![](bg7.png)
In the performed implementations, an Integration
module is used in the our case study. This module
uses a target coordinate, received from low-resolution
simulator via HLA, and calculates the movement pa-
rameters required by the agents of high-resolution
simulator. These parameters are stored in the Vehicle-
Behaviour handler, responsible for moving the agent
in the simulated environment. These parameters are
called steeringParameters (implemented as Steering
Behavior algorithms (Reynolds et al., 1999)). They
are necessary for the agent to transit through the sim-
ulated terrain to destinations avoiding collisions with
static and dynamic obstacles. The algorithm for mov-
ing agents in the high-resolution simulator is called
VehicleBehaviour. The setup parameters for these
modules are the following:
• Move defines whether the agent should move. If
false, the agent stops the movement;
• MoveForward defines whether the agent moves
forward or backward;
• DesiredSpeed required movement speed in km/h.
• SteeringCoefficient defined the movement direc-
tion, varying from -1 to 1. Negative values make
the agent turn left, and positives right. If the value
is zero, the agent moves in a straight line.
An usual example of a dynamic simulation situation
occurs when the aggregated Unid1 has to move from
one tactical position to another. The Unid1 vehicles
are in a marching column formation to simulate the
desired doctrine movement behavior. When the vehi-
cles reach the destination, they occupy the new tac-
tical position accordingly. It means these simulated
vehicles are displaced in another terrain formation, a
ready line (side-by-side) formation.
This simulation scenario can be detailed in five-
time frames (i.e., simulation states). First, the Unid1
vehicles are out of a situation change zone and mov-
ing to it according a doctrine rule that specify column
formation. Second, the Unid1 vehicles arrive in the
situation change zone and getting in it. Third, the ve-
hicles are inside the situation change zone and move
in it. Fourth, the Unid1 vehicles arrive at the situation
change zone border and cross it. Finally, the Unid1
vehicles arrive a new tactical position where the for-
mation doctrine rule specifies an in line formation
(side-by-side). As presented by the high-resolution
simulator, Figure 10 details how these simulated ve-
hicles (agents) behaviors can be mapped from the low
to the high-resolution simulation scenario.
Fig. 10(a) presents a 2D projection of the high-
resolution simulator without executing this dynamic
multi-resolution conversion. Fig. 10(b) presents the
same simulation situation where the high-resolution
simulator uses the simulation information received
from the dynamic multi-resolution conversions.
The four agents are organized in a linear forma-
tion in the first simulation time step. They are moving
toward a simulation situation change zone. There is
no difference between the simulated scenarios with
and without the dynamic simulation treatment in this
simulation period of time. The agents adopt a new
formation organization in the second simulation time
step. However, there is a gradual transition from one
formation organization to another, controlled by the
dynamic multi-resolution handlers. It is possible to
observe the agents continue to move in the same ways
when the dynamic simulation conversion is not ex-
ecuting. It means they do not change the doctrine
movement behavior they are executing. The agents
almost reach their destination positions in the third
simulation time step. These positions are located in-
side the tactical position they should occupy. When
the dynamic simulation treatment is not explored, the
simulated agents keep the same movement behavior
even when they almost reach their destination. In the
fourth (and first) simulation time steps, the simulated
scenarios with and without dynamic multi-resolution
simulation handlers are identical in low and high-
resolution simulators. However, there is a smoother
and more realistic transition in the executed agents’
navigation behaviors with the execution of the pro-
posed dynamic multi-resolution handlers.
4 FINAL REMARKS
This work proposes a doctrine-based approach to
solve the multi-resolution conversion problem in dis-
tributed simulation systems. To integrate simulators
with different resolution levels, the proposed doc-
trine rule-based solution allows the representation of
a greater variety of scenarios in which the transition
between different simulators is required. This allows
the representation of more specific simulation situa-
tions involving the transition of military doctrines into
simulated terrain situations with different levels of de-
tail in each integrated simulator. The multi-resolution
solution proposed in this work allows more realistic
integrated simulations, further increasing the role of
doctrine-based rules in providing precise simulation
data for resolution conversions. Directions for future
work are focused on enhancing doctrine-based inte-
gration and, consequently, producing smoother and
more realistic integrated simulations.
Doctrine-Based Multi-Resolution Conversion for Distributed Agent-Based Simulations
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