Coffee with a Researcher 4: The Future of ATRAVEL (Text Version)

This is a text version of the video for Coffee with a Researcher 4: The Future of ATRAVEL presented on April 27, 2023.

CASS: And now I will pass things over to Joanna Allerhand.
JOANNA ALLERHAND: Thanks, Cass. Hello, everyone. My name is Joanna Allerhand from the National Renewable Energy Lab. And I'm filling in today for Lauren Reichelt. Thank you for joining us. This is the fourth webinar in the EEMS Coffee with a Researcher webinar series, which is part of a larger effort to better connect the US Department of Energy's EEMS Research with Clean Cities Coalitions. We want to open lines of communication between coalitions, their stakeholders, and researchers working on EEMS efforts at DOE.
These sessions highlight available EEMS tools and insights, and help coalition directors identify local and regional partners and projects that might benefit most from these capabilities. We want this webinar to be conversational and provide an opportunity for our featured researcher to ask for input from coalitions, and for coalitions to ask questions as well. So we will have ample time for discussion today. So please collect your questions throughout the presentation. Next slide.
We are also undertaking some additional efforts to connect clean cities with EEMS. NREL is currently seeking coalition directors that plan to or are interested in attending the virtual DOE Annual Merit Review in June. This is an opportunity to learn about the state of DOE's EEMS research and help us gather insights on the opportunities and challenges coalitions face around EEMS.
Coalitions can receive $500 to attend EEMS sessions, document their observations, and share them with NREL and the Clean Cities Network. Please reach out to Lauren Reichelt if you are interested in participating or already plan on attending. And Cass dropped Lauren's email address in the chat.
We are also in the process of finalizing a series of EEMS educational and outreach materials for coalition directors, staff, and stakeholders. There will be an EEMS brochure and model presentation to share with your stakeholders, a clean cities university course, and an informational resource on how to start partnering on EEMS projects. Those materials will be published soon for coalitions to use.
With that, I want to introduce our featured researcher for today's webinar, Andy Burnham. Andy is a principal environmental scientist at Argonne National Laboratory, a US DOE lab. His research focuses on transportation, energy, and environmental issues, specifically with the energy use and emissions analysis for advanced vehicle technologies and transportation fuels.
At Argonne, Andy is most known for developing the Alternative Fuel Life-Cycle Environmental and Economic Transportation Tool, also known as AFLEET, for coalition stakeholders to estimate petroleum use, greenhouse gas emissions, air pollutant emissions, and cost of ownership of light duty and heavy duty alternative fuel and advanced vehicles. And I'll hand it over to you, Andy.
ANDREW BURNHAM: Thank you so much for this opportunity. I have presented on ATRAVEL before, but I'd like to use this as an opportunity to talk about the work we've done in the past, and then open it up to– be interactive, as was mentioned, to, kind of, get feedback because I think this is an area for clean cities that I know many of us are still trying to find the correct paths to work in.
And as lab staff and supporting your work with technical resources, we want to be able to find and provide ample and relevant work and tools to use. So getting your feedback is really, really valuable, and I think this is a good opportunity.
So I believe you should be seeing my slide deck now. The future of ATRAVEL. So we released ATRAVEL last spring. So it's been out for a year. And after that work, we've kind of transitioned to working more on AFLEET and updates on AFLEET. So we are hoping to continue to make updates. We haven't changed anything since the initial release. So I'll talk a little bit about where the tool is and where we're going, and then kind of try to get as much feedback as we can from you all.
So we're going to start off with a couple of questions. And I'd like you to use the chat to answer. You can just put yes/no for this first question. Who has used ATRAVEL? So just in the chat, you can go ahead and drop a yes/no. I want to see where people are.
So I'm seeing nos. Decent amount of nos. I'll give it a second and see if anybody else wants to chime in. Yes or no? The next question after that– we got one yes. Let's– OK. We got one. I love ATRAVEL. All right. Great.
So the folks who have used the tool, how have you used it? What feature do you use? What is the purpose of using it? Maybe this will help give an example to the other folks on the line who– transportation and energy burden. So some of the mapping capabilities.
So I'll talk– and if anybody else wants to chime in, we can chime in. But I'll go over some of the capabilities we have on the tool and what Peggy is talking about. I don't know if people see, like, the chat opening, like, on the screen or if that just is on my side.
And then I'm going to do the one last question. And I guess I'm picking on Peggy here. What has or has not worked well? So I think any feedback on that is going to be really useful, too. And I think any of our tools, I'd like to put that out there. So you guys don't see the chat.
So whenever we develop a tool or resource, any feedback, constructive not constructive, is appreciated. We really, really want to hear back from you– the work that I do, because maybe I'm a little bit different than maybe some of the other presenters in this series is that I work with clean cities primarily. That's– a large part of my work is directed to this effort.
So hearing back from the directors and the coalitions, just in general, about how we can help you or your stakeholders just makes our work more relevant and can hopefully be more useful. So Peggy in the chat mentioned, seeing more granular info. And so we might– I might ask you a little more detail on that. I think I have some idea.
So we'll kick it off into the presentation now. Thank you, everybody, for talking in the chat or replying in the chat. I'm going to have a couple more questions, so please feel free to drop those answers in the chat. Next.
So I know a lot of you haven't used the tool. So I want to introduce it and, kind of, explain what the purpose of the tool was when we originally designed it. So I didn't ask, like, how many people have used AFLEET. But AFLEET is a tool that compares the costs and emissions of fleet vehicles– comparing conventional fuels versus alternative fuel powertrains. And the name AFLEET is meant to, kind of, signify that this is a tool for fleets to examine their choices with vehicles.
With ATRAVEL, the idea behind it was thinking about a more consumer-focused tool to examine some similar metrics like costs and emissions, but also think about travel time, because that's a really important factor when we're thinking about different modes of travel. And so the overlying question that we came up was, we have a predominantly private vehicle ownership model.
A lot of people own their own vehicle, and that's how they get to and from the places they need to go. But there are other modes, with transit and ride hail being two examples of other modes to be able to get around. And we wanted to be able to show how these different modes compare for cost, travel time, and emissions.
And with that, we tried to dig into that to understand for individual choices or more regionally. So the two levels that I just mentioned are consumers who are looking at maybe specific data. And this was, like, the original idea of the tool, is that using your own information. Like I travel from my work or from my home to my work four or five times a week. And then I travel a few other places this many times a week. I could get a sense of what the travel time and, ultimately, the costs in greenhouse gas emissions were based on a bunch of specified data from the user.
And then as we were trying to think through how to support clean cities beyond maybe a real consumer-facing tool is, like, what kind of data could we provide that builds on the work that we're doing in AFLEET and then kind of expanding on to examine these emissions and cost factors at a regional household approach?
So when we think about the impacts for cost, and travel time, and greenhouse gas emissions, really, location, like where you are, will be a really important factor on what modes are available. The distance, your travel patterns, even that kind of builds into it. What are your travel patterns and VMT, as vehicle miles traveled? So how much are you traveling?
If you're in an urban location and you have a lot of transit options, that your options to get around are different than if you're in a rural area, and the distances between locations are requiring highway travel and so forth and long distances. And then, again, flows into the mode availability. Is transit available? Is ride hail available? What are the passenger loads?
This is something in ATRAVEL we include. And it's maybe, kind of, sometimes a little bit under the radar of, like, when we're thinking about passenger travel. But we know single occupancy vehicles, you're moving around one person from point A to point B. But if you are able to increase the passenger loads for a specific car or trucker, that will improve your emissions per person. But same thing for transit and ride hail that passenger loads are really important.
And then a lot of the factors that we think about for AFLEET are efficiency. And so thinking about how efficient each of these vehicles are because a small car efficiency is going to be different than a large pickup truck. So I'm going to walk through how you use the tool.
So I kind of mentioned there's kind of two approaches. One is called the Trip Tool. And that's what I'll talk about here. And then I'll talk about the Metric Tool next. So the first step is the user enters their most common trip or trips via Google Maps interface. So your origin and destination. Here I'm kind of in the example. And I'll show that where I start and where I go to work.
And then the next step that you can do is slide or enter, like, additional mileage. So say you just want to do your daily commute and you only want to focus on that because you don't want to enter all the miscellaneous trips you take throughout the week or throughout the month or throughout the year. You can enter those, kind of, either, kind of, saying that's a daily trip, it's a weekly trip, it's a monthly trip, or so forth. But that can be somewhat tedious to do that travel trip diary.
So you can just, kind of, add a slider and say, OK, I drive another 2,500 miles per year, kind of, beyond the, kind of, daily commute that I normally do. We also have some capabilities to save and load trips so that when you come back you don't have to enter them again.
The next is your vehicle. So just entering your make, model, and year. This is something we need to update in the future, because we released it last year and we need to update with the vehicle types and make some models. What we see that is different than some of our other tools is that we have used cars. So we have estimates of the cost of a used vehicle versus a new vehicle as well. So we're going to provide some better data in our next release on that.
And then that's it for the Trip Tool. It's meant to be consumer-facing, really as simple as possible. Though, like, if you know some of the work I do, simple as possible is not maybe my forte that I like to provide a lot of the details. And so in the screen you see here, you see the overall results. And you see this which one has higher or lower costs, travel time, and emissions. But then you can see some of the key factors underlying these calculations on the left hand side. And you could tweak them to say if they don't represent the scenario.
And the one I mentioned before was vehicle occupancy. So we assume, kind of, a national or, yeah, like, kind of, average vehicle occupancy. And it might not be for your case. You see in this example, it says 1.5. Your trips might be just one person. And that's going to change your– it's going to change your emissions. That's where it's going to drive per person very significantly. And then you can go through that for the ownership, the transit, and ride hailing if you wanted to.
The next thing is that there's little scroll bars. And you can see in a little bit more detail about what breakdown of the cost is, what percentage is depreciation, or maintenance repair, or fuel costs, and so forth. And that's for each of the different mode types that we're comparing– private vehicle ownership, transit, and ride hail. And there are some additional resources and we link to Clean Cities and so forth there.
I won't spend a ton of time going into the details of where the data comes from, but we have a methodology page, and we provide a lot of that information. But we're basically trying to collect information on vehicle cost of ownership. For public transit, there's a transportation fare database that we rely on. And then there are resources to get for ride hail– what the fare estimate is for specific trips, and if there is, like, a ride hail available in your specific location.
Travel distance and time by mode. Some of that comes straight from Google Maps. So that's, in general, pretty straightforward. We have some additional information on– we provide an estimate of like, what's the average person travel in your location. So if you are entering just like one short trip, by default, it can provide an estimate of, like, the average person travels another 3,500 miles. So we provide that type of information.
And then for the emissions data, we're relying on AFLEET. And then we have specific information on fuel economies for cars and trucks. And then we have data on what is the transit mix in your location. So estimating, for transit buses, what's the mix of electric vehicles or biodiesel hybrid and so forth and getting an estimate of the, kind of, grams per mile for this example, a transit bus travel.
So we're going to go back to the chat. And I'm going to ask a couple more questions. And feel free to come up with whatever thoughts you have here. But what are some issues– for clean cities, directors, or stakeholders, what issues do you really focus on related to consumer education of personal transportation? Is that something you work on at all?
I mean, you can just kind of say, no, we're not doing anything on transit or using micro-mobility or anything, kind of, in this space. So I'll, kind of, stop, let you drop in the chat. And I think I should be able to– yeah. Sorry. You should be able to see in the chat message here.
So I see one from Peggy. Depending on the group, focus on cost savings and time spent for rural areas. Yeah. Yeah. That's great. Yeah. So cost. Cost and travel time. Two things that we think about as well. I'll let– if you guys have other things, please drop it in the chat while I'll move to the next thing. And I'll keep this open just in case.
So some of the things that we're going to work on related to updating the data is looking at regional costs of ownership. So having better data on what car maintenance, insurance depends on the area. We need to work on our updated transit, ride hail costs, all the greenhouse gas emission data.
And then I mentioned too, we need to improve our estimates of our used vehicles. Right now, we only have five, six years of used vehicles in the tool. So we want to expand that out to 15 years of used vehicles to better represent what a consumer might be driving.
I see another comment. Need to add older vehicles in the list. Yeah. OK. Yeah. We have a lot of older cars, trucks. Yeah. So that's good. Thank you. Yes, that's something that we are working on to better represent used car cost of ownership.
Something we spent a lot of time on thinking about– we haven't worked on fully implementing it because there's some data limitations and so forth. But working on micromobility, thinking about e-scooters, e-bikes, how those can potentially roll into an analysis. And I'll talk about that in the upcoming bullet here.
Thinking about car share and carpool, adding that as a potential mode and analysis capability. And then, kind of, rolling those things into potentially a combined use of different types of modes to compare to potentially just driving. So you could imagine maybe this is more urban-focused where, OK, I'm not going to own a car but I will use–
I think I saw just added in the chat, talking about walking or biking for some of my short trips. I may use transit and ride hail for other trips. And, kind of, do a combined analysis that's more mixed mode and would more represent, kind of, like– if you traveled only by this specific trip by using transit, it would be this. If it's using ride hail, it would be that. And if it's using a car, it would be this other thing.
So, yeah, the comment is, could you add walking as a mode in what one would save if walked versus other modes? So, yeah, like walking and biking, there are some tools that kind of do that. And oftentimes, what's the emissions of someone who's walking or what's the emissions of someone who's bicycling without an e-bike? And you'd say, kind of, zero, roughly.
There is, like, calories. Like, people can look at that kind of analysis. Like, OK, you're going to burn some extra calories because you're walking or you're bicycling there. So you need to eat a little more food. So that doesn't– it's hard to say. Like, well, is that the exercise I should be getting otherwise or something like that? So that's one we, kind of, left off, like, for walking.
But we could imagine avoided emissions, what that would be. And so I think we do want to consider that in this idea of, like, well, I might walk for my very short trips and I might bike in slightly longer trips. And what are the emissions just to be able to see that, whether it's zero or very near zero compared to driving a car?
Something else that the Clean Cities folks had mentioned that we still need to think through how that would work is kind of a fleet pool car analysis. So imagining if there is a fleet pool car what the benefit, potentially, would be of maybe subsidizing transit or even using ride hail on either cost or emissions and travel time, all of the metrics we think about. What would the difference be?
I'm going to add– one more question for this slide are, kind of, what modes, features, data will be helpful to Clean Cities directors or your stakeholders? I'll give you a little time to think that one through. And you can feel free to drop that in the chat while we move on, if it takes a little bit to think that one through. Or you can email me, too. I think we'll probably provide information about that.
So if you're a person who's watching this presentation later on and have some ideas, or if you, the folks who are on the call right now, are thinking about it as you maybe go and play with the tool a little bit, please feel free to reach out. Really, really try trying to get more thoughts on the travel modes, any features, or any specific data that's going to help.
I see emission saved from walking and biking, multimodal trips. Yeah. Those are some of the things that we've been thinking about. So, yeah, that's good. And then if anybody else has additional thoughts, look forward to hearing from you. I'll move on to our next slide and tool.
So the first bit of ATRAVEL is this consumer-facing tool. The next portion of the tool is our metric tool. And so this was meant to be, kind of, a simple way to represent regional cost, travel time, and emissions using a lot of the underlying data that we worked on for the consumer-facing tool. And then thinking through what other kind of data that we could rely on to provide this information to potentially use it as a screening tool as well.
So the first step and for the metric tool is entering your location. You see I'm entering Chicago, Illinois in this example. The next is selecting a geographic area. So we start with census tracts as our default. So if you enter Chicago, Illinois, in this example, it's going to go to Google Maps. And there's going to be a specific point where Chicago, Illinois, specific address, I should say. And that's going to be in a certain census tract.
So you could picked a more– more specific address is beneficial if you're going to look at that. Otherwise, you could enter something like a zip code and so forth to, kind of, get that broad area. Next is you have the capability. Because by default, it goes– like, the results in this tool are going to be census tract. So you can hit the dropdown and then choose, kind of, a more broader geographic area.
So you can go to a zip code, municipality, county. And then some of the census has a core-based statistical area. So Chicagoland includes actually parts of Wisconsin and in Northeast Indiana as well. And then the coalition. So this was meant to provide that information for a coalition to, kind of, aggregate the data within that. And I'll talk about some of the capabilities that we have there to, kind of, see a distribution of information.
We do need to make sure we're updating for our next release of the coalitions because Chicago ended up being for the state of Illinois now, and that might be the case for other coalitions as well. And then finally, the state too.
So with that, you pick your area. Then, which metric do you want to look at. And so we have several, kind of, default metrics to look at following the lines of what we've been talking about– vehicle cost, greenhouse gas, emissions, travel time. And so thinking about– I can talk about the methodology underlying this. But basically, kind of, the average travel of a household– what their cost, emissions, and travel time are.
We have some equity factors. So we've calculated household vehicle burden. So this is basically our work on vehicle cost of ownership divided by household income. And then there are some other equity factors that you see in many of the other screening tools, EJScreen, and things like that, minority percentage, low income, older population.
Similar air quality metrics that are based on EJScreen– diesel particulate matter, fine particulates, and ozone. Just so you are clear, like, diesel particulate matter is meant to represent vehicle, I guess, in general, diesel emissions, diesel particulates. While PM 2.5 is a broader representation of fine particulate pollution in the area. So they are two different things. And then ozone as well.
And then we have a capability. So there's a dropdown on the left and there's dropdown on the right. And you can add, kind of, an optional screening variable that's going to remove census tracts that aren't in that area. So basically, one of the things we have here is like a disadvantaged communities overlay, which would, kind of, show only the disadvantaged communities, or we would show maybe only the areas that have a high percentage of minority population in the census tract, and so forth.
And then after that, you can view the map and then also the metric data on the left hand sides. We have a histogram of the metric distribution in the area. So basically, what region you chose. So I chose the municipality of Chicago. That compares for this metric to the state average, and then also to the national average.
And then within the next bar down that, the distribution we see, like, of the census tracts. Like, what percentage are in the first quartile, second quartile, third and fourth quartile. So you could see kind of where, potentially, like– how the distribution of those averages. And then that, kind of, provides us that analysis for different levels.
And then we have some other household vehicle metrics where we kind of do this min/max quartile comparison of– in this area, what are, kind of, on a national type average, like, where are you? Are you on the lower side of vehicle miles traveled or are you on the higher side of vehicle costs, and so forth. So it kind of helps you understand where the vehicles and the travel in your area are related to more national average at the national average.
I will again quickly go through this. We have a lot of data underlying this, and some of it's pretty similar, like the total cost of ownership, fuel price data, and other things kind of underlying that that represents what vehicles– I think one of the important things to mention, and what we see in this chart, is thinking about what types of cars and trucks are in a specific location.
As we all probably know is, as the US and in many, basically every single state, less and less cars are being purchased, more and more light trucks, SUVs, and light trucks are being purchased. So, kind of, that regional fuel economy really plays a very important part on the regional emissions of the vehicles.
And so if you're in a rural state or in a rural location and you have more pickup trucks, the emissions are going to be higher for the efficiency reasons. And then also the travel distances. If you're traveling further distances. So those are important factors. And we have that underlying the calculations that we're doing.
Same thing, kind of, the travel time. What's the average speed of trips in different locations and things like that? So we have some estimation of that based on the National Household Travel Survey. And then similar to what I discussed before, like, what are the greenhouse gas emissions? That's really going to be based on some of the things I just talked about. But those miles traveled, how much is our vehicles traveling in an area?
And you can see in this chart, these areas in red, that's where maybe more rural, more spread out areas they're traveling, kind of, more distances on a household basis than some other states that may be a little more dense. But that states are diverse and that, of course, and so it often is urban versus rural locations even within a state are important to understand.
And then the household vehicle burden metric is something I mentioned is something we kind of developed ourselves. Just basically looking at household vehicle costs divided by household income to estimate how much of your income is going to owning your vehicles. So I'm going to finish up here with some updates.
So we've talked about improving our regional total cost of ownership. One of the factors we really need to work on is making sure we can, kind of, more dynamically deal with fuel prices. Fuel prices are hard because obviously they change almost day to day, basically, or week to week, let's say. But what that means for the seasonal, yearly average is one thing.
So we don't necessarily want to say, well, the fuel price today in the middle of the summer is this. So that's, kind of, the annual cost. We try to represent an annual average to better represent it. But those things, we need to make sure we're updating and then think about how we can make that maybe even more upfront, even maybe potentially something that someone could tweak. That might be challenged with our mapping capabilities at this point, but we're thinking about that.
We've done some regional travel analysis trying to figure about travel time in different areas. That's some other work that our team is doing. Or think about adding additional mapping. So we have data on vehicle registration, station counts. That's coming from the AFDC. The vehicle registration is from Experian. I know TransAtlas has some of that data on a state basis.
And we've, kind of, been talking about, well, what kind of level of detail can we provide? Because we can't provide very fine grained levels of vehicle registration data on a census tract basis, let's say. But can we roll it up to a zip code and, kind of, round it and see. And so we're thinking about whether that's going to be valuable or, and see if that's something we can do.
Some other things like transit/ride hail utilization, we just don't have as good of data on. Especially on ride hail, we have nothing. Transit, we have better. So it's more– the mapping is, kind of, more on the private vehicle ownership. So we're trying to think what other things we can do outside of that. Think about congestion, adding some mapping on that.
More visualization on urban versus rural areas. And exporting some of this data to either a PDF summary file, maybe having Excel output so that you could see the data [INAUDIBLE] work with it. Maybe even a shapefile. So I'm going to end the presentation portion on another question.
And, again, take some time to think about it. If there are any metrics or mapping that will be helpful for you or your stakeholders related to, kind of, personal transportation, or even, kind of, fleet-based information. So, yeah. If you have ideas.
The fleet, kind of, thing is maybe a little bit out of what we're– the focus of the tool is. But still, maybe there's things that we can put into this or maybe potentially have a, kind of, a separate ATRAVEL mapping for more fleet-based focus, I guess, for clean city stakeholders and you. So that's something that at least was kind of a little bit on our mind.
So I'll stop talking for a little bit. Maybe give you a chance to ask any questions. Or if you have any thoughts about in this space, like, what would be valuable, like, what are you working on. And then I left enough time to demo. So I can actually go into the tool and see how it works. I know I kind of already in the presentation showed you how it works.
But if you have any specific cases that you'd want to run or like ask, like, can you do this? That would be valuable. I can help show you that in the tool now. So I'll stop there, see if we have any questions or additional thoughts.
JOANNA ALLERHAND: Peggy's got her hand up.
ANDREW BURNHAM: OK. Yeah. I guess I don't see the hands up. So if, yeah, if you can help. Yeah, Peggy.
PEGGY: Hey. Hey, Andy. I feel like Hermione Granger here with ATRAVEL. But– so some of what I do is like [INAUDIBLE] biped stuff and then looking at compact land use. So in a rural state like Vermont, we're looking at some of the downtown centers.
And so what I would love is if ATRAVEL could find a way– and I there may be other tools, but I don't know. I do like just ATRAVEL. It is a pretty easy tool. I encourage folks to fool around with it. I used it just earlier this morning when I was submitting my QPR.
But to be able to look at those other modes of getting around, really active travel in, kind of, walking and personal bike, not necessarily bike share, to get around those, kind of, short distances around a community. It helps the community understand what's walkable and then can maybe promote different kinds of infrastructure in addition to electric vehicle charging but also sidewalks and safety for all users.
So that might fall outside the scope but I would love it if the tool did that too.
ANDREW BURNHAM: Yeah. Yeah. Yeah. I think– thinking about– my headspace has always kind of been thinking about cars and trucks, and changing from a gasoline car to an electric car. Like, kind of what the difference is there. But when we think about mode switching, we can think about beyond the car and the truck.
We can think about transit. We can think about ride hail. We can think about active transportation. And so I think, thinking through how a tool can support that– kind of, whether it's just, kind of, being so straightforward of just like, hey, this is a zero emissions option.
And when we're thinking about multimodal trips, like, kind of talk about, well, the research says for the average person, and say, like, if you're walking less– if the trip is less than a mile, walking is definitely doable, let's say, for the average person without mobility concerns.
And then same thing whether it's three miles or whatever the number is for bicycling, and then maybe even e-bike. We'll expand that. There are all these issues related to how do you get people to be more active in transportation and having the infrastructure that you mentioned.
That's not necessarily, kind of, how we've been thinking about it or, kind of, maybe the capabilities, but I definitely appreciate any thoughts or brainstorming with how you could envision the support on this area. Like, I know walks– there are things like walk score. And I'm trying to think like, I thought there was something– obviously, NREL's got their map metric to– I'm kind of thinking through these things of what the distance and, like, destinations are. And we've been doing a little bit in that area, too.
So, yeah. I'm happy to think through that and get your feedback on that. I think there's something in the chat, too. How many people are currently using the ATRAVEL to– ooh, good question that I should know and don't. I don't have the latest– I haven't looked at the latest metrics. We do that for Clean Cities and headquarters, and we give those numbers. But I don't have that number off the top of my head. So, yeah, that's a good question.
We get our peaks and valleys. Like when we launch a tool and when we promote the tool, we get really good use. And then if we're not promoting it or updating it and things like that, like, it gets to the more core users who find it valuable.
So I think with this being clean cities focused, I think that's probably some type of question that we're trying to see like who uses ATRAVEL consistently. And I know, obviously, Peggy is as self-described Hermione Granger of it and appreciative of that.
But there are other folks who have said, like, on the data side, like, hey, we're interested in getting some of the data from here and that– kind of the greenhouse gas emissions regional type analyses. So I think the metric tool, seemingly for clean cities directors, coalitions, has been more, kind of, the focus of what they were interested in and how they could use that data.
So I don't see any other questions or I don't see any hands raised, too. Please feel free to chime in, raise your hand, and go through– I'll just quickly flip to the actual tool just so you see it in action. Should be– I'm doing a screen share here. There is a home page.
I have weird Zoom levels on my computer so that things are always kind of hard to show. But basically, it tells you as you enter into the ATRAVEL home page, like, OK, what do you do for the trip tool? What do you do for the metric tool? Basically what I described for you in the presentation.
You click one to get started. It has a little bit of, like, concepts. We're thinking about how we could improve this area and maybe even make it a separate page, kind of, just education and things like that. But at least, I wanted to set the table of what the difference of these terms are.
We have– as I mentioned, you enter information via this Google Maps interface. The frequency of the travel. There is kind of a Save and Load capability. I think I have to check the load portion. Like, my computer's weird. But let me– if anybody's using this and they're not able to load, let me know, because I think I'm able to load trips but it's a little wonky. And we can address that.
Then, as I mentioned. So I just kind of did my daily– well, so you can click the X and start over. So I'll start over. Choose your location. Choose your destination. Choose the time you travel. So if I'm only going three times per week, not once.
It kind of finds via the Google Maps interface. It tells you, like, OK, if you're doing that three times a week, it's estimating about 7,400 miles of travel. And I know, well, I drive about 10,000 on a year. And that one's hard because sometimes you just aren't, you aren't going to have that information.
So there is this toggle that, like, adds that additional mileage. So if you want to say, OK, like the person in my area household travel is basically around 11,000 miles. OK, that's a little bit more than what I do. I'm more on the closer to 10,000. That's how you would adjust that, kind of, a little more simply than adding each individual trip.
There are challenges for that, too, like thinking through. Like if I take long distance trips and so forth, like what is the impact of long distance trips? And do you consider– is that something you would include in this type of analysis? The kind of– more focused on regional travel is kind of like what we're thinking of with the tool.
Using the dropdowns here to enter your vehicle type. And then as I scrolling around, it defaults to this page. I was clicking around. But as I showed, you have this capability to change some of the factors and even see what by default the assumptions are. The cost for parking is this. Well, I live in Chicago and I pay a bunch of parking tickets, and it's typically more like that.
And this per person thing really is important. So you can see right now– the results may be like, OK, these all make a lot of sense for costs. Like, vehicle ownership is more expensive than transit. Ride hail is quite expensive. If I was traveling all the time on that, it would be very expensive. Travel time seemed to make sense in general, like transit takes a bunch longer because I work out in the suburbs.
This type of time for vehicle ownership includes waiting and parking stuff. So this is relatively reasonable. And then emissions might be something like, well, that's kind of surprising. Like, my vehicle ownership is actually lower than transit. And that really comes down to occupancy and fuel efficiency. So I have a relatively fuel efficient vehicle.
But if it is only one person, single occupancy, you see that it flips. It's closer. It's in the ballpark. So that's something at least to think about on obviously carpooling around those areas. Vehicle occupancy really matters when you're thinking about travel as a whole.
And then it has these additional details on each of the cost, travel time, and emissions. It gives some type of blurb that represents what– represents your costs for fuel, insurance, and maintenance. Kind of a little bit of what your parking and drive time is, and so forth.
And then ride hail has additional details representing– if I only traveled very small amount of miles, like it actually might make sense for me just to have a ride hail vehicle. So basically, there's a cut point here, about 1,600 miles. So not too much travel. But like at that point, like, I'm going to be better off just using ride hail. It's just cheaper there. But if I travel any more than 1,600 miles, then, like, the costs are going to be much more expensive.
And a little bit more information in transit. Same thing. Kind of a cut pass of whether you take a transit pass or base fare. Additional details. And methodology. I'll stop there because I know we're going to close. And then the methodology page.
So basically entering a location. It will give you a map. Mine's zoomed out a little bit more. It's giving you the quartiles here. So you see the, kind of, shades of green, the different ranges. If I go to a larger area, like a coalition, the data will then kind of represent all the census tracts within this coalition. And then the data here will, kind of, represent the differentiating, like the factors within that coalition.
You can add an overlay, I mentioned. So like disadvantaged communities. So all the non-disadvantaged communities go away and you see the disadvantaged communities, see the results that way. And then you kind of see how you match up kind of compared to the national average.
And we have a methodology page that provides all the definitions of what these metrics mean, how we calculate them, where the data is coming from, and so forth. Methodology here. A little bit of glossary of terms. So I'm going to leave it there. I think maybe one last chat.
Given you develop both the AFLEET and ATRAVEL tools, from your perspective, what is the best way to incorporate or integrate the two to get the best possible benefits from both? That's a good question, Elizabeth. We saw this as two different paths to use the tool, AFLEET being something specific for primarily mode switching, answering a lot of vehicle-specific questions.
ATRAVEL, the idea really is, what are these other modes? What are the costs, travel time, and emissions potentially benefits or disbenefits of using those other modes? That's really where we came from and started to think through. So I think that's, kind of, the focus.
If you want to go to ATRAVEL and think about personal transportation potentially on a consumer level or even in a regional area, how to think about how things differentiate for each of those factors, that's kind of where you might want to go to ATRAVEL.
So, thanks. So I will leave it at there. I think I cruised a few minutes before our stopping time. I really appreciate everybody's attention. And, again, if you have more questions, more thoughts as you use the tool or just, kind of, in this area in general, please feel free to reach out. I look forward to hearing from you.
Thank you so much.
JOANNA ALLERHAND: Thank you, Andy. Any– in the one minute we have left, any final question anyone has? Not hearing any. So I think we'll wrap it. Thanks, everyone, for joining us. And thank you again, Andy. Have a good rest of your day, everyone.
CASS: Thank you.