a signage mystery
Jul. 25th, 2017 03:00 pm![[personal profile]](https://www.dreamwidth.org/img/silk/identity/user.png){kind=small}
cellioI-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?
Predicting the future is hard
Date: 2017-07-27 10:00 am (UTC)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 01:05 pm (UTC)Is "why are the signs wrong" a FAQ in your industry? (For light rail/subway systems I assumed that they mostly weren't wrong, barring train failures -- limited access and you know exactly where the trains are right now -- but I haven't used such systems enough to have meaningful experiences.)
Re: Predicting the future is hard
Date: 2017-07-27 01:39 pm (UTC)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)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)