RaceRoom Racing Experience

About

RaceRoom is the premier free-to-play racing simulation on PC and home to official race series like DTM, WTCR, the WTCC and ADAC GT Masters. Enter RaceRoom and enter the world of a professional race car driver.

A selection of free-to-play race cars and tracks are yours to drive with unlimited wheel time in multiplayer and single player games modes. Sponsored competitions and other free-to-play events allow you to enjoy premium game content at no cost.

Additional cars, tracks, and liveries can be bought individually or as packs inside the game store using an in-game currency called vRP, which is purchased using your Steam Wallet.

-Steam

Throwback 2013 Teaser Trailer:

• RaceRoom Video Recap - June 2013 (Video) - "Video highlighting all the exciting racing cars and racing circuits"
• RaceRoom Racing Experience + DTM Experience 2013 (Video) - The game credits at the beginning go hard

Force Feedback

• Really quite impressive these days. Might be better than rFactor 1, original Assetto Corsa, and different but comparable in quality to Assetto Corsa Competizione. -Shovas, SimuCube 2 Pro

Graphics

NVIDIA Profile Settings

• In-Game:
  • Anti-Aliasing: 4x MSAA
    • Consensus seems to be anything more than 4x MSAA in-game (of any game) is a waste of GPU and further tweaks should be done at the driver level (ie. NVIDIA Profiles)
• NVIDIA Profile:
  • Anti-Aliasing Mode: Enhance
  • Antialiasing Setting: 8xS [Combined: 1x2 SS + 4x MS]

Notes:

• Antialiasing - Transparency Multisampling and Transparency Supersampling
  • I used to think these were good to always turn on but they don't help in R3E, at least
  • Transparency Multisampling was re-introducing shimmering on fences
  • Transparency Supersampling wasn't improving the image much, either
  • So I just leave these off in R3E

Adaptive AI

• Overview
  • Adaptive AI adjusts the AI difficulty level for the current car/track combo by comparing the player's average lap over the last 10 laps against AI grid's average fastest lap
• Tips
  • Adaptive AI Training Strategy
    • Run short 10min races, across various tracks, keeping to a single car class, until you are no longer solidly in last place
    • Make sure you are competent at race pace for each car/track you try by practicing first otherwise you won't be helping Adaptive AI adapt
    • After 5-10 races like this, Adaptive AI will begin to improve AI difficulty level so that they begin to feel more competitive relative to you, stop punting you so much, push/pass with more grace, and you should no longer be stuck in last place
    • Adaptive AI will use the average laptimes for untrained tracks based on trained car classes
    • Adaptive AI will use the average laptimes for untrained cars based on trained tracks
    • Adaptive AI will use the average laptimes for untrained cars and untrained tracks based on all other average laptimes for trained cars/tracks (based on my experiments below)
  • Quickly Training the Adaptive AI:
    • Run a number of short 10min races across various tracks but keeping to a single car class to quickly train the AI
    • Skip practice and qualifying if you already know the track to get through it more quickly
    • Skipping qualifying should be fine as Adaptive AI only trains on Race session lap times
  • Don't confuse car/track unfamiliarity with Adaptive AI
    • Practice until you are competent at race pace
    • I went to a new, unfamiliar car/track and thought the Adaptive AI had reset because they were so dominant but I tried again and practiced until I had competent race pace and found out the Adaptive AI was very competitive.
• Tools
  • The Adaptive AI Primer tool can be used to 'seed' the laptimes data used by Adaptive AI which may help speed up the process of adapting
• Caveats
  • How Adaptive AI was designed to be trained:
    • Run multiple races at the same track
    • Run multiple races with the same car class
    • But, if you're in a new car class or at a new track, it will use average laptimes for the car class or track you've raced before
    • Worst case scenario you're at a new car/track combo and there's no average laptimes for either car or track...
      • Based on an experiment, it might be judging AI level based on existing average laptimes from other car/track combos
      • It's not clear what happens in this case but it's likely it completely breaks as it has no car or track to grab laptimes from to adjust Adaptive AI.
• Quotes
  • From this post
    • "The AAI works by comparing the average fastest lap of the AI grid to the players average lap over the last 10 laps."
    • "So you need to run enough laps for the grid to get spaced out a bit. otherwise they're being held up either by the player or other AI."
    • "4-5 laps is usually enough to get a decent lap-time for the AI."
    • "The player has to run at race-pace during this as well, otherwise the player average will plummet and the whole thing will be for naught."
    • "It will take a few attempts before the AI starts getting up to speed. So do one track/car combo repeatedly until it's up to speed."
    • "Then switch to the next. Rinse and repeat until you have 4-5 tracks done with that class, and by then the law of averages should mean any new track will start in roughly the right place."
    • "Yes, [Adaptive AI] only trains during race-sessions. And yes, you do have to have AI on-track for it to work."
    • "If the AI can't find info on that particular track, it'll take the average of all the tracks you've done with that particular car-class. And vice-versa for new cars on a track you've already run with a different class."
    • "The more tracks you've done, the bigger the chance the adaptive AI will hit the right spot in the first try. Which is where the 4-5 tracks needed come in."
• Review:
• https://forum.kw-studios.com/index.php?threads/adaptive-ai.14262/#post-194212

Adaptive AI Scratchpad

===
240703

R3E Adaptive AI Tracks Run with DTM 2023 Cars, 20 AI, 10min Race 240703:
- No qualifying always grids you 6th. I wonder if that means the goal of AAI is to always give you a chance at a win.
 1. Donington
 2. Mid Ohio
 3. Imola
 4. Brands Hatch Grand Prix
 5. Brno
 6. Zandvoort
 7. Zolder
 8. Hockenheimring
  ^ From being destroyed to comfortably running 10th mid pack, kind of odd
  ^ Maybe there's a minimum laps recorded count before AAI kicks in
  ^ Noticed AI were less aggressive with punting from behind and passed with more care
  ^ Noticing rubberbanding. They never seem to get more than 3-5sec away and you only really catch up if there's an accident.
 9. Hungaroring
  ^ 17th
  ^ AI continue to be less aggressive and pass with more grace
  ^ Similar rubberbanding
10. Interlagos
  ^ 18th. Was last for a while until the AI made some mistakes.
  ^ Similar rubberbanding
11. Monza
  ^ 1st, comfortable 5-3 for a while, worked my way up late, held 1st +0.7sec, almost gave it up
  ^ Forgot to switch car. Hope that didn't mess things up.
12. Moscow
  ^ 1st, Comfortably top 3
  ^ New track to me, nice track though
  ^ There's some weird quirk with isiMotor AI where once you get them to a competitive AI level they seem to run into you less and become more situationally aware of you
  
Conclusions:
- It takes more races/laps than you think while doing it but it's not a crazy amount either
- R3E is underrated. Racing with AI is very decent once dialed in.
  ^ Unpopular but fun cars and tracks are a cool feature of R3E
  
Experiment: Untrained cars at trained track 240703
- Praga R1 (Untrained) at Moscow (Trained)
- Expectations:
  - > If working as expected (ie. has track data), comfortably top 5
  - If working but not as expected, mid pack 10-20th
  - If not working at all, solid last place
- Results: 
  - 5th, comfortably top 5, but AI hot on my tail
  - Maybe some rubberbanding
  - New car, needed to practice to get up to speed
  
Experiment: Untrained cars at untrained track 240703
- WTCR 2022 Honda Civic TCR (Untrained) at Red Bull Ring (Untrained)
- Expectations:
  - If working as expected (ie. no car or track data), solid last place
  - > If working but not as expected (maybe using random track data), top to mid pack
  - If not working at all, solid last place
- Results:
  - 4th, comfortably top 5, rough start and fell to 8th but climbed back up in a few laps
  - Interesting it was apparently able to judge AI level based on average laptimes from other car/tracks because it couldn't have known my laptimes until I raced this car+track combo.
  - New car, needed to practice to get up to speed
  
Next Steps:
- Now that DTM 2023 are trained, how well will AAI apply it to other car sets on the trained tracks?
- Consider the gridding 6th (when no qualifying) for GTR2 AI tweaks
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