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A Big Data modeling approach with graph databases for SPAD risk

EL Rashidy, Rawia Ahmed Hassan, Hughes, Peter, Figueres-Esteban, Miguel, Harrison, Chris and Van Gulijk, Coen (2017) A Big Data modeling approach with graph databases for SPAD risk. Safety Science. ISSN 0925-7535 (In Press)

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Abstract

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.

Item Type: Article
Subjects: T Technology > TF Railroad engineering and operation
Schools: School of Computing and Engineering > Institute of Railway Research
Related URLs:
Depositing User: Rawia El Rashidy
Date Deposited: 23 Nov 2017 14:48
Last Modified: 23 Nov 2017 14:53
URI: http://eprints.hud.ac.uk/id/eprint/33955

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