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The increase of congestion in transport system requires innovative approaches to face the need for sustainable mobility.
The first scheme needs a fine-tuning of border line width, w, to prevent an increase of congestion under high traffic load conditions, while the second one requires a periodic cell-leader election and a replication mechanism.
It is worth noting that the final result could have been in our example a tout-court reduction of car use due to the increase of congestion, which is not the same result obtained by using the activity-based approach.
A (even sophisticated) trip-chain approach could reproduce, at most, how the above-mentioned increase of congestion can influence the trip chain organization of each individual (trip chains vs. round trips), as wtime-period and mode choices of secondary activities (P/D, S).
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This results in the increasing of congestion from the queuing system perspective.
The main consequence of this phenomenon refers to the increase of urban congestions, of average delays caused by vehicles waiting on traffic lights and of number of stops.
The traffic flow is included in the model via the perceived length: the relevant length is equal to its actual length in an uncongested state and increases during periods of congestion, since drivers then experience longer travel times, which are converted into an equivalent increase in the perceived-segment length.
This increases the possibility of congestion.
Increasing the amount of congestion information, however, may end up adversely affecting the performance of the network.
When the number of surface gateways increases, the effect of congestion diminishes, and the effect of clustering grows stronger.
On the other hand, TCP NCE handled the random loss by increasing the size of congestion window.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com