Regarding your first question, maybe Michael ([email protected]) can help.
Regarding you second question: A weight file can be created from edgeData
output (
https://sumo.dlr.de/docs/Simulation/Output/Lane-_or_Edge-based_Traffic_Measures.html)
and captures travel times in traffic-filled network. It can be loaded to
affect routing results using the option --weight-files.


Am Mo., 2. März 2020 um 15:36 Uhr schrieb Raheleh Zarei <
[email protected]>:

> Thanks for explanation.
> I'm trying to use libsumo as you said and based on what is said in
> https://sumo.dlr.de/docs/Libsumo.html#building_it. But when I run it I
> get the error in the attachment. All the environment variables and setup
> seems to be OK. Please check the screenshot in the attachment.
>
> My other question is about the first sentence regarding loading a weight
> file corresponding to a jammed network. what do you mean by weight file? Do
> you mean getting the state of network at the point that some roads are
> congested ,while running the simulation and save it to a file(travel time
> of edges will show the weight?)?
>
> Thanks for your help,
>
>
> On Thu, Feb 27, 2020 at 1:44 AM Jakob Erdmann <[email protected]>
> wrote:
>
>> Then I would use libsumo:
>> - load a weight file corresponding to a jammed network
>> - run lots of simulation.findRoute queries (and measure time)
>> - initialize your own algorithm graph from the sumo data structures
>> - run the same queries against your own routing algorithm (and measure
>> time)
>>
>>
>>
>> Am Do., 27. Feb. 2020 um 03:23 Uhr schrieb Raheleh Zarei <
>> [email protected]>:
>>
>>> The basic comparison I want to do is how fast they find shortest path
>>> when there are many s-t queries and do rerouting (finding a new route) when
>>> there are traffic jam in some edges.
>>>
>>> On Tue, Feb 25, 2020 at 1:43 AM Jakob Erdmann <[email protected]>
>>> wrote:
>>>
>>>> Given the distance/travelTime data for each edge, the shortest/fastest
>>>> path in a typical network  is often unique and thus all algorithms reach
>>>> the same result (manhatten grid networks are an obvious exception to this).
>>>> Therefore it does not matter which algorithm you use as long as they use
>>>> the same inputs.
>>>> Thus, I was trying to understand what difference you would expect from
>>>> using non-sumo algorithms.
>>>>
>>>> Am Di., 25. Feb. 2020 um 05:02 Uhr schrieb Raheleh Zarei <
>>>> [email protected]>:
>>>>
>>>>> I am not sure if I understand the first paragraph of your email. The
>>>>> algorithms are shortest/fastest path finders(I call them non-sumo
>>>>> algorithms). Actually the thing I want to do is as follow:
>>>>> -Import map of a city as road network
>>>>> -Make some source and target points based on the map
>>>>> -Run random number of source-target queries between these source and
>>>>> target points and for every query (or in a time interval for example every
>>>>> 20 second) get the current situation of the network (like the travel time
>>>>> of edges because it might have changed due to heavy traffic in some edges)
>>>>> and find the shortest path/fastest using non-sumo algorithms.
>>>>> -calculate the path found (time/distance) by non-sumo algorithms for
>>>>> each source-target query and also average of time-distance for the whole
>>>>> s-t queries during simulation.
>>>>>
>>>>> Thanks for your help,
>>>>> Raheleh
>>>>>
>>>>>
>>>>>
>>>>> On Mon, Feb 24, 2020 at 2:11 AM Jakob Erdmann <[email protected]>
>>>>> wrote:
>>>>>
>>>>>> It depends on what these other algorithms are. If they are also
>>>>>> shortest/fastest path finders that it would be sufficient to alter the
>>>>>> weights/travel times assigned to the network edges (via TraCI or xml
>>>>>> inputs) and keep using the sumo algorithms.
>>>>>> You could also let these other algorithms compute their routes
>>>>>> externally and then alter the routes in the simulation (via TraCI or xml
>>>>>> inputs).
>>>>>> regards,
>>>>>> Jakob
>>>>>>
>>>>>> Am Mo., 24. Feb. 2020 um 02:58 Uhr schrieb Raheleh Zarei <
>>>>>> [email protected]>:
>>>>>>
>>>>>>> Thanks for your explanation.
>>>>>>> Yes, you are right. So, what you suggest to do if I want to compare
>>>>>>> other routing algorithms with SUMO routing algorithms from traffic
>>>>>>> efficiency point of view?
>>>>>>> Do I need to develop SUMO source code and add other routing
>>>>>>> algorithms, or there is another way I can call these algorithms inside 
>>>>>>> SUMO.
>>>>>>>
>>>>>>> Thanks for your time and help.
>>>>>>> Raheleh
>>>>>>>
>>>>>>> On Tue, Feb 18, 2020 at 3:57 PM Jakob Erdmann <[email protected]>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Libsumo is useful if you need at lot of interaction between your
>>>>>>>> code and sumo because it reduce communication overhead compared to 
>>>>>>>> TraCI.
>>>>>>>> If you are comparing the algorithms in terms of overall traffic
>>>>>>>> efficiency then most of the time is spent on simulation rather than 
>>>>>>>> routing
>>>>>>>> so you won't need Libsumo.
>>>>>>>> If you are repeatedly calling the sumo routers to compare the found
>>>>>>>> routes with your own routes then it makes more sense.
>>>>>>>> For details, see https://sumo.dlr.de/docs/Libsumo.html
>>>>>>>> regards,
>>>>>>>> Jakob
>>>>>>>>
>>>>>>>> Am Mo., 17. Feb. 2020 um 10:19 Uhr schrieb Raheleh Zarei <
>>>>>>>> [email protected]>:
>>>>>>>>
>>>>>>>>> Hello,
>>>>>>>>>
>>>>>>>>> I would like to test two routing algorithms using SUMO as a
>>>>>>>>> framework for comparing these algorithms. Inside the program of these
>>>>>>>>> algorithms (written in C++ in Linux), I need to call SUMO, start it, 
>>>>>>>>> get
>>>>>>>>> the required variables and reports and then close it and see the 
>>>>>>>>> results.
>>>>>>>>> What do you suggest for this? Do you think using Libsumo is a good 
>>>>>>>>> idea?
>>>>>>>>> and if yes what's the procedure of using it.
>>>>>>>>>
>>>>>>>>> Best,
>>>>>>>>> Raheleh
>>>>>>>>> --
>>>>>>>>> *RAZ*
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