series
|
Computer Engineering and Decision Making |
|
Book title
|
Uncertainty Modeling in Knowledge Engineering and Decision Making |
|
From page
|
1099 |
|
To page
|
1104 |