UIC, represented by José Pires and Virginie Papillault (Senior Advisors of the UIC Security Division) and with the support of DG DB Situation Center and Global Crisis Management Corporate Security, coordinated the PREDICT use-case workshop “Train derailment at the Belgium/German border”, which took place in Cologne on 3 November 2015.
The PREDICT project began with an in-depth analysis of recent cases (over 8 500 incidents worldwide). These shall be accompanied by potential crisis scenarios. Project partners shall set up a generic approach (common framework) to prevent or mitigate cascading effects, which will be applied in selected cases agreed with end-users. As modelling each phenomenon separately in a specific environment is not effective, the PREDICT project shall propose cohesive and comprehensive models of dependencies, cascading effects and common mode failure which will include causal relations, multi-sector infrastructure elements and environmental parameters, as well as human factor aspects.
The main project objective is to deliver tools bundled in the PREDICT Incident Evolution Tool, which will consist of two core components:
- Foresight and Prediction Tool (for simulating the evolution of cascading effects and the impact on multi-sector dependencies)
- Decision-Support Tool (for determining the best courses of action and calculating the associated risks)
The quality of the developed solutions shall also be ensured by the strong involvement of end-users (UIC security in the rail sector) in the project.
End-users shall intervene on three levels:
- Partners of the consortium
- Members of the Advisory Board
- Representatives from relevant organisations across Europe invited to regular workshops
The workshops focus on understanding how the incident evolution can be observed, predicted and communicated at the prevention and response levels. Indeed, predicting and addressing potential cascading effects in crisis situations requires a comprehensive view of the evolution and a better understanding of key crisis phases. By taking stock of existing solutions and exploring innovative methods in this field, end-users will be able to exchange best practices and express operational requirements on incident evolution solutions designed to improve their capability to mitigate potential cascading effects and thus facilitate their daily work.
Within that scope, the PREDICT use-case workshop “Train derailment at the Belgium/German border” presented a hypothetical scenario involving a dangerous goods train that derails due to an act of sabotage. Railway operators, civil protection agencies and law enforcement (Police) agencies worked together to study the domino and cascading effects in this multi-crisis situation, and analyse where and how PREDICT methodologies, models and software tools could improve the crisis management decision support.
In addition to the project partners, the following also participated:
- German state Police (Cologne based), disaster management
- German Border Police Region of Aachen (now German Federal Police), responsible for the railways, among other things
- Fire Brigade Aachen (planning of deployment of incidents railway related)
- DB Rail (Meinz) - Head of Crisis management, cooperation of first responders and emergency responders, coordination with the private sector
- DB working for the Director of Safety
- DB Regio, Security Manager and Emergency, incidents and liabilities department
- DB Corporate Security, regional crisis management
- DB Corporate Security - Situation Centre, Crisis management (local and international crisis)
Finally the aim of the PREDICT project is to provide a comprehensive solution for dealing with cascading effects in multi-sectoral crisis situations covering aspects of critical infrastructures. The PREDICT solution will be composed of the following three pillars: methodologies, models and software tools. Their integrated use will increase the awareness and understanding of cascading effects by crisis response organisations, enhance their preparedness, and improve their ability to respond in the event of cascading failures.
Work with end-users on the development of the decision support tools will continue within the next 8 to 9 months (June/July 2016), when a mock-up (a beta version) will be presented and evaluated.
