Page 12 - DCAP601_SIMULATION_AND_MODELING

Simulation and Modelling

Notes The manner in which the support services to augment the simulation model are invoked varies
significantly among software environments. Almost always there is at least some set of
parameters that need to be assigned values in order to choose from available options. Often
some explicit programming steps are needed. Considerable care must be taken when developing
the simulation program to maintain a clear demarkation between the code of the simulation
model and the code required to invoke the ancillary services. Blurring this separation can be
detrimental because the resulting simulation program may become difficult to verify,
understand, and/or maintain. It has, in fact, been frequently noted (e.g., Oren [2.10]) that an
important quality attribute of a simulation software platform is the extent to which it facilitates
a clear separation of the code for the simulation model from the infrastructure code required for
the experimentation that is required for the achievement of the project goal(s).
Figure above indicates that a verification activity needs to be carried out in the transition from
the simulation model to the simulation program. This need arises because this transition typically
involves a variety of decisions relating to the execution of the simulation model and the
correctness of these decisions must be confirmed. Consider, for example, a simulation model
that incorporates a set of ordinary differential equations. Most modelling and simulation
programming environments offer a variety of solute on methods for such equations and each
has particular strengths and possibly weaknesses as well. If the equations in question have
distinctive properties, then there exists a possibility of an improper choice of solution method.
The verification process applied at this stage would uncover the existence of such a flaw when it
exists.

Tasks Analyze the categories that occur in the functional services of simulation
model.

Operational Phases

Thus far our outline of the modelling and simulation process has focused on the evolution of a
series of interdependent representations of SUI. However, with the existence of the simulation
program, the stage is set for two operational phases of the process that we now examine. The
first of these is the validation phase whose purpose is to establish the credibility of each of the
model realisations, from the perspective of the project goals.
The second phase, which can begin only after the model’s credibility has been established, is the
experimentation phase, or more specifically, the simulation phase. This activity is presented in
Figure 1.1 as the task of ‘goal resolution’. This is achieved via a sequence of experiments with the
simulation program during which an ever-increasing body of data is collected and analysed
until it is apparent that a ‘goal resolution database’ is sufficiently complete and comprehensive
to permit conclusions relating to the goal(s) to be confidently formulated.

Tasks Analyze the operational phases that appear with the existence of simulation
program.

1.2 Simulation of a Pure-pursuit Problem

Pure pursuit is a tracking algorithm that functions by scheming the curvature that will shift a
vehicle from its existing position to some objective position. The entire point of the algorithm

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