  Vehicular traffic is a classical example of a multi-agent system in which
autonomous drivers operate in a shared environment. The article provides an
overview of the state-of-the-art in microscopic traffic modeling and the
implications for simulation techniques. We focus on the short-time dynamics of
car-following models which describe continuous feedback control tasks
(acceleration and braking) and models for discrete-choice tasks as a response
to the surrounding traffic. The driving style of an agent is characterized by
model parameters such as reaction time, desired speed, desired time gap,
anticipation etc. In addition, internal state variables corresponding to the
agent's "mind" are used to incorporate the driving experiences. We introduce a
time-dependency of some parameters to describe the frustration of drivers being
in a traffic jam for a while. Furthermore, the driver's behavior is externally
influenced by the neighboring vehicles and also by environmental input such as
limited motorization and braking power, visibility conditions and road traffic
regulations. A general approach for dealing with discrete decision problems in
the context of vehicular traffic is introduced and applied to mandatory and
discretionary lane changes. Furthermore, we consider the decision process
whether to brake or not when approaching a traffic light turning from green to
amber. Another aspect of vehicular traffic is related to the heterogeneity of
drivers. We discuss a hybrid system of coupled vehicle and information flow
which can be used for developing and testing applications of upcoming
inter-vehicle communication techniques.
