Integrating data to support SPAD management

A stop signal passed without authority (aka SPAD) is one of the most serious types of incidents in railways since they potentially cause derailments or collisions. SPADs are complex incidents that have been usually analysed as human factors incidents. Human errors of train drivers such as slips or lapses have been prevalent in SPAD incident investigations. In the big data era, alternatives to the traditional methods can be used to support SPAD analysis of whatever kind. Railway systems produce a huge amount of data from a variety of data sources that can be used to get a better understanding of the factors involved in SPADs. This paper describes a first trial within the Big Data Risk Analysis program (BDRA) in order to combine unstructured data from SMIS/IFCS text records with structured data from of railway signals in order to support the SPAD management.