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Kpotissan Adjetey-Bahun, Babiga Birregah, Eric Châtelet, Jean-Luc Planchet, & Edgar Laurens-Fonseca. (2014). A simulation-based approach to quantifying resilience indicators in a mass transportation system. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 75–79). University Park, PA: The Pennsylvania State University.
Abstract: A simulation-based model used to measure resilience indicators of the railway transportation system is presented. This model is tested through a perturbation scenario: the inoperability of a track which links two stations in the system. The performance of the system is modelled through two indicators: (a) the number of passengers that reach their destination and (b) the total delay of passengers after a serious perturbation. The number of passengers within a given station at a given time is considered as early warning in the model. Furthermore, a crisis management plan has been simulated for this perturbation scenario in order to help the system to recover quickly from this perturbation. This crisis management plan emphasizes the role and the importance of the proposed indicators when managing crises.
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Alexander Gabriel, Florian Brauner, Andreas Lotter, Frank Fiedrich, & Ompe Aimé Mudimu. (2018). The determination of critical components of European Rail Traffic Management systems towards cyber-attacks. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 291–303). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: “Recent events have shown the vulnerability of IT systems of companies, organizations or even governments to hacker attacks. At the same time, information technologies are becoming increasingly established and important in various industries (digitalization). With a view to the modern development of terrorism, cyber-attacks can be used to physically damage critical infrastructures (CI). This leads to a new dimension of cyber-attacks, which are called terrorist cyber-attacks. The following research contributes to the identification of weak information technology components of railway operating systems and thus improves the safety of public transportation in the context of the European railway traffic management system (ERTMS). The core of this paper is an extended literature research on security flaws in the ERTMS. The future introduction of a methodology for evaluating the criticality of information technology system components will build on this using cyber threats and public transportation as examples.”
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Alexander Gabriel, Florian Klein, & Frank Fiedrich. (2020). Modelling of Passenger Handling Processes in Railway Stations – A Mixed-Methods Approach. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 580–592). Blacksburg, VA (USA): Virginia Tech.
Abstract: The constantly increasing number of passengers using public transportation leads to an expansion of the ser-vices offered by public transportation companies. The existing transportation infrastructures, especially rail-way stations, can only partly cope with this rapid growth. There is already overcrowding on platforms and access routes, especially during disruptions caused by natural disasters or major public events. This crowding may result in personal injury or shutdown of operations for safety reasons. The research project CroMa aims at improving robustness, safety, security and performance of railway stations at peak loads. The paper contributes thereto by developing an approach to assess railway infrastructure in terms of the risk of overcrowding. The core of this research is to combine qualitative workshop results with quantitative database analysis. Furthermore, the paper gives an outlook on the ongoing process model development as a basis for a semi-quantitative evaluation tool for railway stations applicable by end users.
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Jiayao Li, Juanqiong Gou, Wenxin Mu, & Liyu Peng. (2017). Modeling of Railway Risk Inter-Relation based on the study of Accident Context. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 328–340). Albi, France: Iscram.
Abstract: In order to detect and control the critical potential risk source of railway more scientifically, more reasonably and more accurately in complex accident context, a knowledge modeling method of risk inter-relation is proposed based on ontology modeling of accident context. First, the mechanism of accident causation is summarized based on the accident case analysis. Then, the knowledge model of accident cause is built based on ontology theory, including the ontology model of two context instances. Last but not least, the risk inter-relation rules with different dimensions of inter-relation patterns are inferred based on the instantiation of ontology model. The two context instances are used to illustrate the identification process of risk inter-relation. The results prove the rationality of the method, which can provide a reference for the precise railway risk prevention.
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