[sumo-user] Large-Scale Model Calibration

[mehdi <kpk628@xxxxxxxxxxxx>]

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



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