 Okay, good afternoon everyone. I'm Harvey Miller from Ohio State and Chair of the Mapping Science Committee and I'm pleased to be moderating this third session on smart communities. I'll first introduce our keynote speaker, Michael Barabay. And then after the keynote, I'll introduce our panelists. Michael Barabay is the Acting Deputy Assistant Secretary for Transportation in the Office of Energy Efficiency and Renewable Energy. In this role, we oversee the office's Sustainable Transportation Sector which includes vehicle, fuel cell, bioenergy technologies offices. This portfolio focuses on the research and development to increase access to domestic clean transportation fuels and improve the energy efficiency, convenience and affordability of transporting people and goods to support U.S. energy security, economic productivity and competitiveness. He brings more than 25 years experience in the automotive industry to his new posts specifically in the areas of environmental compliance, energy and safety policy, and product development and marketing. Michael has a BS in civil engineering from MIT, an MS degree in the technology and policy program and a master's degree from the Sloan School of Management. Michael, please. Do you want me to use microphones in here? All right. Well, good afternoon everyone. Thank you very much for inviting me to speak here. I'm going to take maybe about 20 minutes. We can make sure we have lots of time later for Q&A. Want to do a few things. First, give you a little bit of a feel of what we do at DOE in the transportation area, what we mean by sustainable transportation, kind of how we view it, how we're coming at it. And then given the topic of the two committees here today, I chose three specific examples. We could, I would love to talk all day. I love the work of transportation. I chose three specific examples that I think are all have a significant geospatial mapping related question at its core that are going to be critically important to transportation. Thank you. I was going to do that. All right. So let me give you a little bit of a sense of just background, the transportation sector at DOE. So we are at the Department of Energy, largely an R&D funding organization. And transportation, our budget is approximately $700 million per year historically, of course, subject to appropriations coming across transportation. For those of you that don't know, the national labs of the country, the 17 national labs of the country, Argonne, Los Alamos, NREL, et cetera, those are all part of the Department of Energy. So much of our work is done through those national labs, with those national labs. But by no means all of it, about half our work is done with academic institutions and the private sector as well. And of course, one of the great things about being at DOE is that we have literally, I think, the most amazing scientific resources available to us in the area of computing, especially, but also in the physical sciences as well. So within my area, we have three core focuses. The vehicle tech, and these are four separate offices. The first kind of cross-cutting vehicle technologies office is basically charged with developing new technologies to significantly improve the energy efficiency and the affordability simultaneously and also maintain or improve air quality if possible across all different types of vehicles. So they do a significant amount of work in batteries. They're best known. Literally the vehicle technologies office are the ones who are inventing the batteries that are in your phones, in your computers, and in electric cars. Two of the three recent Nobel laureates for lithium ion battery are actually active researchers still on our program. And we've been funding them pretty much since the beginning. We also work extensively on engines and energy efficiency of engines, all different types of fuels, and a lot of work on mobility overall, mobility as a system and looking at the system level impact. I wanna talk about that a little bit more. Hydrogen fuel cells is a significant program area as well for us looking at not just fuel cell vehicles, but also hydrogen more broadly and the hydrogen economy and how hydrogen can play a critical role in the overall economy as an energy carrier beyond just mobility in vehicles. And then last bioenergy technology. We have it again, another office that while it's core mission is to develop affordable low carbon biofuels. A lot of to do that, you have to create a lot of other things on the way, a lot of products and the ability to make chemicals and other products from biological pathways and routes is a core to what they are doing. So take a step back. We think about transportation. Transportation, I'm a civil engineer, I started in transportation, I'm a little biased, but it is fundamental to our way of life when you think about it. Our economy and our lives fundamentally rely on transportation. How far could you get the food you eat or how far could you work if you didn't have transportation? Transportation today in the economy, three trillion vehicle miles, 11 billion tons of freight every year just in the United States and of course we are just one part of a global transportation system. But when we look at transportation, it is changing rapidly, right? When you look at not just the technology, but you look at the human factor side of it today. First of all, transportation is the second highest expense in a typical American household. One fifth of the average American households at average, if you're in the lower half the income bracket, it can be 30%. So you think about that after housing itself. So transportation is a significant economic cost for people. You look at businesses as well. You look at aging, the population is aging, one third of people 65 and older, which is one of our largest growing demographic segments have some level of mobility related impairment. You look at population growth, right? We're gonna add 70 million people over the next 30 years at projected growth rates. Those will largely be in 11 different mega regions across the country, causing in more people, growing economy, hopefully. You're gonna need transportation to move people and goods from point A to B. And when we think about transportation, while much of it historically has been focused on core ground transportation, vehicles, cars and trucks, we look much more broadly. We certainly spend a lot of our time, our money, our effort in cars and trucks, but you think about micro mobility choices. This chart just amazing to me. This goes through 2018. The yellow bar at the end is the scooter share. And those of you that are from the DC area can relate to when stationary bikes and dockless bikes, yeah, this dockless bike, this must be the thing. And then how quickly, and I like this chart because it very much matches my sense of how disruptive changes happen, right? You don't know it's disruptive until it's disrupted something, until it's here and upon you. And it's often not the first thing in an area that is changing that is the disruptor. It's often the second or third thing, as you can see with scooters. That's 2018. If you look at the 2019 bar, I will hazard a guess will easily, easily be double that if not more. So it shows an example of how quick things can change. Of course, package delivery, I don't know which house here you could relate to the most with the holidays coming up. We'll see more of that. The growth rate, this is just US Postal Service data, which is pretty related to the overall, the largest deliver of goods still, but 50% increase over the last four years in package delivery. And of course, Uber's and Lyft's and transportation options have been changing dramatically when you look at the trends. Now, when you look at that, this is in billions, billions of annual ridership. Although if you put this graph against all rides, these bars would be really tiny because we're in trillions, right, of rides overall, but yet it's a significant change in how people access transportation and also how we study and think about it, right? Because if you purely use a historic measure of rides, you would say, well, this is pretty small, it's not very relevant, but yet it's obviously very disruptive in changing how people access transportation because of the second and third order effects it can have. So that's a core thought we have. So when we look across all of transportation and the work we're trying to do fundamentally and trying to drive towards how do we get a more sustainable and affordable system, it's across this backdrop of this tremendous change in technology that's happening. I'm often a believer, though, that oftentimes, we talk about technology driving change. I believe that oftentimes technology is not the core driver. Technology, I like to think of it as oftentimes more the enabler. There's underlying economics, there's underlying unmet needs, there's something else that's going on and then technology is there at the right time at the right place to help enable it, but technology alone is necessarily the driver. When we looked across this whole space and having energy efficiency as our core mandate, about three years ago we did a study looking at the energy impacts. And this was a bounding study, so it only has so much usefulness, but it is worthwhile noting we looked at and looked at what are all the changes, both on the positive and negative side, that these mobility changes could have on energy or all the impacts they could have and showed that there could be up to a 200% increase in energy consumption or a 60% decrease. You think about, as we looked at that, this is before we had any work going on on automation connectivity, mobility, micro-mobility at DOE, and we basically made the case that we need to be studying very, very well because all the other work we're doing could be completely dwarfed. We could invest a ton of money in a specific technology area and have it wiped out by increased induced demand. Now, we're also very clear to say, our goal is not to say we want to decrease mobility. In fact, we've had to come up with new measures to how to increase mobility is generally a good thing, but how do you understand the impacts of increased mobility and how do you do it in a way ultimately, we like to think of, could we ultimately decouple mobility in energy consumption? So you can have growing mobility without an increased use in overall energy. So I want to, with that, maybe there's a little bit of a background on how we think about our mobility work and I can mention the three different office areas we have are focal areas. I picked three different examples that cut across the work we do as just representative examples that we can talk about, although during the Q and A I'd be glad to talk about any of the areas across mobility more broadly. So, elegantly, just labeled example one. So first, I want to talk about really centers around this change in mobility and how do we measure it and how do we look at it and what's the government's role? There's trillions of dollars being spent today in automation and connectivity technology across automakers and others, Google, Lyft, Uber and when you look at all of those companies and all of that money, their goal, develop a vehicle, a single vehicle that can work perfectly with basically no reliability on anything else around it. It will certainly be connected to the cloud because it can use cloud-based computing but not because it wants to understand and communicate with other vehicles around it and when you look at that, their goal if they're like the auto company can't rely upon other vehicles being there, the question that no one in our minds really asking in a full enough way is what is the system level approach? What are system level impact? So if you look now at multiple levels of automated vehicles, connected vehicles, micro-mobility, change in frame movement, what's the total system level impact these are having? What's the impact to congestion, to affordability, to energy consumption? So we basically created a research program part of that around trying to answer that question. So you kind of demonstrate the single vehicle, we understand that very, very well and we can model an individual vehicle virtually down at physics-based model, the aerodynamics, the engine, the shift patterns no matter what fuel you wanted it. We've taken that and looked at how do we take that vehicle and now model it in a corridor, think about with all the vehicles it can see and sense right around it plus the infrastructure it can see and sense around it and then if you take that modeling, kind of a micro simulation and we go up to more of a mezzo-scale simulation and then put that in the context of an entire city. So we've done that now both with Chicago as well as with the Bay Area, up to 11 million agents. These are agent-based modeling approaches. Fundamentally asking the question what is the system level impact? What are the second and third order impact that you just really can't anticipate up front as new technologies might play out and it's not a forecasting attempt, it's really a simulation attempt to understand what does this technology do? What does that technology do? To help answer the question, when back, I don't know, maybe a year or two ago we were working a lot with Mandi and people in Columbus and someone in Columbus asked this, I don't even know which directs, like maybe with a question around TNCs, should we incentivize it? Should we not? Is it gonna help? Will it help? Will it hurt? Those types of questions are very difficult to answer and that's what we're trying to do here. So not to walk through the full model here, but it's actually a modeling workflow with multiple different models embedded in together, but I wanted to give you a flavor because I think it will obviously apply to many of the types of work that you do here. The most transportation-based modeling is basically modeling, look at links and flows, relatively straightforward simplistic models, basically about how big do I have to build the road and where do I put the road at his core or the train? The goal here was to use agent-based models where you're representing every individual person and then the decisions they're making and the technologies they're interacting with as well as every package or piece of freight that's gotta move essentially is also making decisions or people are making decisions for you about how to move that freight around. You're making decisions about order packages or order goods, you're making decisions about where to go to stores, all interact. So we have the capability to model existing technology, future technology, level four, level five automation, connectivity, micro-mobility services, transit, and to look at the second, third order effects as you start changing some of these. So the model is now, and I guess a suite of models, this is a many multimillion dollar effort across the national labs, operational and our goal in the next year is to really start probing more deeply and then start to look at other cities as well to understand its portability, but ultimately create a tool that maybe not in its full national lab, high performance computing level glory, but in a downsized version of it that can be available for cities and communities as they're asking the question and they're trying to figure out what they wanna do with specific technology, a policy, et cetera. One key thing I'll know, I meant to come up with a new metric. So one of the things we had to ask is what is the goal at the end? And I won't go into it too deeply here, but we basically created a new measure called mobility energy productivity, which is very much a very geospatial based metric and it looks at the question of, for any given individual, any given point in a geographic area, what are all my mobility choices and how much the energy would take, the cost it would take, the time it would take to get to all of those different choices and then aggregating that for every person and every location across an urban area. We've actually shown the data is available to do that. We've done it now for dozens of cities and we can now bake it into the model so you can look at when you have some things going up, some things going down, good or bad at the end, did I improve the amount of mobility per unit energy cost and time from a particular change or set of changes? I'll give you one example of an outcome of being able to do this model. We looked at this question of package delivery and e-commerce and asked the question, so with significant increases in e-commerce, what's the net energy impact? Is it positive or negative? More local delivery trucks? Maybe more class A trucks, maybe going to different locations, less individual person trips, more congestion. When you put all of that together and model all of it, it was pretty surprising if you focus on this chart here in the bottom right. When you had three deliveries a week average, so household typically sees three package deliveries, probably not that uncommon for many people today. There was an overall 40% decrease in energy consumption largely due to decreased trips people take to the stores. And I can anecdotally relate to it myself. I'm doing a little project at home and I would run to Home Depot, which is about 20 minute drive away. I'd have to do that once a week before. Now, go order it comes in. So I'm taking far less trips. I was wondering am I in the end helping or hurting while it turns out it's net net a positive energy wise. So it's just using example of the types of things you can study and look at. All right, moving on completely to a completely different example, lots of discussion today about electrification certainly. And as I said, we are working as aggressively as anyone on electrification, but did a little thought experiments that let's say we were at 20% next year, electric vehicles, magically we could get there. We grow it up rapidly to 40%. By 2040, we're still gonna have 60% of the vehicles on the road driving. And assuming you don't have some major change in kind of pulling vehicles off the road with some pull ahead program that are using liquid fuels. Aviation, we actually are working on electrification and aviation that can be more of an electric assistant very much at the margin. You're clearly gonna have a lot of liquid fuels, heavy duty trucks are actually talking about electrifying more but you're not gonna electrify all of those. So we, if we're gonna hit our goals overall of a sustainable transportation system, we are gonna need significant amount of low carbon fuel. There's no way around that. If you wanna hit, you know, types of goals, people are talking about it even near 2040 or 2050 timeframe. So when you look at that question, what are the options for low carbon liquid fuels? And it turns out there are a lot, a lot of options. We are working aggressively, certainly on, people think of biofuels, they think of corn and ethanol. We are not working on that at all. There's a great corn ethanol industry today that's well developed. We're looking at all the waste crops when you grow corn or weed or you harvest trees for building lumber, all that waste bio material. How can you translate that into fuels? Municipal solid waste, growing algae, purpose grown algae growth, liquid waste from farms as well as bio solids from the municipal wastewater treatment plants. These are in plastics. These are all rich sources of carbon. And what turns out we can replace one fifth of all the liquid fuel we use today from those biological sources. And the cost has come down dramatically. We've been investing quite a bit. We've actually spent over $200 million a year in this area. The costs have come down in this area per gallon. We look at kind of the end gallon that you would have to get to when you're leaving, let's say a factory gate, so to get out to a customer. Our target is to get to $2.50. We've reduced the cost as much as batteries have come down in the cost in the last four years, about a 40% cost reduction. We're currently at about 340 a gallon, which, and we anticipate by mid-decade, we'll be starting getting closer to a point where you are in economical ranges to get there. However, there's a big challenge here. So one of my few busy charts I have here, if you look on the left, this gives you one example of one of the good feedstocks you could get is CO2, waste CO2, or CO2 from air capture. Air capture turns out to be pretty hard. So if you look in the chart on the left, that shows all of the different places where they're currently ethanol plants. They're quite a few. Ammonia plants, as well as natural gas wells, all busy places that have rich, clean sources of carbon. The chart on the bottom shows CO2 concentration. If you want to take CO2 and translate it into something, you can't spend a ton of money to have to concentrate it. If you want a good concentrated source, you want to look at how many they have. But the other thing you need is hydrogen. You need to take the carbon and the hydrogen, and that would be true whether you're using CO2 or whether you're using all those different types of material I talked about. So you think about municipal solid waste, you think about all that waste crop material, it's spread throughout the country. Now some of it is, the biological ones tend to be more in their areas around farm area. But on the chart on the right shows where we have wind power, which is key because where you have dispersed wind power, you are going to have excess electricity. We already have that in a lot of places that you could take that excess electricity and make hydrogen out of it. And then you have local hydrogen. But unlike today, much of our power today is a centralized story. In the future it's going to be decentralized. That's true in creating power for vehicles as well with liquid fuels or hydrogen. So this question of where the source of the energy is, where you translate it into a fuel or its energy source you ultimately going to use and get it to its end user is going to be critical and it's completely different than what we do today. All right, so last example here. So on the trucking side, picture on the left, anyone guess that that's a hub and spoke map from an airline? Anyone guess which one that is? Delta, because I lived in Detroit a long time. So I grabbed a Delta one. I worked early in my career actually on transportation in aviation and before hub and spoke started there was a question, should we have hub and spoke systems in aviation? They obviously have developed for a reason. When you look in the trucking sector today, the trucking sector has changed dramatically. The average trip of a long haul truck has gone from 500 miles to 300 miles in just the last four years. That's average. So you think about that dramatic change. What's happening is to develop hub and spoke systems because they wanna keep the drivers close at home at night as well as some efficiency of operation, package delivery, all these things changing together. Well, when you look at that, it's very interesting that 50% of the goods by weight move with less than 100 miles of the country. 75% move less than 250 miles. As a result of that, you also have a lot of businesses very interested in electrifying trucks and also electrifying both full battery electric. Three or four years ago, the conventional wisdom was you'll never electrify big trucks, class seven, class eight trucks. Well, that is very actively on the table today as well as looking at hydrogen, which maybe can be a little more practical, especially if you wanna go into that 250 to 5,600 mile range. But when you look at hydrogen, there's a lot of work that's been done to get hydrogen cost down. We have technology road max for all of it, but the one we don't have is how do you move the hydrogen to where it needs to be if you have dispersed use of hydrogen? It is just way too expensive and there's no good technological cost-effective pathway to do that. Short of big pipelines and you have to have huge penetration to that. But if you look at trucking, where you have centrally refueled vehicles, and also if you look at places, this is actually a picture of what Nicholas is planning. You look at where that is. Big desert. That's not a coincidence because they have a big solar opportunity there. So if you can make electricity locally, make your hydrogen locally, not have to ship it and have centrally refueled opportunity with fleets, all of a sudden you have a hydrogen truck that now could be cost-effective. That's the first example of really cost-effective use of hydrogen vehicles that someone's really been able to put together. A lot of work still, but at least it's a plan that has a thought behind it. All right, with that, I'm going to wrap up there and I appreciate your attention. Look forward to having more conversation later. One or two quick clarifying questions before we move on to the panel. I guess I'll ask one. Yeah. The chair, progneth. So you mentioned that even with increased electrification that we're still going to have 60% of our vehicles using liquid fuels by 2040. I'm not clear about how biofuels solves that problem because we still have the problem of a vehicle stock that the average age of automobile in the United States is like 10 years. So how does that sound like? Low carbon biofuels. Our goal is we're developing full drop in biofuels. So basically imagine that can go drop into the vehicles that are on the road new car built today. Especially cars built, maybe in the last five, six years, maybe even a little longer than that, all had pretty flexible calibration. So they could even take something that's a little off spec and fuel and probably work just fine. So if we have low carbon biofuels, basically allow you to burn those in the vehicles on the road, the net carbon impact of those fuels is about at 80 to 90% greenhouse gas reduction. So now it does raise the question about local pollutants and part of the question though is if you're making a biofuel and you're molecularly tailoring the fuel at that molecular level, can you do it so it is inherently less prone to making particulates? That's one of the things we're looking at. Oh, Dan. You mentioned the need for infrastructure for hydrogen. If we were to build pipelines, we have pipelines for natural gas all over the country. Why don't we just repurpose those? Two reasons, one there, using natural gas. We are looking at injecting hydrogen in up to 5% maybe a little bit more. The other problem is you would need some pretty significant upgrades on those in order to handle the hydrogen for the materials because hydrogen being, you know, such a nice beautiful, small, tiny element just nice to sneak into things. And so you wouldn't need upgrades but theoretically you could. Would they be going to the right places? I'll follow that because the idea of the, you know, yeah. So there would be some challenges there as well. Okay, with that, I think we'll move on to our panel. Then we'll have open discussion after our panel presentations. We have three panelists this afternoon. Mary Leary serves as the Deputy to the Associate Administrator for the FTA, Federal Transit Administration, Office of Research, Demonstration and Innovation. Did I get that right? Yeah, yeah, okay, sure. I heard some rumbling there. Mary leads all operational and managerial functions to ensure the smooth operations at FTA's research office. She has over 34 years of experience leading major federal programs, spanning careers in the public, nonprofit and private sector. Mandy Bishop serves as the Smart Columbus Program Manager and is responsible for delivery of the US DOT and Paul G. Allen Family Foundation grant-funded programs. During your tenure, she has served as a Senior Project Manager with GPT Group, the staff lead for Ohio Governor's 21st Century Priorities Task Force and Deputy Director of Planning for the Ohio Department of Transportation. And I'll be remiss if I don't mention that she has a BS degree in Civil Engineering from Ohio State University. And finally, Andrew Turner is an international man of mystery because I do not have a bio for him. So I'm gonna ask him to introduce himself. Sorry, yes. So as I mentioned, I'm the Director and CTO of Esri's Research and Development Center in Washington, DC. Previously I was the CTO of G-O-I-Q. It was a startup that worked on building geospatial intelligence systems, both for the web, for consumer industry, as well as the intelligence community that was acquired by Esri in 2012. Prior to that, I was a founder of a nonprofit called Crisis Commons that was building crowdsourcing tools for disaster response for the World Bank and other institutions, my backgrounds in aerospace engineering from UVA in Virginia Tech. Fantastic, thank you. So we'll go in that order. Mary, Mandy, and then Andrew. Mary, please. Great, thank you. Well, I'm a social scientist, so I have to say, when they were telling me to come talk about mapping in GIS, I thought, okay, how am I gonna do that? So, but seeing all the parallels between Michael's presentation and mine, I think I'm on the right track. What I'm going to do is share a little bit about our program at FTA, by the way. Is this working? Am I right? Okay, never know about the right distance. And then I want to drill down a little bit into smart communities and how does that relate to the trends that we're seeing in public transportation today, because it is a very transformative time. And for many of the reasons that Michael's already talked about. And then lastly, I'd like to have one example of a very important program that I think highlights the role of a really good navigation capabilities for people with disabilities. And there are many other areas that we can go to. Oh. Okay, sounds good, perfect. Should be on the mission and priorities slide. We're also talking about it. So, the mission at the Federal Transit Administration Office of Research, our statute says we exist to enhance public transportation through innovative research. We have three major research areas of priority. And they mirror Secretary Chow's strategic priorities for the whole department. One is developing and deploying innovation. Second slide, please. The second is safety first. And it's actually always safety. Safety is number one. And lastly, it's mobility innovation. And it's the mobility innovation side that I'd really like to drill down on a lot in this conversation. And our statute actually has a prescriptive pipeline process that we have to follow. So, ideas sort of germinate in a research area. Then we move into innovative development. And then we do demonstration and deployment. One of the things that my boss in Valdez likes to talk about is we have a grassroots predisposition to what most of our assets, about 70% of, about 160 million that we're currently managing today in demonstration programs. Because our job is to really enhance the ability of public transit agencies to meet their mandates. Next, please. Okay, should I try now? All right, there we go. Thank you. Well, interestingly enough, and a lot of times people don't realize just how pervasive public transportation is. But it's a 98% of urbanized areas, which is probably not a big surprise. But a bigger surprise is we're in 81% of the counties. Now, if you look at the slide over here on the right, the big map, that's by North Dakota State University. The white areas are areas where there are rural areas with no transportation. The red are urban counties with no ruralness to them. And then what's important though is if you look at both the dark green and the light green, those are areas where we have transportation associated with rural counties. So, we're really existing in a lot of areas. It doesn't mean that we're everywhere we need to be. And then interestingly enough, one of the studies that has been done has shown that there is an intimate relationship between public transportation now and ride hailing services. We're seeing a very strong relationship. And we like to say it's first and last mile or in rural communities, and this is not my quote, but it's from a lady in Vermont, first and last 10 mile if you're in a rural community. So, one of the areas where we're using mapping is we just hired a data scientist. And we're trying to move into data driven research and research decisions around data. So, this is actually a map of our research recipient. So, some of the things that we're doing is we've developed a business intelligence system and then we're drilling down and analyzing our work from that perspective. And obviously that's really important when we're trying to make decisions on where do we want to make awards? Because if we've got two equal applicants, maybe we wanna go to an area that we currently do not have a recipient. Now there are a lot of trends and I love the term disruption. I was in the high technology industry for almost 20 years and you talk about change, we went through transformative change. So, a lot of the change management literature is it talks about things that I live through. And what's truly fascinating for me is I actually think the public transportation today is going through what many industries have already gone through. And I believe that it will look very different five to 10 years from now, even 20 years from now. And I was talking to some folks from Kansas about Hyperloop. And I do think, think about hub and spoke. And Hyperloop will probably be deployed at the same time that trans automation is going to be deployed. And they're gonna serve two very, very different purposes. Obviously bus technologies are very important, but also new technologies impacting operations like worker track identification. One of the things that we think will be very, very important is how do we ensure that as we move to more and more automated systems that the safety factor doesn't go away. And then of course we've got user adoption and travel expectations on real-time information. Smartphones are ubiquitous. Everybody has them. So now there's a desire to know exactly what is my transportation resource? Where do I get it? What does it cost? And many, many of our recipients right now are doing research in that area. So this is an ability environment. As a matter of fact, when you were talking about micro mobility, 84 million, that was actually something I was gonna talk about. I worked for Easter Seals at one time. I think of micro mobility in scooters as real challenges for brain injury. I'd like to see helmets. But when you look at it though, we're really shifting the way people get to transportation resources. And that's going to make it available to more and more people as we enable folks to get to the station. And that's really been one of our issues. Obviously we use mapping for transportation demand management. And over the next 30 years with the population changes that Michael was talking about, especially for older adults, I actually was at the Department of Health and Human Services and on the aging side. And it's interesting, most of the research that has been done on older adults has been done on older adults with dementia. So there's this perspective that older people will not be able to take public transportation. And unless you grow up in it and you commute in an urbanized area, but if you think about how far the disability community has come, there probably are a lot of parallels that we can have between the two. So we think that this is a time of significant change. And almost $21 billion, I think, of $121 billion is the cost of what Americans spend stuck in traffic. And I know Michael talked about it, but you think about street space. There really is a contraction of street space. We did an important meeting with our two advisory committees, the Federal Transit Administration, Federal Highways Advisory Committees. And that's a convenient by the National Academies. The number one area that they all talked about was street space. So between transportation network companies and single or maybe two people in a vehicle and then all of the deliveries and then the ability for a passenger to actually get on, particularly if somebody uses a wheelchair, there are gonna be a lot of issues as we go forward. So we talk about mobility services. You'll hear mobility on demand. In Europe, it's modest mobility as a service. I think whatever you call it, the focus of many transportation agencies now, they're calling themselves mobility managers, not necessarily public transit agencies. And the importance of pulling in both public and private assets is a critical component of where they're going. So the thing I wanted to talk about the most is drilling down into something called the complete trip. This is a concept that came from the Accessible Transportation Technology Research Initiative. And that initiative has been developed for, I guess probably about eight years. Muhammad Yusuf from Federal Highway started this a number of years ago. The reason why we like this concept is we feel it gives a framework for how do you assess the gaps and accessibility in a community and how do you develop solutions to address those gaps? And a lot of the areas, and my next slide I'll go into more detail on the parts of the trip chain, really have to do with GIS and mapping and space and how you help somebody navigate using navigational aids. So this is a scenario I kind of contracted the trip chains into these areas. The first area is how do you easily plan and book a trip? So if you think about all the mapping aids that are gonna be necessary, particularly multimodally, it doesn't exist today. You cannot today plan a trip across the United States. The way in which we manage public transportation, it doesn't mirror the way people travel. People travel across public transit boundaries. They travel over states. They travel over counties. They travel across the United States. They take more than one mode. So how do you help plan and book a trip? Then second is how do you get to the transit station and how do you get there safely? Particularly if you are an individual who is blind, how do you do that with as much independence as possible? And there are a lot of new navigational aids that are making that possible and I'm gonna talk about a few. And then while you're on the bus, let's say an individual has a cognitive disability or an intellectual disability, being on the bus is something that can be very anxiety producing for them. So how do we provide resources to help people as they do that? And then crossing the street, how do you get safely across the street? For all pedestrians, I think probably many of you might know, if you're driving a major bus and you're going left. So let's say a person is over here on this side of the street. The bus operator sees the pedestrian. The pedestrian sees the bus operator. But if that bus goes left, half of that street, they can no longer see. But the pedestrian doesn't know that. So if you started to walk across the street, you think, oh, that bus saw me, but it's a real issue. So you actually watch bus drivers get out and contort themselves to look at the window. And we have a research program to look at bus compartment redesign, not only to help them with that issues with being able to effectively see to navigate the bus correctly, but also for safety reasons too. We've got a lot of issues there. And then arriving at the destination safely. These are all the different types of projects that we have. I could go into a lot of them, but I wanna just drill down on this one. And so smart wayfinding, pre-trip concierge, robotics and automation, safe intersection crossing. I thought this might gel into what you're talking about in terms of smart communities and the use of technologies to help people get around. Here are some examples. And I'm not going to go deeply because I wanna close off my 10 minutes stop. But we're doing a lot with a number of our research recipients in terms of wayfinding and navigation. And it's very exciting to see. It's interesting, GPS is not a very good way to get around if you are a person with a disability or you are blind. It's not very accurate. It'll actually send you into a building. So we have to have a lot of new navigational aids and technology to help people get around. These are some of the other things we're doing. Carnegie Mellon's doing a lot of work over there. And then robotics and automation hold a lot of promise for people as well. So here's some links and resources. And when you look at where we're going in terms of a lot of the resources that we have from a mapping perspective, we work closely with Esri. You showed the ArcGIS online. Federal Highway has ATP GIS. Probably many of you are familiar with these resources. So there are a lot of other activities that we're doing to enhance smart communities from the planning side with a lot of GIS and resources associated with mapping. With that, I'll turn it over to my next colleague. Okay, thank you. Mandy. Andrew will go left. Yeah, unless the slides are keyed up differently. But nope, it looks like. Okay. All right, well, thank you all for hosting me here today. I'm just a little bit of context about Smart Columbus. It is an informal public-private partnership between the City of Columbus and the Columbus Partnership, which is a membership organization that enlists the top 75 CEOs in central Ohio. The City of Columbus being the lead on the grant delivery program. In 2016, we were awarded the Smart City Challenge opportunity. We won $40 million from the US Department of Transportation as well as 10 million from the Paul G. Allen Family Foundation to electrify our transportation sector. Our mayor firmly believes that mobility is the great equalizer. So much like Michael shared, transportation is fundamental. And when I took over this program about a little over two plus years ago, I wrote this was a little bit too esoteric for me. And I really had to think back to when I turned 16, got that car with four different tires and the AM radio. And after I got past the initial kind of like disappointment of that, I realized that I could get the softball, my job and to school. And transportation for me has always really been an enabler. And so for it to be a barrier to others in the community, just getting up every day and just having to get past that first hurdle to get to the things I want to do it was just something that really drives me and my team to delivery. Our vision is to really empower our residents to live their best lives through responsive, innovative and safe mobility options. And our mission is to demonstrate how intelligent transportation systems and equitable access to those systems can really help tackle challenges that our residents are facing every day in cities. And so when we won the grant, we really focused on two components. We focused on electrifying our transportation sector. And this is the area where we've probably struggled with equity the most electrification. The early adopter is not your eye or is your eye. It's the middle high income earner, highly educated. But we've really been focusing on that shared component to help drive electrification throughout our community and access to electrification. Our five Vulcan priorities include 42 different initiatives. And we really as a city had to kind of double down on how we were going to really tackle some of these issues. This was relatively new. And through a partnership with NREL with the National Renewable Energy Lab in Colorado working with Dr. Stan and some of his team, our first map actually was a hotspot location where the zip codes were with the most EVs that were sold in central Ohio. So that was really a starting point for us going, okay, what's gonna be our key decision and drivers for making the decisions about where we're gonna place electric infrastructure? We're gonna start it with our downtown region and looking at what was there. And then looking at places we wanted to really develop partnerships with where we had the electric infrastructure, et cetera. And so we came up with a process for identifying publicly accessible charging locations. And we really focused on, again, the origin. Where were the EVs being sold and used? Where were trip destinations? Where was it mostly work, workplace? Where was more charging needed? Did we already have some prevalence of charging in the area? And then what type of charging was most needed? Is it gonna be a level one, level two, that DC fast charging? And some of the things that we also prioritized were looking at where we were gonna hit that interim trip, like maybe people that were traveling cross country and they could start to have that gas station model and we could put DC fast charging just off the interstate but still in our central business district. That could also serve some of our transportation network companies as well. And so ultimately, we ended up advancing an initiative that really looked at charging infrastructure, where we could place charging infrastructure, where we had a need, where our electric grid could really take, had the capacity to support it. Where we had, when you have a public-private partnership, it's great to leverage the private sector. We had a lot of locations that were accessible to us, like Nationwide Children's Hospital. We had AAP as a huge partner. Walmart was getting in the game with opening up some of their massive amounts of parking to us to put those DC fast chargers. And Kroger, various other partners throughout the region that were really stepping up and helping us locate on their property. And so the U.S. Department of Transportation grant portfolio is a little bit different. We're really focused on mobility in this portfolio. And it's all anchored by our Smart Columbus Operating System, which is an integrated data exchange or data management platform. It is available. It's open source. It's built on Elixir, an open source code language. It is available at smartcolumbusos.com. And then it's also the source open source code is available at github.com slash smart city data. It's available for your use of exploration. Our program is organized in really three themes, enabling technologies, enhanced human services. That's a lot of our apps that are using the maps, and then emerging technologies. And so one of our major projects that we're launching is a pretty significant connected vehicle environment. It is about 23, 23 mile long corridor. And through our High Street, which is one of our busiest corridors in Columbus, it goes through the heart of Ohio State University's campus on the east side. Cleveland Avenue, which goes through an opportunity neighborhood, has a lot of low income residents, which were historically disturbed by a large interstate construction project, much like many communities. And then also a very diverse corridor and Morse Road with a lot of commercial, residential, strip malls, back to office, shopping, so just a broad range of different applications. And so when we were launching our connected vehicle environment and we're really getting close to launch next July, we knew that we were going to have to develop our map message. So for us, we've been looking at how we wanted to best do that. And so we looked at US Department of Transportation's ISD tool and their map messaging tool. But we knew we needed really good mapping. They have a disclaimer that says, hey, localize this. Check it out. And so we really had to get into what aerial photography we wanted to use in order to deploy this technology. So we used our Ohio Geographical Reference Information data. And we accessed several online tool, several other maps in order to really evaluate our system. And ultimately, we ended up, and I'm missing a, ultimately we ended up using the tool we went with some ground truth, latitude and longitude coordinates. And then we also had some challenges where the X and Y coordinate weren't the same on different maps. And then finally, we had to use imagery. We had to look at the different time periods of the imagery. But ultimately, we ended up being able to use our Ohio GeoGrip data and aerial mapping because it was the most recent. It was the one that was aligning with our ground truth points in order to insert that information into the ISD tool from USCOT. One of the other projects that we're launching is our self-driving shuttle. We already launched one self-driving shuttle last year. I launched actually in December of 2017 or December of 2018 and went through September of this year. It was with a company called May Mobility. And our next self-driving shuttle is being launched with a company called Easy Mile. And Easy Mile basically uses a LiDAR and to collect information about their surroundings. We set a base map and then we operate based on that information. We are deploying in one of the first residential settings in Columbus. We're deploying in our Linden neighborhood, which is an opportunity neighborhood, which presents some unique challenges from the mapping perspective. Specifically, we have a lot of interactions in the area. We have about eight or nine schools. We have a large residential population where we're parking on the street. So the self-driving shuttle is going to have to map from not only the curve line to curve line, but also those parked vehicles. We are actually installing some additional infrastructure with centerline mapping in order to help the vehicle interpret the information that it's receiving. But ultimately, those are the types of challenges that we're facing as we launch new mobility in the central Ohio area. And so I'm a civil engineer in my trade and I've been working most of my career in transportation. And I've been in private sector most of my career. I've had a stint in state government and now have transitioned to local government. And we're accustomed to civil engineers planning, designing, and constructing using mapping and survey. And what we're really being called on now is to ensure that that mapping is accurate enough to operate our transportation system, specifically when it comes to the connected and automated vehicles and the other types of apps and maps that we're deploying. Specifically, we're deploying a trip planning application as well that is drawing on Open Streets methodology. And so we're really, as a local government, we're learning. We're a little bit on the bleeding edge and sometimes not just on the cutting edge. We are hoping, as this technology continues to emerge, that there is more guidance out there. And then also that we start to acquire the business acumen and the knowledge internally to help us support what's coming. Government doesn't always attract the best and the brightest. They're going to industry. Sometimes they're chasing the dollars. Although I see many bright people in government, we need some of those industry experts in order to help us advance to the city and be ready for the transformations that are already here at our doorstep in transportation and technology. Finally, Andrew. Man of history. Man of history. I have my presentation. So I'm going to talk through a number of few patterns that we're seeing as well as some examples. I can't be comprehensive to all the things that Esri works on or we see the industry and governments working on, but I'll highlight a few that I'm particularly thinking about here. So I'm going to show these couple of examples, taking what we look at the science of where in terms of how do we not only enable geospatial technology, but enable deeper thinking with geospatial technology. But I can make sure they're muted, too. Let's see if this also works or not. I had to go under the table, interesting. Nope. Behind my head. Can you just forward? It's not advancing. So a couple of new technologies, or at least types of classes of new technology that we're seeing growing at scale. I'll go driving to some deeper numerical trends, but we're seeing, obviously, a plethora of sensor, sensor types, sensor granularities, sensor sources. Data is becoming increasingly open and available through numerous sources, numerous formats, different types of data, the use of mobile technology, so even the CPU processing power in our pockets and our watches that are rapidly growing, cloud computing, and finally, quote, big data at large. Great. So you can mute. Just background static. So this is an example looking just alone at Manhattan. And just the wealth of data, we just pulled together in a simple exploration, but it gives you access to all of the camera footage, which is not, and it's now becoming a very common thing to do in terms of accessing cameras that are placed all around cities. And this is just the publicly available ones, not including the ones being embedded in every single light pole in school all around the city. And this is just one city. So it's interesting to see now what you can do with this kind of data and this kind of information. Forward. So we're doing things like feature extraction, capturing the number of vehicles and the vehicle speeds and things like that in terms of lanes that are usage, as well as capturing things like pedestrians. This is a new ballpark where they're actually using the cameras to understand how people exit the stadium, how they cross the street, what happens when you go over capacity and people spill out of the sidewalk into the street as they're walking along it or jaywalk across the street. So now it is to help a city better understand what's really going on, not just its models, but actually helps them to respond within seconds they can change light timings. They can make the entire forest stop a red light while that crowd is moving across the intersection and they can send police off, they have to, but they can actually control their infrastructure at a moment's notice utilizing these cameras. So what we're seeing is this pattern of identifying a goal, analyzing the results, acting on it and then having the outcome occur. And this is a very common, this is simple action, but the important here is the idea of sensing and that's the trend we're seeing here is not just to this closing this feedback loop, but the rapid iteration and micro scale this is occurring. This is occurring at street intersection levels, at individuals, at paces, at mobility and motion, at millisecond responses. So what happens when you have all of that amazing data? So this is Nick O'Day. He's the chief data officer for Johns Creek, Georgia, a small town outside of Atlanta. And he's highlighting the change in government where it's not just paving the entire city in every road just because it's been 10 years time to pave it. He can utilize this data and GIS to surgically fix problems. Understand, can we fix this one pothole? Is this street repeatedly breaking? What about this pipeline in terms of this water main? Is it breaking at some periodic interval based on average temperature over so many days? So able to him to act more efficiently and with better budgetary constraints, resource constraints and actually provide better services to his residents. This is an example that just finished in Washington, DC where they didn't know there was called a curb inventory. Where was all of the parking in the city? What hours was it available and how is it being used? Yet curbs are a fixed resource that become increasingly valuable as we've heard the number of trips going up. Being able to optimize the use of the limited curb space you have is imperative for cities to be able to move cars along. So what happens is now they've inventoried all the spots. They identified temporary pickup drop off zones, PUDs, where people can reserve that at 30 second intervals. So FedEx can say, I'm gonna deliver a package of shoes. They can say, great, here go to spot four. You have it for 30 seconds. Unload and you're back in the car. They can do it for Uber drivers. So you're not picked up right in front of the building. They need to go to the end of the street. There's a PUD walking your car and out. And this is optimizing both the parking spaces as well as the utilization of the curb for micro interactions. So another trend we're seeing is the increased adoption of just the internet globally. So over 50% of the world now has access to the internet. So it's not completely pervasive, but it's essentially something which you can just assume is accessible definitely in the United States across most urban, suburban, and even rural areas now. Next. So you now have, now that the internet was just driving consumer demand, you now have smart devices which are connecting the internet at increasingly fast growing scales. The number of devices has already exceeded, quote, double the population of the world. And it's amazing not just the devices, but what data they're capturing. This is looking at one car with laden with sensors, you imagine autonomous cars sensing all of the spaces, the trees, the curb, the bicycles, the cars around them. It's called HD mapping or high definition mapping. So it's capturing an incredible amount of data just to safely navigate through the existing road infrastructure. But when you start thinking what's actually going on here is what the data can now be used for is not just navigating that one car, but now we know in real time how cars move and all types of vehicles move through our cities which improves for urban planners, not knowing just here's the number of vehicles we see per day on average or the 85th percentile speed. I can tell you Tuesday at 2 p.m. after baseball game when it's been raining for half an hour, here's the average speed. Here's how people move through our city, how they traverse, how they navigate to optimizing, changing roads, infrastructure, transit, and so on. And then look at the autonomous cars. And this is kind of another panel I'll get into is that each connected car is sending 25 gigabytes of data to the cloud every hour. It's an incredible amount of data and information which you think of not only just sending to the cloud to process it, but overwhelming every single communication infrastructure along every single roadway across the country. You multiply 25 gigabytes per hour across trillions of road trips per day or per year. It's immense, it's overwhelming. Simply put, the cloud can't scale. So what happens next? Next. So there's a pattern called edge computing. And you see this pattern go back and forth a lot from mainframes to personal computers, to servers, to the web, to mobile devices and back and forth. And you're seeing the same thing now happen in smart devices. And the internet of things isn't just something sensing, sending it back. It's actually processing the data on the device or sharing that information between one another. So we're seeing overall this pattern going from individuals working on data or individual devices capturing their data to collaborating together around them so fleets of vehicles and organizations. And now networks of organizations, ad hoc data sharing between devices in terms of making intelligent decisions at the point of both measurement and action. So really shortening that feedback loop. Mobile devices themselves are increasingly gaining, becoming ubiquitous and powerful. There's the common trope about the cell phone right now has about 100 times the computing power of the Apollo landing craft. What happens now when you can capture that data and process it on your device to make those real time decisions at the moment that you're carrying it. So one example of this is Waze. Where Waze is capturing both government data as well as road data. So it's actually taking this data and providing back to governments to optimize how people move through the city. Boston is one example to increase their traffic congestion by 18% by analyzing this Waze data and changing signal timing, so similar to pedestrians. It's also interesting as a collaboration is that while Waze knows what's going on right now the government knows the future. They're telling through Waze open data sharing what road's about to be closed in half an hour so don't route me through there. Don't cause congestion before it even occurs. Now you start mixing these things together. This is a project by David Maidman at the University of Texas for flood modeling and pardon me if it was mentioned this morning but they're able to do national flood mapping in just a few minutes based on real time emergent rainfall data. It's a 10 meter resolution but it's good indication it's something about to flood here based on our predictions and models and the current conditions that are occurring. So marrying these two things together Waze is actually taking and putting this data into their routing information where they're saying rainfall is occurring likely to cause a flood on this route. Why do you take a different route? In this case is here which is one example where in fact we can do to Harvey if people can get out more quickly but even on a daily basis having people avoid that bridge, avoid that underpass is because that information data and that prediction model that might be even be running in their car could tell them to avoid that route. And we're looking at different kinds of mobility types. This is looking at bicycling. So you have dockless bike shares and scooters which are also geolocated and sensor laden which are sharing their routing information so you'll be able to optimize both the placement of these vehicles which is occurring today but also the routing and optimization of them as they move through the city. And as I mentioned before even understanding in this case in New York City how it changes by time of day for example on a Friday which as you can kind of imagine both people go home and commuting but even if you went on later in the evening where people go at the evening where are they converging to? So drilling into the devices themselves so the idea I mentioned the wearable watches the wearable glasses all these devices that are being embedded everywhere has doubled in the last four years alone. So 52 million devices wearable users in the US alone. So what happens when you do with this what can you do with this information to augment how people actually interact with their environment around them? So we're seeing these being used for augmented reality we talked about flooding earlier in the Q and A but using it for both operational procedures for example being able to view the underground pipelines electrical lines within a road infrastructure or being able to overlay information telemetry and real-time data on the environment around you for everything from navigation, wayfinding, operations and so on. Although it's interesting to see in part of what's always fun in these scenarios is imagine the future is what happens is taken to an extreme. This is the brick iron building this is actually SNAP Photo which is a very popular consumer photo sharing app has now explored exploring augmented reality layering data on top of buildings in which people are exploring things like what happens I make my building look like pizza. But the idea here is merging these together where augmented reality might be an amazing technology but who's gonna come and download that new app? But can you get that kind of technology into consumer devices and consumer programs so it gets as accessible as possible to as many people as possible. So we're seeing ubiquitous pervasive information access through consumer services. I mentioned SNAP, mobile phones, watches, Alexa devices and chatbots and Facebook. These are two examples that we've worked on where people are using their Alexa to ask data of what's going on around their house. When's my next council meeting? What's the weather today? Which route should I take? Where's my nearest trash day? So exploring the idea of not requiring people to come to an information system so much as taking information and put it into the systems they already use. And so we're seeing a pattern of expanding GIS to support everyone, not just to the government and the organizations and the commercial agencies but also consumers, researchers, scientists, residents and students. So we're seeing ocean data for example become ubiquitously available so people can get involved in advocacy and operations, trying to end quickly. We're seeing crowdsourcing and citizen science. So taking this idea of computing to the edge to its extreme where really it's about the people themselves and how they can utilize this data to provide computing and provide feedback and answers. So this is as well another one so earlier when data aren't or sensors aren't equally distributed they've actually designed a flooding sensor cost less than 100 euros to build and communities themselves are building them, installing them and measuring sending all their data back to the city because so people can measure their backyard, their underpass areas that might not be infrastructure censored by the city itself but they can provide that data back through these sensors so they can have a more comprehensive view of what's going on in their city. We're seeing neighborhood councils start to train up their citizens on utilizing open data and geospatial technology to optimize services delivery. In this case, where should we put trash cans around our city? So an innocuous example but indicative of the pattern that we're seeing here. And you look at more broadly the global to local calls to action as well as guidelines. So United Nations Sustainable Development Goals are creating a call for increasing the availability of high quality, timely, reliable data based on demographics and geospatial and geographic location. So for example, I encourage all of you next April to join the Earth Day Challenge. It's a citizen science initiative which we're trying to crowdsource a billion data points in one day and then for the next year get people involved in analyzing that data around things like food supply, drinking water, water quality, air quality and so on. So these calls to action for accessing and utilizing the data through sensors that people already carry in their pockets through tools they might already used to answer questions that are imperative about their livelihood is something that's becoming increasingly common. So we're seeing that all over the world we're seeing organizations start up their own initiatives around these programs and projects in the data utilizing national and global data with locally crowdsourced data to improve policy and improve infrastructure. So I'll leave this up here for a second but just a few questions that I've seen that we're thinking about trying to think about the merger between or the conflation between the mapping science community and geographic sciences community in particular or those questions of geographic analysis of synthesizing crowdsourced data and authoritative and automated data. Methods for G especially charting distributed edge processing systems. How do you analyze data within each of these cells, aggregate them back together and pass back down regional and global insights, visualization, cartographic techniques for we heard both medium or mixed quality data as well as real time and emergent data. And then finally techniques for effective interactive geolocated AR and VR, right? So just because you can do AR does it actually have an effect? Do people understand it? Does it change behavior? Not just definitely an area right for exploration. Thank you very much. Okay. Thank you for the keynote address and also three really interesting panel presentations. So I think all our minds are really racing right now surrounding these possibilities. We're open for questions now. Again, please use your microphone and please introduce yourself. Those are really interesting presentations. Oh, Glenn McDonald, UCLA. Those are really interesting presentations. Thank you. I had a question and Michael's presentation, you talked a lot about hydrogen and biofuel and Mandy and yours, it was all about electrical. So I'm interested to know if you have any data on what if you look at, take a life cycle analysis of a battery powered electrical vehicle, right? And then you take a hydrogen powered vehicle or a one that you have a panc-ready biofuel. How well are we doing environmentally with the battery powered vehicle actually? The, there's a model at Argonne National Lab called the Greed Model that I'd encourage you to use, G-R-E-E-T. It's open source, it is recognized globally as the by the best life cycle assessment tool and like many things, it just depends on what your assumptions are. So in the case of electrification, it depends what your grid resources are. So if you look at national average grid levels, you're doing quite well in a greenhouse gas reduction basis electrification. If you look at specific sub regions, most regions you're doing very well, there's only a few that currently have really high penetration of coal, but that's not the case. And certainly if you look globally in the future where I'm constantly at meetings and discussions where I hear utilities, states, others with goals of north of 80% renewable penetration. So depending where you are with nuclear, if you have a very high level of renewables and certainly globally, the level of renewables are approaching already high levels and are gonna continue to grow. Electrification will do very, very well. It will probably, of the different pathways when you look across them, biofuels and electrification probably are, have your best overall pathways. Hydrogen, if you make, today you make hydrogen from steam methane reforming from natural gas, so it has a greenhouse gas reduction versus petroleum, but not as good as you make it from an electrolyzer, but it's not cost effective to make hydrogen through electrolyzers today, so we're trying to work that cost down. If you can do that, and then of course you have to have the electricity from a renewable source as well. But in general, all of those technology pathways today are strongly greenhouse gas positive, and in the future, they look to be much more so. Yes, hi, I'm Grady Thule, 3D Ideas on the Mapping Sciences Committee. So to my colleagues on MSC, we have kicked around for a couple of years now just our thinking about route finding and autonomous vehicles. And so Mary, you being the DOT person here, I'm gonna ask you a question actually related to Mandy's presentation. So, Mandy, you outlined beautifully the hard work required to sort of fix and constrain the route finding in Columbus, right? So I'm wondering is there, is there thinking at the national level about scaling this, and how do we get to a consistent set? For example, just recently I was in Huntsville and I often will drive, let my Ford vehicle navigate while I've got another something else going on my iPhone, either Google map or IMAP, and they very frequently don't agree. But there was a situation that I personally came into in Huntsville two weeks ago where if I had sort of blindly followed what my Ford was telling me to do, I would have run into a road that didn't exist. So how do we get to a national program that addresses this or is there one? There definitely is. We've had a huge focus on automated vehicles for quite a while. We've just put out and released the winners of $100 million invested in automated development technologies. We are also on the transportation side, we have something called the STAR plan, the Strategic Transit Automation Research Plan, and it's available on our website. And it articulates all the various elements that we think are really important, particularly when you're looking at transit automation and public transportation. So an area that we're very concerned about right now is bus testing. We run bus testing out of the Office of Research. Right now we test a bus really for durability and some safety features, but we don't do anything to test software. And now having come from the technology, high technology industry, and you just look around, we're going to have to reevaluate how we test vehicles with the new technologies. We have partners, luckily, that have a lot of capabilities in that. Some of our partners have a lot of capabilities as well as in cybersecurity, which is going to be another area that we're going to have to look at. So I would say that absolutely, it's one of the top areas that we've been focusing on. We just did, we've done a number of big events at DOT recently. We've done them on automation. We just did one on accessibility, kind of why I was talking about this, because the secretary herself just announced something called the Complete Trip Deployment Program. And as a lot of the leaders in the disability community talked about, when you can fix the challenges that they face, it benefits everybody. And that's one of the reasons why we often like to talk about it. So I hope that answers your question. So I'm also just interested in the legal aspects of this problem. So from a mapping point of view, we often sometimes refer to the difference between a chart and a map, in that a chart is something with some legal implications that you're going to navigate a vehicle from it and it better be right. So that's kind of the flavor that I'm asking about here is how do we know this right and who has liability if it's wrong in a future context, of course. Well, I think those are the types of very complex and important questions we're going to have to answer. I don't think we have good answers right now, but that's certainly going to be an area of inquiry as we look at all of the governance aspects because oftentimes the technology is, I wouldn't say it's the easy part, but when you deploy it, it's often the governance factors associated with deploying these technologies that get in our way, as well as user adoption. So I think that's a wonderful point and it's one that I hope that you'll continue to ask us to address if you're not seeing us address it. One added comment on that. I think when you look in the future, one of the comments that Andrew made, the technology is able to kind of create its own maps in real time while it's actually doing what it's supposed to be doing to advocate other things. I think there'll be a question out there of how do you share mapping data? Is it that individual companies are improving their own maps? Can they share those maps or not? Are there some that are better than others? There's a lot of nature to that because the map data will be critical to a lot of the self-driving technology. Go ahead. All right. So I'm just curious. So there was an earlier discussion about your vehicle charging stations and in terms of a life cycle and moving a smart city forward, have you looked at or developed any kind of policy or workflow to talk to new construction versus existing construction and how that cost efficient, the coefficient must be radically different for retrofitting. How do you work with facilities owners to encourage the installation and the proper operation of these things? Yeah. So a couple things that we've approached. Michael. Couple things that we've approached from a policy standpoint. First of all, it's about $20 for the conduit to install if you're building new construction, if you put it in with the building, with the parking garage. It's about $200 a linearal foot to install post. So about a 10-time cost differential just in a parking garage type setting. That's where we built the most infrastructure. We are just beginning to start our outreach with the residential construction as well as the commercial construction folks to determine to set a new construction policy with our building and zoning services to help make new construction EV ready. At least at a minimum put in the conduit to run the wire, set the panel up from the get go to accommodate the charging infrastructure. And so that's part of our demonstration program and our learnings is that we wanna go out and actually get that implemented into our zoning code. There's also, when you look at the non-residential space, the charging power levels are changing and are gonna change. We're working on extreme fast charging. Today, 50 kilowatt, maybe 110 is your higher level. We're looking at 350, well above that for trucks. As we've talked to the people who are spending billions putting infrastructure in place, they have largely been able to figure out how to future proof that to people like Electrify America utilities. That has not turned out to be as big a problem as we would have thought it was. They'll be smart about putting in enough now and upgrading later. Yeah, as an EV owner, it's a big location problem. Again, I didn't identify myself, my self-marked record OGC, Open Geospatial Consortium, I think Science Committee, but I think this is a huge location challenge. One of just locating these devices, but also ensuring that the capability is there. Indeed, I guess the automation and apps are moving in that direction? With respect to the EVs, I mean, we've largely focused on residential and workplace charging deployments. 85% of charging is done really at home and then the remainder is at the workplace. So that's where we've gotten a lot of leverage with respect to our, with the $10 million that we got from Paul G. Allen Foundation, they really, they'd already paid for a bunch of infrastructure. They'd already paid for a bunch of infrastructure in whole. And so they wanted us to really incent placement. And we knew with almost all of our new construction in Columbus right now is rental, it's multi-unit development, that we really had to be in those locations and then also in the workplaces. Can we have questions from Dan Brown and Buddha Baduri? Dan? Yeah, Dan Brown, University of Washington Mapping Science Committee. I'm struggling with a conversation we had earlier in the morning and I will admit to being a little weird in that I'm a pedestrian. And all this talk of making vehicles easier to move around an urban space make me nervous. I'm already scared sometimes to walk around the urban environment and this notion of walling off pedestrian or somehow making sure that the world is safe for autonomous vehicles is not a world that I want to live in. And so I guess I want to go to the questions of how we balance livability and mobility. And is there a mapping, planning element to that that it seems as though there's certainly, it's a geospatial problem. But it's not necessarily one that I've heard anybody talk about. In Columbus, it's relatively, so 85%, 89% of people get in the car every morning and go to and from work in Columbus. It's relatively easy to drive. A lot of the conversation for us right now is getting more people to use public transit, which ultimately is going to require them use some feet to get there. I would say that we do a, I'll let Harvey affirm this, but we do a less than a job of getting our roadways really well equipped to accommodate all the users, including vulnerable road users. It's very much part of the conversation, but, and I don't want to really pivot the conversation completely, but for me as a city leading the Smart City Challenge, it's really been an opportunity to work with researchers like Harvey and others that are bikers and pedestrians to really start to understand how research, vulnerable VRUs can actually help us drive the conversation a little bit better and really start to transition our thinking. So we as a region, I think, are really pivoting to focusing on transit. And by extension, I believe that those conversations were right for those to be driven in a little bit better way, but you're absolutely right. One of our conversations with Anissa has really been the interaction between AVs and pedestrians, bicyclists, and ensuring because we are in that first real residential deployment in the country, that that deployment will produce a lot of data, but ultimately I want to see more people using their feet and getting on their cars, including myself. And if I can follow up that question before I turn over to you, Pudu. I'm wondering, and this is, oh, did you want to speak first, Mary, or? Oh, no, I can wait after that, but I don't. Okay, apologies for jumping in there, but it's a related question. I'd like to know what the implications are of this for basic street design. I mean, that's something that I don't see in all the smart technology stuff, as we're trying to pro-information technology data and computation these problems. How are we changing the fundamental way that we design streets so that we can accommodate a wider role of users, a wider range of users besides those automobiles? Is there some way we can use this data to figure out how do we make our streets safer for the Dan Browns of the world and the Harvey Millers, for that matter? There actually is a lot of work going on in this area, but I think we oftentimes don't talk about it in concert with high technology discussions on automation. But if you think about transit-oriented development and you almost think about it, it's interesting when you look at history. Many, many years ago, we had street, the cities really were people that congregated. We didn't have any kind of vehicles and the horse and buggy came around and then the cars came around and then we lost our streetscapes to pedestrians. Now in many places it's coming back and a lot of communities, and in Denver there's a big project that they did and we've increased the access to pedestrians and walkways and we've reduced the ability to park cars and even bring cars into many areas. So I think that's happening simultaneously. You've got the Complete Streets initiative that's been going on for a lot of years and then we have small business innovation research projects that are looking at how do we ensure pedestrian safety with buses in public transit. So I think it's happening, but it's an interesting point you're bringing up that we don't talk about it when we're talking about automation and maybe that's something that we should change. The automation fully automated vehicles certainly have a long way to go technologically. But if you gave me my choice of living in a city that had no automated vehicles or being a walker a lot here in DC or very, very high level automated vehicles purely from a safety perspective it'd absolutely take the automated vehicle one. Absolutely, because to the degree when you get automated, a lot of the promise of automated vehicles on the drive is the underlying safety benefits. Now, I don't know how many of you've driven in a fully automated vehicle before, but I mean it's gonna be like driving and with the safest, most cautious driver in the world, very steady as it goes, very, so it's a very non-aggressive and there are a lot of challenges there because well people accept that or not. It's not how I know most people wanna drive, but will they see the safety benefits of it in the sensor-based technology has the ability to deliver a sense of pedestrian probably more accurately and consistently always paying attention in the human driver. The question now is how do you take that one capability and integrate it in with all the other vehicles doing it and I'm gonna stop because the person in the car behind me don't expect me to act like that are they gonna hit me other things? So lots of questions in there, but I think for pedestrians, the promise and the opportunity is actually pretty good. Okay, Boodoo's been waiting patiently, Boodoo, please. Boodoo Bhaduri, Oak Ridge National Laboratory. So I have a clarifying question for Mary and then two other open naive questions as we committee members are supposed to disclaim for the disclaimer. So you mentioned that 81% of the counties have some left form of public transportation. I would like to know what is included in that public transportation definition because I'm trying to imagine where I live in Knox County, Tennessee. And as far as I could think, there is unless you are counting Uber as part of the public transportation, it's very, you wanna address that before I ask the other question? Sure, sure. I mean, I cited the source of that in the slide and I can go back to that, but it doesn't mean the entire county. It means a element in a county. 81% of counties have some element, some subdivision covered by public transportation. And if you think about buses, we're not talking about heavy rail everywhere, commuter rail, but it is more pervasive than people realize. Now it might just be on demand flex route. It might not be what you traditionally think of as public transportation that you would get in Washington DC or New York City. It could be all on demand and small buses, hailed. Yeah, well, peer transit when you have an urbanized area within the catchment area, three quarters of a mile, you have to provide transportation, but we use the term on demand when we're talking about all non-route specific, fixed-route specific. I'll look up that. Sure, thank you. I have two questions. One that you just mentioned that I did not hear anything about rail. There was once a lot of discussions around platooning of autonomous vehicles. And I quote our chair, Harvey Miller on Twitter and Harvey said, those are called trains, that where you are platooning cars on tracks. So, and I think that's a very good point. I just would like to understand where do we stand because every time I try to look up the train fare from DC to New York, it seems like I can fly for less money. The other thing is maybe for Andrew and the rest of you as well is I am pretty impressed with the way the public-private partnership is going, especially the ways examples. So I've been following that. It's very powerful. The question is when it comes to policy, we have to go to authoritative data sources like USGS that produces foundational data base maps. You have to go census for population. So how are we going to change this paradigm of falling on privately collected data for informing or changing influencing policy? And the second thing is, what are the cybersecurity measures around these modern technologies? So I was shocked to find out, and Michael, you were, you and I were there at the meeting at Smart Mobility or Summit that Luke Vasa, who's the executive vice president for engineering, told me at Lyft, they have almost no investment on cybersecurity. So where is the assurance? Who is investing in this data quality assurance? I think you said the authoritative data. I mean, by type, by which layer you're talking about, the source of that might vary, right? A lot of agencies will readily say they're not the authoritative source of that data. I'm talking about HD mapping. Like when you're mapping HD on the security side, the US two questions. Yeah, not on the security side, just on the data quality assurance side. Yeah, authoritative data. So I always speak to the first one about where are the data coming from, right? Like US DOT doesn't authoritatively maintain the roads, each road, at least local roads, right? Nor the necessary, the source of those road datasets, the aggregate national one. Recently, there's also transportation for the nation, did it, you know, no one knew where all the buses were because they're maintained by the local transit agencies. There was a call for data sharing from those transit agencies to the US DOT to making national map of all the transit, which is amazing, right? So, yeah, I'm excited. So the pattern really is who maintains the infrastructure that then maps it, right? It's nominally gonna be more local, not national, right? At least take that pattern. So the question is, and what we're seeing is the, I mean, that's our SDIs, one of their visions for those wars, Spatial Data Infrastructure. Take all the data that's being managed at a local level and aggregate it up dynamically, which is happening, it's just kind of being very ad hoc. And there's a couple of number of things going on there around data standards, open data has been a big change in that, I think there's gonna be some more, we're gonna have calls to action from national agencies to local, like the transportation for the nation is one example saying, we want your data, here's how to report it. And once you report it, we'll share it back out in a very short turnaround as a national map so that you know how your transit bus lines connected to your neighbors, right? So ideally it facilitates a collaboration there in a way that's much faster than the old, what you used to call the high field. If anyone's familiar with the high field data set, it's a national 500 some layers but it was used to be gathered by CDs and DVDs. And they just finally moved to a web services model where the data they can aggregate from local sources and they can publish as a web service. So the goal being if a road is built or changes from one way to a two way street within an hour, the national map is updated to reflect that by creating data aggregation. So that's most likely is what I was referring to is that idea of quote edge computing but in a different way where the edge computing is each local city and county maintaining their data where we're pouring it up in a national map sharing that data back out in an open loop way. I just wanna suggest that we're at a 415 right now so we could broaden this to a broader discussion surrounding all three sessions but just take these people off the spot a little bit unless they enjoy being up there in the hot seat. But yes, we can broaden discussion right now to talk about all three sessions today, the flooding, the mapping, the Arctic and the smart communities. I guess I'll speak to the cybersecurity a little bit. The Department of Energy has had a mandate for the cybersecurity, certainly the energy system of the country but because of that capability much more broadly. So for example, we were just undertaking a broader cybersecurity threat assessment on behalf of both us and the Department of Transportation. We're gonna kind of get a read out of that in the coming weeks to DOT and DOE leadership. But really that's gonna say what's the current threat assessment? We're there, not enough work happening. What are those types of things we should be doing? So yeah, you could spend all your time and all your money on it. We are investing in a piece of that but it tends to be more like I'm thinking like the electric side and less on the core, let's say a roadway piece of it. I think nobody wants to jump on it, maybe. What do you want to talk about? What's becoming smart about railway systems or how is that evolving to be part of the solutions for the future? Well, I don't know about getting into the details on the technologies but certainly, we're trying to move to more of a multimodal world where you've got heavy rail, then you've got now potentially automated vehicles, integration with the private sector. I would say that rail is becoming more and more automated. We're also looking at automation to make pedestrians safer and also anyone who accesses a system safer. We have a real problem with suicides. Public transit is actually very safe. Our biggest problem with fatalities is suicide. So if you go into Hong Kong as an example, their heavy rail system shut, you couldn't jump into the ongoing train if you wanted to. So we're looking at that also from a safety perspective. So I would say there's a lot going on right now in so many areas, whether it's heavy rail or high speed rail or hyperloop or transit automation, but how we bring it all together it's all local decisions as you all know. And that will dictate, I think, a lot of the progress, if you will. Now, on cybersecurity, just a related note, an area that we're gonna be spending a lot of time on is payment integration, multimodal payment integration and a critical component of that is absolutely security of personally identifiable information, of course, is very critical. And then as public transit agencies start to connect with the Uber's and Lyft and other partners, the data sharing component has risen to be one of the top three areas that has to be addressed and you have to have agreements in place and some places are having more success than others are, but it is an area that we're looking at kind of pervasively. So there's a lot of implications of cybersecurity in the new future of a transformed public transportation system. I cannot, hyperloops come up a few times and it's often a point of discussion. We have a report that is, it's waiting final clearance at OMB, Congress required reports to be back to Congress and of course made public on two things, the energy implications of hyperloop and then some level of transportation analysis of it. But the energy implications are pretty huge. I mean, basically the first hyperloop systems as they were envisioned when we started the report, we basically said these will break the grid or you'll have to have a significant physical upgrade to a lot of equipment, like not putting power but literally the turbines because of the pulsing. By the time we ended the study, the two major hyperloop companies told us that they've changed their design because they realized that this was probably gonna be the case and now they're largely large electric vehicles. But from a, I would say our conclusion is that it is unlikely to be a transformative, massive transportation, it's gonna be a very, when you look at where the economics of it makes sense, it will be a limited scope for relatively, you know, by a high cost type of service but where it makes sense for, you know, probably wealthier clients. So we've talked a bit about, I'll quite a bit about the role mobility, smart technologies and geospatial data. I'm wondering about the other side of the calling of mobility, which is location. How do we use all these data, all these technologies toward the planned cities that can be more supportive, supported by a public transit and walking and biking forms of active transportation. So how do we connect those two using these technologies, land use and transportation? I think Columbus, Ohio is a great example right now with our Insight 2050 report. We're really as a city, probably for the first time in a very long time looking to drive where development it goes. And we are looking right now in our North West corridor, we've identified five other corridors where we can drive development and density, serve the area with frequent public transit, primarily bus rapid transit, incorporate smart technologies, so connectivity, fiber, et cetera, and really drive people to those corridors that can support public transit and start to transform the way we travel in central Ohio because we, at central Ohio, we're expecting a million more people by 2050. So I think it behooves the public sector to partner with the private sector in order to create the business case, establish it and help drive those corridors and make them attractive to developers who are really right now setting the land use policy for many Midwestern cities like Columbus. I think public-private partnerships and transit-oriented development, we have lots of examples of that all around the country, and that's where you really start to get the land use components along with how are you driving economic development, how are you also enhancing mobility, where do we have to fill gaps? And we have example after example after example, and Build America is also doing a lot of investments now in that particular area. So I think there's a lot of really good work and a lot of jurisdictions we can point to that are doing that extremely well. From a research side, one of the things on that large integrated modeling flow I showed up on the top left, we've integrated urban sim into that and updating it to Paul Waddell at Dot Berkeley. For those of you who know, Paul is one of the researchers on that project and our goal is to be able to have this as something we can look at long-term urban planning implications in the 10, 20, 40 year time horizon to see what are the urban planning implications as different technologies change. Do you add high levels of automation? You know, what happens to people that further out? Do they cluster more? What are all the, no, again, that secondary impacts? I just want to comment on that point and since you guys are sitting up there on the hot seat, I guess I'll take advantage of that. One comment that was made earlier that more mobility is better. I don't know if I necessarily buy it. We have lots of technology that allows us to move information and interconnect and interrelate in ways that don't require mobility. And how do we, so decoupling energy from transportation is one thing, but decoupling productivity from mobility is another thing that seems to be a valuable thing to be thinking about. It can get very full, it's all very quick, but if you think about, okay, with new technology, people work from home. It's true as so. We think of, aside from the people think of mobility, I think very tightly of commuting to work, but even if you have, you have a growing population and the needs are far outside of work, right? And again, will people, as people have more time, do they then travel to use it for personal efforts, things like that? Also, if I'm at home doing all my work, I'm still, am I now getting good shift to the house instead of to offices and there's good mobility and needs for good, you know, generally speaking, I think if you have a growing GDP, I mean, it is possible you can have a massively decentralization of an economy and therefore you don't have to ship things as long distance, but it's hard to imagine it. And as a growing population, again, it's hard to imagine not having between the both personal and some amount of work increase need of mobility. So, but it is something I think I'll tell you, could the trends change far enough that you have all these growth of population, growth of GDP, but yet actually physically less movement of goods, less distance. You're gonna have more goods and more people so that they have to start moving not as far. We don't have a lot of good examples of that happening or time where they move not as far. I would say right now, there's still a lot of people that do not have the mobility that they need. And until we fix that, we need to continue to focus on it. We've done a lot of work on health and transportation, the relationship between health and wellness and access to a mobility resource. So I think that's really critical. It's like anything else, we're probably going to continue to go down the path of not having to travel in certain cases, but then in other cases, you're going to also want to travel. I mean, I think about older adults, as they get older, their world contracts because the people that they know start to pass away and then they sit at their home by themselves and that is the absolute worst thing that can happen to a person is being isolated like that. So, I'm not going to go down to philosophical areas because I'm speaking on behalf of my agency, but I do think from where we sit, we still have a lot of communities that tell us that people cannot get around. And so that's why we're focusing very heavily on enhancing mobility. I think that makes no sense, but I don't think... Oh, okay, I'm sorry. All right, as I've been listening, I've been struck between some of the common ground between the discussion of transportation-related issues and the flooding-related issues. And two of the points that really strike me out is, in large part, we're looking at retrofitting, in both cases, we're retrofitting existing cities for smarter streets and safer places and different forms of transportation. And then in the flooding issue, we, people love living by the water. And so these places, the infrastructure, the built infrastructure is already there, and we're having to look at how to retrofit that. So I'm thinking, as I've been listening to this, I've been thinking about how a lot of the mapping, geographical applications we've been talking about really apply in both areas as ways that we need to, things that we need to employ as we do all these retrofits. The second piece that I've been thinking about in combination with this is just, man, what a cultural change. If you, our whole society is so much built around the individual automobile that as soon as you try to, I mean, those of us who try not to use our automobiles are oddballs in this society. And we're so built around the automobile. I mean, if the price of gas went way up or became unavailable or somehow people couldn't use it, there'd be people stranded all over the place in suburbs and who couldn't get to anything they need to because of the way the location has grown around the automobile. So to me, this is just an enormous challenge that we face on both counts. Yeah, I was gonna riff a little bit off what Dan was saying because I think that by looking at transportation by itself, and I think there are mobility issues for some people, I walk a lot. I had, I picked a neighborhood to live in here in the suburbs of DC, inner suburbs where I can walk to just about everything I need. And as I'm getting older, that's fine with me. I can get food, I can get to the doctor, the pharmacy, the bank, the post office, all those kinds of things without getting in my car. That's not to say I don't do it from time to time, but I try really hard not to. I have an almost 12-year-old car that has less than 50,000 miles. So I don't drive very much. But I think we're not thinking about some of the, there's some cultural changes that I'm seeing which people working from home. 20 years ago, nobody worked from home, okay? Very few people did. Now it's kind of a thing that people do. We're not all commuting to work and back. The commutes are not from the suburbs into town. They're from one suburb to another. Edge cities, the kind of satellite cities around the big cities. The patterns of land use are changing. Several cities, big cities have either abolished or very much changed how they do single-family detached residential zoning. And they've said, oh, you can have those mother-in-law units and you can do this. You can put a second unit in. They're changing that whole pattern, completely. And more and more elderly people are choosing to live in one of those little mother-in-law units out back of moms, out back of one of the kids' houses or in the neighborhood because it connects them to a community. I think we need to think about the communities we're creating. I think they're very different than they were when I started out as a planner and have come up through all of this. I think the geographies have changed radically. And we're not, we're thinking about, well, how can we get more automated cars out there so we can all ride around in our little pods? We're not thinking about how do we wanna create communities that we can live in today and not segregate the elderly in warehouses and not keep kids out or keep kids in or whatever. But how can we make communities that we really live in? And what does that look like for mobility and what does that look like for zoning and transportation and planning and all of the geographic technologies that we have to support people working from home but not isolating them? I'm trying to think about this in sort of a bigger way than just these kind of, I mean, the pieces are all really important and it's not that we don't think about them and shouldn't, but I mean, I'm having a hard time with them. I would say part of it's not just thinking about the whole system but also thinking about short-term versus long-term decision-making. So what are the steps we need to take now to make this transition to a different type of community recognizing that for a while it's gonna be painful for some people as we retrofit our cities. Can you explain Jevons Paradox with respect to providing mobility to people? What would you want me to now or? Well, I think it's relevant to this point that we have people who need mobility. We need to provide people mobility but when we provide mobility, we create the need for more mobility. Jevons Paradox induced demand essentially by responding to the need for demand, we generate more demand rather than thinking about the system and inverting it and saying let's reduce the demand generation. Let me, I think- Can I comment on one thing I didn't think about? If you- If you told people 25 years ago I'm gonna automate banking, they would have thought, oh, I'm gonna maybe have go to that teller instead of our human there, there'll be a robot doing that same thing. They would never have been able to think, I'm gonna use something called Venmo and be cashless and do these other things. And I would say when we think about mobility, automated cars get a lot of attention but I think we should think more broadly around automation in mobility and there's ways you automate that mobility that's nothing to do with automating the cars that exist today. It's maybe a little small device that's bringing food to someone that's a small, little automated robot device or things like that. There's a lot of things that, and some of those things in my mind could actually be very helpful for that livable community. So, I think Doug Richardson had a question. Doug, please. Do you have a microphone? Let's get the microphone over there. Yeah, it seems to me that there are a couple of major challenges. You might not be on, Doug. It seems to me that there are two main, they're two big challenges, not the only challenges to a lot of what we've been talking about today. People have alluded to the data quality, data accuracy, and how can you ensure that? I've been in the business of trying to generate, do mapping, real-time interactive GPS GIS mapping since so far ago. But a lot of what, and people toss around the term of authoritative data. Authoritative data right now means someone who got a contract and went out and did the work and had some credentials and so forth. But I think that really we're gonna be looking at really high precision accuracy for these kinds of automatic vehicles and so forth, with lots of sensors on them. And I think we need to really take an approach that is basically a scientific approach to developing those data sets. We really need to follow any other type of data that's collected, except maybe in many cases, geospatial data, goes through, we'll look at EPA for example, if you're measuring air quality, you have lots of steps, you need to have a data assurance plan when you start. How are you gonna do this and what are you gonna do? And that's gotta be agreed to in the contract. And so when these DOT contracts go out for this sort of thing, you gotta really have a data assurance plan required. And then you have to have QA, QC checks on a regular basis and that has to be specified. And then you have to make sure that you're calibrating the equipment that's being used. If you take a scientific approach to the data, you can get really good data that is really authoritative. It doesn't matter whether you got, which some firms say is they can do this and in other firms says they can do that and so forth. So I would really recommend that we apply science to our data collection particularly now when inaccurate data can be lethal in these kinds of situations. The second point I would make and I'm not saying that is that there is a yawning gap between federal laws and policies related to data confidentiality and privacy and what's going to be available to be accessed with these new systems. And I'm not saying that it's a good idea or a bad idea that we have these laws and regulations in place. But I've been on the NGAC National Geospatial Advisory Committee for quite a long time and chairing their data privacy and confidentiality committee. There has to be some fix between that. We have to figure out what we have to tackle that issue because right now it's going to be very hard to meet the privacy and confidentiality data requirements of our laws and our regulations. This is a fact. And so I think that there's a lot of work needs to be done there. And we also have to face the fact that geospatial data is different and it has unique confidentiality requirements or characteristics inherent within it. That's your location and so when you're looking at geospatial data as opposed to most other data that's generated, most other data that's generated when you visualize it, you get a chart or histogram or a graph, et cetera. When you visualize geospatial data, you get a map with features that are generally recognizable to people who know those areas and so forth. So I think we needed to look at what are the unique characteristics of geospatial data relative to the confidentiality and privacy laws and regulations that we have. I will tell you this, that point is recognized at a federal cross agency level. There's a effort to develop a cross agency federal policy around automation connectivity that DOE, DOTE, DOE and many other agencies in the part of the White House and privacy is definitely one of the things we've talked about and we said we'll need to be included in that new policy statement. Comment? So I wanna do follow up on something Dan, I think you said, so there is one thing that I'm not sure we explicitly talked about or not, which is what is the impact of geography or geographic data on travel in the context of technology. So I was surprised to hear from the research that Pat Mokdarian did for the longest time at UC Davis. I think she's now at Georgia Tech and she showed data and seven reasons out of 10 that how the proliferation of international data and communication technologies have skyrocketed travel exponentially. And one of the arguments that she puts forward is the availability of the devices and access to geographic data through those devices to platforms such as Google Earth only feeds the curiosity that makes human more mobile. So and we do not settle for augmented reality because very few of us open up a browser and look at webcams to experience the beach, right? We don't, I don't think anybody in this room does that goes on vacation from the bedroom with a browser. And that's essentially what has been driving this travel behavior with a global scale of the economic growth fueled by this data accessibility that geography has largely influenced. So it has a lot to do with the increased mobility. You're getting to as a social, I'm Harvey Miller again, or as a social scientist, you're getting to one of the core problems with mobility is that mobility is what we call in social science is a collective action dilemma. So mobility is perfectly rational for each individual person to do travel as much as they want. But when everyone does it, it's a collective disaster. And I think that's one of the things that we need to figure out how to connect with all this data is individual decisions to collective outcomes and vice versa. And that's a tough nut to crack at because we're talking about people's self-interest and having to make sacrifices for the greater good in their mobility choices. It's not an easy thing to do. That's my, Bill, did you have something you wanted to? I'm getting used to this thing. This is something that your committee does or our committee does. Well, this is across, yeah. Our panelists are being cut out now. Well, actually, it's something back to the panel. I bill select the city university of New York. So I always, in this whole concept of smart cities and sort of the relative role of emerging data, I'm some of my comments just sort of come from experiences with the city of New York. And it seems in some ways, I guess over the last, let's say 10, 15 years as this topic has emerged, particularly the last 10, but even up to 15, or probably in some cases more. The concept, I think is sort of, in some ways become complicated. Like at the urban scale, a lot of neighborhoods and communities that I work with feel that the smart city technology is something done by Google or something done by the city. They have some capacity. And in some ways, it's sort of a simple view. It seems like these sort of buckets, at least as the perception that I'm hearing, these sort of buckets of data that's emerging. I mean, part of it is stuff that the city does sort of behind the scenes, like monitors, maybe sewage and water use, or the utility looks at sort of peak demand loads and that stuff is very, there's a wall behind that. And then there's of course all the Google sort of, urban myths about like, you enter into a building and suddenly you get an ad on Google about that building, these sorts of things that people sort of feel. And then there's also the citizen science stuff, which is very empowering and the like. But in some ways, the sense I get is that, as it sort of plays out in the everyday lives of, even city managers, but also residents, that these are sort of three separate buckets. And I guess my question is, one, is that a valid assertion? But also, are there ways in which, there are ways to get through those membranes to have sort of meaningful exchange between these data sets? But in some ways, it sort of speaks to this issue of technology versus sort of the role of data in everyday life and social science questions. So I guess it's sort of like, are these three buckets really kind of present? And then are, if so, are there ways of getting through them? One thing we run into a lot of, I'd be curious to get me into this perspective here. So I'm actually in a city, an operating city, but much of the data that we encounter around, a lot of these areas of transportation are all in private hands. And it's very, very hard to get, your hands on it makes research very, very difficult. We spend a lot of our time figuring out how to get good data sets out there. Now there are, so things that are in the public realm, there are some things, but a lot of things of new technologies are based on some level of commercial service. And therefore, and especially in this space right now, because it's changing so rapidly, everyone's very afraid of, is the data that I have my competitive advantage, therefore I don't wanna share it or not. We talk to people like Uber and Lyft about that quite a bit. And they're one hand, they wanna share data to help figure out how to make their systems better and not just make more money themselves, how to make it better in the context of the society they're operating in, but then they're worried about sharing. So that is I think a huge challenge we're gonna have to address, but here's what you've found in Columbus is you've been trying to do some of the stuff. Yes, all the data's in private hands. We have been successful in getting access to private data through our trip planning application that we're building that will ultimately have that common payment system. We basically, as we continue to talk to the shared mobility providers, the TNCs, the scooters, and the micro mobility providers, we came to an agreement that they were already using open streets methodology of anonymization. And so we basically adopted what they're accustomed to so that we can have some insights into how people move in our community using private transportation. We already have access to our GBFS feed for our Central Highway Transit Authority, our bike share service. And so we're starting to get a better picture although we've done a very soft launch of Pivot because the common payment portion doesn't come until very late March of 2020. But nonetheless, we're starting to see some mobility patterns with our users. You can download Pivot on the App Store or Google Play. It's available. So I think as more, we didn't know what we didn't know when the scooters dropped on us last year, we were asking for every piece of data under the sun. All we needed was an API with a service to allow us to put a geo fence around it in order to manage the permit. So we as cities were asking for too much. And I think as more and more people start to understand the private sector and as you work and you really listen to them, they really want to have a win-win situation and for it to be beneficial to all of you, all of us. But we ultimately have to understand the business protections and we really have to acknowledge that they're there. And as public sector, we don't always want to admit that there are very real proprietary implications for exposing that data. Yeah, hi, Glenn McDonnell from UCLA. So I want to follow up on Doug's comment and then where this discussion's going. And this is in terms of confidentiality of data and the use of data. EPA has before at the proposition that you would not be able to use confidential medical data and that regulations and policy from EPA would require non-confidentiality of the medical data which would throw out most of the longitudinal studies which are used for air pollution. And things like, for instance, the incidence of particulate matters, a long transportation corridor and pollution like that. I'm wondering where that might go with this where we are striving to keep confidentiality of people's travel patterns and where they live and where they go and all that. And yet there is a move, at least in EPA, to say that data is actually not gonna be allowed to be used for EPA to develop new regulations. I can say pretty safely neither Mary or I can comment on EPA and that specific issue. Yeah, but you know, something in a general sense, this is a challenge, right? Privacy is obviously important. It's important for individual people yet a certain amount of data is in the public good as well. Those are by two very accurate statements. How do you balance them? Yeah, hi, Grady Tool again. 3D Ideas Mapping Sciences Committee. One thing I didn't expect, it's been such a pleasant surprise is to find the connection between all three of these sessions today. So Harvey, I'm gonna zoom out and Caroline, I'm gonna zoom out here a little bit. We started our day before you all arrived with a brief conversation about that recent paper indicating a underestimation of the number of people at risk for flooding in the future as a result of data issues. And I don't know, is Sandra still here? Or did she live? And then she comes in, boom, the very first presentation quotes the same paper. And so it dawns on me now listening to you all that you are making your agency anyway, are making some fairly significant projections about societal changes based on environmental data and assumptions of personal behavior, people, location of people. And so we come back to what I think is the problem we all know in the geographic sciences that the data is critical. But I do want to ask you a little bit about whether, I mean, the level of confidence that you have in these models that you're running. I took a lot of notes from your very excellent presentation, but I'm not familiar with these models by name and I'm gonna go do a little digging in and try to get more educated. But I just will leave it at you. You're speaking very authoritatively and believing these models. So I hope they're very good. I think the different levels of accuracy on different pieces of it. Some are, some can be directional and in some case, like if you're trying to understand if you have poor technology all changes, are you moving in what direction? Up or down, right? That would actually be an improvement in many cases. Never mind the absolute. At some, we're at the point where we're actually starting to, we just launched a $6 million contract with a place called the American Center for Mobility. We'll run massive automated connected vehicle mobility testing, proving ground. To basically go through and do more physical testings we can now calibrate individual pieces of the model to get it to understand accuracy or not. I think you've got to take all of these things with a grain of salt, but simulation does allow you to to these understand interactions of things and impacts like, wow, when we change this, I didn't think this thing way over here was gonna change. Why is that? Well, it's because we assume these things and then you can ask the question, our approach to that to then say, huh, those assumptions are really important. Are they accurate? Do we know them or not? Can we verify that? Maybe we need to do a research project to develop something better on that. So we are taking it very much in that mindset of try to understand interactions and multiple effects. And we also do a whole one-fifth of the program on behavioral science because it starts with individual behavioral science of pieces. And when you look at that, a lot of the things when you do the type of modeling, you're using distributions of people's behavior, distributions of value of time functions in you. So you're not assuming you want to operate the same way, right? But there's some distribution of things and that kind of averages things out a little bit. It allows you to be a little bit more accurate maybe, or not as sensitive to maybe if you're inaccuracy, put it that way. But now, yeah, I'm sure it's inaccurate. I mean, right, you have to go in the center. The question is, right, is it, but it doesn't improve your knowledge, right? Yeah. Good enough to make some progress, right? Yeah. I think we want to start wrapping up pretty soon, but there's a question over here. And then we want to let these poor panelists off the hook. They've been. They've been a hero. Maria Zemankova, National Science Foundation. And at the end of the day, it was a fantastic, fantastic presentation. Woodhoo brought up trains. It occurred to me, nobody brought up ships, floods, changing coastline, energy. Are we going to have electric ships? I really don't think so in foreseeable future. Seattle was electrifying their entire ferry system. Cross Atlantic or cross Pacific or whatever. And you've made excellent presentation on studying how ships are, how goods are shipped, not how ships are goods. Yeah, yeah, yeah, yeah. Okay, so I just kind of wrapping it all together. This was kind of a missing piece for me. I will say there's not talked about, but there is actually quite a bit of work on Maritime. We work closely with the Maritime Agency at DOT and DOE. And we are actively looking at, there's a major new rule that's gonna take effect in January and in my case, it's like a Y2K thing. I don't know what's gonna happen when all of a sudden, all the fuel that ships around the world currently use will no longer be available to use. And literally, there is not enough fuel in the world to kind of address that at the moment, but there's a mad scramble looking at LNG, looking at hydrogen for energy sources, electrification for ferries, inland waterway movement. There's gonna be definitely a wider variety of ways you use to propulse for propulsion freight. And there's also a good amount on this whole mobility area. Think about the data. If I now take all of the type of data, it's just another version of shipments with trucks on road and I can improve the ability to move that freight across oceans, then you can improve the economics of that as well. But there's a lot of work going on in air quality around ships in ports. And that ties into the energy source you're using for it. And then how you connect them to the inland waterways is critically important. And the short rail that you use to get them from there to the inland ports, as well as the trucks that move around those ports. So we have a lot of work there to help basically reduce local level knocks and then allow the energy improvement. And also incorporating the flood, weather, et cetera. Pick one. We are not currently doing that, yeah. I think we need to wrap up or again close to five, Bill, last question. Well, actually it was just a point picking up on the Grady's comment. You know, we talked about it also earlier for flooding. I mean, because we create this data and of course behind it is a lot of assumptions. And then the question is always bound, like who interprets it, you know, the value of the strength, the validity of the data because we talked about the Pima flood maps, you know, as an early example, like a line on a map suddenly becomes a difference between a whole bunch of things and people look at it and interpret it. So it's really, it's the data that we collect and create, but then it's the interpretation of that. That's the challenge. Okay, I think we need to wrap up at this point. First of all, thank you, panelists and keynote speaker. You guys, it was a marathon for you. We appreciate your indulgence. Thank you very much. We are gonna wrap up now with our joint workshop. I just wanna say I found this to be a very stimulating day across a wide range of topics. And I think we see some themes and emerging from these different topics. Carol, would you like to add some comments as well? Well, I'd like to say that those of us on the committees will definitely be thinking about what questions these presentations and discussions raised for us and how the geographical sciences and mapping scientists might be able to contribute to these. Absolutely. Okay, so don't leave the building or don't go too far because at 530 Bouddhava Dury is giving the Gilbert White lecture in room 100, I believe, is that correct? Just around the corner. Just around the corner, so don't miss it. And thank you very much for participating in this workshop. We are adjourned.