قابلیت اطمینان و تحلیل سؤالات آزمون سیستم چندرسانه ای راننده

Modern driver assistance systems for self-driving cars often rely on data collected by different sensors to determine the necessary system decisions. To prevent system failures, different validation techniques are used. The development is often split between car manufacturers and suppliers, whereby the requested test effort is one main project acceptance criterion. Already available effort estimation methods are not applicable, because they rely on implementation details that do not exist at early phases or on project experiences or individual expert expectations, which are not reliable enough to be employed as trustworthy source. Therefore, we provide in this paper an analytic approach for the computation of the error probability of a multi-sensor system. Based on this, we can give estimations for the test effort such that with statistical confidence no errors of the sensor system can be expected during the tests. The approach is able to take both the dependencies between successive sensor errors and the correlation between different sensors into account, mainly by using discrete time Markov chains. The provided approach therefore allows to design multi-sensor systems such that a specified overall error probability can be met and to give an estimation for the upper bound of the test effort.