Presentation by David George, CEO of the CRC for Rail Innovation, to the Rail Safety Strategic Forum, November 2011

1. CRC for Rail Innovation
Safety Research
David George, CEO and
Prof Andry Rakotonirainy,QUT
Established and Supported
under Australia’s Cooperative
Research Centres Programme

2. Collaborative Research to
achieve more with less
$100m research program over 7 years
Collaboration between industry and
universities
Over 100 projects under 6 themes
Industry driven, adoption focused research

3. Six Research Themes
Research program focusing on
six themes:
Safety & Security
Climate Change and the
Environment
Performance
Smart Technologies
Urban Rail Access
Workforce Development

4. Outline of selected
safety projects
Affordable Railway crossing stage 2
(R3.122)
Baseline Level Crossing video (R2.119)
ITS for safer level crossing (R2.111)
Route Knowledge/Driving strategies
(R2,112/113)
Level crossing intervention (R2.118)
Rail Incident Investigator (P4.113)
Track worker protection technology (R3.120)
Next Generation Fatigue Risk Management
(R2.109/110)

5. R3.122 Affordable Level
Crossings Project – Stage 2
Project commenced in March 2011
Aims: evaluate and trial low-cost level crossing warning
devices in several jurisdictions;
• Candidate devices will be trialled in shadow-mode (i.e.
overlaid on a vital track circuit without installation of the
candidate device’s road-user interface)

6. Why Affordable Level
Crossings?
Collectively, passive crossings represent a
significant safety issue for Australia.
They cost at least 25% of the cost of traditional
crossing technologies.
For a given investment, more crossings can be
treated;
• Greater safety benefit for same investment
used to treat crossings using traditional
technologies.
(ATSB, 2008a; RSRP, 2008)

7. Expected Outcomes
Set of requirements for LCLCWDs with safety and
availability targets;
• Risk assessment model
• Human reliability assessment model
Lifecycle assessment criteria;
• Identification of where cost savings can be made
Trial results;
• Comparative performance and operational data (reliability,
availability, maintainability)
Results from human factors study;
• Effectiveness of various measures to improve
performance of road users at level crossings that are
unavailable (effective communication of crossing state)

8. R2.119 Baseline Level Crossing
Video
Project commenced in July 2011
Aims: capture the context of near-misses using video
obtained from forward facing cameras installed in trains
• Digital image processing algorithms will be developed to identify
events of interest from video footage

9. Problems Project is Addressing
Subjectivity of near-miss reporting
• Near-misses are self reported – a near-miss to one driver is not
the same as a near-miss to another
• Under-reporting is also an issue
Near-miss data is the most important precursor data
available
• Currently because of it's unreliability, it is not suitable for analysis
• Crash data is of limited use due to statistical uncertainty (because
of low number of occurrences)
Precise definitions and sub-categorizations of near-miss
(technically derived from video image processing and
other context data) will significantly improve the
usefulness of near-miss data
• Supports causal analysis, better continuity for trend analysis,
• Improves risk models to support better prioritization of upgrade
funding, etc.

10. Expected Outcomes
Establish precise definitions of near-miss
• Using objectively measurable information (from in-cab video
capture and data logging system)
Establish technical data capture performance criteria to
underpin essential data capture needed
• Allows industry to approach suppliers for equipment that meets
these needs
Improving understanding of the context of near-misses
and causal factors
• Expected to inform measures to improve safety at level crossings
(i.e. Using a data-mining approach, correlations can be found
between near-misses and contextual factors
Project can inform simulator training for drivers
• Can potentially provide the basis for competency assessment in
relation to identification of near-misses

11. R2.111 ITS for safer
level crossings
Project commenced in July 2010
Aims to assess capability of Intelligent Transport
Systems technologies to reduce crashed at RLXs
• Trialing 3 types of ITS on an advanced driving simulator

12. Scope
Research question:
Can ITS intervention reduce crashes at RLX by
improving driver’s awarenessp;
• Trial 3 emerging ITS interventions on the advanced driving
simulator (HMI side).
• In-vehicle and road-based interventions.
• Drivers’ errors or violations the largest contributor to RLX
crashes.
Strategy:
Reduce main driver’s errors at crossings (failure to
detect crossing/train and misjudgments of train
approach speed/distance).

13. Expected Outcomes
A scientific assessment of the safety
impacts of RLX – emerging ITS based
interventions on driver behaviour.
Cost benefits assessments.
Recommendations to industry.

14. R2.112/113 Route Knowledge &
Driving Strategies
Project commenced in October 2010
Aims: Devise simulator scenarios to optimize skills
acquisition and knowledge transfer during learning
• A simulator scenario suite will be developed and tested
under heavy haul and passenger train driving conditions

15. Why Simulator Scenarios?
Increasing need in the Australian rail industry to train
drivers faster and more effectively.
Industry-based simulator usage is widespread but there
is little consistency in application methodologies.
A good understanding of route knowledge and
substantive driving strategies is required to cultivate
train driving competency
• Very little is currently known about how route knowledge is
mentally encoded.
• Driving strategies are subject to considerable individual
differences.

16. Expected Outcomes
A comprehensive picture and understanding of how the
railway is psychologically structured
• Route knowledge review
• Mental schematics
• Alignment with effective driving strategy
Identification of a scenario suite
• Captures train driving skill
• Dimensionalises task demand
Results from simulator evaluation
• Scientifically informed simulator scenario suite
• Advise national simulator training practice
• Introduce better consistency in simulator application and
management

17. R2.118: RLX intervention
framework
Project commenced July 2011
Aim:
Identify an optimal intervention framework for
managing safety upgrades to railway level
crossings.

18. Scope
Research questions:
1. Which framework (incremental or system-wide)
effectively optimizes the goals of increased network
safety and low equipment cost for management of
railway level crossings?
2. Is it legally viable to upgrade level crossings to a
standard that is not fail-to-safe?
Approach:
Basic risk analysis and clarity on the legal position
for implementing countermeasures that do not
render railway level crossings fail-to-safe.

19. Expected Outcomes
Legal advice on argument
to deploy LCLCWDs within
Rail Safety Act.
Decision making framework.
Advocacy campaign (ARA).

20. Rail Incident Investigator
(P4.113)
Project commenced November 2010
Aims:
• Develop a national training program & capability framework for
rail incident investigators.
• Establish the potential market demand.
• Define the curricula for a multi-level national training program.
• Explore training providers & delivery options.

21. Scope
A previous scoping report (P4.107) recognised that
the Australian Rail Industry did not have a national
approach to developing rail incident investigations.
By 1 January, 2013, a National Rail Safety
Regulator will be appointed. This has led to strong
support from the industry for a more collaborative
approach.
There was agreement amongst participants on the
need for a competency framework and qualification
pathway for investigators.
Approach:
Structured interviews and weighted checklists were
utilised to determine core competencies for investigators
as well as forming the basis for the training needs
analysis.

22. Project Benefits
Development of a rail-specific competency
framework and curricula for a multi-level
national training program will:
Allow industry to share training
resources.
Increase the recruitment pool of qualified
professional investigators.
Provide a nationally recognised career
pathway for rail investigators.
Enhance the quality of both curricula and
training providers.

23. R2.109 Second generation Fatigue
Risk management System (FRMS)
Commenced: 2009
Aims:
To develop a framework for a flexible risk-
based national standard for fatigue
management for the rail industry.

24. Benefits
A standardised approach to fatigue risk
management based on current scientific knowledge
and best practice.
A set of practical tools and strategies to be used in
the development of individual FRMS.
Standardised guidelines for the use of pre-existing
fatigue management tools such as FAID.
A set of standardised key performance indicators
against which rail operators and regulators can
assess the performance of a rail organisation’s
FRMS.

25. Outcomes
Framework for a national standard,
based on scientific evidence and
current best practice.
A compliance code to assist
organisations in meeting the standard.
Tools and guidelines for policy
development and fatigue risk
management.

26. R2.110 Next generation Fatigue Risk
management System (FRMS)
Project commenced Jul 2009
Aim:
To improve the reliability and validity
of the data used to inform fatigue
models.

27. Benefits
Work-related fatigue modeling tools
representative of the different social/domestic
profiles of different workgroups within the
industry.
Capacity to inform the likelihood that a given
shift falls within a specified fatigue score
range.
Improving the match between observed and
predicted fatigue (i.e. by using individual
predictors); thereby limiting the unsafe work
hours and reducing unnecessary restrictions
of working hours.

28. Expected Outcomes
New parameters for defining levels
of fatigue risk associated with
working time for different work
groups and demographic profiles.
A more flexible approach to fatigue
modeling that reflects the current
state of the industry.

29. Thank you for your attention
David George and Professor
Andry Rakotonirainy