  We built a multiagent simulation of urban traffic to model both ordinary
traffic and emergency or crisis mode traffic. This simulation first builds a
modeled road network based on detailed geographical information. On this
network, the simulation creates two populations of agents: the Transporters and
the Mobiles. Transporters embody the roads themselves; they are utilitarian and
meant to handle the low level realism of the simulation. Mobile agents embody
the vehicles that circulate on the network. They have one or several
destinations they try to reach using initially their beliefs of the structure
of the network (length of the edges, speed limits, number of lanes etc.).
Nonetheless, when confronted to a dynamic, emergent prone environment (other
vehicles, unexpectedly closed ways or lanes, traffic jams etc.), the rather
reactive agent will activate more cognitive modules to adapt its beliefs,
desires and intentions. It may change its destination(s), change the tactics
used to reach the destination (favoring less used roads, following other
agents, using general headings), etc. We describe our current validation of our
model and the next planned improvements, both in validation and in
functionalities.
