Dear François,
as you already noted, travel times on inflow edges depend a lot on the
insertion rules and the used car-following settings. The next vehicle to be
inserted needs some space (vehicle length and distance to leader) and only
one vehicle per time step and lane can enter the network. To some extent,
your question is similar to "how to replicate the fundamental diagram in
sumo" (especially the saturated part). You need some way to increase the
vehicle density which will lead to longer travel times.
Either create an artificial bottleneck or let vehicles circulate in the
network for longer and keep some distance from inflow places when measuring
the travel time.
Best regards
Mirko
-----Original-Nachricht-----
Betreff: [sumo-user] Validation of BPR Method in SUMO: Seeking Help on
Replicating Asymptotic Results in Straight Road Sections
Datum: 2024-01-15T08:29:15+0100
Von: "François Vaudrin via sumo-user" <[email protected]>
An: "Sumo project User discussions" <[email protected]>
Hello,
I'm seeking assistance in validating the BPR method using SUMO to express
travel time based on road capacity. The Bureau of Public Roads (BPR)
formula is commonly used to model travel time on a road as a function of
its capacity: After reaching a certain flow threshold, travel time
increases exponentially until reaching the ultimate capacity of the road.
where:
* T is the travel time on the road,
* Tff is the initial travel time,
* q is the flow of traffic (number of vehicles per unit time),
* qpc is the capacity of the road (maximum number of vehicles the road
can accommodate per unit time),
* α and β are adjustable parameters.
Despite increasing the flow of vehicles in a network with SUMO, Vehicles
are being pushed backward before entering the network, possibly due to a
required distance (likely related to the car-following model), but the
results are not the same than BPR. The Time Tff appears to be a straight
line rather than an asymptotic curve.
Appreciating any insights or suggestions to obtain similar results of BPR?
Wishing a fantastic year ahead to the SUMO teams and contributors!
François Vaudrin
semaphor.ai
Québec city, Canada
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