  Recently, a fully two-dimensional microscopic traffic flow model for
lane-free vehicular traffic flow has been proposed [Physica A, 509, pp. 1-11
(2018)]. In this contribution, we generalize this model to describe any kind of
human-driven directed flow including lane-based vehicular flow, lane-free mixed
traffic, bicycle traffic, and pedestrian flow. The proposed intelligent-agent
model (IAM) has the same philosophy as the well-known social-force model (SFM)
for pedestrians but the interaction and boundary forces are based on
car-following models making this model suitable for higher speeds. Depending on
the underlying car-following model, the IAM includes anticipation, response to
relative velocities, and accident-free driving. When adding a suitable floor
field, the IAM reverts to an integrated car-following and lane-changing model
with continuous lane changes. We simulate this model in several lane-based and
lane-free environments in various geometries with and without obstacles. We
observe that the model produces accident-free traffic flow reproducing the
observed self-organisation phenomena.
