  A flow of moving agents can be observed at different scales. Thus, in traffic
modeling, three levels are generally considered: the micro, meso and macro
levels, representing respectively the interactions between vehicles, groups of
vehicles sharing common properties (such as a common destination or a common
localization) and flows of vehicles. Each approach is useful in a given
context: micro and meso models allow to simulate road networks with complex
topologies such as urban area, while macro models allow to develop control
strategies to prevent congestion in highways. However, to simulate large-scale
road networks, it can be interesting to integrate different representations,
e.g., micro and macro, in a single model. Existing models share the same
limitation: connections between levels are fixed a priori and cannot be changed
at runtime. Therefore, to be able to observe some emerging phenomena such as
congestion formation or to find the exact location of a jam in a large macro
section, a dynamic hybrid modeling approach is needed. In 2013 we started the
development of a multi-level agent-based simulator called JAM-FREE within the
ISART project. It allows to simulate large road networks efficiently using a
dynamic level of detail. This simulator relies on a multi-level agent-based
modeling framework called SIMILAR.
