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Hmmn. If you assume that increased adoption still leaves us with a similar cohort of drivers traveling on a similar collection of roads with similar driving hab
by GCA10 10y ago
Hmmn. If you assume that increased adoption still leaves us with a similar cohort of drivers traveling on a similar collection of roads with similar driving habits, then this is statistically legitimate.
But each of those assumptions is problematic at best. It's a variant of the "Soldiers in Vietnam" problem. In 1961, the U.S. had 3,200 soldiers in Vietnam, and only 16 of them died. If straight extrapolation worked, you could infer that in 1968, when troop levels peaked at 536,000, we'd be looking at 2,680 deaths.
Actually, 16,899 American soldiers died in 1968. The mortality rate climbed 6x, because the war became quite different. American troops were exposed to all sorts of lethal situations that weren't part of the mix in 1961. Data is here
http://www.archives.gov/research/military/vietnam-war/casualty-statistics.html http://www.archives.gov/research/military/vietnam-war/casual...
http://www.americanwarlibrary.com/vietnam/vwatl.htm http://www.americanwarlibrary.com/vietnam/vwatl.htm
In Tesla's case, it's likely that a lot of the test miles so far have been incurred on California freeways or their equivalent, where lanes are wide, markings are good, rain is rare and snow is unheard of. Start moving more of the traffic load to narrower roads where nastier weather is common, and you're adding stress factors. Demographics change, too. The high price tag of Tesla vehicles today means that most drivers are likely to be in their prime earning/wealth years (let's say 35 to 70.) If the technology becomes more ubiquitous, we'll need to see how it performs in the hands of people of teenagers and the elderly, too. Once again, the risks rise.
- yummyfajitas 10y agoThis could be true. If so, their secondary metrics (e.g. # of near misses, avg distance to other cars, etc) should rise as Tesla use expands out of CA. Again, please note that all I'm saying is that the secondary metrics are the primary predictor here since they are statistically significsnf. The primary metric is just an order of magnitude check since we don't have enough data (note the width of my posterior) to do more than reject the secondary metrics if they are crazily off.