Abstract

International audience; This article describes a contribution to improving the usual safety analysis methods used in the certification of railway transport systems. The methodology is based on the complementary and simultaneous use of knowledge acquisition and machine learning. We used the ACASYA software environment to support the safety analysis aid methodology. ACASYA aims to provide experts with suggestions of potential failures which have not been considered by the manufacturer and which are capable of jeopardizing the safety of a new rail transport system. ACASYA consists of two main modules: CLASCA and EVALSCA, respectively dedicated to the classification and evaluation of accident scenarios. CLASCA is an inductive, incremental and interactive learning system. EVALSCA, built around a learning system called CHARADE, aims to provide experts with suggestions of potential failures which have not been considered by the manufacturer and which are capable of jeopardizing the safety of a new rail transport system.

Abstract

International audience; In addition to identifying safety deficiencies evidenced by accidents, the independent investigative body makes recommendations to eliminate or reduce these deficiencies. Its main purpose is to advance transportation safety by conducting investigations of accidents in rail and other modes of transportation. He must answer several questions: what happened, why did it happen, and what can be done to reduce the risk of it happening again? In this process, one of the difficulties involved is finding abnormal accident scenarios which are capable of generating a specific hazard. This paper proposes an original method based on machine learning to assist investigators experts in their crucial task of analysis and assessment of the safety for railway transport systems in France. This contribution is based on the use of artificial intelligence techniques and has involved the development of several approaches and tools which assist in the modeling, storage and assessment of knowledge about safety. The proposed approach has two objectives, firstly to record and store experience concerning safety analyses, and secondly to assist those involved in the development and assessment of the systems in the demanding task of evaluating safety studies.

Abstract

International audience; The growing increase in the volume of transportation system’s flows has entailed congestion problems of traffic. For railway transport as well as other transportation networks, the increase in traffic demand—without further investing in infrastructure—stands as a chief priority for operators. As a matter of fact they take special interest in improving the operating possibilities for some critical points of the rail network. In order to resolve the problems inherent in the operational management of rail transport traffic, optimization experts have operated mathematical optimization techniques and problem resolving methods that have been developed as part of operational research aimed at keeping a good level of availability. However, these optimization approaches have considerably contributed to balancing and stabilizing the flows of road and rail networks but still do not guarantee security at system, environmental and human levels. This work introduces a management and regulatory approach to rail traffic and takes into account the security component while chiefly aiming at improving and keeping a “good” level of security. To this end, we have set up a security modelling approach based on a hybrid risk analysis, both quantitative and qualitative. This approach seeks to develop a structured framework allowing the integration of the security component into an explicit generic optimization model in accordance with the operating constraints in use by rail optimization methods. On the one hand, this approach constitutes a formal checking process for the management and optimization of traffic even though they are subject to failures. On the other, it is a set of modelling tools and a methodological structure allowing managing and controlling risks at the level of a rail transport system.

Abstract

FloodRisk, 3rd European Conference on Flood Risk Management, Lyon, FRA, 17-/10/2016 - 21/10/2016; International audience; Indicator of Intense Pluvial Runoff (French Acronym) - is a method to map the susceptibility of territories to surface runoff generation, transfer and accumulation. The method is based on a geomatic combination of landscape factors extracted from topography, land use and soil type. This study is part of the method evaluation process and suggests using information from post-event surveys of surface runoff events to evaluate the agreement between the IRIP maps and the field observations. Surface runoff susceptibility maps are produced at five meters resolution for three impact areas on railways with different infrastructure and environment configurations. First, information categories are extracted from the post-event surveys, and then the IRIP maps are analyzed to see if and how the information categories are retrieved. This study shows that the IRIP maps fit the impact description. The areas susceptible to surface runoff transfer fit the gullies locations and the areas susceptible to surface runoff accumulation fit the sediment deposit traces. The comparison also highlights that the IRIP maps can give further information on the event spatial dynamics. Given the simplicity and the robustness of the mapping method, IRIP can be a tool to perform surface runoff post-event surveys and to improve the surface runoff hazard assessment.