cellio: (sleepy-cat)
[personal profile] cellio

I-376, like many other highways, has those overhead digital signs that somebody updates with topical messages like "accident, right lane closed 1 mi" or "stadium parking exit 72A" or, when they've got nothing better to say, "buckle up -- it's the law". There are two of these signs on my commute that, in their default states, say "distance to downtown: N mi, M min". Which, while usually not especially helpful to me (I live five miles from downtown), is still more useful to me than seatbelt nags. (I always use seatbelts.)

This morning, while stopped in traffic near Oakland, I saw one of those signs update from "4 mi, 5 min" to "4 mi, 6 min". That was less inaccurate, but far from accurate -- I reached downtown about 25 minutes later. (This is all very unusual; two of three lanes were closed due to a bad accident. My commute is sometimes slow, but I don't remember the last time I was in stopped morning traffic.)

It got me wondering -- do the indicators on those signs update automatically based on sensor data or are they human-controlled? The fact that an update happened but didn't jump to a more-appropriate number makes me think that we're dealing with an automated system that only bumps one unit at a time. (I would hope that a human would have updated it to warn about the accident.)

Why would it be designed to only increment in single units? Or is it a bug? What are the inputs to these signs, anyway?

(no subject)

Date: 2017-07-25 08:14 pm (UTC)
kayre: (Default)
From: [personal profile] kayre
I don't know about those signs, but was fascinated to learn that Google maps give traffic data based on cell phones with location enabled.

(no subject)

Date: 2017-07-26 10:59 am (UTC)
dsrtao: dsr as a LEGO minifig (Default)
From: [personal profile] dsrtao
You disable the phone functions when it connects to the car's bluetooth system. You enable them for passengers by asking them if they are driving.

GPS can't help except by noting that the phone is moving at a speed consistent with a vehicle, faster than a pedestrian.

(no subject)

Date: 2017-07-26 01:11 pm (UTC)
dsrtao: dsr as a LEGO minifig (Default)
From: [personal profile] dsrtao
It assumes that BT is on because most people leave it on all the time. It assumes that the car has a BT interface because new cars do.

People use BT in their cars primarily for listening to music from the phone over the car's audio system, and secondarily for using the car's audio system for phone calls.

GPS plus other phones' GPS, and GPS plus map data, seems relevant?

Only if you are Big Brother tracking all the phones over an internet connection. Remember, GPS is a one-way radio signal from satellits not dependent on the Internet; any time you think "GPS tracker" you are thinking about an integrated system with map data, mobile data connections and active processing.

E.g. you could build something like that, and GPS would be part of the solution, but you can't do it all on a single phone no matter how smart it is. The phone knows how fast it is moving by knowing the time and a series of position updates; it might or might not have an accelerometer and a compass. It doesn't talk to other random phones in the area to find out if they are moving at the same speed, and if it did, every car in a traffic jam would be difficult to distinguish from the others...

(no subject)

Date: 2017-07-26 12:37 pm (UTC)
metahacker: A picture of white-socked feet, as of a person with their legs crossed. (Default)
From: [personal profile] metahacker
GPS's precision costs a lot of battery. There's an API to ask for location, and the more precise you ask to be updated, the more battery it uses. So most apps opt for a less-precise location and stitch it to road maps, assuming you're at a particular location.

Also, there are many spots where GPS doesn't work as well--it is, after all, relying on Signals From Spaaaaaace that can get blocked by buildings, other signals, weather, or nearby military installations...

(no subject)

Date: 2017-07-26 11:33 am (UTC)
hudebnik: (Default)
From: [personal profile] hudebnik
I can confirm this: cell phone location traces are one of the more valuable signals we use. If a lot of cell phones on a particular stretch of road are moving slowly west, but rapidly east, it indicates a traffic jam on the westbound side; if there are almost NO cell phones on a particular stretch of road that normally has lots of them, it indicates a road closure; etc.

Cell phone location traces are also used to convert addresses to locations. For example, an indoor shopping mall typically has one street address, but lots of entrances, some of which are loading docks. Fortunately, loading docks and public entrances have very different cell phone location signatures, so we can tell which is which.

Cell phone location traces can also tell us that there's something new on the map that wasn't there last month -- a new housing development, a new road, a new business, etc. -- prompting further investigation, e.g. a StreetView vehicle going there to get photographs. The photographs can then be automatically analyzed to determine (in conjunction with cell phone data and volunteer user contributions) what the new thing is.

All of which is one of the reasons Google developed its own phone operating system. I can only assume Apple Maps is doing the same things with iPhone location data.

(no subject)

Date: 2017-07-27 04:22 am (UTC)
hudebnik: (Default)
From: [personal profile] hudebnik
Well-traveled places are already in the database, for the most part, so a lot of the benefit of signals like these is in filling in less-dense parts of the map. But yes, the amount of information we have about a particular place correlates strongly with population density.

Conveniently, many of the people in developing nations skipped the whole land-line thing and went straight to cell phones, albeit perhaps one per village, so we actually have data for places like sub-Saharan Africa.

Sending StreetView cars to sub-Saharan Africa is indeed expensive (although we've got StreetView kayaks, and StreetView backpacks, and there's now annotated StreetView of the International Space Station. Not sure about StreetView camels.) And we can work with satellite imagery when StreetView is too expensive.

(no subject)

Date: 2017-07-29 06:28 pm (UTC)
jducoeur: (Default)
From: [personal profile] jducoeur
(Curiosity drives me to check) Sadly, no StreetView for Pennsic. But I am amused that Vlad's Pleasure Pavilion not only shows up on Maps as a "Nightclub", it has a five-star rating and four reviews...

(no subject)

Date: 2017-07-26 12:44 pm (UTC)
metahacker: A box reading "I am not a statistic! I am a free man!" (statistic)
From: [personal profile] metahacker
an automated system that only bumps one unit at a time.

That is...a bit of a jump in inductive reasoning. The systems have seemed to me to be very sluggish in updating, which makes me wonder if they're time-delayed. It's possible the sign subsequently changed to 25 minutes shortly after you passed it.

The ones around here, when they're not saying "USE YA BLINKAH!", are often hopelessly optimistic--I wonder if they're programmed to make people feel good about the traffic ahead, rather than provide accurate data. (And if you do notice the discrepancy, you get mad at the sign, not at your fellow drivers.) But this seems far to clever.

(no subject)

Date: 2017-07-26 10:36 pm (UTC)
madfilkentist: (Default)
From: [personal profile] madfilkentist
Maybe they saw this XKCD and were trying to avoid that effect.
XKCD Estimation

Predicting the future is hard

Date: 2017-07-27 10:00 am (UTC)
From: [personal profile] moe37x3
I work on technology that's parallel to the one you're describing - for urban rail. Many of the issues and the methods for getting data are different, but there are some fundamental problems that apply to all travel delay predictions. (Also, I've learned something about the road side of this stuff in school and at industry conferences.)

Predicting the future is hard, and all ETAs are inherently predictions of the future, with a lower bound set by various hard constraints but essentially no upper bound, because you never know what might happen between now and whatever even you're predicting the time of. Disruptions, such as an accident that blocks up the road, are especially troublesome because a) the time to clear the blockage may be dependent on too many exogenous and initially unknown factors to be reliably predictable with any useful precision, while b) that's when users especially want to see a prediction with useful precision, so they can make effective routing decisions. Whether there's a human in the loop or not, taking into account that there's a disruption and applying that knowledge to ETAs is a hard problem.

I would guess that the predicted ETAs on the variable message signs (VMS) are driven by automatic systems and not dependent on human input. Most likely, they are based on real-time measurements of actual speeds, flows, and possibly travel times (possible technologies discussed below). Those measurements are going to vary continuously, and changes in them will tend to lag the more discontinuous events marking the start and end of a disruption. So, an automatic system calculating ETAs based on them, especially if there's some smoothing algorithm to prevent momentary outliers from messing with the final numbers, will produce ETAs that creep up continuously after a disruption starts and then down continuously after a disruption ends, almost definitely more slowly than an educated human observer's guesses might change in light of knowledge of the disruption itself.

Technologies I'm aware of for automatic detection of traffic conditions:

- Induction loop detectors: These have been around for a long time. There's a rectangular loop of metal embedded in the road. Vehicles going over it induce a current, which is picked up by a sensor connected to the loop. It's possible to infer from that current turning on and off how many vehicles pass by in a given time and how fast they are going.

- Traffic flow cameras: Visual pattern recognition is good enough these days, I think, that computers can look at a traffic camera feed and determine flow and speed.

- License plate tracking for travel times: A camera at point A picks up when a particular license plate passed by, and then a camera at point B picks up the same license plate some minutes later, providing for a calculation of that vehicle's travel time. Do that across all the vehicles that go by, and you have live, real travel time data. There are, of course, civil liberties concerns with recording everyone's license plates, but I think they tend to implement such technologies with automatic dumping of the ID data. The thing about this is that while it gives you the exact units you'd use as an ETA, the measurement lags changes in conditions even more than point flow and point speed do, since you don't get a measurement of travel time from A to B until a vehicle completes that whole trip.

- EZPass tracking for travel times: Same idea as license plate tracking, except that you don't have to do image processing to identify individual vehicles; they identify themselves using RFID tags. Of course, this can only be used on EZPass-enabled toll roads, and the data may be biased by the fact that it only captures EZPass users.

Re: Predicting the future is hard

Date: 2017-07-27 01:39 pm (UTC)
From: (Anonymous)
I really don't know much about public perceptions on the traffic side, but where I live, people *love* to tweet photos of the train prediction signs showing something other than what they want. Some the time, this is not incorrect predictions but correct predictions of large gaps in service, which is immediately photographable thanks to the sign. Of course, unlike drivers, they can take such photos safely while waiting.

The nature of disruptions on rail is indeed different. You don't have nearly as much volume-based congestion, since every vehicle out there is, at least in theory, there because a schedule said it should be. (However, at junction points, where trains have to take turns going through, they can experience non-linear congestion effects if they're on high-frequency lines and even one falls behind schedule.) So, absent disruption, the travel times are generally less variable than those on the roads. On the other hand, when a single train breaks down, has accommodate a sick passenger, or has to stop for any other reason, nothing's getting by without crossing over onto the opposite tracks, resulting in significant, difficult-to-predict disruption in both directions.

Re: Predicting the future is hard

Date: 2017-07-28 02:27 pm (UTC)
fauxklore: (Default)
From: [personal profile] fauxklore
Seems to be missing traffic helicopters which are certainly still in use in my region. I live close enough to I-66 to hear them when I happen to be home at rush hour.

I think they also use the data to determine whether or not to permit driving on the shoulder lanes (which are normally rush-hour only, but do get opened up at other times).

Re: Predicting the future is hard

Date: 2017-07-28 02:53 pm (UTC)
From: [personal profile] moe37x3
Helicopters, phone-ins from drivers, police reports, etc. all provide qualitative notice of incidents starting and ending, but do they generate data that can be used by automatic ETA-generation systems?

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