S2E03: The Mobility Energy Productivity (MEP) Metric

Between the Lines S2E03: The Mobility Energy Productivity (MEP) Metric

with Venu Garikapati

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Why will the Mobility Energy Productivity (MEP) Metric help save the planet?

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On this week's episode of Between the Lines, we chat with we chat with Venu Garikapati.

Venu is a transportation data project leader at the National Renewable Energy Lab (NREL), where he conducts innovative research on travel and energy-related impacts of emerging transportation technologies. An expert in the development of new analytical and computational modeling systems for forecasting travel demand, his research focuses on understanding the impacts of disruptive technologies on travel behavior and the role that big data analytics can play in enhancing the performance of transportation systems.

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Learn more about the Mobility Energy Productivity (MEP) Metric here.

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And check out our exclusive commuter playlists on Spotify!

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‍Episode Transcript:

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[Voiceover] Commutifi presents Between the Lines with Andy Keeton. Each week we explore the challenging issues transportation demand management professionals face on their journey to transition commuters from driving alone to more sustainable, shared and active commuting habits. Be sure to subscribe to hear next week's episode and check out our exclusive commuter playlists on Spotify. This is, Between the Lines with Andy Keeton.

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[Andy Keeton] Hi, everyone and welcome aboard to this week's episode of Between the lines. This week we are talking to Venu Garikapati. Venu is a transportation data project leader at the National Renewable Energy Lab or NREL, where he conducts innovative research on travel and energy related impacts of emerging transportation technologies. An expert in the development of new analytical and computational modeling systems for forecasting travel demand. His research focuses on understanding the impacts of disruptive technologies on travel behavior and the role that big data analytics can play in enhancing the performance of transportation systems. There's a lot there, we're going to get into kind all of this, but thanks for being on Venu.

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[Venu Garikapati] Thank you for having me Andy, great to be here.

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[Andy Keeton] And we're going to be talking today about a project that you and your team have been working on for quite some time, it's called the Mobility Energy Productivity Metric, or MEP Metric. We're going to be talking like always, about why this metric will help save the planet. But first I want to kind of frame this discussion a bit. So, let's start off by talking a little bit about why quantifying a problem is so important. And specifically, why is it important to quantify a problem in the mobility space.

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[Venu Garikapati] To answer your question Andy, unless we quantify anything, we cannot assess or more importantly, improve what we want to quantify. Quantification is omnipresent in our lives. We quantify our height and weight to compute our body mass index, which tells about the quality of our health. We quantify the financial activity of any state or even the country with GDP, Gross Domestic Product or stock indices. In a similar way, unless we can quantify how efficiently, people in a location, are connected to goods and services that they want to access, using a selection of modes, motorized or non-motorized, we cannot start improving the quality of mobility in our neighborhoods, cities, states or even the whole country. So, quantifying mobility is the first attempt to improving the quality of mobility is the gist of it.

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[Andy Keeton] Yeah. That makes a lot of sense and I wonder, quantifying some things makes sense, it seems straightforward, but mobility is pretty complex. Why do you think it's traditionally been so difficult to quantify the quality of mobility that a location might provide someone?

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[Venu Garikapati] Rather than say it's been difficult, I would say that mobility quantification typically happened at scales that were not the most appropriate. Just as an example, vehicle miles travel is a good measure, it's measured in terms of total vehicle miles traveled at a city, county or state level. It's a good metric, but it would not tell you how much vehicular activity provided the efficient connectivity that a location needs. So, great metric, not the right resolution. There are some other cases, some other efficiency measures that stem from the access domain which actually quantify how we should efficiently connect to the places. Metrics that can quantify things like that have typically been used to quantify access to one type of opportunity. For example : access to jobs or access to health care using only one mode but not multiple modes, so, access to jobs by car or access to jobs by transit are some of the things that have been quantified for many years, even decades now. These give us a good perspective on the efficiency of connectivity, but in a piecemeal-fashion. If there is great access to jobs it does not mean there is great access to everything else. If there is great access by car it does not mean there is great access by other things. So, mobility has been quantified, both in the mobility domain and as a proxy through the accessibility research, but it has not been done both at a comprehensive fashion and at a scale that can be readily interpreted and utilized by decision makers across the board. That's my answer to the difficulty. I'll again emphasize that it's not the onus on the difficulty of the problem, it is viewing the problem in a more comprehensive lens that has been lack.

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[Andy Keeton] It's really interesting, I like that perspective. We have been quantifying each individual aspect of mobility and of access, but really pulling it all together is important because right it is, it might be great to know that you are close to healthcare by car but, does that really mean that you are in a place that god could access by other means, or to other opportunities. So, I'm guessing that's going to lead us in well to talking a little more about the MEP Metric. I'm assuming you're leading us well into what the MEP Metric is and how it helps fill this gap, but I'd love to hear, a little more about that.

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[Venu Garikapati] Not my plan but I like how the conversation is going. So, to answer this particular question, let's actually do a small thought exercise with you and the listeners of this podcast. I'm going to request you and everyone who's listening to this podcast to close your eyes just for a few seconds, and think about the location you're in right now. Now answer to yourself: can you travel to the closest grocery store or back by walking for a few minutes? How about going there on your bicycle? Will transit take you to these activities or do you have to use your car to travel to all these activities? That feeling of connectedness that you're getting a sense of in your mind is what the MEP Metric essentially tries to quantify. In technical terms MEP quantifies how well-connected a place is, and does so, while accounting for time, cost and energy efficiency of all the modes that provide access in a location. MEP builds on accessibility theory, and brings in mobility related factors to quantify the quality of mobility in a location. Most of the existing access metrics only use travel time as the ___ measure. Even as you were doing this thought exercise, the example I gave is : if you travel for a few minutes, can you get to an activity? But time is not the only resource we spend while traveling. Choosing any mode we invariably expend energy, more in some modes than others, and we have to spend monetary costs in order to be able to travel or access places, right? So, when we think about mobility or travel in its holistic sense, any given mode has these complementary aspects going for it. Time, energy and cost, so the MEP Metric quantifies the ease of getting to places in various modes, in the context of the externalities of these modes. We started with time energy and cost, but there are other externalities that we are looking into as well. So, that's in essence our attempt at quantifying the quality of mobility using the MEP Metric.

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[Andy Keeton] I really like that thought exercise because it does give you… everyone has that kind of sense of how well they're connected to somewhere and into the opportunities around them, but that's just for their own life and their own situation. It's pretty hard to imagine that for someone else and some other location, even if you're well aware of those locations and understand what exists there. That's really interesting, and then adding those other factors like even for my own area that I know well. I do understand it by time, maybe to a degree because I'm a transportation person. I have an okay understanding of the sort of the cost and the emissions, implications, but not really well, just kind of high-level, like : "oh, this is better and this is worse." And that's kind of it.

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[Venu Garikapati] Just thinking about the various modes that we could technically use to get around, if you take car as an example, car is definitely a time efficient mode there is no denying that, but it's not the most energy efficient, not the most cost-efficient mode to travel, particularly if you're in a car all by yourself. A single vehicle travel is one of the least energy-efficient modes there is to travel.But walking and biking, on the other hand, are very cost and energy efficient, they're not the fastest modes to begin with. So if we only look at these modes using time as the lens, car will always come out to be the winner, which is not the case if you think about all the resources we are spending while traveling. Using these other factors or externalities of different modes, actually brings all the modes to the same level playing field, which allows us to compare and contrast when you account for everything, which modes provide you which type of quality of mobility in a location.

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[Andy Keeton] Yeah, I think that's really important for us to start thinking about as individuals and as larger transportation program managers, and policymakers and things to start thinking about how transportation really is, and the impacts that it has on individuals and, yeah, all those externalities that go into it. And that's why, one of the reasons I really like the MEP Metric is  it does kind of start filling those gaps that you talked about, which is, yeah, we've always been measuring this and just we've been measuring one little aspect. This is trying to put it all together which is very complicated. How long has your team been working on this? And, how many people? And, how many hours do you think, you've put into this project?

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[Venu Garikapati] The hours question might be difficult to answer. I will say though that I am one person representing the MEP team today, but the MEP project itself is the work of many, many talented researchers. The project has been in being for a little over four years now. All those years ago it started as a thought exercise between a few researchers on a friday afternoon, who were thinking about similar thoughts that we discussed here where we are like: well, "if you want to quantify efficiency of mobility in a location"… we were wondering if there are tools to do that. So, we went in looking for tools, there are a few excellent measures out there. The more popular ones are: walk score bikes for transit score all transit index, which gives you an indication of the efficiency of using these modes to get to places, but there is no one metric that combines all of these externalities, particularly the cost and energy, and combines all the modes together. So, we put a small thought proposal to the Department of Energy, saying : "Hey!, this looks like an exciting idea, can we explore this?". So, we started with a very small seed project, which has blossomed into a multi-million dollar research project and a metric. Over the course of three years, at least the work of about 10 different researchers coming in from the transportation domain, computational sciences, we even have a chemical engineering PhD on our team, who just happens to be interested in transportation. So, this is a continuous iteration based on feedback that we've received from the Department of Energy headquarters personnel. We've talked to various Department of Transportations, demonstrated the uses of the metric, and have received feedback. So, if I have to answer on the order of hours, I would have to ballpark it in the amount of thousands of hours, if I'm only counting the research hours on this. We run the MEP Metric on high-performance computing systems here at the lab on, and on Amazon web service cloud. So, if we count the computed hours, then we are talking about tens of thousands of hours.

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[Andy Keeton] Wow! That's, yeah. I mean, so, if you're trying to find a metric that knows what it's talking about, this seems to be the one, and I thought it was funny actually, a chemical engineer that's working on this. We find a lot in this industry, that people working in transportation are not necessarily trained in transportation, there's not really like many, I mean, you could do transportation planning but besides that, there's not a transportation engineering PhD, probably, out there. So, this is even in the hard sciences looking at this for years, where you have people coming from different disciplines, it makes it an interesting project, and bringing in different thought processes, it makes it really interesting. So, we have this metric that you're developing, sounds awesome, what can we actually do with it? Who can use it? What can we do with it? How does it help us as transportation people or as individuals? Who is this for?

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[Venu Garikapati] Excellent question. So, rather than talk about the potential uses of the metric, I'm actually going to talk about a few use cases that we have already utilized the metric for, and places in the perspective of work that has either been done or is currently going on. The metric in its very basic implementation can quantify the baseline quality of mobility of a location. So, when you see that the score is producing a higher magnitude number for a location, it would essentially mean that from that location.

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- (Venu Garikapati) You're able to access a greater variety of opportunity using a larger number of modes in a time, energy and cost-efficient manner. So, like any metric quantification, a higher MEP score for region is better than a lower MEP score. So, in quantifying the baseline, our intent is that once you quantify that baseline you should be able to track the improvement or lack, thereof, in the overall quality of mobility in that location in response to various external stimulus. The stimulus can be infrastructural investments that are happening in the locations, changes in lane use, that are happening by knowledge or without or even some decision-making strategies, where individuals have been incentivized to take more electric vehicles. Just as an example, If a city makes investments to increase the adoption of EVs, electric vehicles, over the span of a few years, The MEP metric can capture the increase in energy efficiency of mobility for that city, even if the level of conditions stays exactly the same. So, if travel times do not improve over time, but energy efficiency of traveling improves, there is no current metric. Maybe I'm being slightly "boasty" in here, but sort of even there is no current metric that could quantify the energy efficiency difference between these similar network states across the US with the efficiency of traveling that comes from energy, but not from travel time. So that's just one use case for the metric. For the Department of Energy, this is a metric that has been primarily funded by the Department of Energy, particularly by the Energy Efficient Mobility Systems program in the Department of Energy. So for EEMS, Energy Efficient Mobility Systems program, they've conducted research in conjunction with other national labs on future vehicle technologies for land scenarios, and how automated vehicles or shared automated vehicles or mobility as a service, how can they help improve the mobility, energy productivity of cities is the research that we've done and we've published on the Department of Energy. They are currently collaborating with a few State Departments of transportation, integrating this metric into the transportation planning processes, across various DOTs. This means that when the Department of Transportation are planning for infrastructure investment by working nearly in the future, and they want to evaluate the installation of a bike lane in a major corridor versus improvement in transit service, or even, if not the most ideal, add a freewheeling lane. How would those infrastructure investments and improvements in overall mobility, energy productivity is an excellent use case for the metric. This is something that we are working with the DOT currently. And a final use case that is in the making is the American Council for energy efficient economy, ACEEE Comes out with Clean Energy scorecard every year. This year, ACEEE has published the MEP metric as the transportation efficiency measure on their website. From next and subsequent years, our plan is to explore the integration of MEP into the scoring methodology for ACEEE. So these are some of the use cases that we've currently been working on. As I said, I'm not going to talk about potentials, there are a lot other collaborations, if you're interested in seeking out, which increase the impact of the metric in the in public and private environment.

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- (Andy Keeton) This also speaks to the importance of having a metric like this, that goes, once again, beyond the individual looking at one use case or opportunity and thinking more holistically. Just those three projects you talked about are distinct, they're different. They're all solving a different problem, and it's pretty exciting to see where this goes. I'm hoping some of our listeners are sitting there in their office, or in their car, or train on the way to work, thinking : I have a project, I'm going to reach out to Venu. I'm sure that Venu would be happy to talk to you about a way to use the MEP metric to solve come of the problems you have. So if you're listening… Sure, he's always available. I am volunteering you to work collaboratively with our listeners. I hope that's okay.

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- (Venu Garikapati) Sounds good.

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- (Andy Keeton) Cool. So I want to ask… You know, we're running close to the end, so two more questions : I want to ask this one first, and then we'll end with the question we ask all of our guests. So, you talked a little bit about what the metric can do, what it is, what it can do, who can use it… I wonder if you can talk just a little bit more about how it can help us track and evaluate the impact of sustainable transportation, infrastructure investments, decision making, down the line. You talked a bit about the idea of getting EVs, or adding bike lanes… but how does that actually help you track that and evaluate that overtime?

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- (Venu Garikapati) Sure. I start by saying that the number one use of the metric, even amongst the ones I described, is that it could potentially add to the arsenal of tools at the disposal of decision makers in evaluating the quality of mobility, We quantify the MEP metric for a fine spatial resolution. So we do a set of square kilometers resolution. If you give us a city, we'll pixelate the city into square kilometer pixels and do this quantification once for each pixel and then we aggregate the score to any known geography. a certain small group, a certain extract of the piece, or even the whole city. So, for the question you asked, if is a city is planning investments into more sustainable transportation technologies year over a year because of changing mobility trends, how's the metric changing, not just in overall terms, but across different modes and across various locations is probably the biggest use of the metric there is. To such utilization, if cities can evaluate competing infrastructural options down to the dollar, you can think of benefit and have all kinds of measurements. Or how will overall mobility for everybody in the city or of a specific demographic cohort of interest is increasing That's a top priority for us. That's the way in which we evaluate both the impact of sustainable transportation technologies, but also how mobility is improving for individuals across the board. Will businesses make different decisions about their location? Knowing about the quality of mobility that their employees can afford based on the location selected. Also for people, where they choice and where they want to live, If they know the complete picture of the quality of mobility of the location, not just by one mode, but by many modes. One thing we don't recognize is we might incline toward one mode for a majority of our travel, but all of us are multimodal people. Even a simple car trip we make, you don't jump into the car on both intersections. Maybe you do that from your garage at your home, or the parking lot of your apartment. But if you are parking your car somewhere else than your destination, walk into your office. So, no car trip is a car trip. A car trip is a multimodal trip. Even for folks who actually use cars for the majority of their trips, they like to their evenings and in the evening, go to sort of grocery stores nearby you might want to drop by there So all of us are multimodal people in our nature. If you know about access to opportunities using many modes, I think that could lead to more sustainable travel behavioral patterns. This is what we intend to popularize through the use of this metric.

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- (Andy Keeton) I really like how you said that. Yeah, we're all multimodal people. I think particularly in America, North America translation planners probably assume most people drive everywhere, and that you are an unimodal person, if that's a term, but, we are multi modal. I like that, and just giving that information about the access to opportunities that exist can help expand that multi-modality. It is pretty interesting. Okay, so we're toward the end of our time. We have this one question we ask everyone. We were talking a little before, Venu, so I'm excited to hear what you have to say here, But tell us : Why will the MEP metric help save the planet?

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- (Venu Garikapati) That's exactly the most interesting question of all, also the most difficult to answer. Saving the planet is a motto, which is going to be in our collective efforts in making sustainable choices. I'm not going to state all the capabilities of the metric but one of the key things that I haven't touched on before, that we want to bring up to our metrics is not just quantifying mobility for one given location, and a single number, but we want to quantify the quality of mobility for that same location for various sociodemographic cohorts of interest. We all won't have access to the same type of modes. Some people might be car-constrained, as we just mentioned, some people might be train-constrained. So their choice of options for mobility might not even include car. Some people might be constrained on others to be driven, particularly kids who have to be dropped off at daycare or at the school or otherwise. Some others might just have a greater affinity toward walking, or biking. It is just the type of person they are. So not just one metric per location, but quantifying quality of mobility for various cohorts of interest. In doing so, measuring not just the quality, but the equality of mobility is how I think we will help make a better planet. I don't know if this is directly answering your question to save the planet, but I think we should match the words "a better planet" to our mobility choices and sustainable choices, this matches your question.

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(Andy Keeton) I love it. I love the equity lens that you're trying to bring into this. It definitely plays a part. I definitely see. I definitely see how the MEP metrics can help us save the planet, even if you don't want to say it, but really, yes, make a more livable planet for everyone. Yeah, great answer.

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- (Venu Garikapati) Like we talked about: unless we view all of the modes with a common lens, with an analysis including the different modes we can't have a dialog on how various modes are competing with one another, and how certain modes come out on top and you can't say everything that the mode has to offer, existing modes or future modes. Electric Vehicles are a great example where the energy efficiency of cars is being brought up through the use of electrification. So maybe they're much better than an internal combustion engine vehicle, if you are directly comparing the ICE and the EV.

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- (Andy Keeton) Yeah, sure. I think there's a lot of opportunities for this to move forward, as new infrastructure comes, as new decision making at various levels comes, part private and public, and individuals, and understanding that behavior and being able to quantify something that's really not on the surface. A quantifier will think humans behavior, this is really interesting. I'm really excited to see where the MEP metric goes. Thanks a lot to you and your team for putting so much time into this. I know you've been really spending a lot of time, as you said, including the computers next to the computers and the tens of thousands of hours. We're really excited to see where this goes. Venu, thanks again for talking to us about this - (Venu Garikapati) Thanks for opportunity, Andy, I hope this interests some of your listeners, and I truly hope that this leads to more conversations about quantifying the quality of mobility for a better future.

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- (Andy Keeton) To everyone who is listening, that's a good segue. If you haven't yet, make sure to subscribe to our email list, which you can do at betweenthelines.io And that way, you get emails from us every time there's a new episode, as well as some more information. We will send out more information about the MEP metrics, so you can dive a bit deeper into this. Contact Venu if you have any questions and want to collaborate, I'm sure he wants to. I keep volunteering you for this. Make sure to keep up with future episodes that are coming up in the future as well. Well, give us a like and a follow wherever you listen to podcasts. If you haven't yet, check out the video on YouTube as well, that we publish all of this information, All of the episodes that we have already recorded, and we'll record the future can be found betweenthelines.io Once again, thanks for listening. Thanks for being a part of this, and we will see you next time. Thank you, everyone.

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- (Venu Garikapati) Thank you.

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- [Voiceover] Thanks for joining us on this week's episode of Between the Lines with Andy Keeton.

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Be sure to subscribe to hear next week's episode and check out our exclusive community playlists on Spotify.

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