  In this paper, a multi-lane multi-population microscopic model, which
presents stop and go waves, is proposed to simulate traffic on a ring-road.
Vehicles are divided between human-driven and autonomous vehicles (AV). Control
strategies are designed with the ultimate goal of using a small number of AVs
(less than 5\% penetration rate) to represent Lagrangian control actuators that
can smooth the multilane traffic flow and dissipate the stop-and-go waves. This
in turn may reduce fuel consumption and emissions.
  The lane-changing mechanism is based on three components that we treat as
parameters in the model: safety, incentive and cool-down time. The choice of
these parameters in the lane-change mechanism is critical to modeling traffic
accurately, because different parameter values can lead to drastically
different traffic behaviors. In particular, the number of lane-changes and the
speed variance are highly affected by the choice of parameters. Despite this
modeling issue, when using sufficiently simple and robust controllers for AVs,
the stabilization of uniform flow steady-state is effective for any realistic
value of the parameters, and ultimately bypasses the observed modeling issue.
Our approach is based on accurate and rigorous mathematical models, which
allows a limit procedure that is termed, in gas dynamic terminology,
mean-field. In simple words, from increasing the human-driven population to
infinity, a system of coupled ordinary and partial differential equations are
obtained. Moreover, control problems also pass to the limit, allowing the
design to be tackled at different scales.
