(Unedited) Podcast Transcript 572: Evaluating Congestion Pricing Year One

This week we’re joined by Stephen Crim, Director, Policy & Analytical Reporting, Central Business District Tolling Program (CBDTP) at the NYMTA. We chat about the MTA’s one year data report on congestion pricing including some of the results and how the data was collected. Stephen also discusses the numerous government data partnerships and enhancements including air quality monitoring and what other cities can look to in order to consider future pricing schemes.

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And those two things came together After college, I went to get a grad degree in planning and where. I really got the transportation planning interest is when I was helping to found a transit advocacy organization on the Gulf Coast. So shout out to ride New Orleans. And I really came to realize okay, transportation is this great realm in which to make our lives more sustainable, make our cities more sustainable, and supporting the fun and opportunity those cities can bring.

And so then. That took me to the DC area where I worked on encouragement based transportation, demand management programs to get people to bike, walk, take transit, and then I moved into parking and policy and management as a way to manage travel, influence, travel behavior. And I moved back up to New York and 2022 to work on congestion pricing, and it’s been quite a singular experience to be part of something like this.

Glad to, have it bring me to talk to you today.

It was in the ether. There were reports that would come out here and there it was academic conferences, like the Transportation Research Board, which I attended for a decade or so, but it was in 2019 when I saw the law that enabled the legislation pass. I got really excited and thought oh gosh, we can, like maybe this is gonna happen.

Maybe, hopefully.

I think the important thing to realize is that this report is a real partnership, right? And it’s a partnership between our team, our data science team at the NTA, the. The New York City Department of Transportation, New York State Department of Transportation. And so some of the data that you see in there has been collected for many years as part of data collection programs that predate this program.

New York City, DOT, for example, has done work with data coming from the taxi and FHV industry for, a long while. But I think the analysis and compilation dot. Started to come together in, 2022, even before I got here because pulling something like this together is a major achievement, a major undertaking.

even though it took a while from 2019 to program start, there was work going on in those years to lay out how are we gonna deliver this? What data and what measures, what things are we going to report on to fulfill our requirements? ’cause this is all the requirement of legislation, but. The legislature didn’t tell us, oh, measure this metric, or go out and get data on this specific thing.

It just said, report on these topics. So it’s been a long time coming. The system that tolls vehicles coming in to the toll zone, that of course got constructed or installed from the time we got the finding note significant impact in 2023 through 2024. And so that was one of the. Last data pieces to come online.

But a lot of this is us aggregating the work of many others who have been gathering data. Preparing data for many years.

I think that’s important. Obviously great, but I’m curious like how that comes together.

And I have that listed here to make sure I remember all of them. Traffic congestion in and around the zone, volumes and types of vehicles coming into the zone. Transit use and bus speeds, taxi and for higher vehicle use, air quality and emission trends and the money coming in and our expenses from the program.

But those are broad, right? So some of our process was just saying okay. What is readily available? What can we use? Because we knew that, we were gonna have this system tolling people or tolling vehicles coming in. So we would have data on those entries, we don’t have ready made these air quality measures.

And then with the. Federal Environmental Review, we made some additional commitments to the federal government as part of our process and that, I think one of the most complicated ones was setting up a partnership with New York City’s Department of Health to pay for enhancements and leverage their existing, really sophisticated air quality monitoring system around the city, because that was something where.

There wasn’t just some ready-made source. So we tried to find as many places as possible. Okay, what is somebody else already reporting? And that’s why I say, the data on this has been in process for years. We knew we were gonna be building this system and in a few cases it was just a case of a, okay, I guess we have to go out and do this data collection.

this is very fine-grained data and so I imagine that’s difficult in its own right, is trying to find something of a before and an after when you know, now you have more after data, but. The before data was very, sparse, I imagine.

I think New York is blessed with a lot of resources, but it’s still not as much as we may want. It’s also certainly not as much as I think members of the public think exists. So that’s a challenge. It’s like there’s this concept maybe because of our devices now and our connectivity thinking, oh, you must have counts of like just.

Everything out there and it’s no we don’t. And you have to be very careful about before, after comparisons. And that was really a lot of the time that went into the creation of this report. It was saying like, okay, we see before, after, but do we see a change because something really related to the program changed or is it like, oh wait, no, there was a change in that data source.

You need to go back. Yeah. And that’s the kind of difficult work that really took the involvement of these other agencies in concert with us who knew these data sources to produce the report.

obviously one day does not make, a month does not make the other months. And yeah, I’m interested in this hub data, for example, yeah. How did you set the baselines and things like that.

Have been doing this point in time survey of traffic into the section of Manhattan below 60th street, including the West Side Highway and the FDR Drive. They’ve been doing this for years and it’s a really wonderful longitudinal data source. And they take precau, they take measures to try to control for that Yankee game or something.

they try to find weeks when it’s not gonna be, some sort of major disruption. So it’s a really valuable product. You’re right. one of the things that this program has created is a new data source or a new granularity of data that we can refer to. And our baselines refer to the kinds of totals that we were seeing in recent hub bound reports, but we also had to use data from our own crossings, port authority crossings, and the bridges to try to then.

Extrapolate to the entries that would be coming in, not in October, like in the rest of the year because we know traffic is seasonal and so we wanted to make sure we were doing the right kind of comparison of a January after the program starts to what traffic would’ve been, But for the program, adjusted for the seasons.

We don’t yet have devices in everyone’s car, measuring how far they drive. we are glad to see that we’ve seen. Decreases in every month, 25 over 24. But yeah, there has been some variation in that. And of course, one of the complexities here is like entries is not the only thing that goes into VMT, right?

There’s also people leaving and then there’s also a. Driving around inside of it. So there’s certainly some things that, there’s like some distance between entries and then the resulting VMT, and we’re excited to keep gathering data to try to see what those estimated VMT numbers do relative to entries over time.

What does a typical weekday look like for folks coming into the cord?

The program started, we did notice that traffic on specific days of the week varies over the course of the year, and so we don’t really know what that was before the project started. But I will say that, what we can measure is that the speed benefits have been approximately, like 4%. On a weekday, 4% increases in speed, 6% increase in weekends.

and just for those who are very safety minded, I wanna remind everyone that we’re talking about starting from a very low base here, we’re talking about vehicles that we’re moving at say eight or nine miles an hour. the goal here is not. Dangerous speeds. We’re moving four to 6% over some very slow traffic.

And I just say though, because I think sometimes people have come in, especially, your listeners are all over the place, right? And they might be thinking in the context of a place where the starting place speed is not that low. And so a speed increase is actually a problem. But here.

Kind of facing a different situation and yeah, we’re very happy to see the bus speeds have also gone up and really, and reversed, years of decline. COVID, of course, everything was moving faster, buses were moving faster. But since then, it’s been on a downward trend. So we’re seeing this like 2% increase in bus speeds before or after the program that we do have good data on, because the MTA has been collecting information or data on its bus speeds for years and.

Those savings are great because as you may have seen in some of the hub bound reports and elsewhere, the vast majority of people coming into the toll zone, they’re on transit, they’re not driving, and so we have to remember the benefit to those bus riders.

there’s a little bit more for higher vehicles and taxis, but for the most part it was the same. And which is really interesting because of the amount of the mixed type of vehicles that there might be coming into the cordon, I imagine.

Go live is a term that we used internally, pre tolling data. and this is where hub bound, they actually grouped the data by. They grouped everything that wasn’t a bus into one. So this actually relied on some counts that we paid for over the years. you do notice some numerical differences, but given what we have available to us, we don’t wanna call it like some major change.

There could be some differences in the way the taxis and fhv. Like we, we had to have people actually go out. Identify visually, manually, what is a four hire vehicle? Which by the way, I’ve been saying that it’s basically Uber and Lyft in the city. those cars don’t have, they’re not yellow cars that stand out.

They’re passenger vehicles and they have special license plates, but so that requires a human to go out and check. So the difference between a human and our system, which is, recognizing license plates, there could be some differences. So we’re not calling it like some huge change in the vehicle mix.

we’re raising money for transit, we’re improving speeds for bus, passengers, trucks, drivers. We’re reducing entries. We’re reducing VMT and I, I think our. Chair said something about when this is like the clearest success, for a project of this size, it’s like a clear success.

I will say one of the things I was most. Interested in, I wasn’t so much surprised, but the area that I went in thinking I have, I didn’t really know what to expect was, the taxi and, Uber, Lyft trips because, there’s so many dynamics with that. There’s so many choices that are being made.

that program we. Specifically the MTA board adopted a toll structure that charges per trip, not upon entry. And of course, passengers pay that. So I had no expectations of what we would see on the other end. So I was actually surprised that we saw. Very small changes in taxi, Uber, Lyft trips or VMT in the zone, which is, what the per trip charge was meant to do that.

because it was about a. The environmental justice concerns of these people who work as drivers who are predominantly non-white and they, have had a lot of tumult in their industry over the past few years. So I was just like pleasantly surprised. It’s oh yeah, okay. So it worked out with very little change to that industry because I just was like, I have very little preconceived notion of what will happen with this program as it relates to taxis and fgs.

So Ubers and Lyfts are charged a dollar 50 for each of those. And our yellow taxis. Green taxis, and then our other like black cars, they pay 75 cents per trip. Who passengers pay 75 cents per trip on those.

Have you been noticing more crowding, more ridership, those types of things?

Of course, kept service going for our essential workers ’cause that was critical. even with these longer term increases, we did see differences where, we are seeing increases in buses serving the zone that were, about 8%, much greater than we were seeing in terms of bus ridership change on services that didn’t serve the zone, that don’t serve the zone.

Similarly, we saw higher increases from 24 to 25 on trips into the CRZ than we did in the prior year. So we think that while of course this is all part of a longer trend of increasing ridership, there is something different going on and we think it’s in part because, speeds have improved.

I, feel like the general comeback is on its way here in San Francisco, at least we have seen that as well, where there’s more and more people coming back, back downtown. The ridership is increasing, albeit slowly. Commuter ridership is a little lower, the general ridership for some of these lines that just cross the city and don’t touch downtown have been maybe even above pandemic levels.

It just depends on the route. So it’s interesting to see how that all works together and what you can basically say that, pricing has done versus What was already happening. It’s always hard to tease that out,

I will say though, this is a great opportunity though to say that there’s so much interest in this program and its impacts and so we’re glad to see researchers from universities think tanks. All publishing their papers. And somebody told me about a conversation at the Transportation Research Board where a researcher is using some very sophisticated procedures to isolate the change in ridership separate from background.

And so we’ll look forward to seeing what that paper has to say. ’cause there’s plenty of work to be done around this topic.

And also there’s been discussions in different places around the city. Couple, a couple weeks ago, my friend, yo Freemark, you might know yo, we do our annual prediction show. And so Every year we predict what might happen and what might not happen. And, one of the things that we had predicted for the previous year was that a lot more cities will be thinking about pricing.

that one didn’t necessarily come to pass last year, but it might come to pass this coming year because I feel like the discussions are bubbling and they’re, starting to percolate a little bit more than maybe they were, because people were waiting and seeing what was gonna happen in your neck of the woods.

I will say I did not skim, I went through.

we’re also working with the city, by the way, and the state, DOT. Because we’re trying to collect traffic data alongside these air quality monitoring locations. But you know what we have found? In the preliminary results that we released in January was, basically no change from the year prior, though there were some, we did notice some decreases in pollutants in the.

Toll zone, but not enough yet to say that’s not just due to chance or some other factor. And so, far we’re not seeing indications of changes in air quality. We will be reporting more later this year after the team’s been able to analyze a year’s worth of after tolling began data in comparison to before tolling data.

so you know, that’s a very exciting upcoming project for us.

Carpeting the whole Bay Area. And so you can, at any time, you can see the air quality from a 10 minute period on. And there’s obviously, people have done research on them and see how accurate they are, et cetera. Yep. But I’m curious how that contrasts with say the EPA sensors or the public health sensors that you all are looking at.

’cause they are obviously fine tuned and specific for what they’re looking for.

But what New York City Department of Health really brings to the table is what they term is like research grade. Sensors that collect information on particulate matter, ozone, nitrogen, oxides, you know the major criteria, pollutants that you know of, concern for health, and they provide them, like they have somewhere around 100 sensors around the five boroughs, which is.

Much denser than you’ll see from the sensor network that feeds into the EPA sensor network. And they’re just designed for different purposes. The city laid this out as we wanna see information about air quality at the neighborhood level. So they, I think, are a great resource where, there’s the ability to distribute them geographically in a way that.

Captures entire neighborhoods. It’s not just based on, who decides to buy one and put them up near their home? yeah, In that sort of way, they have a good network. And then what our program did is we paid for increased sampling frequency at some of those locations in. Low income and minority communities that had burdens of pollution and chronic disease related to pollution before the program.

And then we also used funds to install real-time pm particulate matter sensors in a few locations as well. And we’ve been happy to see people using data from those as well in their other publications.

There’s a lot of stuff on like where the money’s going, including electric buses, power upgrades. Yep. Mitigation for environmental justice communities. There’s a lot of that stuff and the revenues are going towards a lot of these things, and there’s a lot in the report about that. So I won’t ask you, but I will point people to go there and check out what the money’s going towards and those types of things.

And my last question for you is. Is there anything we should look for, coming up in the next two years specifically that you’re watching for? And then also what is the way that people can take this report and use it if they wanted to, do this type of thing in their own place?

Next two years. I think some of the other things to just to highlight what we’re doing with, the money is you, the sig I think you maybe mentioned signals, but that is like a big one. Signal upgrade so we can run trains closer together faster. That’s like a, wonderful piece of what.

This program is paying for, in terms of the next two years, in addition to what you’re actually gonna get out of it, your new trains on the railroads and so on. for reporting, what I can say is like we’ll be releasing some additional dashboards in the next few months on, All vehicle, VMT, greenhouse gas emissions, and then also taxi and F-H-V-V-M-T.

So those will be coming. we will have later this year a report on air quality. We do have another big report, like the one from January due in January of 2028. At this moment, we are very much focused on those initial, deliverables that I just talked about, especially the air quality report. the report is already.

Just one of many, reports that we’re putting out. We’re putting out open data sets, we’re putting out dashboards. You see us quoting stats in other communications, so I’m sure there’ll be more to come. That’s just not even on our agenda yet. And in terms of what to do with this report? I do think that it makes for some good quotable numbers, of course.

Numbers are only part of the battle or the part of a strategy for anything or any conversation. So I think there’s a lot to be done for anyone else to, think about how their city is different from New York, but to say at least this is something we can start with. This is like a reference point.

Like in New York they saw this, so let’s. Start the actual conversation estimation about what that might be here, because, even on the fastest timeline, these sorts of things take a while. And so really at this point right now, I think it’s like you’re, using this as a starting point for discussion.

But. if you just type in CRZ tolling or CBD tolling program or C-B-D-T-P-M-T-A, you’ll find us, we have really good search engine optimization.

Alright. And Steven, where can people find you if you wish to be found?

And, if you find a Steven J Crim or Steven Crim that works at the MTA, that’s me.