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Article Dans Une Revue International Journal of Computing Science and Communication Année : 2016

Transportation safety assessment methodology based on artificial intelligence techniques

Résumé

One of the research activities which is currently in progress at the French institute lFSTTAR relates to the certification of automated public transport systems and the safety of digital control systems. As part of its missions of expertise and technical assistance, IFSTTAR evaluates the files of safety of guided transportation systems. These files include several hierarchical analysis of safety such as the preliminary analysis of risks (PAR), the functional safety analysis (FSA), the analysis of failure modes, their effects and of their criticality (AFMEC) or analysis of the impact of the software errors. These analyses are carried out by the manufacturers. It is advisable to examine these analyses with the greatest care, so much the quality of those conditions, in fine, the safety of the users of the transport systems. In this process of analysis and assessment of the safety of a rail transportation system, one of the difficulties is to ensure the completeness of the accident scenarios taken into account by all the actors involved in the development of the system. Our study took place within this context and aimed to design and create a software tool to aid safety analysis in order to appraise the suitability of proposed protection equipment. The purpose of this tool is to evaluate the completeness and consistency of the accident scenarios which have been put forward by the manufacturers and to play a role in generating new scenarios which could be of assistance to experts who have to reach a conclusion regarding the safety a new rail transport system. The approach which was adopted in order to design and implement an assistance tool for safety analysis involved the following two main activities: - Extracting, formalizing and storing hazardous situations to produce a library of standard cases which covers the entire problem. This process entailed the use of knowledge acquisition techniques, - Exploiting the stored historical knowledge in order to develop safety analysis know-how which can assist experts to judge the thoroughness of the manufacturer’s suggested safety analysis. This second activity involves the use of machine learning techniques and expert system. This paper presents these two activities which are involved in the methodology of assessing the safety of rail transport
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Dates et versions

hal-02423988 , version 1 (26-12-2019)

Identifiants

  • HAL Id : hal-02423988 , version 1

Citer

Habib Hadj-Mabrouk. Transportation safety assessment methodology based on artificial intelligence techniques. International Journal of Computing Science and Communication, 2016, 1 (1), pp.22-30. ⟨hal-02423988⟩
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