You would then write another script to read edge-based traffic measures
(traffic density, average speed) generated by the simulation and also load
the set of edges for each polygon to aggregate the traffic measurements
yourself.
It may also be necessary to load the network itself to retrieve edge
lengths for this aggregation (we have a python library to read the network:
http://sumo.dlr.de/wiki/Tools/Sumolib)

2018-02-15 0:31 GMT+01:00 Rehab Shaheen <eng.reha...@gmail.com>:

> So, this means that i will write a script to create polygons then define
> which edges are inside each polygon.
> Then, how can i obtain data like traffic density, average speed and so for
> each polygon (district)?
>
> On Feb 15, 2018 12:57 AM, "Jakob Erdmann" <namdre.s...@googlemail.com>
> wrote:
>
> Hello,
> if you write your own little script (basically two nested loops) that
> defines polygons in the sumo format for each of your cells (
> http://sumo.dlr.de/wiki/Simulation/Shapes#Polygon_Definitions)
> you can then use an existing tool to determine all edges that overlap each
> of the polygons: http://sumo.dlr.de/wiki/Tools/
> District#edgesInDistricts.py
>
> regards,
> Jakob
>
> 2018-02-14 17:39 GMT+01:00 Rehab Shaheen <eng.reha...@gmail.com>:
>
>> Hello,
>>
>> I have some research work that requires converting a network into a grid
>> of cells of a certain size. Each cell may contain multiple edges. A single
>> edge may be split into multiple edges each one is located in a different
>> cell. I need to collect some data from each cell as a whole, not from each
>> edge.
>>
>> I found that authors of many papers managed to do that but don't know
>> whether they used a certain tool/script that executes this job or they
>> wrote their own method.
>>
>> In both cases, does any one know a tool to generate the grid or from
>> where to start writing my own method?
>>
>> Thanks
>>
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>>
>
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