A quantitative model for the risk evaluation of driver-ADAS systems under uncertainty - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Reliability Engineering and System Safety Année : 2017

A quantitative model for the risk evaluation of driver-ADAS systems under uncertainty

Résumé

In this paper, a quantitative model is proposed to assess the probability of accidents occurring in driver-Advanced Driver Assistance Systems (ADAS) under uncertainty using Valuation-Based System (VBS). Two kinds of uncertainties are analyzed: data uncertainty related to the states of components, and model uncertainty related to the system structure. The components and the system structure are modeled using variables, spaces of variables, and a set of valuations represented by basic probability assignments (bpas). Besides, the positive influence of learning and cooperation processes is also quantified. Finally, the proposed method is applied to a real use case: the Car Navigation System (CNS).
Fichier non déposé

Dates et versions

hal-01702349 , version 1 (06-02-2018)

Identifiants

Citer

Siqi Qiu, Nedjemi Rachedi, Mohamed Sallak, Frédéric Vanderhaegen. A quantitative model for the risk evaluation of driver-ADAS systems under uncertainty. Reliability Engineering and System Safety, 2017, 167, pp.184-191. ⟨10.1016/j.ress.2017.05.028⟩. ⟨hal-01702349⟩
84 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More