Unhappy Truckers and Other Algorithmic Problems

http://nautil.us/issue/3/in-transit/unhappy-truckers-and-other-algorithmic-problems

by bdon • 13 years ago

166 38 13 years ago

cinquemb3• 13 years ago

All of this makes me wonder: will business be the first to adapt to self driving vehicles, as opposed to passengers? or are there still significant legal barricades to impede either one now?

msrpotus• 13 years ago

Of course, you still need someone to actually make the delivery; even a self-driving car can't really give a person a package.

At least, not yet.

cinquemb3• 13 years ago

That is true. I guess it just made me wonder since he was going over how much trouble incorporating the human element into the equations is, and maybe trying to do without might be more practical (or maybe more predictable) going forward.

gizmo6862• 13 years ago

For consumer deliveries at least. However, (I suspect) much of the trucker industry goes to businesses, which would be much more willing to have an employee unload the truck when it arrives.

NicoJuicy2• 13 years ago

Actually, delivering a package is nothing more then someone who walks in the truck and using a QR-Code (smartphone) as authentication.

Or just let them put a NFC sticker on their smartphone to automate it more..

(Explanation is simple, execution is something else though)

PS. The only problem i really see, is making deliveries in snow (can't detect the road).

chiph• 13 years ago

How would a pneumatic cannon that launched my package from the truck at the curb be any different from the current driver who slings it from the driveway onto my doorstep?

dwild• 13 years ago

Self driving vehicle still need a conductor. It's not safe enough to have a vehicle that have no one to stop it. Metros, trains and planes have drivers even if they are doing nearly nothing. They are there in case of a problem (which happen too often...).

mikeash2• 13 years ago

Lots of trains have no drivers at all: http://en.wikipedia.org/wiki/List_of_driverless_trains

dredmorbius• 13 years ago

My strong suspicion is that it's going to be closed-loop and business-oriented services that adopt autonomous vehicles first. Deliveries within a factory or campus complex, people-movers, and the like.

Delivery in rural areas where there are long stretches between deliveries (so that loiter times and waiting for someone to come and receive a package isn't a large overhead), and the vehicle could page recipients in advance, skipping those who don't respond, or where deliveries are headed for depots (e.g., local warehouse or distribution center, food/grocery deliveries, etc.).

dyeje• 13 years ago

This was a really quality article. I wish I saw more stuff of this quality posted on here. Definitely checking this site out more.

tempcomment• 13 years ago

I agree, this article is really well written, and a lot of their content seems to be very high quality.

However, a word of caution - major funding for this magazine is provided by the Templeton Foundation, which is a right of center religious group. This magazine is very new, so it's hard to say what influence this has on their content, but it seems like a good thing to be cognizant of. After all, trust but verify.

Sources:

http://www.nytimes.com/2013/05/07/science/a-glossy-science-m...

http://www.slate.com/articles/news_and_politics/assessment/1...

pja• 13 years ago

The Templeton Foundation also funds a fair bit of fundamental research in theoretical physics and maths. I wouldn't write them off entirely!

drostie• 13 years ago

The only problem is MIT's news office; "roughly speaking, P is a set of relatively easy problems, NP is a set of incredibly hard problems, and if they’re equal, then a large number of computer science problems that seem to be incredibly hard are actually relatively easy." (It's wrong first because P ⊆ NP and second because it doesn't tell you what's really at stake here.)

I think you could instead say "Roughly speaking, P is a set of easy-looking problems, while NP is a set of problems which can be solved the hard way, by a brute-force search. If they're equal, then every brute-force-able problem is hiding some much easier solution." You could also add a sentence like, "Most computer scientists believe that this is wrong -- that sometimes you can't really improve on a brute-force search. But nobody knows how to prove that negative, it seems to require understanding everything which computers can possibly do."

In one paragraph you can explain the gist of P = NP, I think, to a lay audience. I guess many of them might not know what a brute-force solution is, but you might replace it above with "trying all the combinations" or so. (Hat tip to Scott Aaronson for an essential element of this explanation.)

jmduke• 13 years ago

While I think your definition is apt, I think you vastly overestimate the number of people who grasp the phrase 'brute-force search.'

gweinberg2• 13 years ago

This is just wrong. Roughly speaking, P is the set of problems that are easy to solve. NP is the set of problems for which it is easy to verify that a solution is correct. There are problems which can be solved by brute force but which are not in NP.

For example, the traveling salesman problem.

jules3• 13 years ago

Something doesn't add up here. The article says:

For each mile saved, per driver, per year, UPS saves $30 million.

Then at the end it says:

As for UPS, Santilli notes that a driver in Gettysburg, Pa. is now driving nearly 25 miles less per day, from an original route of more than 150 miles down to 126 miles—with the same number of stops.

So they are saving $30 million * 25 * 365 = $274 billion per year. However, UPS' revenue is only $53 billion. What gives? Is this driver in Gettysburg saving a very atypical number of miles, and the average number of miles saved with this system per driver per day is way less? It's a bit disappointing that they left the actual savings out of the article.

StavrosK2• 13 years ago

For each mile saved, per driver, per year, UPS saves $30 million.

Err, there's no way a single mile per year costs them $30 million. Looks like the $30m figure is the total savings, unless they're using gold, single-use robots that burn gold to push the gold trucks.

jules3• 13 years ago

They did say per driver. It's still a high number of course, but I don't see how you can read that differently? UPS has around 400,000 employees, so if 200,000 of those are drivers that number becomes $150 per mile saved. Still way too high, but not single use golden robots high.

aptwebapps• 13 years ago

Nice article. I would love to know more details about some of the specific examples, though. Like this one:

Yellow Freight used to have some 700 “end of lines,” Powell says, which are sorting terminals where cargo is transferred to its end customers. Powell developed a model that delivered a counterintuitive message: Trucks were traveling farther to get to the customer with so many terminals. Today, he says, Yellow Freight has 400 end of lines. “That was the right number,” he says.

I can understand 400 endpoints being more efficient for some overall process, but I have a hard time seeing how it could reduce miles travelled without some sort of unmentioned complexity (like sending stuff to the wrong endpoints through confusion). Or maybe it includes miles driven taking stuff to the endpoints in the first place? That I could see.

Unhappy Truckers and Other Algorithmic Problems

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