UKERC Energy Data Centre: Projects

Projects: Projects for Investigator
UKERC Home >> UKERC Energy Data Centre >> Projects >> Choose Investigator >> All Projects involving >> EP/I036222/1
Reference Number EP/I036222/1
Title Extracting Leading Indicators from Transport Data Monitoring Programs using Human Factors Methods
Status Completed
Energy Categories ENERGY EFFICIENCY(Transport) 15%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields SOCIAL SCIENCES (Psychology) 25%;
UKERC Cross Cutting Characterisation Sociological economical and environmental impact of energy (Consumer attitudes and behaviour) 100%
Principal Investigator Dr G H Walker
No email address given
Sch of the Built Environment
Heriot-Watt University
Award Type Standard
Funding Source EPSRC
Start Date 01 March 2012
End Date 28 February 2013
Duration 12 months
Total Grant Value £95,955
Industrial Sectors Transport Systems and Vehicles
Region Scotland
Programme NC : Engineering
Investigators Principal Investigator Dr G H Walker , Sch of the Built Environment, Heriot-Watt University (100.000%)
  Industrial Collaborator Project Contact , Rail Safety & Standards Board (0.000%)
Project Contact , Aerobytes Ltd (0.000%)
Web Site
Abstract Flight Data Monitoring (FDM) is the process by which data from on-board recorders (or so-called 'black boxes') is subject to regular and systematic analysis, not just after emergencies but after every flight. This is performed so that subtle trends which arise as pre-cursors to more serious incidents can be detected in advance and used to proactively manage risk. The same technique is also used as a way of meeting environmental and economic goals through improved operational efficiency, fuel consumption and maintenance.FDM is relevant to the railway industry because since 2005 all trains now have to carry similar on-board recorders. The primary motivation is to provide accident investigators with an invaluable diagnostic tool, but like the aviation sector, because accidents are comparatively rare a far greater quantity of data is collected on normal, routine, non-accident journeys. As a result, recorder data in the rail industry represents a significantly underused resource.The proposed research relates to a class of problem which occurs firmly at the human/system interface and which is shared by both the aviation and rail sectors. Both domains experience problems, for example, Signals Passed At Danger (or SPADs) and Controlled Flight Into Terrain (CFIT), where several safety systems are defeated by human operators and otherwise fully functional trains or aircraft are placed in highly unsafe conditions. Problems such as these fall within the purview of Human Factors. On-board recorder data, be it from the rail or aviation sectors, represents a novel source of input for established human factors methodologies targeted at addressing them.The primary goal of the research, therefore, will be to couple recorder data to human factors methods in a way not previously attempted. The outcome will be 'leading indicators' of problems which, so far, have proven resistant to conventional safety interventions. Related to this are leading indicators, or metrics, that could help to inform ongoing research into operational efficiency, 'eco-driving', and potentially cost-saving insights into future maintenance practices. These opportunities can be systematically examined with reference both to human factors methods and to the mature FDM processes that currently exist in the aviation industry.The project is set against, and motivated by, a wider backdrop of European rail interoperability, a desire to maximise the environmental benefits of rail travel and the UK's position as a world leader in FDM processes. Whilst the research has at its core an innovative programme of theoretical advance, it is also coupled to several near-term applications. Firstly, the UK Civil Aviation Authority (CAA) seek to inform (and be informed of) best practice in other transport domains and the proposed project aims to provide a conduit for such knowledge. Secondly, both the CAA and the Association of Train Operating Companies (ATOC) are activelyseeking leading indicators of safety related problems, particularly those which occur at the human/system interface. The project will map important theoretical developments in human factors methods to these real-world applications. Third, the proposed research is directly relevant to current industry projects managed by the Rail Safety and Standards Board (RSSB), including several relating to safety management systems, eco-driving and route knowledge.In summary, the proposed research represents a highly innovative approach to understanding and diagnosing issues which occur at the boundary of humans and transport systems. It is also an example of research with high economic and societal impacts, and an example of research application with great potential to develop further work and collaborations with industry partners
Publications (none)
Final Report (none)
Added to Database 10/07/12