  In this paper, we propose the METANET with service station (METANET-s) model,
a second-order macroscopic traffic model that, compared to the classical
METANET, incorporates the dynamics of service stations on highways.
Specifically, we employ the (so-called) store-and-forward links to model the
stop of vehicles and the possible queue forming in the process of merging back
into the highway mainstream. We explore the capability of the METANET-s to
capture well both traffic back propagation and capacity drops, which are
typically caused by the presence of vehicles joining again the mainstream
traffic from the service station. Therefore, capturing these effects is crucial
to improving the model's predictive capabilities. Finally, we perform a
comparative analysis with the Cell Transmission Model with service station
(CTM-s), showcasing that the METANET-s describes the traffic evolution much
better than its first-order counterpart.
