![](bg8.png)
43% during scenario-based hazard analysis (at the
early stage by clustering and grouping) is counted as
an outcome of this paper for supporting a complete
HADF scenario set. Furthermore, using a stochas-
tic program to optimize the safety-relevant parame-
ter’s boundary reduces the number of logical scenar-
ios which reduce the effort of modeling scenarios.
A simple stochastic program is advantageous at the
function level to deal with a large number of scenar-
ios and uphold to sustain a systematic approach that
supports the safety aspect of HADF. This approach
supports in general to build confidence in simulation-
based scenario investigation in HADF development
which can be cost-effective and time-efficient. Al-
though, a further scenario reduction approach is re-
quired from a logical scenario to concrete scenario
determination.
In our future research, we would like to focus on
the complete scenario database for a complete HADF
and propose a reduced set of concrete scenarios based
on simulation results that can support to provide ev-
idence for safety approval (homologation). Approxi-
mation techniques that reduce more scenarios in each
step of clustering and/or grouping at function level
may be improved by other types of stochastic pro-
grams like a multistage program. Interesting is to ob-
serve the accuracy rate of the experiment and simu-
lation result by studying a huge number of scenarios
which has to be investigated.
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