Thanks much for the support and it seems you understood exactly where I am coming from with this project, if I decide to do it. Which seems likely considering the effort I've went into explaining things both on this thread and the document I am writing...
I do *think* that this is not what I am after actually. I haven't truly come with the correct symptom, still writing and thinking about that to be honest. But I think my symptom is: The AI cheats.
By the way, its not only changing what the AI receives for input, but how the AI reacts with the input. In what form is the AI cheating if it see's the cone, that the player sees. Sure it sees it in mathematical values. But there is no way around that. It is seeing the data as an estimation. Which is how the player interprets it. So if this is still somehow cheating please do let me know, I would be interested as I am trying to remove that.
Of course the reaction time would fall under the "super control" category. I may have mentioned it somewhere in the thread already, but I know it is included in my document and covered already. I am almost finished writing this document, (one hour or so), for the general public. And will begin researching and writing the specification part of the document: which will be more technical probably including math, code and good stuff like that. Heh, boring for the average person.
Mmm that is a really good point morpha.
I was thinking, what if it was a restriction that the host can run only 1 InSim app. (Or at least only 1 'main' app.) And the main app is the one that gets priority over things like this. However, this adds a limit that I don't think is good for the InSim protocol since it already supports multiple connections it could be that there are already host-side systems that require this feature.
I think the "Main App" idea would work. The first insim connection will get that slot, which allows special controls over MSO, and anything else that would have a conflict.
I was thinking, what if it was a restriction that the host can run only 1 InSim app. (Or at least only 1 'main' app.) And the main app is the one that gets priority over things like this. However, this adds a limit that I don't think is good for the InSim protocol since it already supports multiple connections it could be that there are already host-side systems that require this feature.
I think the "Main App" idea would work. The first insim connection will get that slot, which allows special controls over MSO, and anything else that would have a conflict.
I was trying to do this back in Dash for Cash so that the racers could talk and chat normally without being inside the 'chat box' that I made for them. It didn't work because the messages don't get filtered by InSim in anyway that I found.
Hmm, seems my objective is still being misplaced, and will probably be understood when I finish this paper.
On the LFS stuff. I could get the left side, right side info with almost as much work as making a quick environment myself I think. But I would be missing the important reference points of cones, and other trackside things like the billboard. It's hard to say what I mean, but I think these other reference points are more important then the track. It's also extremely important to know I want a line of sight on the reference points.
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Please make any repsonses, I am going to try writing my paper as quickly as I can so that you hopefully understand where the project is going and why. The problem isn't a simple effect, and more to the point I don't have an AI system that I am working with. Its not like I have AI working like LFS or something already, if I did and was talking about rewriting everything to test something I would be absurd - especially if it was late in development or something. I am however proposing a new way of doing racing AI. For better or worse.
How would many algorithms be made and known today if someone didn't try them first? Man use to make fire from only sticks, so we are told, and we would continue doing it that way if the person who saw sparks from stones didn't *try* lighting a fire from said sparks... That is probably the most primitive analogy I can find.
I almost missed your post, must have written it while I wrote one. Your probably correct here, but you can also look at your RPM gauge. So in this example the AI can do that. Of course you did just add another point to my simulation - thanks. Which is that the AI can tell the engine speed within some degree, I can usually guess accurately to within about 1000 RPM depending on the car, and would bet people with more sensitive hearing can go to 500 RPM. But anyways, you have added a piece of input to the AI for constant updating. RPM +/- 750. Unless the AI chooses to observe the gauges which will be a very accurate RPM gauge.
If the car has a shift-light I would say the AI can know immediately that it is on. Even in peripheral vision that is easy to detect.
About over-steering / under-steering you're 100% right about the detection can be simple and not cost CPU time and others using the reference points that would take time to get. Two ideas to do this, The way I will likely use is tire sounds, from each of the tires... Though the other idea, less known but is a though is using 4 reference points that are known to a good degree of accuracy by the AI. Previous and Current Positions. Previous and Current Directions. These are not saying collect position code from the physics: but it could. It could also take the two closest reference points. (remember closer reference points are more accurate). What ever it is. And remember them between two frames. Which will allow us to know our direction of travel, and should tell us the direction we are aiming.
However, the more thought about and quite seriously the way I will probably choose is the tire traction data from "sounds". The physics will tell the AI sensor about each tires traction limits. UNDER LIMIT, NEAR LIMIT, AT LIMIT and OVER LIMIT. If your front tires are over the limit and rear tires under/at limit then you are under-steering. If rear tires are over the limit and front are under/at you are over-steering. Pretty simple, and very fast to compute. More importantly it follows the logic that a human can use - though there may be some more known values here depending.
This area is likely the only place where the AI needs to ask the physics system what is happening. It is the only place a human really knows the physics of the world too. Besides knowing that turning the wheel turns the car. Still wondering about that process for the AI, but it will come.
However, the more thought about and quite seriously the way I will probably choose is the tire traction data from "sounds". The physics will tell the AI sensor about each tires traction limits. UNDER LIMIT, NEAR LIMIT, AT LIMIT and OVER LIMIT. If your front tires are over the limit and rear tires under/at limit then you are under-steering. If rear tires are over the limit and front are under/at you are over-steering. Pretty simple, and very fast to compute. More importantly it follows the logic that a human can use - though there may be some more known values here depending.
This area is likely the only place where the AI needs to ask the physics system what is happening. It is the only place a human really knows the physics of the world too. Besides knowing that turning the wheel turns the car. Still wondering about that process for the AI, but it will come.
I have a lot of posts in this one - sorry:
Because I don't have the much needed reference points, and if I made them it would take tons of time - for what I am trying to achieve. I believe you can send commands to set an axis position, though I could be wrong. Either way, LFS would be a great platform tool to use, I wish Scawen would open a few possibilities to me, but it won't happen for security reasons.
True, and false. Remember the objective is not to write the most outstanding AI ever, but to do it based as close to human limitations as possible. Some parts of this will still need to cheat, I think but I am trying to figure out what, and why. Just because something is the norm, doesn't make it best. Its called inventions, there are often times with things are actually better. Not saying this is, or isn't that will be found out.
Do you really? Go sit on a track and tell me exactly where you are. You know the billboard to your left is at coordinate <X, Y> and that the cone somewhere in front of you is at coordinate <X+23, Y-14> (Shooting numbers from nowhere, with no meaning here) Point is, you do not know your exact distance from either of those. Humans do not know where they are, nor do they need to. We can know that we are 10 to 15 meters from that cone, and at this spot is where we begin turning. If the cone is blocked from vision from a car ahead, we use the billboard on our left, we know that when its almost directly to our left is where we start turning. These are very rough estimations.
The problem with using a 2D image that LFS or a sim generates is that it is 2D. The algorithm to reverse engineer that entire image would be very complex, slow and umm, a challenge a lot harder than what I wanna achieve...
As far as your position on track, you don't know it exactly, as I mentioned above. I waited to write this here though: More importantly your exact position is quite useless. Your position compared to these reference points are everything. It is all the brain uses to, as you said triangulate your exact position. So with that, yes you know your position relative to the reference points, but its not your position that tells you to turn - its the reference points. This was an exercise that I did, and am writing in more detail in my paper:
Think of the two corners after the long stretch in BL1 (normal direction). Without starting LFS I can invision this perfectly, and I would bet you can too. You know you have a right hand turn coming up because you remember the bridge and the hill telling you a right comes after the straight. (With never playing LFS with no mini-map you have no idea what comes next.) That, combined with knowledge of the wide corner approach tells you to get to the left of the track. You see the small meter signs counting down, and start braking hard at the appropriate spot - which again is from those ref points. then you see the tires, and turn in towards them.
Now, imagine the world being completely empty; no track, tires, distance markers or bridge. Drive the corner knowing your exact position, but not knowing anything else. You want to get from position <X,Y> to <X+10, Y+10> but you can't drive straight there. You can't do it, well with math you can. But it isn't how you drive. Driving is all based on reference points, and estimations.
The Math.Random() will be called in the Pre-AI step. It will be in the vision sensor where the AI is estimating the distances to each object. I am hoping these estimations will allow the AI to brake at a slightly different spot each time. Have you watch the super 'judgment' of an AI in LFS or 90% of the games? They turn-in, brake and accelerate at the same spots on the track, not making a mistake - (until you enter traffic which is not being talked about yet so irrelevant here).
Because I don't have the much needed reference points, and if I made them it would take tons of time - for what I am trying to achieve. I believe you can send commands to set an axis position, though I could be wrong. Either way, LFS would be a great platform tool to use, I wish Scawen would open a few possibilities to me, but it won't happen for security reasons.
True, and false. Remember the objective is not to write the most outstanding AI ever, but to do it based as close to human limitations as possible. Some parts of this will still need to cheat, I think but I am trying to figure out what, and why. Just because something is the norm, doesn't make it best. Its called inventions, there are often times with things are actually better. Not saying this is, or isn't that will be found out.
Do you really? Go sit on a track and tell me exactly where you are. You know the billboard to your left is at coordinate <X, Y> and that the cone somewhere in front of you is at coordinate <X+23, Y-14> (Shooting numbers from nowhere, with no meaning here) Point is, you do not know your exact distance from either of those. Humans do not know where they are, nor do they need to. We can know that we are 10 to 15 meters from that cone, and at this spot is where we begin turning. If the cone is blocked from vision from a car ahead, we use the billboard on our left, we know that when its almost directly to our left is where we start turning. These are very rough estimations.
The problem with using a 2D image that LFS or a sim generates is that it is 2D. The algorithm to reverse engineer that entire image would be very complex, slow and umm, a challenge a lot harder than what I wanna achieve...
As far as your position on track, you don't know it exactly, as I mentioned above. I waited to write this here though: More importantly your exact position is quite useless. Your position compared to these reference points are everything. It is all the brain uses to, as you said triangulate your exact position. So with that, yes you know your position relative to the reference points, but its not your position that tells you to turn - its the reference points. This was an exercise that I did, and am writing in more detail in my paper:
Think of the two corners after the long stretch in BL1 (normal direction). Without starting LFS I can invision this perfectly, and I would bet you can too. You know you have a right hand turn coming up because you remember the bridge and the hill telling you a right comes after the straight. (With never playing LFS with no mini-map you have no idea what comes next.) That, combined with knowledge of the wide corner approach tells you to get to the left of the track. You see the small meter signs counting down, and start braking hard at the appropriate spot - which again is from those ref points. then you see the tires, and turn in towards them.
Now, imagine the world being completely empty; no track, tires, distance markers or bridge. Drive the corner knowing your exact position, but not knowing anything else. You want to get from position <X,Y> to <X+10, Y+10> but you can't drive straight there. You can't do it, well with math you can. But it isn't how you drive. Driving is all based on reference points, and estimations.
The Math.Random() will be called in the Pre-AI step. It will be in the vision sensor where the AI is estimating the distances to each object. I am hoping these estimations will allow the AI to brake at a slightly different spot each time. Have you watch the super 'judgment' of an AI in LFS or 90% of the games? They turn-in, brake and accelerate at the same spots on the track, not making a mistake - (until you enter traffic which is not being talked about yet so irrelevant here).
Clear Answers
My goal, if pursued, is to make artificial intelligence circle a track using only the known reference points. That doesn't mean there won't be sub-goals but I am leaving it as that for now, since maybe my posts keep hiding what I say.
Just to be clear, yes I want to traverse the track with only information a human can get. And also with only the controls the human can get. Now that you know what I am doing, the reason is because I want to. I talked with a few friends asking what is lacking from games these days - graphics certainly has become an area that far too many people use to chose the new games and it is extremely annoying. The general consensus was AI. With further thought on what I had been told it hit me, what the entire problem with AI in games actually is. However, it also hit me that that problem doesn't exist in racing AI, but the problem with racing AI is simple, the human generally feels cheated.
- Catchup; Where the AI goes fast when you're in front, and slow when you're behind. Great for arcade, console and pick'em up racing, but cheesy for a simulator because real people don't slow down for their competitors . . .
- AI Controlled Physics; This is when the AI has different physics that the player car. The players input travels through the steering column, to the wheels and eventually turns the car via physics, while the AI just rotates their car in the direction they want. Sometimes it works by hitting them and they don't budge while you fly out of control. Not to be confused with AI Super Control
- AI Super Control; [i]The AI can calculate 'exactly' where they want to place the controller at an 'exact' point in time, and they are capable of doing it. The fastest human can't do this. It takes at least a tenth of a second to shift, with an h-shifter and both hand starting from the wheel, unless you prepare for it. And if you're prepared for shifting it takes at least a tenth to turn the wheel over 180 degrees since it requires the second hand... The AI has no delays.
Now of course I will play around with the AI after getting it to traverse a track with the human inputs and outputs. It would be nice to see what type of performance the AI can actually achieve, I have high hopes for their level of performance.
Not at all, even if I can't get the AI to traverse, I will have learned something. To me, learning is an invaluable tool that humans are capable of, and you can't learn without being prepared to fail. After all, learning why something didn't work is sometimes more important than doing something correct on the first try and taking it for granted.
Two ways to answer the question.
- First as you, and everyone should now know, my goal isn't the most realistic AI possible though it would be an amazing place to end up...
- By using these reference points it should make more realistic AI because the AI should be able to drive, NEAR, their same track line each time. But they won't drive the EXACT track line each time. [i]I get that this might not make them fast[/i]. But the point here, is the AI shouldn't have the exact same lap time each lap, they will tend to misjudge where a reference point is now and again. Want harder AI? Just make the reference points more accurate. I think this part of the question will be answered in a lot more detail by my write up.
Might wanna ask yourself if you are interested, and answer truthfully. It is new. Why be scared?
Last edited by blackbird04217, .
Reason : Spelling Errors
Heh, I do know the scale of what I am diving into. Where as I don't have experience with AI exactly, I do have experience designing code and solving problems with said code. I have a fair understanding of what I am asking of myself, yes I am skeptical about the project, but more because I don't want to waste time making the environment and physics. I am far more concerned with the world and physics than I am about the AI challenges. Even a 2D world, still needs to be made, same with the physics - its required. No matter how basic they are, they need to be written before the AI, and that is actually my main concern, and reason that I have not started the project.
Like I said, the goal here isn't for AI that you would look at and say "OMGWTFBBQ" it more about tackling a situation in a different way. Most games allow the AI to control their car completely thus adding hacks or cheats (in my opinion).
And Vain, your right about the easy part is aquiring the data, the hard part is using that data; made especially easy in this case since there is less data. But the idea here is to make an AI using a human like approach. I sat and envisioned myself driving a few laps, figuring out what is needed and what goes on in our little brain. Besides having FAR more reference points than the AI will get, we actually get very little information. Sounds of the tires represent stages of traction, and even then its not an exact number. But its the reference points I am after.
The only single problem I am having with the AI, mostly because I haven't looked further into it - nor have I developed the code to start trying ideas, is to take said reference points and make use out of them. As said in all the other posts, I haven't commited to the project quite yet. But I am not afraid of the math, and problem solving that it presents me. Actually I look at it as a nice challenge to see what comes. It could totally fail, but then I know I tried, and I know why it failed. I just don't feel motivated to work on the world/physics - which are required for the AI to be tested.
I assume that the concerns displayed here are to be sure I am aware of the challenges, and that you don't want to see someone set themselves up for failure - and I appreciate that concern, thank-you. But do understand, I wouldn't look at failure as a bad thing, I would have learned exactly what about the technique does not work. I've actually started writing an article on the problems I see with *most* current AI approaches, and how the system I wanna try would address these concerns.
Like I said, the goal here isn't for AI that you would look at and say "OMGWTFBBQ" it more about tackling a situation in a different way. Most games allow the AI to control their car completely thus adding hacks or cheats (in my opinion).
And Vain, your right about the easy part is aquiring the data, the hard part is using that data; made especially easy in this case since there is less data. But the idea here is to make an AI using a human like approach. I sat and envisioned myself driving a few laps, figuring out what is needed and what goes on in our little brain. Besides having FAR more reference points than the AI will get, we actually get very little information. Sounds of the tires represent stages of traction, and even then its not an exact number. But its the reference points I am after.
The only single problem I am having with the AI, mostly because I haven't looked further into it - nor have I developed the code to start trying ideas, is to take said reference points and make use out of them. As said in all the other posts, I haven't commited to the project quite yet. But I am not afraid of the math, and problem solving that it presents me. Actually I look at it as a nice challenge to see what comes. It could totally fail, but then I know I tried, and I know why it failed. I just don't feel motivated to work on the world/physics - which are required for the AI to be tested.
I assume that the concerns displayed here are to be sure I am aware of the challenges, and that you don't want to see someone set themselves up for failure - and I appreciate that concern, thank-you. But do understand, I wouldn't look at failure as a bad thing, I would have learned exactly what about the technique does not work. I've actually started writing an article on the problems I see with *most* current AI approaches, and how the system I wanna try would address these concerns.
I don't know if I made it clear enough in the first post, but creating a super fast and difficult AI is not the goal, although I would like to see how good I can do it. The main point of the exercise is only using data that the player can use. For instance a player does NOT know the heat of the tire, size of the tire or any of this information - but just as well we do know how to sense the limits of the tire by listening to the sound, and by seat of your pants feeling which is lacking in a simulation environment.
Weight distribution doesn't really matter either - if the physics side of things simulates it then great, but all a human is concerned with is the tires being at the limit without going over. Your correct that the AI will need to sense the data somehow; through the reference points which will be placed in some sort of editor or something.
It is likely I work on this in a 2D environment, although I have not made my finalized plan. I've been thinking about this quite a bit, and yes it is a big project. No it will not be easy. And most importantly it will likely be far from perfect. I have reasons to think that some of my techniques will help the AI a bit, but there are still a few lacking ideas. I don't have a 'best' line on the track, and am going to try using only the track side reference points.
I don't think the AI needs to know all the physics of the simulator to be fast. Actually, I think traditionally developers go this route just because it is proven.
For instance: Put yourself in an unknown setup, even in a car you haven't driven in some time. But you are on a course that you know reference points of. (You generally brake *near* the 50m mark in most cars, this car you might brake slightly after, or before - but you know the 50m reference point - and that is all that is needed.) You also know that turning the steering wheel left will turn the car left, but by how much you don't know exactly. Setup could be strange there. I think the point is clear with the example that you don't need to know the dynamics of the setup or car. The only thing the driver is aware of, as far as physics is concerned, is the traction levels of all the tires.
Front tires lost grip, try braking more, (or less if hard on brakes), and try less steering input. Now, as far as getting the AI to find, and drive the perfect line - avoid the other cars when they only know estimation points, and things like that - it will be interesting. This may work great, or it may be terrible.
"All our dreams can come true, if we have the courage to pursue them." -Walt Disney
Weight distribution doesn't really matter either - if the physics side of things simulates it then great, but all a human is concerned with is the tires being at the limit without going over. Your correct that the AI will need to sense the data somehow; through the reference points which will be placed in some sort of editor or something.
It is likely I work on this in a 2D environment, although I have not made my finalized plan. I've been thinking about this quite a bit, and yes it is a big project. No it will not be easy. And most importantly it will likely be far from perfect. I have reasons to think that some of my techniques will help the AI a bit, but there are still a few lacking ideas. I don't have a 'best' line on the track, and am going to try using only the track side reference points.
I don't think the AI needs to know all the physics of the simulator to be fast. Actually, I think traditionally developers go this route just because it is proven.
For instance: Put yourself in an unknown setup, even in a car you haven't driven in some time. But you are on a course that you know reference points of. (You generally brake *near* the 50m mark in most cars, this car you might brake slightly after, or before - but you know the 50m reference point - and that is all that is needed.) You also know that turning the steering wheel left will turn the car left, but by how much you don't know exactly. Setup could be strange there. I think the point is clear with the example that you don't need to know the dynamics of the setup or car. The only thing the driver is aware of, as far as physics is concerned, is the traction levels of all the tires.
Front tires lost grip, try braking more, (or less if hard on brakes), and try less steering input. Now, as far as getting the AI to find, and drive the perfect line - avoid the other cars when they only know estimation points, and things like that - it will be interesting. This may work great, or it may be terrible.
"All our dreams can come true, if we have the courage to pursue them." -Walt Disney
Artificial Intelligence in Racing Simulations Project
I didn't know whether to put this in Off-topic or here, but for the past 8 hours I have been thinking about developing the most realist AI Racing Sim I can. I would like to discuss it here with a few programmers because there are a few around, and there is an obvious passion for racing. My idea comes from the fact some tests I've been running in LFS, I am not mentioning them for fear of flaming since what I would have to say is purely my thoughts and opinions based on what I've witnessed. I don't have the code so I can't be sure what is happening.
Regardless. I want to make an AI that can take in only the amount of information that a human can. Information will be limited to Reference Points. Track Reference Points will be placed every 20 meters or so on the left and right side of the track. General Reference Points consist of buildings, billboards and other large / obvious points along the track, and then Detail Reference Points will consist of points close to where the AI Driver is supposed to brake, turn-in or hit for apex.
However, the driver will not get the reference point as a solid position. Instead they will a vector in the direction of the reference point and with a length of near the distance between the view and reference point - but it could be longer or shorter. The error comes into play based on how far the reference point is. Closer points are easier to judge distances, therefore are more accurate.
These reference points are also "culled" by a FieldOfView each frame, so the driver needs to turn their view to see more. This fov can change based on the drivers concentration level. Example, if the driver suddenly starts spinning and losing control they will likely have less fov, and less accurate points of reference.
Other information the driver will be able to gather:
- Reference Points
- Velocity of the vehicle
- Useful Car/Dashboard/Gauges Information: RPM, Fuel, Gear etc.
- Traction Information (FULLGRIP, NEARLIMIT, ATLIMIT, OVERLIMIT)
- G-Meter (Represents "feel of the seat")
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Development has not started on this, although I have started working on a writeup of the particular AI problems I am trying to solve, and eventually how I am going to go about solving those. I am looking for a few people who are interested in the project to contact me. I will be working with Visual C++ 2008 Express Edition. I want to keep the environment simple and to the point. The physics of the racing do not need to be 100% accurate or even near it, but the AI is the thing to tackle.
This Artificial Intelligence system will not be dependant on physics. If done properly the driver should be able to drive near the limits. That is not to say that physics won't effect the AI. A bad physics system with the traction could cause issues, though with any luck some rudimentary game physics will work.
See attached file for some existing AI problems.
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Youtube: AIRS: Computing the Racing Line
Youtube: AIRS: Driver Predictions
Youtube: AIRS Driving XRG at FE1 (2014)
Youtube: AIRS Playing with Genetic Algorithms
Youtube: AIRS Driver Lapping XRG at FE1 (early 2016)
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Last edited by blackbird04217, .
Reason : Changed thread name to official project name
Because there is, its almost like the ballast and air restriction, do people drive around with those on all the time? No, because the optimal setting is with them turned off.
Just like the tires. Doing a sprint, 1 to 3 lap race and R1s will be used likely, do a longer race 10 to 15 lap and likely R2s will be used since the R1s will burn up. These are two situations that 90% or more of the players in LFS already know and use. Its rare to find someone who plays with the less ideal performance trade off. R1's would help you in the first couple laps of a race with everyone on R2's, but do you really think you ca get a lead big enough for when you need to slow down from overheated tires.
It is the same principal. If setups were not so personalized to different driving styles everyone would likely get the 'best' setup. But different driving styles require different setups.
Just like the tires. Doing a sprint, 1 to 3 lap race and R1s will be used likely, do a longer race 10 to 15 lap and likely R2s will be used since the R1s will burn up. These are two situations that 90% or more of the players in LFS already know and use. Its rare to find someone who plays with the less ideal performance trade off. R1's would help you in the first couple laps of a race with everyone on R2's, but do you really think you ca get a lead big enough for when you need to slow down from overheated tires.
It is the same principal. If setups were not so personalized to different driving styles everyone would likely get the 'best' setup. But different driving styles require different setups.
Start with it or you never will, but really it isn't any harder than anything else: just get used to it.
@Bose: there is an option in LFS that allows you to turn the wheel past 720 degrees although it doesn't effect the car control. You can watch because the steering wheel in game stops moving. This is essentially driving at 720, you just don't hit the sudden dead point. This is my enjoyable setting anyways.
Those video's are quite interesting. I saw BMW clip before, but the under-cam was great, especially watching the tire lift off the ground during hard cornering.
Did you have a chance to get it and look it over? I'd be interested in feed back since it's my first, and currently only, real technical article.
Did you have a chance to get it and look it over? I'd be interested in feed back since it's my first, and currently only, real technical article.
I'm not fully against eating meat as it is normally, although I am also not against this new idea. My first impression is it sounds horrid. But taste, nutrition and other factors are more important than a first impression. To be honest, imagine long ago when hunting was the only way to feed the community/family. Then someone comes up with the grand idea of 'growing' animals to eat. I am sure they were just as disgusted with that idea as it seems that a lot of people here are with this new idea.
People fear new. But this could be a great thing, if taste and nutrition can compare with true meat. It could be more efficient in feeding the billions of people in the world.
People fear new. But this could be a great thing, if taste and nutrition can compare with true meat. It could be more efficient in feeding the billions of people in the world.
This is not an accurate test of any sort of simulator in my opinion. If I never retried LFS when I got a wheel I would have said it sucked via keyboard as well . . .
Let's face it, digital input just has lacking issues! The gas pedal is not an off/on switch.
Might look similar in many ways, I havn't driven it so I don't know if it feels the same. I didn't notice tire deformation, and one would have thought you would with those huge truck tires! Also in/car or driver view seemed really buggy/strange with the steering wheel.
I wouldn't think the license plates need colors? So when setting the value remove all the color code from it allowing 8 characters still? Would probably be an easy solution, I think?
Hmm, actually I misread your post. I read it three times over, but after examining the picture more I see that the effect, could, be noticeable. Although as I did say, it would require a change to the spring system which I do not think I am updating at this time until I find additional features I want to add to the tire itself. I think as a base Deformable Tire it is pretty much what I was aiming for.
Right, though as a visual effect how notice-able is that when you really sit with a camera and look for it? I think you wouldn't notice the effect much at all really. I created limitations when I deleted many of the springs that used to 'hold' the tire together. One limitation is: Tread width is always the same, and is not bendable. Nor are the sidewalls bendable. The center of the tread is the only point that really can move, the edges of the tread just follow it.
Where you have a valid point it would be neat to see, I don't think the effect would be seen too well, just like the longitudinal deformation really isn't seen all that well. I was about to make a video showing that deformation, but even looking for it, and exaggerating the effect did not help. (Though I know it is there because when the effect was exaggerated enough it was noticeable and looked bad :schwitz
Thanks for the idea though!
Where you have a valid point it would be neat to see, I don't think the effect would be seen too well, just like the longitudinal deformation really isn't seen all that well. I was about to make a video showing that deformation, but even looking for it, and exaggerating the effect did not help. (Though I know it is there because when the effect was exaggerated enough it was noticeable and looked bad :schwitz
Thanks for the idea though!
I like! Okay, just made a small update to the tire. I have completely changed the positions of the springs. They still effect the Center Line of the tread like they did in the video, except coming from completely different spots. Testing shows it to be almost identical, though I now have the ability to remove 2 springs if I want only lateral deflection. After running some tests with longitudinal deformation I don't know if it will be worth keeping. The visible difference is tiny.
However, the benefit of the four springs in the new position is complete control over sidewall stiffness vs the outward force from the rim to the tire. Which should mean, if ever used on a car, that tuning the deformation should be easier to make the sidewall look stiffer!
Thanks guys for the ideas, or at least for getting me to come up with the idea as I read your posts!
However, the benefit of the four springs in the new position is complete control over sidewall stiffness vs the outward force from the rim to the tire. Which should mean, if ever used on a car, that tuning the deformation should be easier to make the sidewall look stiffer!
Thanks guys for the ideas, or at least for getting me to come up with the idea as I read your posts!
I almost misread what you said to just having springs that can change the stiffness. But I see what you mean now, so that the spring acts differently to horizontal forces vs vertical forces. While this is completely possible, I think it is also a bit overkill for a simple effect. The easier way, using already existing spring code, is to attach springs in the proper direction, some based on the sidewall stiffness and others based on air pressure. Though, I will keep in mind what you have said, who knows, in the end it might be what is used.
The old spring system had so many springs it wasn't funny, for some reason I had believed that more springs would stabilize the tire. And it did, to a degree. But the new spring system has fewer springs, and close to the same appearance and behavior. I won't say that the cpu cycles spent on updating that old tire was outrageous, but the new one being less than 10% is a lot better. I am thinking about a way to add no more than 2 more springs to achieve all other desired effects. Even if I have to rearrange the 4 that I have now.
Which just gave me a great thought that I didn't think of before . . . :doh:
The old spring system had so many springs it wasn't funny, for some reason I had believed that more springs would stabilize the tire. And it did, to a degree. But the new spring system has fewer springs, and close to the same appearance and behavior. I won't say that the cpu cycles spent on updating that old tire was outrageous, but the new one being less than 10% is a lot better. I am thinking about a way to add no more than 2 more springs to achieve all other desired effects. Even if I have to rearrange the 4 that I have now.
Which just gave me a great thought that I didn't think of before . . . :doh:
Awesome. Glad I didn't have to go any faster than my own speed during my walking adventure... Course it was with different situations . . . but still. I commend your efforts!
EDIT: Hmm, maybe I oughta try reading the remainder of the thread now?
The original spring structure that I made the tire from would have. However the current version uses only four springs attached from the rim to the center of the tread. This has an effect on the lateral force, but is also attached to the vertical force as well. So increasing the spring strength would make the sidewall stiffer but at the exact same time it would also make the tire more resistant to being pressed toward the rim. I have been trying to think of a way to re-add this ability without losing the performance I gained from the optimization.
FGED GREDG RDFGDR GSFDG