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Re: [sumo-user] Fast Pedestrian Walks/Negative Time Loss

Hello Jakob,


Thanks for your response.

I've regenerated the network and adjusted pedestrian routing based on your advice.

This seems to have fixed most of the negative time losses.


However, there seems to still be an issue with the output routeLengths.

Attached is a simple example that includes a pedestrian walking back and forth between two points over a crossing, i.e. crossing from one side of a road to another.


Watching the simulation shows the path taken is the shortest, as expected, for both legs.

Yet the output has different routeLengths of 33.20 (shortest path) and 173.20 (longer path along the edges).

The duration is identical, as would be expected, resulting in a small and a negative time loss respectively.


It would seem that the output generation isn't exactly tracking the nodes in the route taken during simulation.


Thanks,


Greg




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Subject: sumo-user Digest, Vol 13, Issue 112
 
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Today's Topics:

   1. Re: Efficient way to count #vehicles within a distance    of
      junction (Shuyi Yin)
   2. Re: Efficient way to count #vehicles within a distance    of
      junction (Jakob Erdmann)
   3. Re: Fast Pedestrian Walks/Negative Time Loss (Jakob Erdmann)


----------------------------------------------------------------------

Message: 1
Date: Thu, 26 Jul 2018 11:17:02 -0700
From: Shuyi Yin <shuyi.yin1@xxxxxxxxx>
To: sumo-user@xxxxxxxxxxx
Subject: Re: [sumo-user] Efficient way to count #vehicles within a
        distance        of junction
Message-ID:
        <CAMYW88ykdm3N+MCatyAAfVrY_A=c94P2ktAULP97WNviKafvGA@xxxxxxxxxxxxxx>
Content-Type: text/plain; charset="utf-8"

Hi Harald,

Thank you for letting me know the other approaches: they may be worthwhile
to explore in the future. And equally thankful for pointing me to that
discussion.

Sincerely,
Shuyi

On Thu, Jul 26, 2018 at 12:15 AM Harald Schaefer <haraldschaefer@xxxxxxxxxxx>
wrote:

> Hi Shuyi,
>
> there are different approaches to control traffic lights depending on the
> traffic.
> One is to look for gaps in the incoming traffic flow (see
> http://sumo.dlr.de/wiki/Simulation/Traffic_Lights#Improving_Generated_programs_with_knowledge_about_traffic_demand
> and
> http://sumo.dlr.de/wiki/Simulation/Traffic_Lights#Actuated_Traffic_Lights)
> For your approach see also the discussion recently here about "Locating
> cars around certain coordinates"
>
> Best regards, Harald
>
> Am 25.07.2018 um 23:43 schrieb Shuyi Yin:
>
> Hi SUMO community,
>
> I'm using TraCI to control traffic lights and would like the traffic light
> to know the number of cars approaching it. Also, I'm only interested in
> counting vehicles that are close enough, i.e. within 20 meters.
>
> My current implementation is to get the ID of vehicles on a lane and
> calculate the distance to the junction. Code is shown as follows. But is
> there a more efficient way fo doing so?
>
> Thanks,
> Shuyi
>
> def numberv(lane):
>     nb = 0
>     for k in traci.lane.getLastStepVehicleIDs(lane):
>         if traci.vehicle.getLanePosition(k) < X-100:
>              nb += 1
>     return nb
>
>
>
>
> _______________________________________________
> sumo-user mailing listsumo-user@xxxxxxxxxxx
> To change your delivery options, retrieve your password, or unsubscribe from this list, visithttps://dev.eclipse.org/mailman/listinfo/sumo-user
>
>
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Message: 2
Date: Fri, 27 Jul 2018 08:52:28 +0200
From: Jakob Erdmann <namdre.sumo@xxxxxxxxx>
To: Sumo project User discussions <sumo-user@xxxxxxxxxxx>
Subject: Re: [sumo-user] Efficient way to count #vehicles within a
        distance        of junction
Message-ID:
        <CAMbUcbymYxk52_obxWZf8xanywLrOe_qz2bAhROuCevTDbh3qw@xxxxxxxxxxxxxx>
Content-Type: text/plain; charset="utf-8"

I was thinking of placing a 20m long detector on each approaching lane to
cover the area of interest and count the cars therein (and also measure
speed and flow as needed).

2018-07-26 20:14 GMT+02:00 Shuyi Yin <shuyi.yin1@xxxxxxxxx>:

> Hi Jakob,
>
> Thank you for replying. In terms of E2-Detector, are you suggesting that I
> put a 20m-long E2-detector on the lane to measure the number of vehicles,
> or several E2-detectors connected to cover the 20m distance?
>
> Or are you saying putting one normal E2-detector to monitor the flow, but
> not the number of vehicles in a 20m-long area directly?
>
> Thanks,
> Shuyi
>
> On Thu, Jul 26, 2018 at 12:50 AM Jakob Erdmann <namdre.sumo@xxxxxxxxx>
> wrote:
>
>> In my own control scripts I often use explicit list of lanes but you
>> could also use
>> E2-Detectors generated in advance http://sumo.dlr.de/wiki/Tools/
>> Output#generateTLSE2Detectors.py
>>
>>
>> 2018-07-26 9:14 GMT+02:00 Harald Schaefer <haraldschaefer@xxxxxxxxxxx>:
>>
>>> Hi Shuyi,
>>>
>>> there are different approaches to control traffic lights depending on
>>> the traffic.
>>> One is to look for gaps in the incoming traffic flow (see
>>> http://sumo.dlr.de/wiki/Simulation/Traffic_Lights#
>>> Improving_Generated_programs_with_knowledge_about_traffic_demand and
>>> http://sumo.dlr.de/wiki/Simulation/Traffic_Lights#
>>> Actuated_Traffic_Lights)
>>> For your approach see also the discussion recently here about "Locating
>>> cars around certain coordinates"
>>>
>>> Best regards, Harald
>>>
>>>
>>> Am 25.07.2018 um 23:43 schrieb Shuyi Yin:
>>>
>>> Hi SUMO community,
>>>
>>> I'm using TraCI to control traffic lights and would like the traffic
>>> light to know the number of cars approaching it. Also, I'm only interested
>>> in counting vehicles that are close enough, i.e. within 20 meters.
>>>
>>> My current implementation is to get the ID of vehicles on a lane and
>>> calculate the distance to the junction. Code is shown as follows. But is
>>> there a more efficient way fo doing so?
>>>
>>> Thanks,
>>> Shuyi
>>>
>>> def numberv(lane):
>>>     nb = 0
>>>     for k in traci.lane.getLastStepVehicleIDs(lane):
>>>         if traci.vehicle.getLanePosition(k) < X-100:
>>>              nb += 1
>>>     return nb
>>>
>>>
>>>
>>>
>>> _______________________________________________
>>> sumo-user mailing listsumo-user@xxxxxxxxxxx
>>> To change your delivery options, retrieve your password, or unsubscribe from this list, visithttps://dev.eclipse.org/mailman/listinfo/sumo-user
>>>
>>>
>>>
>>> _______________________________________________
>>> sumo-user mailing list
>>> sumo-user@xxxxxxxxxxx
>>> To change your delivery options, retrieve your password, or unsubscribe
>>> from this list, visit
>>> https://dev.eclipse.org/mailman/listinfo/sumo-user
>>>
>>>
>> _______________________________________________
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>
> _______________________________________________
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Message: 3
Date: Fri, 27 Jul 2018 14:09:22 +0200
From: Jakob Erdmann <namdre.sumo@xxxxxxxxx>
To: Sumo project User discussions <sumo-user@xxxxxxxxxxx>
Subject: Re: [sumo-user] Fast Pedestrian Walks/Negative Time Loss
Message-ID:
        <CAMbUcbwy=nh6OXearZDBc-4Z8ro8E2E+RbofEH9ZHXvS5sFuvg@xxxxxxxxxxxxxx>
Content-Type: text/plain; charset="utf-8"

Hello,
the problematic behavior is caused by an invalid pedestrian route.
The edge sequence 633 -629 leads to junction 476 which is not connected
with next route edge -813
This causes the person to walk contrary to the expected direction and thus
reach the arrival position earlier than expected.
In the latest development version of SUMO additional warnings have been
implemented to make the faulty behavior more obvious.
A possible fix would be to either use the sequence 633 -629 -629 -813 or
633 -813

The network itself is problematic insofer that it deviates from the two
possible styles for pedestrian network modelling:
1) with crossings and walkingAreas. This makes it explicit where
pedestrians may cross the road and is the recommended style for detailed
pedestrian simulation (
http://sumo.dlr.de/wiki/Simulation/Pedestrians#Building_a_network_for_pedestrian_simulation
)
2) without crossing and walkingAreas but with sidewalks that have no
connections. In this case, pedestrians will assume a fully connected
topology at each intersection but their paths are not modelled (they "jump"
across). This type of network is generated automatically by netconvert when
not generating crossings or walkingareas. Note, that "jumping" potentially
causes negative timeLoss in the current version but this will only be
noticable if the dwadling option is disabled.

In your case the network contains sidewalks that are connected but this
forces awkward detours because there are no connections that allow changing
the walking direction.

regards,
Jakob






2018-07-25 15:15 GMT+02:00 Albiston, Gregory 2012 (PGR) <
gregory.albiston2012@xxxxxxxxxxxx>:

> Hello,
>
>
> I have a scenario where there are numerous pedestrians undertaking walking
> stages.
>
> Some of these stages are resulting in negative time losses meaning the
> pedestrian is arriving faster than the maximum speed.
>
> All the vehicle stages have positive time losses.
>
>
> Attached is an example scenario for one pedestrian which shows the issue.
> The first and final stages are completed with a time loss of -79.75 and
> -188.83. This equates to speeds of 1.84 and 2.41 when the max speed is set
> to 1.79.
>
>
> Is there a modelling reason for the negative time losses?
>
> Apologies if I've missed something.
>
>
> Thanks,
>
>
> Greg
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