Fuzzy renewal theory about forecasting mistakes done by a locomotive driver: a serbian railway case study

Abstract

The human factor is one of the most dominant causes of railway accidents. For example, human impact appears to be the main reason for 44% of railway accidents in the Republic of Serbia. Thus, a remarkable effort is undertaken to investigate human factors. Therefore, plenty of researchers have analyzed a human influence on railway accidents. This paper develops a model for forecasting the number of railway accidents caused by the human factor. The proposed model is based on the renewal theory and assumes that working time between the faults of a locomotive driver has exponential distribution (or another Erlang distribution of a higher order) characterized by parameter λ that is treated as a fuzzy dependant variable and considered as a function of job complexity, the exposure of locomotive drivers (i.e. time spent in driving) and a tendency of locomotive drivers to make mistakes. The application of the model to the population of 777 Serbian railway locomotive drivers provided encouraging results in predicting the number of railway accidents.

First Published Online: 09 Jan 2012

Keyword : traffic, railway accident, human factor, fuzzy theory, forecast, locomotive driver