Abstract: This paper introduces a research aiming at the development of a decision support system concerning the approval of automated railway transportation systems. The objective is to implement a valuation method for the degree of compliance of the automated transportation system in-group of safety standards by the analysis of the scenarios of accident. To reach this target, we envisaged an approach Rex (Return of experience) who draws the lessons of accidents / incidents lived and/or imagined by the experts of the analysis of security in the IFSTAAR. Our approach consists in offering a decision support in the side of the experts of the certification based on a reuse of the scenarios of accidents already validated historically on other approved transportation systems. This approach Rex is very useful since it provides to the experts a class of scenarios of accidents similar to the new case treated and getting closer to the context of new case. The Case-based reasoning is then exploited as a mode of reasoning by analogy allowing to choose and to recollect one under group of historical cases that can help in the resolution of the new case introduced by the experts. Process-Oriented Case-Based Reasoning (PO-CBR) is a growing application area in which CBR is used to address problems involving process data in a variety of specialized domains. PO-CBR systems often use structured cases. Our approach is characterized by a two-phased retrieval strategy. A first phase consists in retrieving a set of cases to be considered (a class of cases most similar to a problem to resolve). In a second phase, a more fine grained strategy is then applied to the pool of candidate cases already selected by the mean of similarity measures. This approach can enhance the process of retrieving cases compared to an exhaustive case-by-case comparison.
Keywords: componentSecurity of transport; Artificial Intelligence; Ontology; Case-Based Reasoning; Resolution scenario; Scenario of accident.