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

S. Qiu, N. Rachedi, M. Sallak and F. Vanderhaegen

Reliability Engineering and System Safety, 2017, vol. 167, issue C, 184-191

Abstract: 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).

Keywords: Risk evaluation; Advanced driver assistance systems; Valuation-based system; Belief functions theory; Uncertainty (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:167:y:2017:i:c:p:184-191

DOI: 10.1016/j.ress.2017.05.028

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