  Vehicles in developing countries have widely varying dimensions and speeds,
and drivers tend to not follow lane discipline. In this flow state called
"mixed traffic", the interactions between drivers and the resulting maneuvers
resemble more that of general disordered self-driven particle systems than that
of the orderly lane-based traffic flow of industrialized countries. We propose
a general multi particle model for such self-driven "high-speed particles" and
show that it reproduces the observed characteristics of mixed traffic. The main
idea is to generalize a conventional acceleration-based car-following model to
a two-dimensional force field. For in-line following, the model reverts to the
underlying car-following model, for very slow speeds, it reverts to an
anisotropic social-force model for pedestrians. With additional floor fields at
the position of lane markings, the model reverts to an integrated car-following
and lane-changing model with continuous lateral dynamics including cooperative
aspects such as zip merging. With an adaptive cruise control (ACC) system as
underlying car-following model, it becomes a controller for the acceleration
and steering of autonomous vehicles in mixed or lane-based traffic.
