Hello, you are posing an interesting question that hasn't really come up before. It appears that typical scenario creators didn't have access to both OD-Matrix and counting data. Hence, there is a gap in documentation and tooling for this use case. Your thoughts on the matter are correct.
With regard to 1. (using equilibrium routes rather than free-flow routes) you could employ the following alternatives: - create candidate routes by loading the trips in sumo and writing --vehroute-output (see https://sumo.dlr.de/docs/Demand/Dynamic_User_Assignment.html#oneshot-assignment ) - create move variance in the routes by running duarouter with option --weights.random-factor With regard to 2, you should be able to use the routeSampler.py option --od-files to ensure that all vehicles are put into the simulation (rather than only those that pass city-center counting locations). This should in principle allow a perfect fit with the OD-Matrix. There are some limitations to this approach: - there is currently no tooling to generated the od-files (i.e. https://github.com/eclipse/sumo/issues/10058) - by using a fixed assignment of trips to edges (from od2trips), you are losing degrees of freedom that might be needed to match the counting data. A possible fix is outlined at https://github.com/eclipse/sumo/issues/6890 - there is no guarantee that the sampled routes have a similar frequency compared to the "equilibrium" input. You can set option --weighted to improve this likelihood but if the counts go in a particular way you could get artifacts Overall I'd be quite interested in hearing about your progress if you chose to follow the OD2trips + routeSampler approach. If you happen to work on tooling, pull requests are also welcome. regards, Jakob Am Do., 27. Jan. 2022 um 09:45 Uhr schrieb Schaniel Joel < joe...@student.ethz.ch>: > Dear all, > > > I am working with a real-life network in SUMO and could need your advice > for calibrating the simulation. > I have an OD-matrix and a network given. Further, I have traffic count > data from edge counts in the city center (but not from the rest of the > region). > > So far, I have created TAZ's according to my OD matrix and generated trips > with od2trips. This comes with the benefit that origins and destinations > are spread over the whole TAZ. > > Now, I would like to use routeSampler.py to calibrate the traffic > according to the edge count data. My idea so far was to: > > 1. Use duarouter to convert trips to routes (since origins and > destinations spread over all edges this would basically create a route for > each trip) > 2. Use this set of routes and my edge counts as input for > routeSampler.py > > > However, I see two major problems with this approach. > > - Duarouter creates all routes based on free-flow speed and does not > include alternative routes which would only be used during congestion. > - All traffic count data is from the city center, therefore, > routeSampler would not use any route that does not pass an edge with > traffic counts (e.g. traffic that bypasses the city center). > > > The first problem could probably be solved by using duaIterate.py, > creating a set of routes in the dynamic user equilibrium. > But the second point seems to be tricky. In the documentary > <https://sumo.dlr.de/docs/Tools/Turns.html#origin-destination_restrictions>, > it is also briefly mentioned that OD files can be used, but only > edge-based. Could I work with this option to make sure the routes still fit > the OD more or less? > > > Are my thoughts correct? Would it be better to use another tool to try for > example to scale the OD as a whole to fit the traffic counts? > > > Thanks a lot for your help in advance! > > > Best regards, > > Joel > _______________________________________________ > sumo-user mailing list > sumo-user@eclipse.org > To unsubscribe from this list, visit > https://www.eclipse.org/mailman/listinfo/sumo-user >
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