Thanks, Jakob. the plots were I mentioned before: https://filebin.net/bhvv8wow4cx0e9x8/Headway.zip?t=h3x55hiu as you can see in the plots, tau was not effective to the mean headway. (all other parameters left at their SUMO default values)
I have real data aggregated with a time resolution of 5 minutes, so the exact time pass of vehicles in every 5 minutes is unknown to me. in order to generate vehicles in the simulation scenario, I use exponential distribution for the departure time of each vehicle. (I've tried some distributions and exponential seems to work relatively better than others) now my questions are: 1) by leaving step-length, action-step-length and tau at their default values, what would happen if I use a subsecond time for the departure value of vehicles (for e.g, the first vehicle depart at 1.2s and the second one depart at 1.7s)? dose SUMO take care of that? 2) I use departLane="best" and departSpeed="max", what would happen if the departure time isn't safe? the departure time is delayed or the speed adapts to the safe one? 3) also, what is a safe situation in vehicles generation? the distance greater than the minGap and the headway greater than the tau or you mean something else by stating safe situation? With Best Regards, Mohsen On Mon, Sep 9, 2019 at 1:47 PM Jakob Erdmann <[email protected]> wrote: > Your plot attachments are missing (possibly blocked by the mailing list). > Mean headway is mostly influenced by the 'tau' parameter. > However, it also depends on the desired speeds (speedFactor, speedDev) and > traffic density: > - if all vehicles have the exact same desired speed (speedDev= 0) then > they will never close the gap to their leader and the headways are fully > determined by the insertion procedure. > - if the desired speeds vary and the density is high, then most vehicles > will be in a queue following a slower leader with headways determined by tau > - if the desired speeds vary and the density is low, then the headways are > determined by insertion as well as the width of the speed distribution (and > of course tau) > > Am Sa., 7. Sept. 2019 um 20:12 Uhr schrieb Mohsen Rahmati < > [email protected]>: > >> Hello, >> I'm working on calibrating a highway section based on real data gathered >> from detectors. >> I've changed 12 parameters* in car-following and lane-changing model to >> decrease the "Absolute Magnitude of Mead Headway Difference" but it seems >> none of them works. Plots were attached. >> I wonder if you could introduce me the parameter that has the most effect >> on mean headway? >> >> by the way: >> SUMO version: 1.3.1 >> car-following model: KraussPS >> lane-changing model: LC2013 >> >> Note*: the effect of simultaneous change of parameters was not >> considered. so by changing a single parameter, all other parameters were >> left at their default values. >> >> >> With Best Regards, >> Mohsen >> _______________________________________________ >> sumo-user mailing list >> [email protected] >> To change your delivery options, retrieve your password, or unsubscribe >> from this list, visit >> https://www.eclipse.org/mailman/listinfo/sumo-user >> > _______________________________________________ > sumo-user mailing list > [email protected] > To change your delivery options, retrieve your password, or unsubscribe > from this list, visit > https://www.eclipse.org/mailman/listinfo/sumo-user >
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