Open AccessGeoSRM – Online geospatial safety risk model for the GB rail network
Author(s) -
Sadler Jason,
Griffin David,
Gilchrist Alex,
Austin Jeremy,
Kit Oles,
Heavisides Jay
Publication year - 2016
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2015.0038
Subject(s) - geospatial analysis , transport engineering , computer science , data science , risk management , range (aeronautics) , engineering , geography , cartography , business , finance , aerospace engineering
RSSB and the University of Southampton's GeoData Institute have collaborated to research and develop a toolkit for managing large volumes of rail risk data. The pilot system encompasses concepts of highly complex geospatial ‘big data’, open standards, open source development tools and methodologies, and enables stakeholders to filter, analyse and visualise risk across the rail network, for a range of risk models. These include train derailments, suicides and passenger slip, trips and falls, and feature a wide range of spatially dependent parameters that affect the causal, escalation and consequence mechanisms. The risk has been calculated to a high resolution, splitting 2,100,000 m of track typically into 10 m sections. By creating geospatial representations of risk, the tool can help to identify risk hotspots and in this way contribute to the improvement of rail safety. Once scaled up to a National level and full range of risk models, the tool will deliver a powerful capability, unique across Europe. Further research is extending the prototype to incorporate live and historic environmental and related rail incident data to augment and improve the risk model.