Interesting. Thank you Jakob and Ilya for your comments. |@Ilya|: I
don’t use public transport, but I do use parking areas. Will let you
know if I have any progress.
It seems that I have two options to systematically improve the traffic flow:
1. modify |duaiterate.py| and implement some basic evolutionary algorithm.
2. use APIs to somehow link MATSim and SUMO.
I'm thinking of the 2nd one, but not sure how to convert the demand data
between the two programs. I'll do some research - thanks again for your
help :-).
2020/06/15 08:57, Jakob Erdmann wrote:
There is currently no tool in sumo that would systematically adjust
departure times to improve traffic flow.
Am Mo., 15. Juni 2020 um 01:41 Uhr schrieb Илья Левашев
<levashev1...@gmail.com <mailto:levashev1...@gmail.com>>:
It looks like you need duaiterate.py, it iterates defined number
of iteration or unless changes between iterations will small
enough. However, I've got some problems using parking flows and
public transit, unfortunately, I haven't fixed it.
The second annoying thing is amount of output files you will have
and instead of MATSim you will have just one folder for all
iterations.
If you will successfully use duaiterate it will be great to see
how to fix file-chaos and problem with pt and parking.
вс, 14 июн. 2020 г., 23:23 Chris Abraham <chrisb...@gmail.com
<mailto:chrisb...@gmail.com>>:
Hi everyone. MATSim (another agent-based simulator like SUMO)
makes use
of an Evolutionary Algorithm to optimise the demand to prevent
unrealistic traffic jams.
The software runs the simulation multiple times, and in each
iteration,
it slightly adjusts the times and routes of the trips, gradually
eliminating traffic jams. Is there anything like this planned or
implemented in SUMO?
The reason I am asking this question: I am using a statistics
file to
describe the city, then use ActivityGen and DuaRouter to
convert the
statistic file into demand that can be imported to SUMO.
However, there
are jams because the vehicles follow the statistics file too
precisely.
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