This paper proposes a model to assess train passing a red signal without authorization, a SPAD. The approach is based on Big Data techniques so that many types of data may be integrated, or even added at a later date, to get a richer view of these complicated events. The proposed approach integrates multiple data sources using a graph database. A four-steps data modeling approach for safety data model is introduced. The steps are problem formulation, identification of data points, identification of relations and calculation of the safety indicators. A graph database was used to store, manage and query the data, whereas R software was used to automate the data upload and post-process the results. A case study demonstrates how indicators have extracted that warning in the case that the SPAD safety envelope is reduced. The technique is demonstrated with a case study that focuses on the detection of SPADs and safety distances for SPADs. The latter provides indicators for to assess the severity of near-SPAD incidents.
|Number of pages||5|
|Issue number||Part B|
|Early online date||6 Dec 2017|
|Publication status||Published - 1 Dec 2018|
FingerprintDive into the research topics of 'A big data modeling approach with graph databases for SPAD risk'. Together they form a unique fingerprint.
Rawia El Rashidy
- Department of Engineering and Technology - Senior Research Fellow
- School of Computing and Engineering
- Institute of Railway Research - Member