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Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri Jan 25, 2019 12:22 am
by AlexAegis
hansjoachim wrote: Thu Jan 24, 2019 9:05 pm
AlexAegis wrote: Thu Jan 24, 2019 5:52 pm
Sadly I don't know how can I improve this further
So I improved it with correct signals.
I also made a better version with extra right turns.
Original: 30 trains/min set 1
Correct signaled: 41 trains/min set 1
With extra right turns: 48 trains/min set 1
btw: those test are with rocket fuel. With Nuclear fuel the numbers would be higher
Thanks! Yes, I'm using nuclear fuel that's why my numbers are higher.
I wanted to let the trains as far in into the intersection as I could without completely deadlocking it, that's why I don't have chain signals everywhere. Guess it was a bad idea. Also, on every left turn before merging back to the "output" track why isn't that signal a chain signal?
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri Jan 25, 2019 6:22 am
by hansjoachim
AlexAegis wrote: Fri Jan 25, 2019 12:22 am
Thanks! Yes, I'm using nuclear fuel that's why my numbers are higher.
I wanted to let the trains as far in into the intersection as I could without completely deadlocking it, that's why I don't have chain signals everywhere. Guess it was a bad idea. Also, on every left turn before merging back to the "output" track why isn't that signal a chain signal?
Nuclear explains it partly, but not from 30 to 50.
Left turns are often the limiter so if you have more straight turns or right turns your number would be higher. But also if all trains go left your numbers would be higher as every cycle two trains can pass the intersection.
Your test isn't wrong, it's just different.
The new signals might not give an increase in your test
The last signal isn't necessary, you don't need chain signals for merging.
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Mon Feb 11, 2019 12:34 am
by Dolu1990
I got a 2 way, 415 trains on 5 minutes => 83 trains/minute (3 length trains)
This solution has some good sides :
- Trains can turn back by crossing the middle section three times.
- It can be scaled without too much cooking
- The flow is good, the main slow down come from the middle horizontal vertical 6x6 cross
Deadlock/congestion of the loops is avoided via wire signals.
intersection screenshot.png (916.94 KiB) Viewed 9736 times
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
Copy blueprint
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Mon Feb 11, 2019 2:18 pm
by hansjoachim
Dolu1990 wrote: Mon Feb 11, 2019 12:34 am
I got a 2 way, 415 trains on 5 minutes => 83 trains/minute (3 length trains)
This solution has some good sides :
- Trains can turn back by crossing the middle section three times.
- It can be scaled without too much cooking
- The flow is good, the main slow down come from the middle horizontal vertical 6x6 cross
Deadlock/congestion of the loops is avoided via wire signals.
There are many good things about this intersection
Separating left, right and straight
Multiple lanes to increase throughput in the center.
Staying at 2 lanes
The signals are correct just lacking a couple.
The throughput is significant higher than the best unbuffered intersections.
It also looks good
I haven't checked out the circuitry but do you need it? Well probably for u turn
This intersection is really designed for 2 levels, as everything is in one level in factorio the left turns doesn't make sense. They cross many too many paths. You should let left turn drive to the left first and not to the right first.
The U turn here is horrible as it crosses way too many train paths multiple times. You should have a good U turn before this intersection to prevent trains from taking U turns in this intersection.
There are some lacking signals in the cross where left turns trains "reenter". It should be seperated with signales to increase throughput.
To compare this to the other intersections and to get it added to the list someday, you need to make a 6 car design.
Tldr
Add U turns before the intersections
Add some signals to fix the 'cross'
Left turn is this intersection largest problem and should be addressed
Make a 6 car version aswell
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri Feb 15, 2019 4:37 pm
by Dolu1990
This intersection is really designed for 2 levels, as everything is in one level in factorio the left turns doesn't make sense. They cross many too many paths. You should let left turn drive to the left first and not to the right first.
Sorry, i'm confused, i'm not sure to read your words properly.
When you say left turn, is it from a left hand drive or a right hand drive perspective ?
I mean on the picture, which is left hand drive, the left turn is the first thing the train can do, and it cross nearly nothing.
About wire signals, they are required to avoid having all the 24 inner slots busy, which would create a dead lock.
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri Feb 15, 2019 4:53 pm
by Dolu1990
Were you talking about the left turn after the middle cross ?
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri Feb 15, 2019 5:02 pm
by hansjoachim
Oh I am sorry, its right turns for LHD
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri Feb 15, 2019 5:33 pm
by Dolu1990
Ahhh, ok ^^
How would you " You should let left turn drive to the left first and not to the right first" ? (LHD perspective)
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri Feb 15, 2019 10:07 pm
by Dolu1990
Damned i mixed myself with LHD / RHD.
My question was, what exactly do you mean by "You should let left turn drive to the left first and not to the right first" (RHD perspective)
You mean before the middle cross ?
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Sun Mar 31, 2019 1:22 pm
by Themme
Hello folks,
Ive been messing around with some intersections, and I am kinda curious what you think of this design, how to measure throughput?
Ive created it myself a moment ago in my own factorio save.
https://www.dropbox.com/s/vhn8s5as89ipu ... 1.jpg?dl=0
Thanks, Themme
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Sun Mar 31, 2019 1:50 pm
by hansjoachim
To test it, you can throw it on the test bench. Download my version of it if you want to understand the test bench more easily.
It doesn't make any unnecessary crossings, no roundabouts and is correctly signaled. It should perform exactly like the compact intersection or really any good 4 way 2 lane unbuffered intersection.
There are four unnecessary chain signals in the center.
Is you want more throughput you have you to add buffers in some way.
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Thu Apr 25, 2019 1:46 am
by Requia
I widened the multicross interior so that I could fit a roboport in the center and I got slightly better performance. 89-->91 on the p1 test in hansjoachim's test bench.
https://pastebin.com/14CXYw5B
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Thu Apr 25, 2019 5:23 am
by hansjoachim
Requia wrote: Thu Apr 25, 2019 1:46 am
I widened the multicross interior so that I could fit a roboport in the center and I got slightly better performance. 89-->91 on the p1 test in hansjoachim's test bench.
https://pastebin.com/14CXYw5B
Great
91 is within the margin of error. As Aaargha wrote in the first post:
I let it run for 15 min while counting how many trains exit the intersection. When the time is up I calculate the average throughput in trains/min. Note that this is not too exact and small measured differences between intersections may not really mean that much.
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Thu Apr 25, 2019 9:58 pm
by Tallinu
Let's see...
http://fbpviewer.trakos.pl/b/OoOTd5Vodk ... tHjTMrkK2w
Interesting adaptation. That 6x6 square in the center means it would still have room for LHD signal placement. Would only be able to put a medium power pole in there with the roboport, or a nearby substation could be used to power it...
I had originally gone for the closest possible track placement to minimize the time required for a train to make the crossing, but two track segments is undoubtedly not the biggest performance factor.
I've made a note to change that in the "official" versions next time I fiddle around with them. (Who knows when that will be though, heh)
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Tue Apr 30, 2019 7:36 pm
by yvanaquino
Is it possible to submit a design for testing and improvement/feedback? I helped my kid develop this but it's his intellectual property.
0eNrNnU2PHMmRpv8KUacZgCGEf7v3sW/a2blopb0MBIFsVo8KosgGm9RKEPjfN4uVmVWsMst4n8gIjE5qtcSHnuEeFuZur9v7z5u377/c/vLp7sPnP739+PEvNz/88/Hf/Hrzw389+a/3/9vdTx8/PPzrX+/++8Ob9/f/7vM/frm9+eHm7vPtX29e33x489f7//bpzd37m6+vb+4+vLv9+80P4esfX9/cfvh89/nu9uHPf/sv//jThy9/fXv76fB/OP/JXz8f/ux///nz9A3x+uaXj78e/tTHD/d/1YGU5tc3/7j5Yerx69fXLzBRxeSLmIRHM1uYjEdjYsoZ89OXT3+7fedA4niAtHJ47u/uPt3+9PA/FgNZv5uo6ac/v7n7MB2n9CW4/6Yc0Yd/skbY6PNq3cJ07YfmYP/QbCAHnQJ7ZGH+/oF5jyqH7x7V4vACXvetmuPDC9/h4JXfssnBS9/hqGv/+NTr+P6ZB4tZ8W80g0Ro+DfaHHXZP/5GizLwrzKDTZzxr7I5eGVX882LeGU7nKS9wTGe3uBa7GAXs0jqi6SCn5H51saKn5HNaeSz8Bjrvv2+xVgXO6I3SJfX//38feOaESfNeE5sTsBzYnP09V8vchJ+PnZqlPHzsTkFPx+bU/HzsTkNPx8z7qWOn4/NwZmLzckzfj42J9DnU8w4nCN9Pg4n0efjcDJ9Pg6n4OdjxuCMsxOHg7MTh9Px87E5OD4XM44VHJ8dDo7PDgfHZ4eD43Mx41jB8dnh4PjscHB8djg4Phd7M43js8PB8dnmVByfHQ6Oz9mMYxXHZ4eD47PDwfHZ4eD4nM04VnF8djg4PjscHJ8dDo7P2YxjDcdnh4Pjs8PB8dnh4PiczTjWcHx2ODg+Oxwcnx0Ojs/ZjGMNx2eHg+Ozzek4PjscHJ+TfUaK47PDwfHZ4eD47HBwfE5mHOs4PjscHJ8dDo7PDgfH52TGsYHjs8PB8dnh4PjscHB8TmYcGzg+Oxwcnx0Ojs8OB8fnZMaxgeOzw8Hx2eaEGQdoD4QjdHRqRThEeyAcoz0QDtIeCEfpaNeZZhymPRCO0x4IB2oPhCN1tGtfAYdqD4RjtQfCwdoDJbGulx4wYSzXtEPItMRz/0/2+Mq6ArkP5OvdLhbyqqMH6rSk/e3HCSXtgReJPcKoFt0bHCGvTUb7k8GLkx4o4WfmgHD6EuxIH3H+4oFwAuOBmhYz7t+Qb5j0/VKIJlSO+vH0M+v32GRicTU+OHoMXI73QAFPgwOKJDROcZxezpCev5zmjCQsQQn2NyZhDYoHKvjROaCqreApnT574fsHVk2q/EWY7lf7N25UJqLr3Eq4Q+dmwNUrndN93Na5QefOhCt/PKZA5k2vjE6BzJteKZ0Cmreic9G8VZ2L5k1/39C06a8bmjX9bSOTVsDLRrDyu0ZmTK/RorHqORuhym8ZWQV6NZcsWb22i14wvdSL4gGv/AZ7X8JLvw6I1349UFATi5NGXHhevBIc7D0JLwV7IHyM5YGKtrOc8vmooEnJa60rk2MR37Rx36faiItfDXuLVvGbYXMafjEcjp66ndVvwuPSa8pTzgCrJ245Aqyet52lhApWT9tSB1g9a0tkyvSkLZEp05O2RKZMT9oSmLI+452ihA14oyhhI94nStiEt4kSNuNdooQteJMoYSveI0rYhreIErbjHaKEHXiDqGD1CvsEZkyvt09gwkaku0OJmujmUKJmuDeUoAVuDSVohTtDCdrgxlCCdrgvlKCDbgsFatTr/CAGRL3oDwJW1BUAILpGXQ4APgVR1wZEMlv6e0Vmq+JLOgpVl8aQ2dIrS2S2hrbTP1UQynKxKnKdgX17MIinEKdDiLRc049cceCMDVeVss3R66unQu3yjeTI5AbpXO9+UVGz55dLfO3fjq/52z0a1AvPx3USbAhXGdjXi2f0Qgk15YjlBfYFal1ccFxqs7AWsNDAGRuVGTgPn637elz3L1QeZujAwgNnjI2eIWVljXR6hCRRBzsHVqKHrkA4nUopI02BHkpJ1EjPpCRqokdSEjXTEymJWuiBlESt9DxKomLhgkTFsgWJikULCpVLFiQqFixIVCxXkKhYrCBRsVRBomKhgkTFMgWJSkUKEpRKFCQoFSgoUCxPkKBQnCAxoTRBYkJhgsSEsgSJCUUJEpNKEiQoFSRI0A5PniTogAdPClSXKYDAD+6r6xOlSxbA57TSm2USNMMzJwla4JGTBKU3F+zDA3DfvV7CoCZSj/qNFz2kqkkfTKD77FZKM3tqibcYHsUg2lifaBuEJ3FWhIhwqv1x+olR5Y+DobofB0PbrdmN5BrttuZg6AvhYDrdRIVZeOuBAuEYoCQsUSBkgA10H6VhI91IadhEd1IaNtOtlIYtdC+lYSvdTGnYRndTGrbD7ZRGHXA/JVGB/gDMF9AfgOnS9QdgskArAADNbFOlQQvbVWnQyrZVGrTBfZVG7XBjpVEHuij4/JJVMruC0hqprTxOM72K7XFoXdTjJJqdhqBkkGnOUKqscgvcN4a8XIBNuB2BLcRPuBuBx6HNCDzOQPfsQ7Nb2eLF77TExYvf4eDF73CoKMC+Eptwt3OPQy+aehy8mrvNwavZ4eDV7HAG7LwdZ7sdQ4p0RdvX7VOkK9rjxFWdt7/9vsV+BwkX/b1R5lUdvNVR0t4ydtuIFOnq9zh09Xscuvo9Du0rE51G4HjtOxy89h0OjeYeh57T2v17Eu5w7nFoBw2Pg3UsDod2ALN7QCXc4dzj0MtiDgd3OPc4tP+X3Ucs4Q7nHocennocenrqcWh8To6BAI3PHofGZ49D47PHofHZbmSYcIdzj0Pjs8eh8dnj0PhsN8JMuMO5x6Hx2ePQ+OxxaHy2G6kmfM/d49D47HDwLXePQ+Oz3Yg34XvtHofGZ49D47PHofE5O4YquODrcGh89jg0PnscGp/tRuAJdzj3ODQ+exwanz0O1jnYcQx3OPc4ND57HBqfPQ6Nz7YRQcIdzj0Ojc8OB3c49zg0PhfHQInGZ49D47PHofHZ49D4bBuhJNzh3OPQ+OxxaHz2ODQ+20Y6CXc49zg0PnscGp89Do3PthFTwh3OPQ6Nzx6HxmePQ+OzbeSVcIdzj0Pjs2Mshhucexwanz1DOawNczhYHOZwsDrM4dD4bBsJZlxL9Dg0PnscGp89zkA9sU/Ky5rsGkwOM/L2rW25hpBDWNW32x8jXuvZ5uC17nAy8gp+/syKySywEXhNSj0nhwrbd6tceg3ZNrvNoCp5mUN7PVfHGJO2evY4AfnFt2RT6Mq3baBzTMjUvaVltUaOtN7ujY0Kgm0D74z9lz0OXdm2aXqOdGV7HFpvb9WJo7jmaNvTZ1xz9Djr6u3fft9yhMItzJtjcYvXucPBwnf7fUlY+X7g/PH1zd3n278e/szb919uf/l09+Hz4f///s3b2/eHf1f/8OrHLz//fPvp9t2r30//68uHh+f6+uZvt59+fbhUkeZQa4ux3PdHufvw7vbv31od/PMJ7/CX3v308cOvNz/81z9vjrN4+Hef//HL/Vi//fXfzffNIyncD/DbD727ffjzz9sZsY6eM2t3H8U3LDCsGHSnWPRG83mXNuhllybodZcW6G2XBuh9l/bnY5/m5/Muvc/DLq3P4y6dz9Mujc/zLn3P92h7Xvfoet72aHre9+h5PvZoeR7nPTqeR9zbTqLi3nYSFfe2k6i4t51ELejgYlIuGOhbiHNr3q5cPqU96LrQraxf25zYHCpvedyVexsrszepb3oKNHvTsJF3Y1885uG2SlW4N5Fx++u8vBR4D6NJ8OSSzZdiM1snmrdR2h69pEkHI70lJ+hgBNqHgg5GoNUp6GAE2rKSDkb6bJEORvpsgQ5GYLLKDj2kQf8iMFVthw7SutATzNPYvn+0LgDVH6guBtVnXheG6ktUF4mCl0lXjIL3XpePghAF2heBeWo79I0ufYe20brkFHxOq1pnbHLLZF2K6iQoVoYGdKl2LmVlaFU9CUwn11ThgWZqYykwC/ZnycI8VdYtOywnp7qq1RmnOfVqR+Smj3OoFlePJ9bK5qSt3VFpdLyj0rCs3APHDF8x4TSAWzYJfRG4YZMCxXZNCrSxAKM80U7jizLOQTeqAhS0SEry3JMGSfLck/ZI8twTeyZ5oog5kz5RhW7TFWilu3QF2ugmXYF2ukdXoINu0QUoaIgU5IkC/ZDkeQJuTPI0AS8meZZGhrtzhVnY5lxBVrY3V5CNbc0VZGc7cwU52MZ8Vgq/M9yYS9AAN+YSNMKNuQRNcGMuQTPcmEtQ2iBJgla4MZegVLAvQTtsrCtBB6yjKdDAnGcEhU4I3HlGGCc9l5CgCe14pR+f4c5cGme5zoTHhuo3BMByotcFJGi/0qQkmNTBSnFl+bgjRHbKp7hiAx8n87fb44xXGrQUk5ooVajuBtbv6fGsJ0um47HAsx4RW2G4qsqsNQgVDicDF1JUZSlgIYWg+QgJO9UoTqEJO9VIVOxUI1GxU41ExU41EhU71UhU7FQjUalTjQSlTjUSlDrVKNBMnWokKHSqkZjQqUZiQqcaiQmdaiQmdKqRmNSpRoJSpxoJSp1qJCh1qlGghTrVSFDqVCNBqVONBE3Y4GI59cHttgQtXiiF1iMEiWMolV17CUH5/Q2pfUNQJop6Q3flmY512XqYpby6zjBdV7k4B9SuKeAkUMPiLFDD4jRQw+I8UMPiRFDD0kxQo9JUUKPSXFC7BkOTQY0Ks0ENCtNBDQrzQQ0KE0INCjNCDUpTQo1Kc0KNSpNCjUqzQu0iGE0LNSrNC19SF+9G//bD+7sPt6/+z+c3P/3l8JcuXYsO/6rXosOpQ8Ah9dryWnRiWPla9FEPGNOW16JP6tqYN70WXXVqxdcqFGrD1yoUasfXKhTqoNcqFCi4FQ0mC9yKBpMFbkWDydJvRYO50gt6ZKQFXq6QoBXerpCgDV6vkKCd3q+QqINesFCo4FY0mCtwKxpMFrgVDWZLL+tFMFvgVjSZrcKuWTz/tl57K/o0WfOW16JPd2GfU6+8F326bR36phejT9jno93gZvRjAhfGplejE+TiSzLPH8aVl6OjPXPX3o4+tR+o216Pnu3RXnc/+jRhbdsL0s5Yr7whHTrADt42qG97RzoDbOCNg/q2t6TBlIFr0mDGwDVpMmEFdw7qm16UJtPVaOegvuVNaTLSQTsH9S3vSoP51yt+YKnqFT/yWoH70mCqwIVpMlcFdw7qm16ZJrPVcOegvumlaTJbtHG+RJWvTQ87Hbjy3rQz0isvTmc7zbru5vS5M+OWV6cDgPJ+OaFueHna+f1X3p6u9kivuj49wEjV+9Ops9acbfXGK216gzpBLrtCHSFdfdly0huWglvUCTSVa4UGBuV+Mr5HrY210Xizy11qbayDh7G4x31qDRv4aU/c4061hsW3qjUsvletYcsurYb53WoN23ZpNszvV2vYsU+74XmXfsP4lrVGjXv0G8Y3rTVq3qPfML1trUHrDv2G6Y1rDdp36DdMb12LDbfnPRoO85vXIjbu0XKY374WsXmPpsP8BraIrfjwIO5xC1vE0nvYIpbexBYb0FN/EhGL+8Rp2Ah35tL16YRPUaSxZrzjj+xetrbllx4BvZctjpXezBaxussPWlz6MT1ZB5G6GIpY3RCITJku5yhkynQ9RyFTFkG7uCo3jw+RnysqV4kjLTQ3dkFbOq1uymPtNHRJT1VtfpCH2Y/02uvZoGc8uZ8NusYH5r715AhUap//9Ka2eAQqcmmDEcX3ANzVPlGVy2CJ+0kozQWInqPLTWrDPh3vwz4t78M+Pe/DPk3vwz5d78M+be/DLn3vwy6N78Mune/DLq3vwx6978Meze/DHt3vwx7t78Me/e/DLg3wwy4d8MMuLfDDLj3wwy5N8MMuXfDDLm3wn17gFg966qbXt4EDUOC98JWuA+Dy9ulQSmm+JYs6ot5m/unVbUlOHza9t33K5pU2Vk80HVDQoPUH6FjQoHHFfVi2J61ed3/7dBqx7f3t02HEthe4T2cR297gnsqpDeF1l7ZBH2xwaxs0wgbXtkEnbHBtG7TCBte2QS9scG1bb4YNbm3r3bDBpW29HXbocft+2KGnzRtih54374gdetm8JXbodfOe2KG37Zti975DU+w+dmiKPeYdmmKPsENT7BF3aIo90g5NsUfeoSm2rsw4FouikEzqyozTVzmaX+XRUNdm5eRal2KchpbtoQ3KqV/NO8cz5XSbEygnzDYowiqEx0ms7hCezV42oRlVop8zi8kstJqlXBKIc2US4yjs0uLMyk4xKLfeO9z7Krc74zyoGDpKFuMz1S1r2EAlxhoWN9/WsImWyTRspsUWDVvoKYiGrVRirGGxxbKGxRUnDYsrThI24oqThsUVJw2LK04aFlecNCytOGlUWnHSqLTipFFpxUmjwoqTBoUVJwmaYMVJg8KKkwaFFScNSitOGpVWnDQqrThpVFpx0qi04qRRacVJo9KKk0TNtOKkUR/frHvoh+nXzx9/8Qf6vHXR68NY3jz8882NyafNB+OLK451ubNjefX7+8Hft3a8/zOv/u2h1eO/L/Z4jP8TPR71XjsXmzle3iOeriAKm8RESk7p0c+3H2bqmh6OT9r/XNO08ck17Gu6NJ4x5pEI61s+jQ1bMnra+3SxI6O0OoZQkJ1XqO4vN2BkVtdDMyqiVtcalreysitw+TqVbr2q9+JZ5te3bL54Vvn1LbsvnkV+fcv2i2eNX9+y/eJZ4te3bL94Vvj1LdsvTvpkRXyhs2/ZfHHSpyri65wdtV7UxH0Kk17mVJj0LqfCpFc5FSa9yan0lsP3ODvqsijK+vqWLRZBiEr4BqcCxfc3FSi+valAcU5nJpjXy+/b5W6KUqaYtuyk6Nw+SJf7KEqpYlpOFXPgOsPLPRPFNivLldGcVmafUsOdnGn2qWELV4NebpUo9iIV+vTzVqRxy06Jj+3/t2yV+Nj+f8teiY/t/7dslvjY/n/LbomP7f+37JY46ZNVcA/SuGWvxAlMFe5AGrfslAjmifYfjVt2SdQfaKXdRxUmbT6qMHHvUQWKW49G1CBR7fm/ZYNEEE0r7juqQHHbUQXa8Tnu18sdEVU5wnLu2WaUeybUAFFLPYVm+Y0dYQuJp9zw8IgUpHRtpVt7lBo0UrN2jVqpHsc+6W4sXSxC70isD8mbdjg8xoy8aX/DY3TLm3Y3PMbhvGlvwxBlKFaF5E37GurzRBUhedOOhvosUTVI3rKXoT5FUAmSt+xhKD/MAVUgecvmhfLSHFQBkrfsW6i/64OqP/KWTQv16Dmo8iNv2bJQ/x4N3HHXPP0CPQodN++20KJQSQ3Hpu0JY5e9zOdEn2L/utCNUEoJg3CI+LQXIUoKu1RrfqKp17JCEdvoE3Vq2HO/zhC+XteC8GxYPm/agvBsWD5v2oLwbFg+sxaEqmG5hE3YsHzetAnh2bB8Zk0IRcNyiVqpYfm8aRPCicxXp4bl86YtCMFk6XIGMFLQfhBAIzQsnzdtPQiWqq5mIK+VLmcgMUAXNJCApUsaSHTVRQ3kUwDE82C2SOvBs7/8lc0Gj9lZUFrJJHzny5ZTPm0rqOVnTel8l/Ho7Bw84Wadtob1aefABeObs/55tlW1pFvg6brdIY9blE7nR+n0T3+5/fTq3/7v7afPdz+9eb8snk7/guLpU6uhtiCeFnuQ2hi1JWY+lfvrtVLp08+qV0qlL2LEtZradz9r8V5zwz/SfClx/1gbM/Bo7AA24+Hkr1f50p/HYwd8vLQdTsLjWVI8q+OxOYWOp9iRuNLxOBy8mov9icHL2eHg9Vzy16v0yekyB6/nYq7DiNezw8HrudhfDryeHQ5ez9luiYHXs8PB6znbrT7wenY4eD1ncx0mvJ4dDl7P2VyHCa9nh4PXc7ZTGLyeHQ5ez8kW4+L1nK4U9Z7HY67DhNezw8HrOdkiTryeHQ5ezyl+vcrYPF3m4PWczHWY8Xp2OHg9x/71Kn/ydJkDLx5GRafdSRnjcRcTq7OLwWs8mu9KwWvc4QS6kfn2yxY3MrqM9vw7zXdQF86myxy8fYzmO1jw/tHhiELz4JhcX2kd/nhterHMWOAljecjLdcZh9dLF7wrfwtsDrxwW8/3uiUDjyreuA0FcvEHwT56q9wqy+YUehtFEMTVyo1p65aC10dj2rql5PXRmFbBDm5MW5EluGxMW7dUwj4a01bkBC4b01ZkAS4b0yrYzI1pK9LDqsa0dVM9LJmwho1pFWrHxrR1S4ksmKw+U2PauqVEFjzUHqkxbd1SIguWas/Yl7ZuKZIlMaBX7EpbtxTKPvkgXiWOTZc5g/bMfNGfpV1WxWopcthSFhsfW9wsd5KJMEUOyyny4LmdufEZPLezOXJu18x+OeGyBBam3ZLTxmg47da4axyGr1LBpoucpzJYLe8eitow8Lx73lQK+5h4z5tadT9m3vOmXt2Pqfe8qVn3Y+49b+rW/Zh8z9tqYwOat87T73lTw+7H/HtjuSyZNiCXJbMG5LJk0oBclsyZXglHM1ZoFr6tWhY92Ebz8G3VsmjJDpyJb6uXRfFAr7aj8BXxQbdzZSDik24PlHE6Xpkpt5SOl02lsTHqFsQR1oGEtp9AGBvrhT5KQAqbLnLSDNPxpGhC1x6DF61BJD4GL9R2W9Vhfb3SZvsyp1DHiykvKWK1vD4JeT1p5WV7UcZrnbQzwA6c1edtnbTjDLAB5/R5YydtMGXESRtMGXDSDmTKCs7n87Ze2mTGGs3m86Ze2hOZr0Fz+bypmzaYLL3lFxlphIl83tRNG8y/LmIASxV4aZOZqjSJz9t6aZO5wrmd/bkuOLezOXXG+YN9LlixmdXMLLKVjYDkD52wckXxh+aan68LjtiqyuTrdS7Yp3m1N3i1sdxfSf1rX5f6z9TyWsv8NawuX4j1kuVzgPPrYCI2uvu64GQtZf1K0g/ECCfrtW1drU8+K9u6Wp+sVrZ1tY6zTsVdWOO2rtZBn62Ou7DGbX2tgz5bHXdhjZs6W0/6ZHXahTVu6m09gamiXVjjpu7WYJ5gF9a4qbm1/kAH7MIaN7W21pfooF1Y46bO1uC9H7QLa9zU2fr87bvOyzpVzcpaTBMc3+lOk3vllH9QZXa+0sw6XcQE+qzqkpW1lDEL2pU401NnZ2j00NnB4DNnxz28wl/lYBr8VQ6m01/leZCPVdd4hn2JB5hPx4vW6CFsY7GuWnqdb/EM5Q7PU3vphY4c48gN0XtiGc+kfUcZX3L3ODSaexy4GX9+PSZfZxJ9+pHOBXPV466YYyvXWUKni2PDt99t8WnEt989Do3n9h2YiG+/e5yCnehnZfpgTfH5Jcm2YOR8ueI+TOaVNs6nrM2OjaDiHs3HmK6zbk4XR4fvzEendUNExqTx1EHpRbf0cp1Tc7o8Sn4MlTc1Zz6fQ+VN3Zknz/P3Onvm80lU3tSf+XwUlTc1aD6fReVNHZrPh1GZWTSrp1ESlh9HSVh8HiVR8YGURMUnUhIVH0lJVHomJUHpoZQEpadSCrTQYykJSs+lJCg+mJKo+GRKouKjKYlKHYI0KrUI0qjUI0ijdlj71aj6ORaYrUr3/XYziljpvt/jPL4/95hDwvf54y/+gnx+t/D14W9/8/DPNzcmP8G6bXyh2KwmN8OukN+4Jgmf7dq7v4oPdx1OQ3l4c5+beS5Q8Z7IaYhGlSoOBxfg7UZCEVfgPQ4V49uNlmKj+x2PQxUodiOq2KgCxePQ0127UVds9HjX49D1nJx1SNezw+l0PduN3mKn69nj0PVsN8KLna5nj0PXs90oMHa6nj0OXc9eQ0a6nj0OXc9Oo8lO17PDGXQ9O404B13PHoeuZ6dR6aDr2ePQ9ew0ch10PXscup6L0xiUrmePQ9dzcdYhXc82J810PduNktNM17PHoevZbiSdZrqePQ5dz9VpCEvXs8eh69nuQ55wOdnjdLjvqM3ed6SZ6iTsNvIJ90b3OLSPY20vdxzEAOH+zzwaILx+9b9vf/68bIOQ/wVtEKa0jQ/CFLcwQpieWQZc44QwpW2sEKa4hRfC9MzjYTszhClt44YwxW3sEKa0kR/CFDcyRJjSRo4IU9zIEmFKG3kiTHEjU4QpbeSKMMWNbBGmtJEvwhQ3MkaY0kbOCFPcyBphSht5I0xxI3OEKW3kjjDFjewRprSRP8IUNzJImNJGDglT3MgiYUobeSRMcSOThClt5JIwxY1sEqa0kU/CFDcySpjSRk4JU9zIKmFKG3klTHEjs4QpbeSWMMWN7BKmtJFfwhQ3MkyY0kaOCVPcyDJhSht5JkxRNU1QLn4+8wG47JiwIDB0bBjyVbYJU9rIN2GKmxgnTM88ITZ0TpjSRtYJU9zIO2FKG5knTHET94TzGlNU14XHeFvUWdhd6nReIOGFLL9dZZ5wMrecFGVwVTtKRceSol02VpBn3HZo4G+F41HA34prTROmy+2Ta1ljcHClU0Lexykh7uOUMO/ilIAsDeZ9LA3CPpYGcR9Lg7SPpUHexdKg7GJpUHexNGi7WBr0HSwNdKlF3MMnIe/hk1D38Enoe/gkIEuDvIulQdnF0qBCGezGRgnkUwBEHmS2BnYmEKhAAAJma4QVBhTLVPGStmcelS67KIgbhbC8URgrMr8lTwW4UUjKRmFUvFF47nZRLtsqiBuFIIyVn4s5z1RsNTU9cX3Iimj5qcuCcoe8UbyuSXFMVMKVdgtLLhMrdk4OKYtv+tlK5EoDhYWO2XNdY3VxpUlC3MkkIe5kkhB3MkkIO7kkhJ1sEsJOPglhH6MEaG5R9jG3qPuYW7R9zC36PuYWYw9zizjvYW4Rwx7mFjHuYW4R0x7mFjHvY25R9jG3qPuYWzS8LZOwHe/LJOzAGzMFq5f+0acXdH4gU5bW+JEgjwVpczaE/rwpw82ZUD0LK7QDfcl8gW3OmrI3IzYMyfY+KQs2DNrmTBrrwPmx/UzzjDdnXdo85bBubybSI92aVWFntkKdYKv3VqgTHFBh+7L09UpHhct90PMap5IrfRPiTsYJuzgnIG+Sso83SdnHm6Ts401S9vEmKft4k5RdvEnKLt4kZRdvkrKLN0ndw5uk7uFNUvfwJql7eJPUPbxJ6i7eJHUXb5K6izeJrpIg0VUXSZBPAegGAWarYctuiRrp7kuiJu4kI1Az23slYe8FOkpctKhrdaV8NNjqUeLTcNltpa1W4Un7t7ZChSfs3zpU4QmlNWLRcNkIp0e8fYvSBqundds3kZ7h9m0Wdm8dv0DOM8W7Jbvy1PFmyeF0tAe0t4Cgf8Ulo6Mx02fjtNwP3P3mOh8F4ncz0h5+NyPv4Xczyh5+N6Pu4Xcz2h5+N6Pv4Xczxg5+N8CFQfe7IZ4MVYfG7f1u4py297sBfg1gnsrmfjfAyAE80La53w2weABLdGzvdwM8H/T3HhhA6CEq6mIGPZpGXcmgB37gChHBRBXaUFSBVtpPVIE2bEwkQDvaLQqbxRhoOudcxcfp3LXOEdNFk6KItzNJ6m4a1+1mRDjdzAilKOA1ccmSKka8l3GsOPBexuGwvcy41j/ikgVVwou/X2kYMV10aNJ1Ahf9onjzAMfCiDcP8EBMVP2d19NyB169o8BlQyreUMDxH+INBTyQKJxOdcnrSe8ocNnqiTcUcKyGsmr/Fovu0ZSxHNobHVNDSyZNvM+A44rE+wx4IL7g7YiT+YJ3QLingOPhw3sKeKCAT4IUy6eiLv8wdMunwgRhkuVTobmNZNVU8LvguBcV/C54INZz47G7flRs0Z86KlxyBTifej3bVdRFW4DC3xzHv2Be4Qd1naECshOqcRc7oZp2sROqeQ87oVr2sBOqdQ87odr2sBOqfQc7oTp2sBNq8w52Qi3sYCfU4g52Qi3tYSfU8h52Qq3sYSfU6h52Qq3tYSfU+h52Qm3sYSfU5z3shHrgdkICNdJOw667Tse7e8cWp3Pjx7rkHIF296LBDq/GO844vBzvgTodkeON07GI3wHxqrzjjsPL8h4I33F2/HEG3tN7INwiwHHIGbg5lAfCK9vxyBl4ZXsgvLIdl5yBV7bTdnTmBYp4pb/EFC+D8Mr22tfile2B8MrO9UqPiSleBuGVnfuVLhNTvAzCK7vMV7pMTBcNfIDNxHTRMScFvLI9EF7ZxemnjFe2B8Ir2+6mngJe2R4Ir2zHNyfgle2B8Mp2nHMCXtkOiBeVHe8cXlX2QHhlO+45Ea9sD4RXtuOfE/HK9kCV7lFcJx7edN6x0OFN5z3QoK2Btzbj+d394JfdeMr/hBvP5RLEqeNPEuoaaCd41owPp291orfiRr1sznPxhxb7d+ZrbHrypXGJL1z57jFtaNFzemj5KoeefIky8GDidfY8+SJGXfLheG2nN+HaQcS/cb7OpydfxIirfZx/4XUOPafmAlca9OSLGLym+5XuPPkiBq/qfqU1T76IUdve37coPIKcq16RNynuS9Y8l8fUFoeU8cOO11nz5IsYdLmufPfrls86G71b6wwS3bMLAY5y8EUyX2ngUy9yaGcsBxPx05+vNO85PZ/WrzTvqRc5dOm3K517Ts+nXWvcc34+1xr31IucQZ9Pvc615/x86pWmPefnk6807akXOTQzcTC4fZvDKfz5xCsNe+pFTqPPJy649KjPx+bw+GzboxYcnx0Ojc8OBsdnh8Pjs2PWiuOzw6Hx2cHg+OxweHy2j5QKjs8Oh8ZnG1NxfHY4PD7bh4AVx2eHQ+Ozg8Hx2eHw+Gwf21Ycnx0Ojc8OBsdnh8Pjs33Q3nB8djg0PjsYHJ8dDo/Pdmmk4fjscGh8djA4PjscHp/tYlbD8dnh0PhsYzqOzw6Hx2e7/NhxfHY4ND47GByfHQ6Pz3bBuOP47HBofHYwOD47HB6f7RL/wPHZ4dD47GBwfHY4PD7booyB47PDofHZweD47HB4fLZlNAPHZ4dD47ONCTMO0B6IR2hb+kSsVOplEI3RHgcHaQ/Eo3SO11qp1MsgGqc9Dg7UHohHaltmSMxR6mUQjdUeBwdrD5TYxbZzjSh1px1g4A17bbnpU2sTSYKQitCuL9R1IgT/9+Lqo/dzOxIiJKW3fqCx3RlbnKEYIXWlVgRcS07r2BugeIXisZqljjBBUUBKCnXFS2J/LCOuxXsgWoz3OA0pDJKgGyL2I/PlwfFPgn1f4KnHiBJHxnnZvWgaE67zGjlPqzNO2o/a46APRfN/7pKxiDrBzjALfF3jUGaj8mVj5ySJfy0cEBWreJyBXtc4lmxC1Pmzh7OiupkcoVNk2UO0pU4Zqwy98TCdYVS0ZZlubb2x4b2tB+Kb29iXHEBQfI1dagadsUjLGWehKi2PE1bF15c/t1zn+XGaYG+Y/HTHvhcaeHnUA9GXwOPgl8ADtZV7qpicPUbp/Knb38cy1m1/3KFVvDV2Rlbp1tjjxFUSvJik7UDFxu/eMPM6EZ46TjkPSsce+kMII7zkavfTCbjm6nHEPfMp23v+K/N1XhvnX2l/DRv+NjgcvBkIjlCabgY8TmL9qQ6rjLlmyFbBlTlnSJlgULakT8q1SjoXlFOBhg1pnv/+suCrcfklcX7/kpuG8iHp5wAWktIS66mtxsJ9s07JgTWkSJSPPkD4ubBWtRiPPkvnzpIyvmiz2gYFi6/j1E+LPCg+JPp2pp+cZBXzANAipM+Eq3+5WgdcUKpulXD1D1vLhKvX/RqZN1DbbmTeSKkbzRs4HEbzBvJANG/gdAzNGyiVo3nT37cC5o3YgJRKuPr7VjLh6u9biYSrv29lJlz9fcto3vT3LaN5A70X0bzp71tG8wasRdG8gTamZN6C6uGWkp09pOusQs7GeGFbt5ApkdUA+rIkshrUO8dnh3MlNwOmIVMiawy0cIlojXFv7ADdQ1SrbI074K5ZmTTQ+4WsMF1GQFZCjGyLr8QEvUNMRA8gU3NUDSuenMRGHkGllqvaWBvzXNXWq97xlMQC4FBCFqx+YxrFb12LgD43wM+ErAP9fjVKEXSFAspowOVrNGW6mAdNmX5sj6ZM1zKgKZPfMrR50LUOaK+jKx/Q1ky/5Y12krosAm189UvgFU2Z/JZVNGXyW1bRlOmmjWjK5LesoimT3zJyJAYsWsgJHjBsIQeOUddXkPPRqKstyHEucG3paMrEbLGThLmoB/vjuDVvykibut8vAArt6891paEoQp9auCzsops55rZg5yLVwro75rRg8qKpENrGFi+nTjzKo8AWL4f/VJ5BZr4ZL6hlweNFEj5Ii6HCkXZh2VbxVYvgTavoTYuVvWhVfNFS0h9tQ+9ZCuw1a+JrNsBiaKonxTg/3iZ5XbW0Ujgg4jPWDYjgslI2IOIrDJXKUm6NRQm7xV7r6yQH4g8f6xQHGl2VkTwKDkQuEpGMDOn6J26cencoWP0TNzLA6tW0EQFWP+AfM8Dq5/u9AyyQipApA0oRMmUDC1sULNCJdDBlRCYCpoyoRMCUEZEImDKgEWlkygqWtEjYihUtErZhQYuE7VjPImEHlrMIWGJ6U2eADVjMImEj1rJI2ISlLBI2YyWLhC1YyCJhK9axSNiGZSwStmMVi4QdWMSiYEHPhwymjIhCwJRxcx4Nm7DURMJmrDSRsFwSImG5IkTCckGIhOV6EAk7qNO5hCWCEDBlwBoogCnTG+AHMGO6JgSNNUOzVo1aqH5FolYqX5GojQpNJCqWhEhUrAhRqFwQIlGxHkSiYjmIRMVqEImKxSASFWtBJCqWgkhUrASRqFgIIlGxDkShchmIRMUqEImKRSASFWtAJCqWgEhUrACRqFgAIlGx/kOiYvmHRMXqD4XKxR8SFWs/JCqWfkhUrPyQqFj4IVHld6uT2dKr0WS25Herk9mS361OZkt+t0D9I+kNO0CxJundO0BlKbFeHlM4d/Nw3MJSTazKKtzaTzWjIqvQXCBVVGt+bCAzK71BUoWSKkGCkPSGHqeKZVbmv9OCpUQdtF6pUIHdwvF1laiBVislaqTFSomaaK1SomZaqpSohVYqJWqlhUqJ2midUqJ2WqaUqINWKRVqn2mRUqIGWqOUqJGWKCVqohVKiZppgVKiFlqflKiVliclaqPVSYnaaXFSog5am1SoQLNR9NkCko2szxZQbGR9toBgI+uzBfQaGcxWoVVJiVqZHl7JCIFUI4EV0GmdU6IOWuYUqBnoNFLUqYHdAyjL11wz0GikWR9ponVTiZpp2VSiFlo1laiVFk0laqM1U4naaclUog624RYiS1a7dRw33MoLoKsygr6mgEmH/kB1RQaYe12PAZapat8Riz7ztE4sjZOWiSUorRJLUHYzRVn4uv4CBH5dfQG+e7r2AnyidemFnk1kXXmhJz5ZF15kMFEVVpwlaIMFZwnaYb1Zgg5YblaguuZC305lXXKh7/yyrrjQN6lZF1zo++ms6y0KmKgCC80StMI6swRtsMwsQTusMkvQAYvMClRXWuiHf1kXWujnlFnXWehHqlmXWeinv1lXWTQwUQWWlyVohdVlCdpgcVmCdlhblqADlpYVaJnRhWElkdTFFXr1K+vaCr1Ql3VphV5TzCUzu5rTNdbyG+nhFtbdeixf8M6lihelzzewxbEy95PzNWyR3lmnzqHM3WD9KZWnSxtrJPQUaqC9KgSfgMwbawgNILIsudCXbkVWWsoSqIW1vujKKGE7DcHKIte26iq+uKo66vYoPdeBmjIqk9/EG/2JhdjG/LcGg0fUGUl5ss/baCy2HhBHmtc1MWqK61qmPTS6Rzfjl9xC42H9hvDVpDQSXJ73sDJDYFvXr0Z8pmNVaxntkQLhxTH7ft69yFy8QHlx3Clo2EjlNxo2Uf2Nhs1UgKNhC1XgaNhKJTgatlENjobtVISjYQdV4UhYIMGoYMqABqOCKQMijAKmDKgwCpgyIMMoZMoK1eJo2ErFOBq2UTWOhu1UjqNhB9XjKNgC5Bg5AmygihwNG6l8RsMmqp/RsJkKaDRsoQoaDVup3EXDNqp30bCdCl407KCKFwkrW6kcrSGVJrAFNM0Ay0DXZ4BFEBIyW1RcCAqWZ2gjLVBMoVGpu4NGbVBOoVE7FD9o1AHVDxIVCDXAbAGlBpgtINUAs6VrNch3VhdrkKQAqDXIbFUogtCoDaogNGqHMgiNOqAOQqICyQaYLaDZALMFRBtgtnTVBtgpFl22UclsFaiG0KgVyiE0aoN6CI3aoSBCow6oiJCoQLwBZguoN8BsAfkGmC1dvwHOOkvOtHwbglIBKLmsq9+q+LquMKriG/WQD3n5BL9k6O0ABz2g7/vzMVuFgVLmVbVCccwlwDKcyo2r6nAqHd7/D+2riWFX/kMTllgBtyYfqNUem54kXsQ0OpxuczocjoMZcDhxNjl694t8ERNYY4pTQIhOY4pCtBcPX98YbRCTW0ShClgqKwq3xR9Ll7r3Wysp1UahN0bR+1jkiyND34vy9IEJY9Q/F/OlQTJTkhDYKJvs/fMQJGNToPw1yfZvT3QJOpwM14uDEQV+w3xU5kur96I4rRJnaA0/cvuLwlQQ0+nLfi+HED6fDX8g7FF2+oFwMExO5P5W8zhc1zmcptYZZMJTa3+de2bvehJUM6Xjr4QzOJgQeZhGXtEUbEinM+cMZtCZS3YiM2aULqRkUwKcKm80kU2Vh0kkL0hJWIy6jOA4cd7QCp44++M96qpomoIiKiuDZv/eKGH272HGmmj68rdaH8qq6wJOU2sOsgIhwGlqsw2K9OE7nAQfvoPBS9/hFPHE6rxbuj87sFEVP+pqg5o4prY4pE4nzRnRgJNmY8K8ZgOSqpLaV9AtYb44yLhqA6KOEmc3qdvDzHRqHU6BU+tgaGLvcXBin2cbRJe+x4FL38FEGs89Do7n2f4wRBrPPQ6M5x6GxnOPg1OZbH8YYqXPx+HAsxsPQ3N0j4Nz9GyHyTTT5+NwAnw+DobuPj0Ojs/ZDmSJxmePA+Ozh6Hx2ePg+FzsQJZofPY4MD47mEzjs8fB8bnYgSzT+OxxYHz2MDQ+exwcn4sdyDKNzx4HxmcPQ+Ozx8HxudiBrND47HFgfPYwND57HByfix3ICo3PHgfGZw9D47PHwfG52oGs0PjscWB8djCVxmePg+NztQNZpfHZ48D47GFofPY4OD5XO5BVGp89DozPHobGZ4+D43O1A1mj8dnjwPjsYWh89jg4Plc7kDUanz0OjM8ehsZnj4Pjc7MDWaPx2ePA+OxgOo3PHgfH52YHsk7js8eB8dnD0PjscXB8bnYg6zQ+exwYnz0Mjc8eB8fnZgeyQeOzx4Hx2cPQ+OxxcHxudiAbND57HBifPQyNzx6nrdPQ3Ws+bWCnD7zbkZGVG8+1IW9gbaYL3B5Xm+EC9zBRK3qVp79rsd7S9HLjqXuUMzxR2X6uB6njK0yk0iUoje092j8axnYP04lIpQvl8TZTYVU3PxctQGGVh6FSk15tDpSaeBjY3SzYFBrhe7c5MMJ7GKSrHYKYqwUqKBl2cAhQUOJh6KIe9vsW4aL2MAHKEO67etkkmosP+zWjtUYPk9fIEL79umex94+vb+4+3/71AHr7/svtL5/uPnw+AN6/eXv7/vDv6h9e/Xj4C97dvnv145eff7799Op3H798ePfm7ccvn1/953/89reH/+/fbj/9+qB4SnOoh214LPct9+4+vLv9+/G6yCP6MKC7nz5++PXmh//6581xvId/9/kfv9z/lm8j+e6X3TySwv1Yvz2Iu9uHP//sqdAINoXZfE9hBPMwaVWyc6A5UpjMf54tT8U/z87DSSw7QATLz8byp+OjWsR29Ck5UMPy53vwyTDfZPr1djkrFr8ZMwNf/TYn8QGZ35SQ8YBsDroKMA3zhlqAvUe/DWZxMekf8SN1CA1igXrouG+YRl2WsIbBsv1pCLcM9M/941j7sqA/4pdi2B8E+k44GLqRe/EjrcWDZUcvptmcEXxINw3h8mysHCv0740NT7T5TYudTrSN0S+SOT/SdK+eMVW4gp3AafXpR8fliU6RY7Pgfoi/KnYCnehHxcGI35RwTFjsbWpS++see1tNfQjzyl8J8zue8CthYwaOUiYnzzyAmOlA5t8Gm4O/DTaGfxtsTsbPxz6syPSWmMeBt8Q8TKPPx+F0/nzMGJ/xDsDmFLoBcDBhzYHA1It05zjih28PMq26l6COMkOvSW+UqFFLaHCUqj1IGGewcyhFhFL9hLKvPdIbRP6YBn+/nGtN8OjOHVLFkd4ZEY30DgZHeofDl7vNKXwVOcIrPvU2CKcuDoemLg4Gpy5eEQlPmM0JfMLs0/rIJ8wG4azc4dCs3MEUPGE2p+IJszk8Ttul/caTFweEkxebQ5s6eBh679HjRDphDifxCTNTic6zcQeEs3GHQ7NxB4OzcYfT8YTZnMEnzPwYDr69dEA46XA4NOlwMDjpcDg46XA4POmw1YSDJx0OCCcdDocmHQ4GJx02J8w46/BAPO2wBbJh5nmHR8KJhweimYfHwamHB8K5hwfiyYet+w4zzz48Ek4/HBCunnocnIB4IJyBeCCegtjXGULgOYhHwkmIB6JZiMfBaYgHwnmIB+KJiH1LJ0SeiXgknIp4IJqLeBycjHggnI14IJ6OVEc9wfMRj4QTEg9EMxKPg1MSB5RwSuKBeEpi36kMiackHgmnJB6IpiQeB6ckHginJB6IpyT2VeGQeErikXBK4oAyTUk8Dk5JPBBOSTwQT0nsG/BhRZHSI+GUxAPRlMTj4JTEA+GUxAPxlMRu7BAKT0k8Ek5JPBBNSTwOTkk8EE5JPBBPSex+JaHwlMQj4ZTEA9GUxOPglMQBVZySeCCekthteALvXO+ScErigWhK4nFwSuKBcErigXhKYneXCpWnJB4JpyQOqNGUxOPglMQD4ZTEA/GUxG6aFhpPSTwSTkk8EE1JPA5OSTwQTkk8EE9J7F6AofOUxCPhlMQD0ZTE4yR4GyYnRX8UcBsHd4AF3ieWR4ijujdC8ULRo4ZLHSGzXHiUcuVoa5TCigqm3T40jHnd9X9/bCPwl8wZW1x3J84fGk5tvJHR1Mbj4NTGA/GXwAGtSG3sJGmsSG0c0mBX8pJgzBJxNwhndHEO6GpjEgx24oy/Cs7Y8EbVA+GNqgfiG1W7cXacK7xalory5HG7Knd8tF+VC4INqzyO6gk/7MdlvkW8FOoNDif5Hogn+XZf/LiiFOqRyiqXkMMUKKZLMVS80pxxNrrSHE5fYxRi/Fz7miY+xnGGGfExjgfixzi2O0d8UjQVg5rQ9iPGxFeyMz7cVsAD0b4CHqeyoBZsCt70esPBm14PJF+cPv6yOIRwnfgG2LbZiSmwnOwwPBMT8XpyxoPMpl48LfO1wTVVb2w4y/dA4mIPzf6VZsaTVmQ8dm6X+srP3Ky4YUVedHXGiYuuHies+8zNiiFWzPganTfMtHKLH5u9j44rKrK2g17kFVkPRI8/PQ7+Enigvu724reHvvzWZvX7EE/ctGxnH0HNNp4mVmm4UAIz/H4xWvMNKbzmZVtwxrKy+1IszhuCm+27I6N5ksepq278RumWaiz8rXGG2ZGl+4t1Yo9O/nDE2V7U5vKr4n46Omva7njCLM37Y9x4cRZtvuFV7Do6pUHJfJNhex3Hyl8eB4RfHodT8fJ2QKjZ7r3DHpsC8WZ26xSsfm36KfN8ti2tZhse/WvTTysmCqMFV177TLj696Z1wtXfnFYJV3+PWiZcPWlraN70c6yG5g0IkdC8gRNeNG9go0PmDZS/K5k3Ugwn8wYcDQqZN3Bht5B5A/d3C5o3/X0raN70962gedPft4zmTX/fMpo3/X3LZN7A9eBM5g1U2DOZN/328JTIvIGyeyLzBhwZEpo3/X1LaN709y2heeMneNE+YBy4ZumBaM3S5iTsCu+C5HcmgqWd9EI9mdGk1+3JAkx6FZ+8L0mv6ZPXO+mXmhOaMr3IiaZMF6mjKdNfJDJl4Co0mTJdDkA+/EkXB5A8JelSAZJWJV03UNCUyW9ZQVMmv2UFTZn8llU0ZfJbVtGUyW8Z2XAlXWBA9odJlxuQ7WzSL2yT3XfSxQfksCDpSoSGpkx+yxqaMvkta2jKmnYu15N9LGc2TdY1DNM4LoTQlR7PVNIQmvAIiKThNGOz0jqay5ijWX9NXOPggRJNqh0O1vR7IF3YkO1Hb3YupzKH5+vEXH26zKFXe1GbfbPBnfJxXCahKsMdnCt4HKQ8r6wvhaZUClIOuL6kktltgJgon9evgu3k80QeoVnICHKQlJmGtNNfj+rD00zxjfn/CEXnxBQW+IFglamzGgp64yJ94Vgr78eSooqPtKSoguXXrXc7vpmviS68OGMFf5ME7tePk7GQYHCSinqJYST7zagmtfHRCjKepF/En7yna68F/WN3/jgr3AoKzJlwAy5ca9yIC9caN+HCtcbNuHCtcQsuXGvcigvXGrfhwrXG7bhwrXEHLlxLXCDoqGTegKCjknkDgo5K5g0IOgqZNyDoKGjeCi5ca9yKC9cat+HCtcbtuHCtcQcuXEtcIOjIZN6AoCOTeQOCjkzmDQg6Epk3IOhIaN4KLlxrXDWbTMHOJs2sD8g5EloNqtNqbCD3BWKORNYYEHNEssaAmCOSNQbEHJGsMSDmiGQ1ADFHRPPGL5xr3IrPnTVuw1aIGpe3YwjV9uYba0iLI8wzt3XVuGC3RrDqVd2iR6/MW9RrY9Vfrkyw+ruFFoL8aqFlIB5BJv3TmHXRB/r9VDwlUXXJB1lZuuKDvFsB3320Y1UOaQVIGF+m5roaFtfTNCxuDqRh9UtfaO47va2lYfVLYGTKonoJrICwogs8SOqW1eYScYAvli7vIOlr1uUdJNvOuryDbA6yLu9IaHE1qtfUsJ3qNTXsoHpNCasLPMiZQdb1HeSII+tiD3Iik4H0g0wZ6HCBpqxQvaaGrVSvqWEb1Wtq2E71mhp2UL2mhNV7YpCT8Kz7EpCD+6z3xiB1hqxLQEhZJOvtMiqaskL1mhq2Ur2mhm1Ur6lhO9VrathB9ZoSVu+vQeq7WTdIIOXorPfXINXzXMRWTX2AlFnXfQznyRYTWzA2L8tJsi77OD2DoDxYIPuo9mjtZ6se1KdERjuQ4iw9CqOS0hUxq+05zh1yno+6mVTWnyNWf9Tms660AaD0rOvaFlAh2w1ucuUtoEK2SQUfz0Zloio97orKomqo3aC2pDo+o3Ke5GANaaSl05h8McO3tImdoVIAT7QhqXAc8B3V5R0j2mHW/NY0UTY8SLxqYtv9Kczx/BiCouDMra6Vkov8xqXkIpk1Kox45AMGcaEbZV5hXhHMu9C5BxTEhg3hR/TOaNK6RnkhKq3J8hMNh4KnS6mXlfJrEV+x/FoEo05UYZ4pH5Sb59PuYVbAoPo8RwAepPw8E7Befx6dcCNP9yVu4upxiZv5lSaJW/h9RYlbudpd4jaudpe4navdJe7ganeBW4Deo8+EG7jaXeJGrnaXuImr3SVu5mp3iVu42l3iVq52l7iNq90lbudqd4k7uNpd4YaZq90lbuBqd4kbudpd4iaudpe4mavdJW7haneJW7naXeI2rnaXuJ2r3SXu4Gp3hRtnrnaXuIGr3SVu5Gp3iZu42l3iZq5Ll7iFK8glbuUKconbuIJc4nauIJe4gyvIFS7oBBLJvCXu7qNxI1eQS9wVjQzM/h6FNwrxQFzYKP1SLmyUsFzYKGG5sFHCcmGjgtUFIejl1wUhKFbpghAUWnVBCPoS6IIQ9OHSBSHoO6sLQlBaoAtCUBajC0JQ0qULQlCOqAtCUEqrC0JQBq4LQtCGQW8FgvY3uiQEbcd0SQjaPZaK5YIStmG5oITtWC4oYQeWCypYvQ8IOqjR24CgcyW9Cwg6BtObgKBTO10Igg4ZdVUIOhPVVSHoCFdvAIJOnHVlCDog19t/oPN8vfsHKT8UvfkHqZYUvfcHKe4UoA0hU6Z3/hhoynR5I5oy+S0baMrkt2ygKQP6KzRnoIMcmbQVQhCzM13p2Lzb4cSV6kLHPa90foJRbRA+wHA4haoyl5UpBdivnH5ltkcHRYnLWrTSsSbRGdpYJ+7JiranDP4mmBqkMvCb4HAiVr0obzxQZJxCiYRV+5SOhwYsQvPoQtptHKOpNNRKNTQSFQvmJWqn+hmJihsCC9QKNBhj1qmBKmckaqS6GYmaqGpGomaqmZGohSpmJGqlehmJ2qhaRqJ2qpWRqIMqZRQq0Fs0fbaA2qLqswW0FlWfLaC0qPpsAZ1FBbNVqDpGolaqjZGojSpjJGqnuhiJOqgqRqECbUXRZwsoK7I+W0BXkfXZAqqKrM8W0FRkMFuFKmEkaqU6GIna2GVHISmuQEmRwAoYVFejUIGKIukrAGgokr4CgIIi6isgJXZxVLC6rilTjY400kIVOhK1Un2ORG1UnSNRO9XmSNRBlTkKNc/sEEmJLBm7FJkCnZojOUJSVnymndecgWWoHJJmokDdkAStUDUkQRvUDEnQju4JS+uQipCUcRYqQZKgVIAkQan8SIImdDVaeSl1SQT4CuuCCJAw6HIIkNvoYgiQhulSCJCF6kIIkDDrMgiQ2+siCLAN0SUQYMekCyDA5k6XP4B9qC5+AFtmXfoAdve68AEcROiyB3BmoosewPGOLnkAJ1G64AEcmulyB3C+p4sdwFGkLnUAp6a60AEc8OoyB3AWrYscwLG5LnEAJ/y6vgEUI3RxA6ib6EIHUOLRG2CAalSnrngSlPZGk6AFKpIkqNgXzS5Imymv7l4ywNx3KHCSoAPKmxSoLpEA5fhK9BL67A+oIzp3LHrRksRcCUM91xsPG6qy3F6pkp4WD8tLaA9Yh9q0qc/sCbCOTakzemPuQ0VZEtAjSJqzsa77k/QU2jyvE8NFWwvXZnzCF21OhG324rJMrM0JOR07vzAjIxVhittciNeHsBDbXImBsdD5rukCiWrNRzKZVLbnrJWxqmeW9oIE5pigTE4IyNhAWUFB9D1Ojf141OyswSerNhAM+pOlAvGsPFuxqdlj1zHx9zcqkRPaMjYgizhSBUPpFlZ2v33RodJ8wnFe16X2Bd18IhF/kkxxcIu0haCDWddAUJIYt5hXtT8Vp6ms6lMqzlKFG7SqjLhBqNBfugF5xHGDWpXfPyi1C+8tkEcct/1CS/QG5BHHEwqJGqkIVaImKkKVqJmKUCVqoSJUiVqpCFWiNipClaidilAl6qAiVIWaZypClaiBilAlaqQiVImaqAhVomYqQpWohYpQJWqlIlSJ2qgIVaJ2KkKVqIOKUBVqmakIVaIGKkKVqJGKUCVqoiJUiZqpCFWiFioYlaiVCkYlKrYHl6idCkYl6qCCUYVaZyrulKiBijslquwv8nBW0oT8vWJLcGmk2BBcomI7cImKzcAlKrYCl6jYCNy8E93q4Jzl0TVsAi5RqQW4BI3Qq1uCJujULUEz9OmWoIW5dEvMyvy0JWZjbtoSs7Oze4k5mJO2wuwzPGGzX3XcKEIaW4Qe2hI0Qbm4BBXP1UOzPpnmUXWnCnRpnFSBLkGpAl2CdigXl6ADysUVqK6fAKmdLp8AWajeewIkzHrnCZDb66IJsA3RG0+AHZPedgJs7vSuE2AfqjedAFtmveeEvrvvessJ/SCi6yoJ/cyk65IJ/Xin6/0m9JOorrebKGCiCtR2S9AKtd0StEFttwTtUNstQQfUditQvdGEfmze9T4T+gl/19tM6MWIrneZ0OsmXW8y0cBEFajtlqAVarslaIPabgnaobZbgg6o7VagensJvcjbddmEXY9uJjRCaF0+0Ougt8RRht6XC/I9qjq/fhT9BOX3Y6lsU7REPa6Uyor0xvQ5idE7PY183ncymFh84Ge2i+wJKmTZxCVm0B0YHCnUK2PTC/PO06UX5p/PvfmaJaZUgk+1Qq2liG2rtJYiXBSmO7HM/EDoqgo76pqxXO86cbztn8xlxRtN2FYwPdNTc4+T2LGuh6EdYj2OqDg/9fZIQsAFWohjFvbcw95cZkAMccwYNWynWisNO6jYSsICPcRx16BhA5VbadhI9VYaNlHBlYbNVHGlYQuVXGnYSjVXGrZR0ZWG7VR1pWEHlV1JWKCMKGDKgDSigCmrkSqvNGyi0isNm6n2SsMWKr7SsJWqrzRso/IrDYsb9mlY3LFPwjbcsk/D4p59GjbC9npJyHIbdgwI5tW3DqQS9SKnwPTUwVSanjqcxlp+JWELpIsgInj1dBkEWXS6EIK8IbougrzOujCCxB5dGUECpd5agkR1XR1BPkG6PIJ8L3V9BPm46wIJkonoCgmSNukSCZLj6RoJkpDqIgmSPesqCZLq6zIJsi/RdRJkE6ULJciOT1dKkO2pLpUge2ldKwE2/kMXS4BTiqGrJcCRytDlEuD8Z+h6CXBYNXTBRCezxfu2JOW0ecxrG7eI+EYF/EG44z5mrDQP5g3vAfw56iWOLpTIFzFUDutxIpRWBuGK9njeYmK5c4W2SEJe17pCpBd2LyUM+5FiT7VQbVBDnW0Ow1ksgI8n+gflLT7Pj2OTNwJ+LezfGulr4WACaZHz/IllE4nqreXpAxPgtODq/W4mD3/+w83QKcsa6kkaEPpvhIYuA+oazu2pQnMWYWz4jes2qLP2+DEoc4xfEXtwib4iDiaQNvtRcGociTZR8Ya2rotKaNK7Bto7nLqYzfYwkRBhOn2F4vwboSfXAJ0d6sVRwjtHHgZ9MJr7W5MJH7RXmD3IjE04Y7RBAQYAZUax3MAbHJQbeJiMAoAdcoF9xXxxMJXehY12IpvxN8ADdZR1xWZTaNB3RlNg0PcwKC+KTVjVhQZ9b2gJXkPzOBmvJDuXAjX+00pyQHXdd6IojbsGKO7Xi6PscIU5mLHqO1GUPmKj0jukziD1on24+MxAlf601uyMp+KaoQeiNUOPA2uGHobWDD1OoxPmcLBHV7IzDd5xwAGBgnm9yAlswjwMjeYeh0Zzj4OjebITjIajuQeiebnHgXm5h+lrjiVSlLZKjeblziD7vGpDJ46y02jujRKd8IQGRymehU7nHsYpOeccnb8Udq7U1aOd89mLPyZ82umNqYljaotD6vRNdUY04JtqYwZNXjwOXu4OBycvyc6CBk5ePBBNXjwOTF48DE1ePA5NXjwOT17sLGjw5MUEhXnG2YsHoumLx8H5iwfCCYwHwsE6zw4JpzAuieYwLggmMS6HmgW4oAGnzQOFGU9bdEi8RblHogeILgieILocemPJBdEeRC4InyPm7JDwQaJLonmIC4KJiMeJNBNxQTQVcUE4F8nVIeFkxCXRbMQFwXTE5dB8xAXRhMQF4YwkO19JfqHbIyWakrggmJK4HGwt4YFoSuKCcEpSnK9kwimJS6IpiQuCKYnLoSmJC6IpiQfKOCUpzleS36B2STQlcUEwJXE5NCVxQTQlcUE4JSnOV5LXNl0STUlcEExJPE6hKYkLoimJC8IpSXG+kgWnJC6JpiQuCKYkLoemJC6IpiQuCKckxflKFpySeKRKUxIXBFMSl0NTEhdEUxIXhFOS6nwlK05JXBJNSVwQbfvscWhK4oJoSuKBGk5JqvOVbDglcUm4F7oHgimJy6EpiQvCnZo9EE5JqvOVbDglcUk0JXFBMCXxOLxhuQeiKYkLwilJdb6SHackLommJC4IpiQuh6YkLoimJC4IpyTV+Up27nPhkAZNSVwQTElcDk1JXBBNSVwQTkma85UcOCVxSTQlcUEwJXE5NCVxQTQlcUBhxilJiw4JpyQuiaYkLgimJC6HpiQuiKYkLginJC07JJySuCSakrggmJJ4nDBr2piTzKtJxsIHLr1F6g5QtCo/S7zkEdKo7o4wiyNsdITsNtBZ5dWcK5UHIn8lqkNq627aXRgbvk/tjm2suonqDy3S1MYbWYSpjcuhqY0LSuLtzuMjEi4CH6BqK+zjndEelLch8pSnOz8apzweiKY8HgenPB6IN7F2ch5c83RBcMm7HLrkXRDeqHYnwUh0o+qC4EbV5VRy/64X5WXWi5+np5WXrxgdsJ1i4/KtzwN2UFPJ58O1nwIplB65Qg+RAxfeCu1NCZW4hNqd1IaWUF0O3Rz0qiwifFX0+WTbiyhj4fnz4TqLCG8jepcWEd1UdCcboKVXj6OXXrv5M+3Z1uuw3ZwUe7JJUXY2R2tPNinRPnDHrEw2Lth2J1cohVzcHUEaXIULyBsb608zkoOhL8ZwcoYCXwyPg8u2w/nS07Kty6FfiuFE+Aq/FC4nw7s6o3q7NlC2Pf42J5xVuKpdTltzse7bDxQ++uQi6vzweRnO61dpiwEP1GCPAZcT8G8Ls/MOtriC5bw+pDHzmeWsfHIv9cxyVhq5mnpmHZ79H1/f3H2+/evhj719/+X2l093Hz4f/sj7N29v3x/+Xf3Dqx8PlHe37179+OXnn28/vfrdxy8f3r15+/HL51f/+R+//e1vD//nv91++vXhI57mw5vTYiz33+G7D+9u72/nW3/F9Pbjx788+Xt+/+fbV787jPb/vfnHqx/v3r6/Pfxvbw5r/2+3fzpiovP3fP3/kYM3UQ==
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Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Tue Apr 30, 2019 7:39 pm
by hansjoachim
yvanaquino wrote: Tue Apr 30, 2019 7:36 pm
Is it possible to submit a design for testing and improvement/feedback? I helped my kid develop this but it's his intellectual property.
Yes it is=)
But please provide a screenshot so that one doesn't have to open factorio to see it.
On this forum I'd prefer 4 way intersection. The trainstation looks decent, you could add some more signals so that a train is right behind the train at the station. Apart from that you could probably make it smaller, but I never cared for saving a bit space or rails.
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri May 10, 2019 4:29 pm
by lee1026
Does today's patch (0.17.38) change all of the deadlock discussions?
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Fri May 10, 2019 4:39 pm
by hansjoachim
lee1026 wrote: Fri May 10, 2019 4:29 pm
Does today's patch (0.17.38) change all of the deadlock discussions?
It probably does, needs to be tested first.
Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Sun May 19, 2019 8:43 am
by SkiCarver
Similar to some of the designs posted, but it works well.
Left Side Drive
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Right Side Drive
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Re: 4-way intersections: Throughput and deadlocks [image heavy]
Posted: Sun May 19, 2019 8:55 am
by SkiCarver
4 lane version of the above junction.
Sorry to say I have not tested this, as I dont use 4 lane rail networks.
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