Hello,
1)  It depends on the kinds of randomization you are using.
departLane="random", departPos="random" and departSpeed="random" introduce
a lot of noise. I wouldn't expect the default value of sigma="0.5" (driver
imperfection) to have a +/- 15% impact but I also haven't done systematic
tests on that). If you are also randomizing the vehicles (routes, departure
times) my next point applies.

2). I would expect significant variations on a timescale of 10 minutes
(particularly in low and medium traffic situations). When we test traffic
light programs, we usually average results over several hours.

3). summing the waiting time is a resonable performance indicator. Even
better In my opinion would be time loss (which also occurs if vehicles
drive slower than optimal but do not stand still). You can compute this by
using tripinfo-output: First do a simulation for every route where there is
no delay at all (no other traffic and the traffic light is green). Then
compare this to actual travel times with traffic light and full demand.

regards,
Jakob

2014-01-31 SEMET Yann <[email protected]>:

> Hi all,
>
> I'm observing rather strong variations (up to  +/- 15%) of performance
> with respect to the random seed fed to the simulator. I work on traffic
> light optimization and my performance is measured in terms of average
> waiting time over a period of 10 minutes after a 5 minutes installment
> period. I'm worried for two reasons : 1) it may mean that the impact of
> good vs bad TL programs is indistinguishable from natural simulation noise
> 2) it will force me to average my objective function over several
> simulation seeds, say 10, which will make optimization 10 times slower..
> Hence a few questions for you expert SUMOers :
>
>
> 1)      Is this amplitude of variation normal or indicative of a problem ?
>
> 2)      Is my timeline (5+10 minutes) sufficient ?
>
> 3)      I use edge data aggregation to one big chunk (begin=300, end =
> 900) to sum waiting time over all edges. Is this a proper way of performing
> TL performance assessment ?
>
>
> Thanks,
>
> Yann
>
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