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models of the driver. These models shall be able to replace the driver in that
they are capable of reproducing human behaviour. Combining them with
executable models of the car, trac scenario, and the assistance system, a
complete operational representation of the assistance system in its applica-
tion environment can then be constructed and employed to predict effects
of introducing the assistance without having to resort to experiments with
humans. While the construction of driver models is a both scientifically and
practically challenging task which is addressed in a number of other reports,
e.g. [5,6,8], in this paper we focus on techniques concerned with using these
models, i.e., with evaluating functionality and safety aspects of driving with
assistance. The evaluation is performed by studying the emergent behaviour
of the integrated models. As the models are rather complex, the main means
for assessing them must be simulation, because other analysis methods (e.g.,
computing all states the model may reach or even formal verification) are
only applicable to much simpler classes of systems or smaller models.
Of course, the simulation activity must be well organized to produce re-
liable assessments. Our approach combines a systematic parameter coverage
with property-specific guidance. If, for instance, we are interested in a par-
ticular aspect of criticality, we start with a function assigning a numeric
criticality value to each run. After covering the parameter space roughly, ar-
eas where high values have been observed get analysed in more detail. Thus,
the simulation proceeds, guided by observations, towards points of interest.
In particular, the (hopefully low) probability of situations like those involv-
ing a high accident risk can be assessed with much greater accuracy than by
simpler procedures.
The application scenario on which IMoST develops and tests its approach
is that of an advanced driver assistance system (ADAS) supporting the driver
in filtering into an expressway, including the gap selection and speed adapta-
tion. This scenario captures one of the most critical expressway manoeuvres.
On the other hand, compared to other potentially critical trac situations
(e.g., crossings), it is limited in its variability and is thus suited for developing
and assessing a new approach. Variables we considered were the number of
other trac participants, speed differences, and gap sizes.
This paper is organized as follows. In the following section we present our
simulation platform, i.e. list the components of the considered co-simulation
and state how the interaction between all components takes place. In Sec. 3
we give a formalism allowing to specify (among other) safety properties. The
succeeding section deals with the online evaluation of the specified formu-
las. In Sec. 5 we will give a procedure to automatically determine critical
situations, and we conclude with Sec. 6.
2
Simulation Platform
The complete model consists of several software modules. These are provided
from different sources: They incorporate a commercial trac simulation, the
