Python analysis of abnormal front tire wear on windy US mountain roadsShafer Canyon
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads.
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads
in your community, I will run a python script (I just wrote) on those roads to predict the abnormal wear the front outboard tire shoulders will incur.
To limit the number of datapoints, since I'm running Python on an 2009 Windows 10 box, try to keep each road to less than about 10 miles long.
I've already run a half-dozen tests on my own local roads, but I want to
see how well the Linux/macOS/Win script works in roads elsewhere in the US. Moki Dugway
Blaine wrote:
I've already run a half-dozen tests on my own local roads, but I want to >>> see how well the Linux/macOS/Win script works in roads elsewhere in the US. >>>Moki Dugway
Shafer Canyon
Burr Trail
Guardsman Pass
Maria Sophia wrote:
Python analysis of abnormal front tire wear on windy US mountain roadsShafer Canyon
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads. >>
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads >> in your community, I will run a python script (I just wrote) on those roads >> to predict the abnormal wear the front outboard tire shoulders will incur. >>
To limit the number of datapoints, since I'm running Python on an 2009
Windows 10 box, try to keep each road to less than about 10 miles long.
I've already run a half-dozen tests on my own local roads, but I want to
see how well the Linux/macOS/Win script works in roads elsewhere in the US. >> Moki Dugway
Burr Trail
Guardsman Pass
Python analysis of abnormal front tire wear on windy US mountain roads
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads.
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads
in your community, I will run a python script (I just wrote) on those roads to predict the abnormal wear the front outboard tire shoulders will incur.
To limit the number of datapoints, since I'm running Python on an 2009 Windows 10 box, try to keep each road to less than about 10 miles long.
I've already run a half-dozen tests on my own local roads, but I want to
see how well the Linux/macOS/Win script works in roads elsewhere in the US.
Piergiorgio Sartor wrote:
I've already run a half-dozen tests on my own local roads, but I want to >>> see how well the Linux/macOS/Win script works in roads elsewhere in the US. >>How can you test this?
I mean, ground truth data is there?
Do you have? Can you get it?
Anyone who commutes on mountain roads has *already* measured this.
Or are you asking about road inherency metrics obtained from the GPX files?
Or about basic suspension engineering related to tire wear under cornering?
Huh? I'm testing the python script. I need eyes on it.
The roads are data. Control data. I said I already ran it on local roads.
It's a script. It's gonna have bugs.
What have you found so far by examining it?
Now, what should the code do?
Take the road, in some data formant, and spit
out what? The tyre wear, I understood.
To know if this is correct, you need the
measurement done by someone, or not?
There isn't a person alive, who commutes in single-lane mountain roads, who hasn't had a tire shop not honor the warranty saying the tires were abused.
Do you have this data?
If you have it, you have the road too, I think.
I live in a mountain community where EVERYONE knows that even Costco won't honor the tire-wear warranty, even at the very first scheduled rotation.
You can feel the abnormal tire wear on the front tires within 100 miles.
Maybe I understood this completely wrongly.
Sorry, if this would be the case. Apologises.
Driving on a mountain road is considered "abuse" by tire warranty shops.
I explained in the post to "Your Name" what the engineering reasons are.
The goal here was to get others to run the code on their local roads.
And then we'd find bugs, or necessary enhancements and/or improvements.
What enhancements do you suggest now that you've looked the code over?
On 04/11/2026 23.22, Maria Sophia wrote:
[...]
Huh? I'm testing the python script. I need eyes on it.
The roads are data. Control data. I said I already ran it on local roads.
Input, I understood, and output?
Do you have the output to compare with
your script output?
If you have it, again, why ask for roads?
Piergiorgio Sartor wrote:
On 04/11/2026 23.22, Maria Sophia wrote:
[...]
Huh? I'm testing the python script. I need eyes on it.
The roads are data. Control data. I said I already ran it on local
roads.
Input, I understood, and output?
Do you have the output to compare with
your script output?
If you have it, again, why ask for roads?
Why not, dude? What are you doing?
The point of Usenet is for smart people to help each other & for results
to be archived so that anyone can access our immense tribal knowledge.
On 04/11/2026 23.51, Blaine wrote:
Piergiorgio Sartor wrote:
On 04/11/2026 23.22, Maria Sophia wrote:
[...]
Huh? I'm testing the python script. I need eyes on it.
The roads are data. Control data. I said I already ran it on local
roads.
Input, I understood, and output?
Do you have the output to compare with
your script output?
If you have it, again, why ask for roads?
Why not, dude? What are you doing?
Just curious, I mean, again maybe I did
not understand the point, but asking for
data to test a piece of code makes sense
if one has the output to check.
At least some expected output...
There are metrics.
If you have the data, why ask for something
more *without* ground truth?
Or there is a ground truth?
Otherwise one can generate some plausible
pseudo random data and be fine.
I just wanted to understand the process, if any.
That's all.--Sometimes I just feel like I need to get away
Or there is a ground truth?
You should do some reading on statistics. It's useful to have data 'out
of left field' to test corner cases and general hypotheses.
As I said, I have no complaint about the information provided on the 4
Utah mountain passes. Mission Accomplished, as they say.
I just wanted to understand the process, if any.
Perhaps it's a bit rude. It looks to me like you are a wild animal
waiting to pounce on some perceived affront to the Python computer
language or perhaps coding in general.
On 05/11/2026 00.16, Blaine wrote:
[...]
Or there is a ground truth?
You should do some reading on statistics. It's useful to have data 'out
of left field' to test corner cases and general hypotheses.
I beg to differ. Without data, no statistics.
And here half data is missing.
But, I repeat myself, maybe I do not get it.
So, please explain.
As I said, I have no complaint about the information provided on the 4
Utah mountain passes. Mission Accomplished, as they say.
Why should you complain?
Why you think about complains?
I just wanted to understand the process, if any.
Perhaps it's a bit rude. It looks to me like you are a wild animal
waiting to pounce on some perceived affront to the Python computer
language or perhaps coding in general.
Well, what should I say.
I apologized a couple of time, I mention multiple
times that maybe I do not understand the point.
All I get is complains and no answers.
I'm not sure about who is the "wild animal" here.
bye,
On 2026-11-04 15:18:48 +0000, Blaine said:
Maria Sophia wrote:
Python analysis of abnormal front tire wear on windy US mountain roadsShafer Canyon
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads. >>>
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads >>> in your community, I will run a python script (I just wrote) on those roads >>> to predict the abnormal wear the front outboard tire shoulders will incur. >>>
To limit the number of datapoints, since I'm running Python on an 2009
Windows 10 box, try to keep each road to less than about 10 miles long.
I've already run a half-dozen tests on my own local roads, but I want to >>> see how well the Linux/macOS/Win script works in roads elsewhere in the US. >>> Moki Dugway
Burr Trail
Guardsman Pass
Simply driving on a road doesn't create "abnormal wear". Abnormal wear
on a tyre is due to incorrect air pressure in the tire, misaligned
wheels, unbalanced wheels, and/or bad driving (including doing wheel
spins, donuts, etc.).
Maria Sophia wrote on 11/4/2026 4:22 PM:
The point of Usenet is for smart people to help each other & for results
to be archived so that anyone can access our immense tribal knowledge.
Yes indeed Mary.ÿ When will you start this new tribal project?
Python analysis of abnormal front tire wear on windy US mountain roads
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads.
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads
in your community, I will run a python script (I just wrote) on those roads to predict the abnormal wear the front outboard tire shoulders will incur.
To limit the number of datapoints, since I'm running Python on an 2009 Windows 10 box, try to keep each road to less than about 10 miles long.
I've already run a half-dozen tests on my own local roads, but I want to
see how well the Linux/macOS/Win script works in roads elsewhere in the US.
Keith Thompson wrote:
Your script, if I understand correctly, predicts tire wear resulting
from driving on mountain roads. Are you comparing the script's
predictions to actual measured wear resulting from driving those
roads?
I've been studying this issue for decades, where I've been driving the same mountain roads for those same decades, when I was in a conversation with other mountain folk recently on an alias that has 5000 residents on it.
We *all* mentioned the same anecdotes, no matter which vehicle, no matter
the drive train, the suspension, the "bushings" (as Bob West waxed laconically over), even as we drive completely different commutes
I wrote the Python code to COMPARE the commutes, where the whole goal was
to look at the inherency of the road in the downhill direction, and compare roads for how they would affect the very special tire wear that occurs in mountain driving (i.e., low speed, braking with shift, lateral g forces, etc.)
When I compared a half-dozen of our mountain roads, we were all pleasantly surprised (much as Blaine seems to have been) how *accurate* the inherency comparisons were, given we discussed it among scores of respondents and all of us agreed on the particulars of our roads.
Road A, wore the front-left tire more, and that was the prediction.
Road B, wore the front-right tire more, and that too was the prediction.
Road C wore both front tires' outboard edges reasonably the same,
and *that* was also predicted by the results of the Python script.
Notice, given I have multiple degrees in a variety of fields, that it took engineering knowledge, programming acumen and mapping skills to write the program and test it on the variety of roads tested, so I was "hoping" to
find other intelligent people on these newsgroups who might know more about this subject than I do, which would IMPROVE the results for everyone.
It started off well, in that INTELIGENT people UNDERSTOOD the challenge. Unfortunately, the uneducated trolls infested the thread, as they are wont
to do, such as Hank, Old McDonals, Bob West, Pergiorgio, et al.
Not one of them understood a single line of the Python code.
Not one of them has any education whatsoever in engineering.
All of them came up with utterly absurd challenges to the science involved, even down to the wholly uneducated claim the "bushings" make a difference.
If we added up their combined knowledge of Python, creating GPX routes, and how the automotive suspension works from all of them, it would still be negative.
That was disheartening, that there are so few intelligent people on this
ng, but the bright light was that a few, not many, but a few, were intelligent, and that is what we do on Usenet to share our efforts.
It's 1:99 intelligent people to the morons on this newsgroup.
But I'm hopeful at least ONE person will run the code on their commute.
Is there a single intelligent person on this ng who can run Python code?
How about you?
Keith Thompson wrote:
Your script, if I understand correctly, predicts tire wear resulting
from driving on mountain roads. Are you comparing the script's
predictions to actual measured wear resulting from driving those
roads?
I've been studying this issue for decades, where I've been driving the same mountain roads for those same decades, when I was in a conversation with other mountain folk recently on an alias that has 5000 residents on it.
Road A, wore the front-left tire more, and that was the prediction.
Road B, wore the front-right tire more, and that too was the prediction.
Road C wore both front tires' outboard edges reasonably the same,
and *that* was also predicted by the results of the Python script.
Bob West wrote:
He was posting about this tire wear
thing at least 20 years ago on rec.autos.tech, or some auto group used by
mechanics.
Hi Bob,
I get it you want to infest this thread with your childish trolls, Bob.
We go way back where you've been desperate to insult me for two decades.
I feel sorry for you because you couldn't make it into college so you don't own the knowledge necessary to understand what the Python script actually accomplishes, nor how downhill mountain road inherence overwhelms typical suspension geometries and drive train particulars.
However, given you've been desperate to insult me for decades, you're actually right about one thing.
I have been studying this problem set for decades, where I could wager that maybe, oh, one out of ten thousand people understand it as well as I do.
Maybe one out of a million.
Dunno.
Certainly only one or two people who posted to this thread understood it.
Given your absurd argument about the drive train, it's clear you haven't learned a single thing in those twenty years, which, well, it's just sad.
Meanwhile, I've actually done the empirical work, built the tools, and learned what actually moves the needle, and just as importantly, what
doesn't (like realizing road banking or a minor cross-slope is basically a rounding error compared to the brutal geometry of a 4.8-meter hairpin).
You've spent 20 years clinging to basic alignment checks and irrelevant drivetrain trivia because you've never bothered to look at road relevance.
Your claim that all roads are the same, and worse, that all directions are the same, is so absurd at to ring loudly and clearly that I'm insulted that you TRIED to insult me, by proving you don't understand a thing about it.
That's just sad.
You're so embarrassed you know nothing, that you try to insult me.
Why?
Why have you been acting childishly like that for the past 20 years?
When, if ever, will you grow up?
Since you've had two decades to learn about this problem set, let's ask you which specific suspension bushing or alignment setting prevents a tire from experiencing lateral contact patch scrub at extreme steering lock under downhill braking?
Let's see your math, or at least an educated explanation, why you feel the direction of travel & road inherence doesn't overwhelm "bushing" design.
Q: What were your results when you ran the Python script on your commute?
A: ?
Maria Sophia <mariasophia@comprehension.com> writes:
Python analysis of abnormal front tire wear on windy US mountain roads
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads. >>
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads >> in your community, I will run a python script (I just wrote) on those roads >> to predict the abnormal wear the front outboard tire shoulders will incur. >>
To limit the number of datapoints, since I'm running Python on an 2009
Windows 10 box, try to keep each road to less than about 10 miles long.
I've already run a half-dozen tests on my own local roads, but I want to
see how well the Linux/macOS/Win script works in roads elsewhere in the US.
What exactly do you mean by "how well" the script works?
Disclaimer: I don't drive on mountain roads, I haven't examined
your Python code, and I'm not planning to run it.
Your script, if I understand correctly, predicts tire wear resulting
from driving on mountain roads. Are you comparing the script's
predictions to actual measured wear resulting from driving those
roads?
I've been following this thread, and I see it's led to some insults
(which I largely don't care about) but I don't recall any mention
of measured data from actual tires. It's possible I've missed it;
if so, please point me to the information I missed.
Bob West wrote:
He was posting about this tire wear
thing at least 20 years ago on rec.autos.tech, or some auto group used by
mechanics.
Hi Bob,
I get it you want to infest this thread with your childish trolls, Bob.
We go way back where you've been desperate to insult me for two decades.
I feel sorry for you because you couldn't make it into college so you don't own the knowledge necessary to understand what the Python script actually accomplishes, nor how downhill mountain road inherence overwhelms typical suspension geometries and drive train particulars.
However, given you've been desperate to insult me for decades, you're actually right about one thing.
I have been studying this problem set for decades, where I could wager that maybe, oh, one out of ten thousand people understand it as well as I do.
Maybe one out of a million.
Dunno.
Certainly only one or two people who posted to this thread understood it.
Given your absurd argument about the drive train, it's clear you haven't learned a single thing in those twenty years, which, well, it's just sad.
Meanwhile, I've actually done the empirical work, built the tools, and learned what actually moves the needle, and just as importantly, what
doesn't (like realizing road banking or a minor cross-slope is basically a rounding error compared to the brutal geometry of a 4.8-meter hairpin).
You've spent 20 years clinging to basic alignment checks and irrelevant drivetrain trivia because you've never bothered to look at road relevance.
Your claim that all roads are the same, and worse, that all directions are the same, is so absurd at to ring loudly and clearly that I'm insulted that you TRIED to insult me, by proving you don't understand a thing about it.
That's just sad.
You're so embarrassed you know nothing, that you try to insult me.
Why?
Why have you been acting childishly like that for the past 20 years?
When, if ever, will you grow up?
Since you've had two decades to learn about this problem set, let's ask you which specific suspension bushing or alignment setting prevents a tire from experiencing lateral contact patch scrub at extreme steering lock under downhill braking?
Let's see your math, or at least an educated explanation, why you feel the direction of travel & road inherence doesn't overwhelm "bushing" design.
Q: What were your results when you ran the Python script on your commute?
A: ?
AMuzi wrote:
Good perspective about models generally, aside from this
specific problem. See also 'Global Warming".
By including intelligent people from multiple Usenet newsgroups,
this thread was clearly intended to IMPROVE existing testcases & models.
Hence, it's obvious this thread was hoping to add to the modeling for
1. GPS: How to calculate the track for any given mountain road
2. Python: How to compare any set of tracks that have been calculated
3. Suspension: How to correlate with real-world abnormal-wear experience
That's expressly why these specific ngs of intelligent people were included
1. alt.satellite.gps
2. comp.lang.python, alt.comp.os.windows-10
3. rec.autos.tech
The choice of newsgroups makes it obvious we're seeking
1. Better methods of obtaining measured inherence of mountain roads
2. Better methods of calculation & prediction for specific metrics
3. Better correlation with the real-world shoulder wear we all see daily
Thankfully, we partially accomplished the goal of adding to our test sets
the ability to predict (using map software and the python script), abnormal front tire shoulder wear in an arbitrary set of steep windy mountain roads.
But we haven't exposed yet the algorithmic flaws in the python script.
The script calculates a circumcircle through three consecutive GPX points. That gives a local geometric radius, but the result is sensitive to GPX
point spacing and route-tracing accuracy (which brings up mapping
software).
Initially, I obtained tracks from helpful cyclists who emailed me their GPX tracks, but unfortunately all were done differently, so we decided to normalize the mapping activity to the methods previously described
a. <https://gpx.studio/>
b. <https://overpass-turbo.eu/>
c. Others?
That can't be the only sites that provide road-inherency metrics, can it?
It may be that intelligent people on the mapping newsgroup are aware of a
far better method to obtain road inherency for any steep mountain pass.
Likewise, it may be that intelligent people on the Python newsgroup are
aware of better algorithms for calculating specific road inherency forces.
In particular, we're aware that the same physical road can produce
different calculated radii depending on sampling density, and that several consecutive measurements can represent one physical corner, rather than independent corners.
For example, I'm sure there are bugs in the Python code, as the reported 2.04-meter radius for Guardsman Pass deserves investigation, does it not?
It may be a sampling or tracing artifact, for example.
Also, for the intelligent people on the automotive newsgroup, some should note that a mere count of left/right curvature observations may not be equivalent to a count of actual turns or a measurement of tire loading.
I acknowledge these limitations where the whole point of including trained programmers, automotive experts and mapping experts was to improve the
tool.
Keith Thompson wrote:
Python analysis of abnormal front tire wear on windy US mountain roadsWhat exactly do you mean by "how well" the script works?
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads. >>>
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads >>> in your community, I will run a python script (I just wrote) on those roads >>> to predict the abnormal wear the front outboard tire shoulders will incur. >>>
To limit the number of datapoints, since I'm running Python on an 2009
Windows 10 box, try to keep each road to less than about 10 miles long.
I've already run a half-dozen tests on my own local roads, but I want to >>> see how well the Linux/macOS/Win script works in roads elsewhere in the US. >>
Disclaimer: I don't drive on mountain roads, I haven't examined
your Python code, and I'm not planning to run it.
Your script, if I understand correctly, predicts tire wear resulting
from driving on mountain roads. Are you comparing the script's
predictions to actual measured wear resulting from driving those
roads?
I've been following this thread, and I see it's led to some insults
(which I largely don't care about) but I don't recall any mention
of measured data from actual tires. It's possible I've missed it;
if so, please point me to the information I missed.
Carlos E. R. wrote:
You still have not answered Keith question, which is the same as
Piergiorgio Sartor did. I also have the same doubt. You refuse to
answer, that's clear, but I don't understand why. You are surely
intelligent enough to understand the question...
Hi Carlos,
Ah! My bad. I goofed. Mea culpa.
I apologize for falling into the trap of reacting to the uneducated trolls (mainly, Hank Rogers, Bob West, Old McDonald) so I will reset my response.
By reacting to the uneducated trolls, I wasted everyone's valuable time.
There are explicit reasons why intelligent people were asked to help:
a. The mapping ng can help us obtain road inherency metrics
b. The Python/OS ngs can help us write the calculation/prediction code
c. The automotive ng can help model the shoulder-rollover camber scrub
To help us all improve the tool, the questions from Keith is fair.
From his question, I realize I haven't explained the background adequately, and my earlier responses didn't directly answer what you were asking.
Let me try again since there are multiple aspects to this investigation.
1. The existing real-world observations
Our local Santa Cruz Mountain community has experienced decades observing a particular type of abnormal front-tire outside-shoulder wear on our steep, winding roads, which we've been discussing lately on our local reflectors.
Our local community includes approximately 5,000 mountain residents.
Over the years, we've exchanged photographs and discussed similar wear patterns on numerous vehicles with different drivetrains, suspension configurations and alignments. We've even set up roadblocks, in the past,
on weekends, to stop all vehicles and examine their tire wear patterns.
We set up a weekend visit to all mountain homes that accepted our request
to document their abnormal tire wear in the past, so the abnormal tire wear is well known to us in our specific mountain community.
Recurring examples emerged in out studies of local abnormal tire wear.
a. Road A: Predominantly premature front-left outside-shoulder wear.
b. Road B: Predominantly premature front-right outside-shoulder wear.
c. Road C: Relatively equal premature outside-shoulder wear on both.
These observations motivated the investigation.
They weren't conclusions generated by the Python program.
In fact, the Python program doesn't even make conclusions or predictions.
2. The Python analysis
After decades of study as shown above, and during a recent spate of complaints that the local Costco wouldn't even honor the first scheduled rotation on new tires, I developed the previously included Python program
on my Windows PC (which should work on macOS & Linux equally well) to
examine road geometry, particularly corner radii and the distribution of left-hand and right-hand turns, but note that I didn't add the steepness, which is also a factor given the initial braking sets up the tire wear.
The intention was to investigate whether inherent road geometry, combined with downhill braking and steering-related tire loading, could help
calculate road metrics such that we can explain the data that we've all
seen, where some roads wear the left, some the right, and some both.
Therefore we needed a method of obtaining/comparing road inherency metrics.
As noted in the original post, I first tested the program against approximately half a dozen local mountain roads, where its qualitative predictions were consistent with the representative observations above.
However, I want to be precise about what that Python script establishes.
The current program analyzes road geometry so that we can compare roads.
The Python script makes no attempt to calculate actual tread loss, predict miles to the wear bars or establish a quantitative relationship between curvature and tire life. It simply compares road inherency metrics.
Clearly, we haven't conducted a controlled experiment measuring tread-depth loss over known mileage on the Utah roads, but my hope was to find other experienced mountain commuters with whom we can compare road inherency metrics to correlate to THEIR particular front-tire shoulder wear patterns.
3. Why I asked this group for help
The original request was an attempt to extend the investigation beyond our local roads and to obtain expertise that our community might not have.
Specifically:
a. Mapping expertise:
Better GPX tracks, road geometry, elevation and grade information.
b. Python expertise:
Improved algorithms and more sophisticated calculations.
c. Automotive engineering expertise:
Tire loading, suspension behavior, camber effects
and steering-induced tire scrub on downhill right-radius curves.
I was hoping to have intelligent people suggest roads they knew well so
that we could compare their tire-wear observations on their mountain
geometry with our existing mountain observations to improve the model.
Keith, your question about comparing predictions with actual measured tire wear is entirely legitimate. That's an important distinction between a plausible model and a quantitatively validated one.
Carlos, I wasn't deliberately refusing to answer. I was trying to explain
the broader background, but I can see that I wasn't answering the specific question being asked, as I was unduly flustered by the ignorant trolls.
I apologize.
I should have made the distinction clear from the beginning.
I'm not claiming that the present Python script proves a universal
tire-wear theory. I'm trying to develop and improve a model that might explain a phenomenon we've observed repeatedly in the real world.
Constructive criticism, better algorithms and additional expertise are precisely what I was hoping to get from this discussion.
Specifically:
a. Mapping newsgroup: How to get better road-inherency metrics?
b. Python newsgroup: How to improve the road-inherency comparisons?
c. Automotive newsgroup: How to predict/explain the abnormal tire wear?
Does that answer your concerns so we can improve the tools together?
Keith Thompson wrote:
Python analysis of abnormal front tire wear on windy US mountain roads
Specifically:
a. Mapping newsgroup: How to get better road-inherency metrics?
b. Python newsgroup: How to improve the road-inherency comparisons?
c. Automotive newsgroup: How to predict/explain the abnormal tire wear?
Does that answer your concerns so we can improve the tools together?
I goofed!
I humbly apologize as I errantly conflated Sergio & Keith's intentionally helpful questions about the methodology with those of the intentionally unhelpful ignorant trolls (Bob West, Old McDonald & Hank Rogers).
On 11/4/26 15:04, Hank Rogers wrote:
Maria Sophia wrote on 11/4/2026 4:22 PM:
The point of Usenet is for smart people to help each other & for results >>> to be archived so that anyone can access our immense tribal knowledge.
Yes indeed Mary.ÿ When will you start this new tribal project?
He's circling the drain.
He posts the stupidest sigs.
Old McDonald wrote on 11/4/2026 6:46 PM:
On 11/4/26 15:04, Hank Rogers wrote:
Maria Sophia wrote on 11/4/2026 4:22 PM:
The point of Usenet is for smart people to help each
other & for results
to be archived so that anyone can access our immense
tribal knowledge.
Yes indeed Mary.ÿ When will you start this new tribal
project?
He's circling the drain.
He posts the stupidest sigs.
He has some good ideas, but I think he has the same brain
worms that infected RFK.
AMuzi wrote:
Constructive criticism, better algorithms and additional expertise are
precisely what I was hoping to get from this discussion.
Specifically:
a. Mapping newsgroup: How to get better road-inherency metrics?
b. Python newsgroup: How to improve the road-inherency comparisons?
c. Automotive newsgroup: How to predict/explain the abnormal tire wear? >>>
Does that answer your concerns so we can improve the tools together?
It's not the tool per se.
Yes, there is an actual problem but no, there is no
practical solution. Dramatically reducing vehicle speed
would change the wear rates, but no one's going to do that
willingly. A few billion or tens of billions of dollars for
rock demolition, bridge spans and roadbuilding generally
might reduce tire wear rates but I'd bet the residents
wouldn't stand for the change of scenery and the taxpayers
wouldn't go along willingly either.
So, at best, your program may predict tire replacement
intervals but hasn't provided any actual resolution.
THANK YOU!
You bring up a great point that all the theory in the world doesn't change the fact that our 50K expected-life tires last only 15K to 20K even with rotations, due to the abnormal wear on the outboard front shoulders.
One amelioration, of course, is a directed rotation pattern, which is the same as many but DIFFERENT from others as the "driving wheels" don't influence the cross-rotation pattern so much as the FRONT wheels do.
That is, there are well-established cross-rotation patterns which take into account the driving wheels when "flipping the carcass" (asymetric treads).
But the rotation pattern we've collectively come up with is thus:
1. First rotation:
a. Move the front wheels to the rear (keeping rotation direction)
b. Move the rear wheels to the front (keeping rotation direction)
2. Second rotation: (assuming non-whitewall asymmetric treads)
a. Move the front wheels to the rear (keeping rotation direction)
b. Flip the carcass on the rear wheels (outboard side inboard)
c. Cross rotate the rear wheels to the front (keeping rotation)
3. Repeat as needed (there are few rotations since the tires still wear).
Note that we've studied the old wives' tale myth about radial tire carcass rotation direction and we've found it might have been a factor when radial tires first came out, but nobody today says not to change direction for
tires that are able to be flipped.
Yes. We are aware of various fundamental styles of tread patterns:
a. Directional
b. Non-directional
c. Symmetric across the centerline, versus asymmetric across it
d. Whitewall on one side only
Clearly I fully agree with your pragmatic assessment, although I think
there may be more practical mitigation options than dramatically reducing vehicle speed or rebuilding mountain roads.
The purpose of the program isn't necessarily to eliminate the underlying
road geometry problem. It's to understand the mechanism well enough that we can identify practical ways to reduce its consequences.
In fact, we've already experimented with two possible mitigation approaches in our local mountain community.
1. Increasing front negative camber
We've experimented with increasing front negative camber to compensate for the outside-shoulder loading associated with repeated cornering.
The hope is to compensate for expected loading forces by modifying the
static alignment to better accommodate the dynamic camber changes and tire loading encountered on these roads for the outside tire outboard shoulder.
Of course, there's a tradeoff when we commute into the Silicon Valley flatland, where too much negative camber can move the abnormal wear toward the inside shoulder, in addition to affecting handling.
2. Increasing tire pressure slightly
We've also experimented with increasing tire pressure by a few PSI, within appropriate operating limits, to increase sidewall stiffness to better
combat tire deformation which helps to mitigate outside-shoulder wear.
Again, this isn't necessarily a universal solution. Tire construction, vehicle weight, suspension geometry and operating conditions all matter.
As you note, these are practical variables that mountain commuters can implement without waiting for a billion-dollar road reconstruction project.
3. Why I'm interested in the road geometry
What I really want to understand is why one mountain road appears to
produce predominantly left-front outside-shoulder wear, another
predominantly right-front wear, and another relatively equal wear on both front tires.
If we can identify the geometric characteristics responsible for those differences, we may be able to make better-informed decisions about
alignment settings, tire selection, inflation pressure and other mitigation strategies.
For example, knowing that a particular commute has a sustained downhill sequence of tight right-hand curves is potentially more useful than simply knowing that someone lives in the mountains.
The current Python program is only an initial attempt to quantify those
road characteristics.
4. I agree that a prediction without a practical application has limited value.
I'm not proposing that mountain residents rebuild their roads, nor am I suggesting that everyone should dramatically reduce their commuting speeds.
I'm trying to understand the physical mechanism behind a recurring and expensive problem, then determine whether relatively inexpensive vehicle setup changes can reduce its effects.
If we can improve the model sufficiently to identify which road characteristics are associated with which wear patterns, we might
eventually be able to recommend more appropriate tire, alignment and suspension configurations for particular mountain-driving conditions.
That's a considerably more achievable objective than rebuilding the Santa Cruz Mountains.
I'd be particularly interested in seasoned automotive perspectives on
whether the negative-camber and tire-pressure approaches are addressing the likely mechanisms, or whether there are other practical variables we should investigate.
Thanks for raising the practical side of the problem.
It's an important part of the investigation.
What do automotive guys think of the camber/pressure/rotation resolutions?
Blaine wrote:
I've already run a half-dozen tests on my own local roads, but I want to >>> see how well the Linux/macOS/Win script works in roads elsewhere in the US. >>>Moki Dugway
Shafer Canyon
Burr Trail
Guardsman Pass
Perfect! Thank you for providing a random test sample, which helps
us improve the program as it's tested on control conditions now.
With more eyes on the program & results, we can improve it together!
Chris wrote:
Maria Sophia <mariasophia@comprehension.com> wrote:
Blaine wrote:
I've already run a half-dozen tests on my own local roads, but I want to >>>>> see how well the Linux/macOS/Win script works in roads elsewhere in the US.Moki Dugway
Shafer Canyon
Burr Trail
Guardsman Pass
Perfect! Thank you for providing a random test sample, which helps
us improve the program as it's tested on control conditions now.
With more eyes on the program & results, we can improve it together!
Which is impossible with python code posted on usenet as you cannot
guarantee preservation of whitespace.
As I've told you many times, it would be much more helpful for you to post >> code where it makes sense i.e. github
Here's your code on a gh account thet only took 5 min to set up. Am sure
you could do the same with a throwaway email address once you've verified
it
https://github.com/ithinkiam-ng/roadCurvature/blob/main/mountaincurves.py
Of course, the code doesn't work given the issues above. I encourage Arlen >> to edit it to make it work.
It is also impossible for others to test as we don't have an example
dataset to run it on. I also encourage him to share a test file.
Hi Carlos,
Wow. I'm impressed. Really. You added a *lot* of value to the team!
Thank you.
You even taught me some things (see below).
I'll implement most of them, in fact.
But first, the dataset...
You're not the first person to think that I didn't include a "sample dataset" (i.e., a GPX file), but I actually did because I showed
how to get the file (i.e., I 'taught a man how to fish for it').
This *is* the dataset, for example, for the Moki Dugway GPX file.
<https://gpx.studio/app#14.41/37.27473/-109.93787>
Of course, I "could" have posted the GPX files but anyone can
use the web site to get the same GPX file that I had used.
<https://i.postimg.cc/DydH9gFb/mokidugway.jpg>
I showed in the code and in the writeups HOW to obtain the data set.
For any given section of road, we can find the GPX inherence using this:
<https://gpx.studio/>
1. Open the appropriate road link listed below.
2. Select File > New.
3. Select the route-planning tool (pen icon).
4. Select the appropriate routing mode (e.g., bicycle to stay on asphalt)
5. Trace the complete road (or just click beginning & ending points).
6. Select File > Export > Download GPX file.
7. Save using the suggested road-based below filename.
8. Run the Python analysis.
python mountaincurves.py mokidugway.gpx
python mountaincurves.py shafercanyon.gpx
python mountaincurves.py burrtrail.gpx
python mountaincurves.py guardsmanpass.gpx
python mountaincurves.py angelescrest.gpx
python mountaincurves.py mulholland.gpx
For example, for the given unbiased kindly volunteered testcases,
the python script generated an apples-to-apples commute comparison.
Moki Dugway
<https://gpx.studio/app#14.41/37.27473/-109.93787>
<https://i.postimg.cc/DydH9gFb/mokidugway.jpg>
Shafer Canyon Road
<https://i.postimg.cc/HLjN71MB/shafercanyon.jpg>
<https://gpx.studio/app#15/38.45303/-109.82112>
Burr Trail
<https://i.postimg.cc/X7f6VWKC/burrtrail.jpg>
<https://gpx.studio/app#14.55/37.85138/-111.03141>
Guardsman Pass
<https://i.postimg.cc/JnDSSC4x/guardsmanpass.jpg>
<https://gpx.studio/app#13.81/40.61548/-111.52533>
Angeles Crest Highway (CA-2):
<https://gpx.studio/app#12.39/34.23487/-118.24127>
<https://i.postimg.cc/dV8qhd8f/angelescrest.jpg>
Mulholland Drive (Hollywood Hills):
<https://gpx.studio/app#14/34.13106/-118.44057>
<https://i.postimg.cc/8kB9fH36/mulholland.jpg>
Note that I provided another more detailed method of obtaining a GPX
file using the <https://overpass-turbo.eu/> web site as shown below.
<https://i.postimg.cc/3x8VYvxN/mokidugway.png>
<https://i.postimg.cc/9M7NJPJ1/shafercanyon.png>
<https://i.postimg.cc/CxJyq4Q0/burrtrail.png>
<https://i.postimg.cc/G3DZQR55/guardsmanpass.png>
My observations of the code are:
* no consideration for the gradient of road. a significant issue on
"mountain roads"
Yup. Since we're ONLY looking at the DOWNHILL direction, the
elevation needs to be taken into account. It's my first WIP.
* the curvature calc is hugely dependent on the gps track. Slight
variations will make big differences.
* the curvature calc is based only on three points which again is highly
dependent on the gps resolution/accuracy. It could potentially find
non-existent bends.
Yeah. I know. I don't like taking just 3 points in the curve.
I need to assess the TYPE of curve, and take as many points as needed.
That's my second WIP!
* no checking of travel direction.
You made me think about that, and you're right. I need to doublecheck
that the GPX track is always downhill, and, what's worse, it can go
over the hump, and then I have to decide how to calculate the wear points.
This was NOT on my radar screen, but I've added it as the fourth WIP.
I thank you for catching that lack of error-checking in the Python script.
* no checking of side of the road. A rh turn will naturally be tighter then >> a lh turn *of the same bend*.
That is completely correct but since the goal is to take only the DOWNHILL motion, that should not matter as there is only one direction of curve
going in the downhill direction.
Given the above, have you tested the code for the same road but measured by >> different people at different times? Have you compared the script with real >> world, physical measurements of the bends?
The measurements come from the web sites, where I simply put a dot at the beginning of the road and another dot at the end, whenever possible.
That means everyone would get almost the same GPX file out of any given
road, as long as that road is simple enough that there's an obvious before and after (although I noticed a "loop" on a road Blaine suggested).
You really, really do need to add gradient information. You're completely
ignoring the third dimension which is nonsensical. It's like drawing a
straight line on a map of the world and saying that's the shortest route
for a flight between LA and London.
What I'm missing is not only the grade (e.g., 9% or 10%) but also the pitch of the road for runoff, which is NOT crowned on our local roads.
On our local roads, the cross slope is for drainage, and it always slopes into the mountain wall, so it's a different pitch per turn of a degree or two. This may be impossible to calculate so I may need to estimate it.
I suspect it won't make a big difference, but I need to test it first.
That's my third WIP.
Of course, this whole exercise is based on the predicate of "abnormal"
wear. It seems obvious that constantly driving up and down high gradient,
twisty roads will wear tyres faster than a daily commute into the city.
This is entirely *normal* and predicable wear.
Well, it's "normal" wear for a steep twisty mountain road.
And, more importantly, the mapping expertise, programming algorithms, and automotive suspension particulars are technical tidbits which have far-reaching implications in any similar exercise when comparing commutes.
Thanks for looking at the code and suggesting improvements, almost
all of which I easily agree with as I'm nothing if not sensible.
Bob West wrote:
What do automotive guys think of the camber/pressure/rotation resolutions? >>First, I'll ignore your insults because even though I used to think that you >> are a nutcase, I've downgraded that to just another quirky personality on
usenet. But I am an automotive guy, so you addressed me.
Wow. I'm impressed. Really.
Thank you for writing a post worthy of an adult purview.
In fact, here's an excerpt from *that* Stanford professor, who gave us hope that it can be done, &, in reality, who sparked me to write the code comparing his commute to my commute (since nobody on my hill can get
anywhere near those kinds of miles on the inherence of our mountain road).
-------- Begin Forwarded Message --------
Subject: Why your front tires are unduly wearing the outside shoulder
Tire wear is a subject of substantial interest to me, living at 3800' ASL
at the end of XXXREDACTEDXXX Road, another windy, abrasive mountain road.
Many years ago I bought a new Honda CRX, and I was stunned when the tires
were worn out at just 3,000 miles! When I complained, the dealer said,
"You're not supposed to drive it so hard." Bah.
I've spent quite of bit of effort since then, and the last set of tires
on my Mini Cooper JCW lasted 50,000 miles. In large part, this was a
result
of things I'd learned in auto racing, see my recent race-winning video at
XXXREDACTEDXXX https://www.youtube.com/watch?v=XXXREDACTEDXXX.
In setting up a race car, we adjusted camber and tire pressure to get the
same temperature across the tread after several hard laps. If it was too
hot on the outside, more negative camber (or vice versa). Then if it was
too hot at the edges, raise the pressure to bulge the middle (again, or
vice versa). That process made the average tread essentially flat for a
given suspension setup, and lap times showed it. Of course our expectation
of tire life was dramatically different, but today I still use a variation
on these two techniques, and it's made a big difference.
I do essentially the same process, without the temperature measurement,
on our cars. Each car may have a different weight, drive wheels and
suspension design, but especially on front-drive cars I start the front
at the negative limit of factory settings, and go 1/2ø more if I see
excess wear on the outside. On some of our cars, we've had to install
conservative suspension mods to do this. Then I typically run +2-3 psi
pressure to keep the center working, and go even higher if I see too
much wear at the edges. Especially on rear drive cars, I'm more
conservative on the drive wheels, since they aren't steering.
But the same concept applies.
This optimizes the setup for the curvy, abrasive XXXREDACTEDXXX-mile road
we drive fairly vigorously every time we're going anywhere. Since the tire
wear is mostly from our runs up and down our hill, we don't find adapting
to this use makes much difference in traction or wear in the rest of our
driving on freeways or city streets. We're not racing, and we're not
looking for the huge show-off negative camber you see sometimes, just
enough to correct the car from general-driving setting to our primary use.
But 50,000 miles? Yep, the secret is a tire that sticks very well,
but has very high tread wear rating. I've settled on Michelin Pilot Sport
All Season (we get snow up here, and I no longer feel like swapping
seasonal tires). The tread wear rating on these is an amazing 540 with
still good wet/dry traction, and they're guaranteed for 45,000 miles.
Last, re reliable tire service, the jury is still out. I agree most
places don't pay enough attention. One I won't name tightened the wheel
lugs so tight I had to replace them, even though I told them the torque
I wanted, and had the torque wrench with me. If I find a gem, I won't be
shy.
I hope this adds to your discussion.
-------- End Forwarded Message --------
These cars are immaculately maintained. Bushings and all.
The alignment is not wrong (on almost all of them).
For a vehicle in flatland, for the wear patterns we are discussing, if the vehicle is properly maintained, the wear you claim is patently impossible (assuming the vehicle is well maintained & only drives typically on flats, i.e., they don't do 180's in the Las Vegas parking lots to wear the tires).
Am I wrong?
Performance tires? They
wear out quick. HIgh mileage tires? Lower traction. There are tradeoffs.
As you know, I'm well educated, so I know that statement to be false.
At least in terms of information printed on every passenger tire sold in
the USA.
But it's not really the point of this thread that I can find tons of passenger tires rated for high treadwear and also high wet straight-line traction, just as I can find passenger tires rated for low treadware and
low straight-line traction, and every permutation in between.
But that's simply because of the information printed on every USA passenger-tire sidewall is inherently insufficient to make any claims
that treadwear and traction *must* oppose each other.
In short, that's an interesting discussion for a different thread.
You
are obsessing over nothing at all. That's why I downgraded you to just another
quirky personality.
I'm different than most people on Usenet for a few reasons, one of which is I'm extremely knowledgeable, and part of that knowledge is gained by having an excellent memory on Usenet threads over the decades, where Zeno was instrumental in helping all of us understand, long ago, what's happening.
I'm also very different from many Usenet posters as most seem to treat it
as entertainment, and even fewer seem to have any education on the topics.
I'm also different in that I have access to my old Stanford and Harvard professors, which most people here wouldn't have that kind of contact.
In addition, I'm wired to the core to write helpful tutorials and PSAs as
I'm someone who cares deeply that others can do what I can do.
Whatever happened to nospam? He fell off the face of the earth. Is he dead?
There's a recent thread from this week about him.
Some say he was paid by Apple to deny everything bad about Apple on the iOS newsgroups, where when we pointed that out, he instantly disappeared.
Who knows what really happened to him, or David Empson (who truly
understood his stuff) or Michelle Steiner (who fought for the group to be included as misc.phone.mobile.iphone) or the Apple religious zealots JF
Mezei or Alan Browne (both of whom believed every word in every Apple white paper).
There's only Ant, and badgolferman, Chris and maybe we can include -hh,
left who have any sense. Although, the uneducated trolls such as Jolly
Roger, Alan Baker, Haemactylus, Joerg Lorenz, Snit, Rod Speed, and Your
Name still post.
Looking at your information in a clean light, I appreciate the distinction you're drawing that it's not failed bushings per se, but the designed compliance in them that lets the geometry shift under load. This is a much more subtle and convincing explanation than blaming worn parts.
On my K1200, I used Continental tires, but they wore out within 8K miles, but, as you are aware, beemer tires don't last as long as bimmer tires do.
I must agree that the "solution" may be more onerous than the cost of
simply replacing tires every year or two, but we can't make that
calculation reasonable without knowing what the possible solutions are.
1. 'Better' tires (in terms of sidewall stiffness and tire wear ratings)
2. 'Better' bushings (in terms of stiffness to geometric deflection)
3. 'Better' rotation pattern (in terms of X-rotation & carcass flipping)
4. 'Better' alignment (in terms of increased negative camber)
5. 'Better' maintenance (in terms of stiffer tires due to adding pressure)
Anything else?
Whatever happened to nospam? He fell off the face of the earth. Is he dead?
There's a recent thread from this week about him.
I remember that you and him used to squabble over Mac. I have no use for Apple
evangelists, but I did switch over, and to me I think he was right about them
just working, but I also understand why. They work fine for me, as opposed to
my Win science projects. There's no right answer.
Be careful in that in my decades of posting to Usenet, I have posted facts, and, when/if those facts were wrong, I openly and publicly corrected them.
Also note, that due to my scientific and engineering training, I don't fall for statements that nospam and the like would claim that are marketing BS.
An example is Android had 200% the RAM and Apple products had half the RAM but an "efficiency" of 1% that "supposedly" made up for the lack of RAM.
My point?
The absurdity of Apple's Marketing bullshit what we sparred over.
What nospam and I sparred over was his absurd claims for Apple products. Witness we sparred over the efficiency of Apple's crappy batteries, where
the very first EU benchmarks proved Apple's claims to have been a lie.
Fancy that.
Apple lied.
HINT: We sparred because nospam always propagated the Apple lies.
That doesn't happen on the adult operating system newsgroups simply
because nobody is gonna defend Google, M$ or RedHat to the death.
Chris wrote:
This *is* the dataset, for example, for the Moki Dugway GPX file.
<https://gpx.studio/app#14.41/37.27473/-109.93787>
No it isn't. That's an app. Provide a file that can be used reproducible by >> anyone.
OK. For the Angeles Crest Highway
Python analysis of abnormal front tire wear on windy US mountain roads
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads.
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads
in your community, I will run a python script (I just wrote) on those roads to predict the abnormal wear the front outboard tire shoulders will incur.
To limit the number of datapoints, since I'm running Python on an 2009 Windows 10 box, try to keep each road to less than about 10 miles long.
I've already run a half-dozen tests on my own local roads, but I want to
see how well the Linux/macOS/Win script works in roads elsewhere in the US.
Your Name wrote:
I've already run a half-dozen tests on my own local roads, but I want to >>>> see how well the Linux/macOS/Win script works in roads elsewhere in the US.Shafer Canyon
Moki Dugway
Burr Trail
Guardsman Pass
Simply driving on a road doesn't create "abnormal wear". Abnormal wear
on a tyre is due to incorrect air pressure in the tire, misaligned
wheels, unbalanced wheels, and/or bad driving (including doing wheel
spins, donuts, etc.).
Many people don't live in the mountains, but *everyone* who does, knows
there is abnormal tire wear on the front outboard outside tire shoulder.
A vehicle, perfectly aligned to OEM specs, with even a bit extra negative camber, and maybe even a few psi extra sidewall stiffening, will *still* experience abnormal tire wear, as compared to those who live in flatland.
The mechanism is dynamic tire loading and suspension geometry under
sustained cornering, particularly on steep mountain roads with tight, slow-speed switchbacks.
Several things contribute.
1. Lateral weight transfer: When negotiating a tight turn, vehicle weight transfers toward the outside wheels. The outside front tire carries a disproportionately large share of the cornering load.
2. Body roll and camber change: As the suspension compresses on the
outside, body roll and suspension geometry can cause the outside front
wheel to lose negative camber or gain positive camber relative to the road. This concentrates loading on the outer shoulder.
3. Steering angle and tire scrub: At very low speeds and high steering angles, the front tires experience considerable lateral deformation and scrub. This is especially pronounced in tight hairpins and full-lock turns.
4. Combined braking and cornering forces: Descending steep grades while negotiating sharp turns adds longitudinal braking forces to the already substantial lateral forces. The front tires have to manage both simultaneously.
5. Repeated exposure: Roads such as Moki Dugway, Shafer Canyon, Burr Trail, and Guardsman Pass can involve repeated tight turns, steep grades, changing road camber, and substantial steering inputs. Repetition makes the wear pattern more pronounced.
People who commute in the mountains have already tested this for decades.
On Nov 4, 2026 at 2:43:10?PM CST, "Your Name" <YourName@YourISP.com> wrote:
On 2026-11-04 15:18:48 +0000, Blaine said:
Maria Sophia wrote:
Python analysis of abnormal front tire wear on windy US mountain roads >>>>Shafer Canyon
I'd like to run a test of my Python code analyzing abnormal tire wear
under the specific conditions of steep short windy curvy US mountain roads.
If someone will choose about 3 steep windy curvy hairpin'ny mountain roads >>>> in your community, I will run a python script (I just wrote) on those roads
to predict the abnormal wear the front outboard tire shoulders will incur. >>>>
To limit the number of datapoints, since I'm running Python on an 2009 >>>> Windows 10 box, try to keep each road to less than about 10 miles long. >>>>
I've already run a half-dozen tests on my own local roads, but I want to >>>> see how well the Linux/macOS/Win script works in roads elsewhere in the US.
Moki Dugway
Burr Trail
Guardsman Pass
Simply driving on a road doesn't create "abnormal wear". Abnormal wear
on a tyre is due to incorrect air pressure in the tire, misaligned
wheels, unbalanced wheels, and/or bad driving (including doing wheel
spins, donuts, etc.).
Yep. He is calling the expected *rapid* tire wear "abnormal". If you drive a car aound a race track at its limits, where there is little difference from those mountain twisties, that's going to cause rapid wear, but it's expected, therefore not abnormal. And he didn't include in his list the make and model of any specific vehicles, and they all have different suspension components, which includes all the rubber and plastic parts that are the bushings. The alignment specs are important, but not all that has to be considered. Cars with identical specs but different soft parts will have different tire wear. When he started on this 20 some years ago, i think he referred to some Chevy or GMC full size SUV. The GM engineers knew about the tire wear thing, and did
not consider it abnormal, and the bushings had something to do with it on that
heavy vehicle. There are tradeoffs in design. Arlen can't live with that.
Bob West wrote:
Simply driving on a road doesn't create "abnormal wear". Abnormal wear
on a tyre is due to incorrect air pressure in the tire, misaligned
wheels, unbalanced wheels, and/or bad driving (including doing wheel
spins, donuts, etc.).
Yep. He is calling the expected *rapid* tire wear "abnormal". If you drive a
car aound a race track at its limits, where there is little difference from >> those mountain twisties, that's going to cause rapid wear, but it's expected,
therefore not abnormal. And he didn't include in his list the make and model >> of any specific vehicles, and they all have different suspension components, >> which includes all the rubber and plastic parts that are the bushings. The >> alignment specs are important, but not all that has to be considered. Cars >> with identical specs but different soft parts will have different tire wear. >> When he started on this 20 some years ago, i think he referred to some Chevy >> or GMC full size SUV. The GM engineers knew about the tire wear thing, and did
not consider it abnormal, and the bushings had something to do with it on that
heavy vehicle. There are tradeoffs in design. Arlen can't live with that.
I'm going to make a very strong point, so that people can LEARN from this.
1. Run the python script on your daily commute
2. If you're not SHOCKED (you'll have a heart attack!), I'll be surprised
3. Your commute, most likely, is child's play compared to mountain roads
The strongly held point I'm going to make anyone who claims to disagreewith what happens with mountain driving, needs to run the python code.
Just running it once, on their commute, will turn them into a knowledgeable person from a novice, since the road inherence is TREMENDOUSLY different.
For example, people who know nothing about the problem always bring up the drive train, but the drive train essentially has no meaning at all.
People "think" it does.
Because they don't understand the problem set.
People who have never studied the problem set, think the drive train would matter, and yet, the fact is, it doesn't. Not in the downhill direction.
I don't know why people don't understand, but I think they are thinking everything is flat, and when things are flat, drivetrain differences can
have a greater effect on tire wear than when we're talking DOWNHILL runs.
Most people have never driven on mountain roads day in and day out, so they have no idea that the similarities to flatland wear and tear don't exist.
In the argument above, Bob conflates conflating general tire maintenance
and suspension compliance with high-geometric-load cornering.
I realize I didn't emphasize this enough initially, but we are looking specifically at downhill driving on tight mountain roads.
When you're going downhill:
The drivetrain is almost irrelevant: The engine isn't putting power down to accelerate through the turns. Gravity and braking forces dominate. Whether it's FWD, RWD, or AWD, the front tires are handling the steering lock and braking loads entirely on the overrun.
Camber scrub overrides bushings: While soft rubber bushings, vehicle
weight, and alignment specs change the rate of wear or how a specific suspension loads up, they don't cause the primary phenomenon. When a 4.8-meter hairpin forces near-maximum steering lock, the contact patch undergoes severe lateral scrubbing. The tire is literally being dragged sideways across the asphalt under a forward weight transfer.
Semantics on "Abnormal": You call it "expected rapid wear" like a track
day, which is fair that if you drive a road with 600 hairpins, rapid wear
is the expected physical result. But for the average driver who just
visited Costco for the first scheduled rotation, seeing an outer tire shoulder chewed down to the cords while the rest of the tread has 60% life left looks and acts like an anomaly compared to normal commuting wear.
The road geometry itself is what dictates the high-slip-angle scrub.
The make, model, and drivetrain are just secondary variables turning the volume up or down, but EVERY passenger car in the mountains wears tires the same way.
That's why the Python script concentrates on inherent road metrics.
What did you get when you ran the script on your daily commute?
And what he fails to acknowledge is that the same things that increase
tire loads going down a mountain road, decrease those loads when you
travel up it.
They may experience MORE wear going down a road, simply because the
loads from braking and cornering my tend to be somewhat greater,
but on
the way up that road, those loads will be proportionately less.
On Nov 9, 2026 at 1:30:42?PM CST, "Alan" <nuh-uh@nope.com> wrote:
They may experience MORE wear going down a road, simply because the
loads from braking and cornering my tend to be somewhat greater,
I would change that to "will be much greater".
but on
the way up that road, those loads will be proportionately less.
That crossed my mind too, but I think it would be pretty close to the same, especially if you are taking into account all 4 tires.
Alan <nuh-uh@nope.com> writes:Believing that anything that "Maria Sophia" states as "fact" is in any
[...]
And what he fails to acknowledge is that the same things that increase
tire loads going down a mountain road, decrease those loads when you
travel up it.
Disclaimer: I know next to nothing about tire wear. My comments are
based entirely on what's been posted here and a bit of common sense.
Assuming your statement is correct, how sure are you that it
invalidates the claims? Suppose, hypothetically, that driving
down increases tire wear (relative to driving on a straight flat
road) by a factor of 5, and driving up decreases it by a factor
of 2. Then surely the result would be substantially increased
wear, by a factor of about 4.5.
I made up those numbers. Do you have better ones? Are you anexpert on the subject?
Are you asserting that driving on winding mountain roads *doesn't* substantially increase tire wear? "Maria Sophia" has described
drivers experiencing increased ("abnormal") tire wear on mountain
roads; are they making it all up?
On 2026-11-09 15:39, Keith Thompson wrote:
Alan <nuh-uh@nope.com> writes:
[...]
And what he fails to acknowledge is that the same things that increase
tire loads going down a mountain road, decrease those loads when you
travel up it.
Disclaimer: I know next to nothing about tire wear. My comments are
based entirely on what's been posted here and a bit of common sense.
Assuming your statement is correct, how sure are you that it
invalidates the claims? Suppose, hypothetically, that driving
down increases tire wear (relative to driving on a straight flat
road) by a factor of 5, and driving up decreases it by a factor
of 2. Then surely the result would be substantially increased
wear, by a factor of about 4.5.
I made up those numbers. Do you have better ones? Are you an
expert on the subject?
Are you asserting that driving on winding mountain roads *doesn't*
substantially increase tire wear? "Maria Sophia" has described
drivers experiencing increased ("abnormal") tire wear on mountain
roads; are they making it all up?
Believing that anything that "Maria Sophia" states as "fact" is in any
way related to reality is your first mistake.
Alan <nuh-uh@nope.com> writes:
On 2026-11-09 15:39, Keith Thompson wrote:
Alan <nuh-uh@nope.com> writes:
[...]
And what he fails to acknowledge is that the same things that increase >>>> tire loads going down a mountain road, decrease those loads when you
travel up it.
Disclaimer: I know next to nothing about tire wear. My comments are
based entirely on what's been posted here and a bit of common sense.
Assuming your statement is correct, how sure are you that it
invalidates the claims? Suppose, hypothetically, that driving
down increases tire wear (relative to driving on a straight flat
road) by a factor of 5, and driving up decreases it by a factor
of 2. Then surely the result would be substantially increased
wear, by a factor of about 4.5.
I made up those numbers. Do you have better ones? Are you an
expert on the subject?
Are you asserting that driving on winding mountain roads *doesn't*
substantially increase tire wear? "Maria Sophia" has described
drivers experiencing increased ("abnormal") tire wear on mountain
roads; are they making it all up?
Believing that anything that "Maria Sophia" states as "fact" is in any
way related to reality is your first mistake.
I know nothing about either of you. It seems there's a lot of
history. I'm delighted to be ignorant about it. I have no basis
for judging "Maria Sophia"'s statements -- or yours -- other than
what I've read in this thread.
I read comp.lang.python fairly regularly. When this thread showed
up, I found some aspects of it mildly interesting.
I've asked you a few technical questions about what you've written
here, and you've answered none of them. Even if your opinions
about "Maria Sophia" are accurate, I would think you could address
my questions.
As an outsider to this topic, I merely observe that even if tire
loads are increased when going downhill and decreased when going
uphill (and I have no basis for judging the accuracy of that claim),
that doesn't imply that the effects neatly cancel out, nor, as far as
I can tell, does it refute anything "Maria Sophia" has posted here.
Do you have any comment on that?
Bob West wrote:
On Nov 9, 2026 at 1:30:42?PM CST, "Alan" <nuh-uh@nope.com> wrote:
They may experience MORE wear going down a road, simply because the
loads from braking and cornering my tend to be somewhat greater,
I would change that to "will be much greater".
but on
the way up that road, those loads will be proportionately less.
That crossed my mind too, but I think it would be pretty close to the same, >> especially if you are taking into account all 4 tires.
Hi Bob West,
First off, Alan Baker is an uneducated Apple religious zealot troll who happens to have recently infested this thread, but notice that it doesn't matter, mathematically, that you drive DOWN in the morning, and then UP in the evening.
Think about it.
Think...
Think...
Think....
Do you realize yet why almost all the wear is on the way down or not?
You could drive five miles down and ten thousand miles up, and it wouldn't change the wear pattern.
So the fact you agreed with Alan Baker on the directional math is scary.
On 2026-11-09 15:44, Bob West wrote:
On Nov 9, 2026 at 1:30:42?PM CST, "Alan" <nuh-uh@nope.com> wrote:
They may experience MORE wear going down a road, simply because the
loads from braking and cornering my tend to be somewhat greater,
I would change that to "will be much greater".
Ummmmm...no.
That would depend entirely on HOW you drive down those roads.
but on
the way up that road, those loads will be proportionately less.
That crossed my mind too, but I think it would be pretty close to the same, >> especially if you are taking into account all 4 tires.
Nope.
If one argues that the downward grade increases loads, then how can the upward grade of the other half of the "commute" not result in
proportional decreases in the load on the tires?
On Nov 9, 2026 at 8:40:03?PM CST, "Alan" <nuh-uh@nope.com> wrote:Except for the fact that this is about TIRE wear.
On 2026-11-09 15:44, Bob West wrote:
On Nov 9, 2026 at 1:30:42?PM CST, "Alan" <nuh-uh@nope.com> wrote:
They may experience MORE wear going down a road, simply because the
loads from braking and cornering my tend to be somewhat greater,
I would change that to "will be much greater".
Ummmmm...no.
That would depend entirely on HOW you drive down those roads.
but on
the way up that road, those loads will be proportionately less.
That crossed my mind too, but I think it would be pretty close to the same, >>> especially if you are taking into account all 4 tires.
Nope.
If one argues that the downward grade increases loads, then how can the
upward grade of the other half of the "commute" not result in
proportional decreases in the load on the tires?
Because you are fighting inertia in either direction. A flat, straight road will have the least wear, and any uphill or downhill twisty road will have more wear. And please don't bring up straight downhill roads. They are irrelevant for our purposes.
On 2026-11-09 22:00, Bob West wrote:
On Nov 9, 2026 at 8:40:03?PM CST, "Alan" <nuh-uh@nope.com> wrote:Except for the fact that this is about TIRE wear.
On 2026-11-09 15:44, Bob West wrote:
On Nov 9, 2026 at 1:30:42?PM CST, "Alan" <nuh-uh@nope.com> wrote:
They may experience MORE wear going down a road, simply because the
loads from braking and cornering my tend to be somewhat greater,
I would change that to "will be much greater".
Ummmmm...no.
That would depend entirely on HOW you drive down those roads.
but on
the way up that road, those loads will be proportionately less.
That crossed my mind too, but I think it would be pretty close to the same,
especially if you are taking into account all 4 tires.
Nope.
If one argues that the downward grade increases loads, then how can the
upward grade of the other half of the "commute" not result in
proportional decreases in the load on the tires?
Because you are fighting inertia in either direction. A flat, straight road >> will have the least wear, and any uphill or downhill twisty road will have >> more wear. And please don't bring up straight downhill roads. They are
irrelevant for our purposes.
And if you "fight inertia" by braking in a straight line, you only wear
your brake pads; well, you certainly don't cause asymmetric wear on your tires.
But if going downhill leaves you with greater momentum approaching a
corner that you must deal with, then going uphill will reduce the
problem of added momentum due to gravity, right?
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