Sensitivity Assessment to Analyse Dependability of a Multisensor Localisation System based on GNSS

This paper proposes to use sensibility measures to analyse the dependability and safety of railway localisation systems based on GNSS. In such systems, train positions are determined by combining all available sources of localisation information. However, each source of data suffers from specific errors, which are inherent to the nature of the sensors and, which are difficult to manage with common dependability methods. The proposed evaluation method based on a sensitivity analysis aims at showing the influence of the variability of sensor parameters on the RAMS (Reliability, Availability, Maintainability and Safety) attributes. This implies (i) to identify characteristics of the different sensors that compose the system like features, behaviour and error model, and (ii) to make assumptions about the nature of position error on the output system (continuity, differentiability, etc...). This paper proposes a sensitivity computation method and interpretations related to a train positioning system. This can constitute a new approach in dependability analysis in GNSS-based systems with a low or nonexistent feedback.

• Authors:
  • LEGRAND, Cyril
  • BEUGIN, Julie
  • CONRARD, Blaise
  • MARAIS, Juliette
  • BERBINEAU, Marion
  • EL KOURSI, El Miloudi
• Conference:
  • ITST 2013, 13th International Conference on ITS telecommunications
  • Location: Tampere
  • Date: 2013-0-0
• Publication Date: 2013

Language

• English

Media Info

• Media Type: Digital/other
• Pagination: 7p

Subject/Index Terms

• TRT Terms: Artificial satellites; Location; Railroad trains; Railroad transportation
• ITRD Terms: 9061: Localisation; 9125: Satellite; 1268: Train (chemin de fer); 1173: Transport ferroviaire
• Subject Areas: Railroads; Vehicles and Equipment;

Filing Info

• Accession Number: 01537544
• Record Type: Publication
• Source Agency: Institut Francais des Sciences et Technologies des Transports, de l'Amenagement et des Reseaux (IFSTTAR)
• Files: ITRD
• Created Date: Sep 16 2014 11:20AM