Huge 80's Historical IMSA Carset

Huge 80's Historical IMSA Carset 0.9

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This really started as a way to reduce duplicate paints in offline races and I may have gotten a bit carried away... it has evolved into a carset that includes 49 period-specific paint schemes. Many of these cars bear striking resemblence to iconic liveries from IMSA, SCCA and NASCAR; but because I've had to take some liberties adapting these paints, it leans more towards fantasy than historical. I originally approached the idea as an 'alternative history' perspective, a scenario where SCCA Trans-Am and IMSAs GTO were merged into one super competitive series that screams ADRENALINE PUMPING, FENDER-TO-FENDER, NEON-FUELED 80s RACING ACTION!

Along with this carset, I've included drivers from that era with talent files (as well as 'Wisdom' files) for each of them. The idea is to compete against a field much as it was in the mid-to-late 80s. This means that the AI uses a broad range of values to simulate not only top class drivers, but the gentleman drivers and field fillers as well. I've tweaked with a lot of the values but still don't fully understand some of the AI parameters and how they effect one another. That being said, I've had several very enjoyable offline races against the AI using these settings.
Anyone who uses this and can find ways to improve the AI functioning and behavior, please PM me.

There are no in game UI thumbnails, so in the *.zip as well as this post is a reference card with each car. The original cars packaged with the mod are still intact and will be a part of your racing experience. I've also included historical drivers and talent files for some of those cars as well.

rF2_80sScreen03.JPG



INSTALLATION
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1) You must have the TOYOTA CELICA GTO v1.0 Mod by 32_Pixels already installed for rFactor 2.

2) Extract the 'CELICA GTO' folder to "rFactor2/UserData/Player/Settings/"

3) Extract 'celica26EXTRA3.dds' to "rFactor2/Installed/Vehicles/Celica GTO/1.00/" where the *.MAS files and *.MFT file are located. This reworks the hard-coded contingency decals without bothering the encrypted *.MAS files.


rF2_80sScreen01.JPG



SPECIAL THANKS
------------------
32_Pixels for creating an absolute masterpiece, the Toyota Celica GTO.

Jurgen-By for helping me work around certain limitations

Guimengo for Gianpiero Moretti & Klaus Ludwig's Driver Suits


rF2_80sScreen02.JPG



KNOWN ISSUES
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1) AI Track learning was originally intended to be the new and improved 'Wisdom' file system, however the AI went absolutely crazy for me when using the *.wis files so I resorted to the original AI learning mode with *.ini files. I hope to update this project with better *.wis files in the future.

2) Possible AI oddities at certain third-party tracks. In many cases this can be fixed by teaching the AI the track with AI LEARNING.

3) No UI thumbnail for paintschemes until I can get permission from 32_Pixels to incorporate my skinpack into the Official Mod *.MAS. I don't believe there is a workaround that doesn't involve altering the original package files.

rF2_80sScreen04.JPG


REFERENCE CARD - LOW RESOLUTION
80sFantasyCarset_FullRefCard_1.jpg

80sFantasyCarset_FullRefCard_2.jpg
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Latest reviews

very very cool!! excellent work!!
Fantastic looking skins for one of the best car mods. Have tried to install them but was unable. Would be great if you could upload these on the steam workshop as they are really good skins.
Thank You! Amazing work.
Wow, well done m8.
What a perfect carset. All we need now is a genuine career mode to compliment this.
Looks great.
Simply beautiful
top notch
Excellent Skins - Check
Excellent Choice of Skins - Check
Amount of Skins - Check
Attention to detail - Check
Clear, concise instructions - Check

5 Stars! Thanks.
OverTake
Premium
Wow Steve you have put a huge amount of time in this fantastic skinpack. Big five stars rating!
D
Great diligent labor of love work you've created. You're very welcome for my Momo stuff, in the future feel free to take anything else from Martini to Elf stuff :).

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Author
Steve Rosswick
Downloads
1,289
File size
161.2 MB
Views
9,430
First release
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User rating
5.00 star(s) 15 ratings

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