Abstract
The well-known Lighthill-Whitham-Richards (LWR) theory is the
fundamental pillar for most macroscopic traffic models. In the past,
many methods were developed to numerically derive solutions for LWR
problems. Examples for such numerical solution schemes are the cell
transmission model, the link transmission model, and the variational
theory (VT) of traffic flow. So far, the latter framework found
applications in the fields of traffic modelling, macroscopic fundamental
diagram estimation, multi-modal traffic analyses, and data fusion.
However, these studies apply VT only at the link or corridor level. To
the best of our knowledge, there is no methodology yet to apply VT at
the network level. We address this gap by developing a VT-based
framework applicable to networks. Our model allows us to account for
source terms (e.g. inflows and outflows at intersections) and the
propagation of spillbacks between adjacent corridors consistent with
kinematic wave theory. We show that the trajectories extracted from a
microscopic simulation fit the predicted traffic states from our model
for a simple intersection with both source terms and spillbacks. We also
use this simple example to illustrate the accuracy of the proposed
model. Additionally, we apply our model to the Sioux Falls network and
again compare the results to those from a microscopic simulation. Our
results indicate a close fit of traffic states, but with substantially
lower computational cost. The developed methodology is useful for
network-wide traffic state estimations in real-time, or other
applications within a model-based optimization framework.