Reference:
P. Deo,
B. De Schutter, and
A. Hegyi,
"Model predictive control for multi-class traffic flows,"
Proceedings of the 12th IFAC Symposium on Transportation
Systems, Redondo Beach, California, pp. 25-30, Sept. 2009.
Abstract:
In this paper we first present an extension of the macroscopic traffic
flow model METANET to multi-class flows. The resulting multi-class
model takes into account the differences between, e.g., fast vehicles
(cars) and slow vehicles (trucks) including their possibly different
free-flow speeds and critical densities. Next, we show how this model
can be used in a model-based predictive control approach for
coordinated and integrated traffic flow control. In particular, we use
Model Predictive Control (MPC) to coordinate various traffic control
measures such as variable speed limits, ramp metering, etc. Using a
simple benchmark example from the literature we illustrate that by
taking the heterogeneous nature of multi-class traffic flows into
account a better performance can be obtained.