Article 31NDQ Challenges to Automatic Enforcement: Q&A with Mark Hallenbeck

Challenges to Automatic Enforcement: Q&A with Mark Hallenbeck

by
Lizz Giordano
from Seattle Transit Blog on (#31NDQ)
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Bus only lane clogged with cars
Image: SounderBruce

Automatic cameras have been approved by the state legislature to monitor speeds, discourage drivers from running red lights and penalize cars not yielding to stopped school buses. But so far, they are not authorized to keep cars out of transit-only lanes by consistently ticketing offending vehicles. (A previous STB post explored the path to using automatic cameras in Seattle.)

According to Mark Hallenbeck, director of the Washington State Transportation Center, using cameras to enforce transit-only lanes is a much more difficult undertaking than it might seem and complicated also by privacy concerns. Here's what Hallenbeck had to say, transcribed and edited for clarity and length.

LG: What are some hurdles to using automatic cameras to ticket vehicles using transit-only lanes?

MH: Okay, so first the problem comes from the geographic problem of interweaving lanes. For example, look at Highway 99, which uses what's called Business Access Transit (BAT) lanes to solve the problem of how to make right turns across the bus lane. You don't want people to have to drive three blocks out of the way in order to come back around. The reality is, there's no good way to make a right turn across the (transit-only) lane and be safe. So the solution is, you let cars in the (transit-only) lane, so they can make right turns into the shopping centers. Then, of course, you want people - as they come out of those shopping centers - to make a right turn onto the street.

Once you allow that, now you've given permission for cars to be in that lane to make the right turns. The problem is now, is how far are you allowed to really drive in the (BAT) lane and can I (the camera) watch you long enough to actually determine if you are in fact a violator? You can't just say car bad, car fine. Determining what is a violation makes the technology much more difficult.

Unlike with school buses (with onboard cameras), where the technological opportunity to use a camera to catch (offending drivers) is really simple. The camera points in a particular place, and it's only on when the (bus) stop sign switch is on, and then it's triggered by something going by.

If you wanted to use the same kind of technology for the BAT lane, you need video versus photo.

LG: Which then can lead to privacy concerns?

MH: Agencies are highly reluctant to just capture video and this has been true from day one. Storing and dealing with video is brutally expensive, as the Seattle Police Department will tell you about body cameras. So the transit agencies kind of look at that, and say 'well" let's wait a little bit.' If you store it, it's accessible via the Freedom of Information Act, which means you have to be able to not just store it, but you have to be able to give it to people.

It's not just grabbing files and stuffing them on the hard drive, though even that would be expensive: video takes a lot of disk space. But it's also how do I retrieve the information and how complicated is that? And then, by the way, how else will other people use the video, if in fact they can get it through the Freedom of Information Act?

LG: Let's say the privacy issues using video were somehow solved: could cameras be used to enforce HOV lanes?

MH: For the most part, video and still images can't see inside a car. (Earlier in the interview, Hallenbeck said the angle of the windshield, degree of window tinting and location of the sun all influences the position a human eye or cameras needs to be located to see inside a moving car.) Human observers trying to look inside a car use their eyes to follow the car until the angle is just right so they can see in. But using video or still images tends to be a disaster for occupancy counting, because the camera is fixed at a particular location which means at any given time, the camera position is good for some vehicles and not others, which is not a way to do enforcement.

You can't use infrared (IR) either, because IR doesn't see through glass. So the technology they've been playing with is near-infrared. Near-infrared can go through glass and gets away from many of the problems that visible light has associated with glare. How accurate? It's in the high 80s, low 90s (percent) if carefully calibrated. Which is okay for indicating whether a policeman down the way should pull over a car to physically look inside, but it's not the same thing as writing an automated ticket.

LG: So we're pretty far from using cameras to catch distracted drivers and enforce the state's new distracted driving law.

MH: Not going to happen. Enforcement of that law is not what's going to make it happen. What will make distracted driving go away is the same thing that made drunk driving really drop, finally. And that is individual peer pressure and whether society accepts it, and right now society accepts it.

LG: What I find really interesting about cameras is the ability to reduce bias in ticketing.

MH: No, it just changes the bias. The bias becomes, well can I see in these vehicles but not those vehicles? That bias is quite likely different than if I pull over all the black people and I don't pull over the white people. But you'll see well inside everybody's cars who didn't tint their windows, and you won't see very well inside the cars of people who did tint their windows. So those technological problems will create biases in the data set that you have.

LG: Do you think manual enforcement is better to educate drivers, rather than getting a ticket in the mail?

MH: I'm not sure getting a letter in the mail has nearly the same impact as having an officer standing there. But I think the fine structure has a far bigger impact. So maybe the first fine is a warning, the second one is a fine, and the third one is a really big fine. I think that has much more of an impact. To me, that's a higher level of deterrent than whether there's a cop or a picture. The bigger deterrent is, what's the likelihood of you being caught and what's the level of social deterrence, whether that's the size of the fine or whether that's how people view you.

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