GeoSRM - Online Geospatial Safety Risk Model for the GB Rail Network

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, analyze and visualize 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.

• Record URL:
  https://doi.org/10.1049/iet-its.2015.0038
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/1751956X
• Supplemental Notes:
  • Abstract reprinted with permission of the Institution of Engineering and Technology.
• Authors:
  • Sadler, J
  • Griffin, D
  • Gilchrist, A
  • Austin, J
  • Kit, O
  • Heavisides, J
• Publication Date: 2016-2

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 17-24
• Serial:
  • IET Intelligent Transport Systems
  • Volume: 10
  • Issue Number: 1
  • Publisher: Institution of Engineering and Technology (IET)
  • ISSN: 1751-956X
  • EISSN: 1751-9578
  • Serial URL: https://ietresearch.onlinelibrary.wiley.com/journal/17519578
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Data analysis; Data collection; Derailments; High risk locations; Passengers; Railroad safety; Suicide
• Uncontrolled Terms: Big data
• Geographic Terms: Europe
• Subject Areas: Data and Information Technology; Railroads; Safety and Human Factors; I81: Accident Statistics;

Filing Info

• Accession Number: 01591763
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 29 2016 9:19AM