Scenario-based Uncertainty Quantification for the Design of Reliable Automated Driver Assistance Systems

This presentation was made at the NAFEMS European Conference on Simulation-Based Optimisation held on the 15th of October in London.

Optimisation has become a key ingredient in many engineering disciplines and has experienced rapid growth in recent years due to innovations in optimisation algorithms and techniques, coupled with developments in computer hardware and software capabilities. The growing popularity of optimisation in engineering applications is driven by ever-increasing competition pressure, where optimised products and processes can offer improved performance and cost-effectiveness which would not be possible using traditional design approaches. However, there are still many hurdles to be overcome before optimisation is used routinely for engineering applications.

The NAFEMS European Conference on Simulation-Based Optimisation brings together practitioners and academics from all relevant disciplines to share their knowledge and experience, and discuss problems and challenges, in order to facilitate further improvements in optimisation techniques.

Resource Abstract

Advanced Driver Assistance Systems (ADAS) see a constantly growing attention by researchers and industries as more and more vehicles are equipped with such technology. It is generally expected to see first Automated Driving Systems (ADS) in the market in the next years. One of the most important aspects for reaching this goal and releasing ADS is testing and validation.



Several publications stated out, that the required mileage needed to proof the probability of failure of the system is impossible to reach in field operational tests. Therefore, statistical methods combined with Software-in-the-Loop (SiL) simulation may help to overcome this limit. The field of robustness analysis, initially developed for structural mechanics, provides algorithms and approaches which can be applied to assess ADS. Due to the different kind of parameters and criteria, available methodologies need to be analyzed and adapted to ADS specific challenges.



In this paper, the presented process is based on event based simulations where specific traffic scenarios are parametrized, simulated and analyzed by a set of criteria. By using predefined distribution functions for each input parameter a safety statement can be given by approximating the probability of failure for each traffic scenario by determining the unsafe region in the parameter space. Therefore, multiple steps of different algorithms are combined to ensure trustworthy results by being very efficient in reducing the number of required simulation runs.



Based on established uncertainty quantification methods, known from civil engineering and from aircraft design, small event probabilities are estimated. In this paper, it is shown, which challenges appear in applying these methods for Software-in-the-Loop simulation models.

Document Details

ReferenceC_Oct_19_Opt_17
AuthorGräning. L
LanguageEnglish
TypePresentation
Date 15th October 2019
OrganisationDynardo GmbH
RegionUK

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