Regarding jams: I don't think that there is a traffic-count mismatch. After
all, the traffic counts at the intersection should be no higher than you
real-world measurements.
Also, by using turn-counts instead of edge-counts, a big part of the
route-related ambiguity is eliminated. At least when taken in isolation,
every intersection should be a close match to reality.
>From my experience, there are plenty of things that can go wrong with turn
lanes and lane-to-lane connections that can reduce intersection flow and
create jams in a scenario that is already close to saturation.
Here is a somewhat systematic approach to understanding the jams:
- pick one of your intersections with lots of traffic that appears to be
oversaturated (queues keep growing over multiple traffic light cycles)
- create a sub-network with just this intersection and plenty of incoming
edge length (to better observe growing queues)
- use routeSampler to create traffic for just this intersection (it should
be easy to get a perfect traffic match for a single intersection)
- look at the simulation carefully,
  - Are all lanes used?
  - Is the traffic light switching reasonably?
  - Is the measured flow even plausible?
  - Are there any deadlocks?
If you still cannot figure it out, send me an offending single-junction
scenario at I'll check it out myself.

regards,
Jakob


Am So., 12. Apr. 2020 um 22:43 Uhr schrieb Jakob Erdmann <
[email protected]>:

> regarding public transport for a reduced network, see
> https://sumo.dlr.de/docs/Tools/Routes.html#cutroutespy.
>
> Am Do., 9. Apr. 2020 um 06:55 Uhr schrieb Tetris <
> [email protected]>:
>
>> Hello,
>>
>> I'm still figuring out what causes the traffic jam in the simulation.
>> There
>> is no specific junction at which the traffic jam starts. It's more in
>> general that there are way too many vehicles.
>>
>> I'm going through the list from
>>
>> https://sumo.dlr.de/docs/FAQ.html#the_simulation_has_lots_of_jamsdeadlocks_what_can_i_do
>> :
>>
>> 1. invalid network
>>
>>     invalid lane numbers -> where can I see that the lane numbers are
>> invalid? netcheck.py? But netcheck.py is for edges, not lanes.
>>
>>     missing turning lanes -> Does this mean turning lanes at junctions?
>> This
>> is something I could check just by looking at my network. I created routes
>> for every turn for all the junctions in my network (at least for those
>> that
>> have traffic counts)
>>
>>     invalid connections -> that's checked by netcheck.py?
>>
>>     invalid junctions (big clusters of small junctions should be joined)
>> ->
>> used join junction command.
>>
>> 2. invalid traffic lights (see Improving generated traffic lights) -> I
>> used
>> actuated traffic lights.
>>
>> 3. invalid demand (too many vehicles overall, too many vehicles starting
>> on
>> the same edge). -> This seems to be causing the trouble.
>> I haven't defined starting edges, just the routes and maybe too many
>> routes
>> start with the same edge?
>> The traffic demand is build upon traffic counts which have been made on
>> different days, even different months. Nonetheless I just put these
>> traffic
>> counts into the turncounts.xml for routesampler.py. Can I calibrate the
>> traffic counts with Cadyts or is Cadyts for different use cases?
>> https://sumo.dlr.de/docs/Contributed/Cadyts.html
>>
>> 4. invalid routing
>>     only shortest path were used instead of a user assignment algorithm
>> -> I
>> used randomtrips.py as input for routesampler. Would it be useful to run
>> duaIterate.py on the random trips?
>>
>>     too many vehicles start/end their route with a turn-around. -> I have
>> seen in the simulation that vehicles turn around at the end of the road
>> where the network ends.
>>
>> https://sumo.dlr.de/docs/Simulation/Turnarounds.html#controlling_where_turnarounds_may_happen
>> I could use one of the --no-turnarounds options in netconvert.
>>
>>
>>
>> 5. invalid insertion (vehicles being inserted on the wrong lane close to
>> the
>> end of an edge where they need to change to another turn lane). This can
>> be
>> fixed by setting the vehicle attribute departLane="best" -> I already
>> updated my rou.xml and inserted departLane="best" to every vehicle.
>>
>> I think the main cause of the traffic jam are the traffic counts that
>> don't
>> fit together.
>> https://elib.dlr.de/127994/1/08569938.pdf The chapter V-B"demand
>> adaption"
>> suggests 3 methods: Cadyts, SUMO Calibrators and REROUTER.
>> Which of those 3 methods fits the best to routesampler.py output from
>> random
>> trips?
>>
>>
>>
>>
>>
>> --
>> Sent from: http://sumo-user-mailing-list.90755.n8.nabble.com/
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>
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