Dear All, I am working on a large-scale simulation. I have all the OD matrics; using OD2TRIPS, I generated the trips file, and using Duarouter, I generated the rou.xml file. I also arranged about 200 E1 detectors in my networks. At the same point, I have the real-world annually average speed data for one day. Now I want to calibrate the model with real-world data. I want to change some parameters such as acceleration, deceleration, Tau, Sigma, max speed, gap distance. This speed data is the only data that I have from the real world. To change these parameters, is it accurate to change with "vehtypedistributionpy"? How vehtype distribution works? Do I need to adjust parameters one by one? Because I think vehtype distribution shift the parameters of the car randomly, I believe. Each time I need to change the parameters and run theSUMO, then calculate the RMSE between model speed data and observed data. And adjust until reach minimum square error is reached. Is it a proper way for calibration? Are there other ways or scripts to calibrate a large-scale network? I also using --meso to run faster. But there is congestion and deadlock traffic and cars just stock on streets. Changing these parameters does not have any effect on my traffic flow. I appreciate it if you could help me.
Best wishes Mehdi -- Sent from: http://sumo-user-mailing-list.90755.n8.nabble.com/ _______________________________________________ sumo-user mailing list [email protected] To unsubscribe from this list, visit https://www.eclipse.org/mailman/listinfo/sumo-user
