All right hello again! Thank you everyone for joining us today!
 
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Hello and good afternoon! I’m well I’m happy to welcome you all to our sixth webinar in a series in which we summarize the work and the results from DOE’s Smart Mobility Laboratory Consortium. My name is David Anderson. I’m the program manager for EEMS or Energy Efficient Mobility Systems. EEMS is a program of DOE’s Vehicle Technologies Office that's part of DOE’s energy office of Energy Efficiency and Renewable Energy. Now the Smart Mobility consortium is a cornerstone research effort of the EEMS program and is focused on two things. One understanding the system level impacts that emerging transportation technologies and services will have on mobility and two identifying solutions that improve mobility energy productivity. That's the energy the time and the affordability of transportation. Now in our last webinar two weeks ago we focused on moving people in the Smart Mobility system, but people are only part of the transportation equation. In addition to moving people, we move our things our stuff that's freight today our focus is on moving goods. In a Smart Mobility system, we transport 11 billion tons of our stuff on roadways every year and that's in addition to three trillion passenger vehicle miles travel and we're doing research to find ways to do this more efficiently and more affordably. Our two speakers today will tell you about that and they are Dr. Alicia Birky from the National Renewable Energy Lab and Dr. Monique Stinson from Argonne National Lab. Now before I turn it over to Alicia and Monique, I’ll again give you some context for the work that we're doing.
 
Now as many of you know by now, EEMS is one of several research programs within the Vehicle Technologies Office or VTO has a long and successful history of conducting research on vehicle powertrains and component technologies that's batteries and electrification engines and fuel systems in advanced materials. Now a great example of this in the context of today's discussion on freight mobility is our super truck 1 and super truck 2 programs of the last decade. These programs were focused on increasing the brake thermal efficiency of the engines in class. A tractor trailers to 50% and achieving a 50 improvement in freight efficiency in terms of ton miles per gallon the second iteration of super truck upped the game and focused on 55 brake thermal efficiency and a 100% crate efficiency goal while doing it through cost effective solutions. But these solutions were vehicle and powertrain focus EEMS and Smart Mobility extend VTO’s scope up to the transportation systems level. We look not only at technologies at the vehicle and powertrain and component level, but also at how vehicles interact with each other and with infrastructure at the small network or corridor level and then we can evaluate the system in terms of overall traffic flow and energy consumption and ultimately understand the future of mobility in the context of an entire urban or metropolitan area integrating both passengers and freight transportation within that purview. The EEMS program has taken a multi-disciplinary consortium approach to transportation research. We created the Smart Mobility lab consortium by convening the five national laboratories shown here they brought to the table their most skilled transportation scientists and engineers to build a multi-year multi-laboratory collaborative dedicated to further understanding the energy implications and opportunities of advanced mobility solutions.
 
Now the first phase of our consortium was divided among five pillars of research shown here connected and automated vehicles, mobility decision science multimodal, freight urban science and advanced fueling infrastructure. The research results that Alicia and Monique will describe today largely come from the multimodal freight focus area but as I’ve said in past webinars since the consortium is multi-disciplinary and cross-cutting. These focus areas were very much interrelated the research in any one area relied on activities from our other areas for example the research on freight movement depends on the technologies being applied including connectivity and automation. It depends on consumer decisions and behavior which is what we researched in the mobility decision science pillar. It depends on traffic networks the built environment and curb space especially when you're talking about last mile goods delivery and that's what we researched in the urban science pillar and if the trucks use electric drive powertrains it depends on where and how much and how long they have to recharge which is what we investigated in the advanced fueling infrastructure building.
 
So, this interconnectedness is why it's more important to look at the consortium and mobility research in general like this as a complex system of systems. We can't really study any one area in isolation without considering the impacts that related areas have on it which is what we set out to do to the consortium for every area that is directly relevant to freight and goods moving. You can literally draw a line to the other areas that may be indirectly relevant and still have an impact on it.
 
So, when we discuss goods and freight movement one of the first things that comes to mind is e-commerce and we've seen a big shift from brick-and-mortar retail to online shopping and delivery over the past decade even before the impacts of COVID-19 which at least based on this last data point has only accelerated the trend. We're trying to understand to what extent will this trend continue and what impacts will it have on our transportation system. We're all familiar with the images shown on the left side here the packages dropped off at the front door and the daily delivery trucks driving through our neighborhoods, but we also have to consider new delivery systems in new modes like package lockers and delivery drones parcel lockers can be an efficient delivery mechanism. But their energy impact all depends on how customers access them which is why it's important to consider both freight and passenger travel together and on drones we've done testing of drone delivery systems to understand their energy efficiency it turns out that it's not all that efficient to fly packages through the air, although there may be other benefits which we'll hear about later in the discussion.
 
So, we're doing research and analysis related to e-commerce and novel last mile delivery, but we have to remember that old-fashioned commercial trucking accounts for nearly a third of our highway transportation energy consumption. If we want to address the freight sector, we have to include this part of the puzzle in this area we've researched the application of connectivity and automation to the heavy-duty sector for platooning of class 7 and 8 trucks. For example, and we've evaluated opportunities for electrification of class seven big trucks. Again, you'll hear more about this from our speakers. Finally, I want to remind you all that VTO in coordination with BETO's Bioenergy Technologies Office and our Hydrogen and Fuel Cell Technologies Office recently closed a request for information or RFI in support of our medium and heavy-duty truck research and development efforts. So, you can no longer respond to that RFI, but we do plan to host a webinar on December 15th from 1-4 p.m. Eastern time to discuss the key findings and provide a summary of the results that RFI. So, we invite you to use the link provided here to register for that webinar if you are interested.
 
As I wrap up, I want to reiterate that freight is a very important part of the mobility sector and we expect it will only become more. So, reported in the future as I stated earlier medium and heavy-duty vehicles currently account for a third of the overall transportation energy consumption in the U.S. and based on scenario analysis in the Chicago metropolitan area which Monique will describe later, we expect that the medium and heavy-duty vehicle share of transportation energy will increase to up to 50%  in the future. Now this is due to both the faster pace of efficiency improvements in the light duty passenger vehicle segment driven by an increasing market share of electric drive vehicles there. So as the share of light duty vehicle transportation energy decreases the medium and heavy duty share necessarily increases and secondly is driven by the expected significant increase in freight demand as population grows and as purchasing habits evolve. So, freight will be what will be and continue to be a focus of ours not only within the Smart Mobility consortium and within ease but within VTO more broadly. So now I will stop talking and turn it over to our two speakers for today first Dr. Alicia Birky from NREL will speak covering a lot of the data analysis and empirical studies done under Smart Mobility including drone delivery, parcel lockers, platooning and electrification and after Alicia concludes Dr. Monique Stinson from Argonne National Lab will discuss the freight related results from the metropolitan area analysis that we did using our integrated Smart Mobility modeling workflow which has been the subject of previous webinars. Afterwards we'll have some time for Q&A, and I’ll ask that you type your questions into the Q&A box not the chat box, but the Q&A box on your screen at any time during or after the presentations and we'll go through as many of your questions as time will allow thank you and at this point, I will turn it over to Alicia.
 
All right just one minute to get my video going.
 
I’ve lost my video, is everybody hearing me first? Yes, we can hear you Alicia and if you are unable to get your video working that's quite all right you can see your slides. Yeah, I might just go ahead because I’ve actually lost that menu somehow. Thanks David I am Alicia Birky of the National Energy Laboratory and I work in the center for integrated mobility sciences. I’m really excited to participate today in the webinar. 
 
I’ll be presenting some of the smart consortium research and results that focus on new technologies and modes for freight movement and urban delivery and longer distance shipping. But before we dive into the research and the results, I’d like to first highlight our motivation. As David mentioned freight movement is critical to our economy and it's a key aspect of our national mobility system the national picture by tons moved about 65% of U.S. freight movement is delivered by truck and we expect that fraction will be stable in the future and DOT freight analysis framework estimates that because of growing demand for freight truck freight will grow from about 32% will grow by about 32% in absolute terms by 2045. And if we look at the resulting energy demand, current fuel consumption standards for commercial trucks are going to be fully phased in by 2027 and the unused stock will turn over and the energy and information administration is projecting that net fuel consumption will decrease a little bit by 2035. But they do project low adoption of efficiency technologies and advanced powertrains after that and as a result the freight demand growth by 2050 is going to overwhelm and surpass those efficiency gains. So, combining that with those increases in light duty fuel economy that David mentioned if we look at EIA's projection the commercial truck share of national highway fuel consumption is going to grow from about 30 to 37 that's not quite as dramatic as the projections from the systems modeling that Monique will discuss later.
 
So, the smart consortium portfolio includes a lot of great print related research I’m just going to be able to touch on a few of those projects that looked at how emergency emerging freight technologies might impact energy consumption. These individual technology assessments are critical to informing the system level analyses of the sort that Monique’s going to be presenting. I divided the presentation basically into two sections, the first on urban delivery modes and then the second on longer hall freight. But we'll cover drones parcel lockers, equal electrification, and truck platooning for each of these technologies. I’m going to provide kind of a high-level takeaway and then a little more information on the approach and results that are behind those insights there's way more research than I can present in the time we have today. 
 
So, it's this really what's your appetite then I encourage you to look for the capstone reports and also the annual merit review presentations that VTO has available on their website. So, starting with the new modes for urban delivery the parcel lockers are an emerging technology that's very appealing for carriers and e-commerce customers not necessarily from an energy perspective but because it solves a lot of other issues in last mile delivery. Those issues include limitations and curb space for parking limited package delivery space and multi-unit dwellings, refused deliveries that might require re-delivery and also being something that probably everybody on the call is familiar with which is packaged off of porches. We wanted to consider how that innovation in combination with some of the other technologies like electric vehicles and drones or delivery bots might impact the energy consumption of last of the last mile delivery fleet when you compare it to delivery to the consumer's door and the interesting finding is that the net impact is strongly dependent on the technology that the consumer uses to retrieve the package from that locker. 
 
So, if consumers drive a typical gasoline SUV for example kind of worst-case scenario if they drive that SUV to the locker that results in a 200% increase in energy consumption relative to just the diesel truck delivering it to your door, but if a drone were to complete that last leg, we would actually see a net in savings of 30. So talk about how we came to those high level conclusions research included a testing program to characterize drone energy consumption but also analysis of real world package delivery data for a carrier in Chicago this allowed us to model baseline energy consumption for the fleet and then construct and analyze alternative scenarios that incorporate new delivery technologies including the parcel lockers and the geospatial model also allowed us to estimate energy consumption for the consumers portion of that parcel retrieval from the locker. So, we started with this drone energy characterization and the testing looked at a range of payloads basically up to the maximum takeoff weight for the drone and so, you see we go up to about 15 pounds of payload weight which is pretty close to the limitation for this. In fact, I think it's over the limitation for this particular drone and we were able to collect we looked at different flight phases and we also looked at the impact of altitude and temperature and were able to collect some of the first empirical data on fuel consumption.
 
So, the drone testing on the right page here there were there were a lot of interesting findings but one highlight I think from the experimental research is that with higher payload the drone energy consumption per mile actually approached that of an electric car. But given their payload capacity that means they wouldn't save energy on a ton mile or a pound mile basis but they could be more efficient than a dedicated vehicle trip to deliver a small package and they might still save on overall energy because the miles that they travel could be shorter due to a straight-line flight path and they also have this potential to reduce congestion on the road because of reduction in the number of truck trips that are taken and this is where that system level analysis becomes. So important and of course drones also offer a number of other unique advantages such as fast delivery of time critical parcels and access to remote areas which can be especially important during disasters and such.
 
So, if we look now at the parcel delivery analysis, we start with the baseline average energy consumption for the fleet that we analyzed using diesel trucks to deliver that package to the consumer's door and that's what you see on the bottom of the graphic there. But if we replace those trucks with electric trucks then you can actually see in the middle there, we have a 77 decrease in the energy consumption, now we add to that the delivering the packages to the parcel locker either by a diesel or electric truck. So we have two different blocks of data there the lower one with the diesel truck and the upper one with the easy truck and then we can just consider the consumer picking up that that package using a variety of modes and as we mentioned earlier the energy impact is highly dependent on that consumer's choice of mode and that if they drive an SUV we see this fleetwide energy consumption relative to that baseline increasing by 200 when the diesel truck is still used for the first leg if you replace that first leg with the electric truck we still see an energy increase of 163 and in fact that unless the consumer retrieves that package either by foot or using an EV the energy savings from using an EV truck would be negated by the consumer's leg of the delivery and that's all assuming that the trip to pick up the package from the locker is a dedicated trip. So, if there's trip chaining that's a that's a different situation and then finally if we use a drone instead to deliver the package from the locker to the consumer's door even though we said that they were potentially on a par with a light duty vehicle we do see an energy savings relative to the diesel truck delivery of 30 to 70% depending on whether we use the diesel truck or the EV truck for that first leg.
 
So then moving on to our long-haul technologies the first technology I want to touch on is truck platooning this was covered really well in a prior webinar on automated vehicles and I’m just going to hit a few highlights here. So, if you're interested in more of the details the prior presentation and the recording are available on VTO’s website and the other sources that I talked about but the key high-level insight here is that individual trucks in a platoon can save from 7 to 13% on fuel depending on a number of factors that that we looked at including the truck spacing the speedo trucks and then of course the position in the platoon. So, here's some of the highlights of that that that the empirical data that was collected the Smart Mobility researchers led some of the most comprehensive test track evaluations of class 8 for platooning to date including investigations of some of the complications of operating in real traffic. So, some of the new findings that they had they resulted in were include that for really close following distance for example in the left-hand graphic the lead and middle truck which typically don't save as much as the trailing truck as the that gap decreases the savings from those trucks actually does approach the trailing trucks savings that the trailing truck would achieve at those wider spacings. And meanwhile the trailing truck actually has a decrease in energy savings and the team was also able to identify or quantify how passenger vehicle cut-ins which occur in real world operations wouldn't would reduce the platooning truck's fuel savings that's shown in the right-hand graphic if we put this combine this then with kind of a system level view considering how much opportunity there is for tuning we found that about 60% of highway truck miles may be platoonable and if we were able to take advantage of those opportunities we could reduce truck diesel consumption at a fleet wide by 6-8t% and favor over one billion gallons of fuel annually.
 
To evaluate that national platooning opportunity we actually analyze both real world truck movements and national level freight demand data and using vehicle speed and the temporal and spatial proximity of the trucks the results from these two data sets were very consistent and resulted in that 60% tunable number we then developed a model based on the freight movement data that could estimate the fleet-wide fuel savings when we combine that opportunity with the truck level assessments and that leads to a 6-8% of national class 7 and 8 fuel that could be saved.
 
So, the last technology I wanted to talk about here was electrification and an electrification specifically in regional and long longer haul trucks and our analyses indicate that by 2050 the national energy savings could be up to 17% amounting to 1.4 quads or 10 billion gallons of diesel equivalent annually. The petroleum savings are even higher than that, however we also found that operational changes likely are necessary even for freight moved under 500 miles. So we had three different studies that inform these findings on electrification the first study looked at deploying battery electric vehicles at a sufficient share to electrify basically all freight that was moved under 500 miles based on the freight analysis framework data and some average payload assumptions the second study analyzed deployment of a portfolio of electrification technologies that included hybrids plug-in hybrids and battery electric trucks and in that study we assumed that fleets would adopt technologies when the fuel savings paid for the extra vehicle cost within four years both of those first two studies considered stock and sales. I’m sorry sales and stock turnover but they also assumed that there were no charging infrastructure constraints. So, our third analysis was a case study that used real world truck movement data for a tractor fleet and There we assessed battery electric vehicle suitability based on the ability to complete their daily operations when you consider the battery capacity the range of riding and then the charging opportunities throughout the day.
 
So, looking at the first study on the left to cover all freight moved under 500 miles we estimated that we needed to fully electrify only 16 to 24 of the class 7 and 8 truck population by 2050. That amounted to a 40% reduction in diesel and a 17% reduction in energy consumption from these trucks when we compared to the AEO reference case. In the second study we found that some amount of electrification provided a four-year payback. Four-year or better payback and enough trucks that by 2050 we had 55% of the class 7 and 8 truck population with some amount of electrification. These were primarily hybrids and plug-in hybrids, but the battery electric trucks did have a sweet spot in the 200-to-500-mile daily range driving, and this actually had energy and petroleum savings that were very similar to the second. I think it highlights kind of the value of that that varied portfolio.
 
So now if we look at that 200-to-500-mile sweet spot for beds it points to deployment in regional operations which is where there's a lot of expectation for that technology. So, we examine that real world operational data for a private regional fleet to understand their actual routes and the dwell times which are the periods when the trucks are stationary primarily at their depot and might be able to charge. One of our interesting findings was that regional hall it really isn't a single duty cycle but that different trucks or even a single truck from day to day might be used in a variety of ways we selected a truck that made trips. All the trips were under 500 miles meaning that the distance between their deliveries or regional distribution centers was under 500 miles and then we defined a truck circuit as a group of trips that went from starting from the regional distribution center and then returning back there and assumed that they could charge the entire time they were stopped at that regional distribution center and we looked at two battery capacities at 300 mile and 500 mile ranges and charge power is 150 and 350 kilowatts and over all the upper operational days that we have for that truck we looked at how much range capacity the truck would have left at the end of their circuit. So, in the graphs a negative range means the truck wouldn't have been able to complete their daily operations given the day's charging opportunity and while it's really not a surprise that longer range batteries enable more operations, but it might be surprising that some of the trips simply couldn't be completed even with a faster charging solution. Meaning that even regional trucking fleets might need to make operational changes to deploy the battery electric vehicles and electrify their entire fleet.
 
So that's actually all I have for my presentation and I wanted to take a minute to thank our multimodal pillar lead, David Smith as well as Amy Moore, Victor Walker, Joanne Zhou, and Kyungsoo Jeong and also all the many contributors to these studies across the consortium and of course thank you for participating today and I look forward to questions and discussions. Thank you Alicia I will remind everyone as we transition from Alicia to Monique please feel free to go ahead and type your questions into the Q&A box, we will cover questions once Monique is done with her presentation.
 
All right good afternoon everyone and thank you David and Alicia for that introduction and the technologies that was a very nice lead into the metropolitan analysis that I’ll be talking about. So first I would like to just briefly go over this end-to-end modeling workflow which was actually presented early on in the webinar series and as David mentioned the Smart Mobility program was a consortium of national labs that shared and integrated all sorts of data and modeling tools to be able to identify and really estimate system level impacts of changing vehicle technologies and other factors the workflow centers around an Asian-based transportation modeling system. And at Argonne we use our in-house system Polaris, and it interfaces with land use EV charging microscopic traffic flow and other models the goods movement piece is as David alluded to earlier, is really an integral part of all of this it interfaces with traveler agents in the passenger. I’m sorry in the micro mesoscopic simulation model during the traffic simulation and during retail estimation there's vehicle markets feeding into the model and then finally energy estimation.
 
Within this entire analysis framework, we looked at three different scenarios to estimate the impacts of some of these future technologies focusing especially on high sharing or low sharing of passenger vehicles and how that would impact things at the system level. Partial and high automation and then on the freight side the number of e-commerce deliveries that a household orders every week currently or rather as of 2018 or so that number was on average one delivery per week for every household. So, we looked at scenarios of three deliveries per week and five deliveries per week and then compared what would happen compared the results against the base case.
 
We also considered three different time frames in this analysis. Today's time frame which again was you know say 2018 before COVID obviously and then the short term and long-term cases in the short term and long term we do expect population growth changes in land use changes in vehicle technology as well as increases in freight demand of 10 and 28 in the short and long term. On the vehicle technology side, we tested two different cases of improvements for freight vehicle technologies one is the so-called business as usual case which has rather modest technology improvements and the other is a more ideal scenario where the VTO research and development targets are achieved. So that covers the sort of the overall workflow approach and the scenarios that we looked at together as a consortium now I’ll introduce the three main research questions that we examined at the metropolitan level the first one has been really an outstanding question in the transportation community for several years now and that is what is the net effect of e-commerce. Now we all know there there's a lot more parcel delivery truck traffic happening making deliveries to households and businesses at the same time there's a lot less household shopping going on and in fact entire retail scenes have closed partly you know because of this reduction in brick-and-mortar traffic but what is the overall impact I mean we also know delivery vans are more fuel intensive than passenger vehicles. So is the overall effect good in terms of energy consumption and VMT or mobility or is it causing more problems for the region and in those two areas. So that was a major research question that we set out to investigate the second question we looked at was what are the regional impacts of commodity flow growth and as Alicia mentioned the freight analysis framework forecasts a pretty substantial increase in freight traffic over the next say you know 20-30 years, and we want to know. So, there's this both a regional increase in freight traffic as well as this long-haul increase. So, what are the regional impacts of these two areas and then finally as I mentioned we looked at the vehicle technology impacts focusing especially on medium duty and heavy-duty truck technologies. 
 
So now I will spend a little time just describing the approach that we took to study these questions and as I mentioned it sort of centers on the agent-based modeling approach which for the Chicago region it's been under development for about 10 years it's a very solid Asian based model it models all of the passenger vehicles and individuals like you and me moving throughout the region. So we introduced into this platform the so-called top-down freight model it's called the top-down model because this version of our freight model uses some aggregate sources namely freight analysis framework commodity flow survey data regional truck trip data from the Chicago metropolitan agency for planning and then we also use a disaggregate source the parcel delivery tour data that our partners at Oak Ridge developed for this project and to make this level of details more commensurate with the agent other agents that are already in the model. We increased the granularity of these sources we did some spatial disaggregation as well as temporal disaggregation. So that the vehicle trips associated with these flows are sort of running alongside the passenger vehicles in the model at six second intervals throughout the entire day.
 
Part of this also obviously was the scenarios and this is where we introduced the different permutations of the scenarios. So finally using the Polaris-Asian based modeling platform we estimate the vehicle miles traveled or VMT that's associated with all of these baseline and scenario freight movements and then we also use our in-house tools SV trip and autonomy to estimate the energy impacts.
 
Now the e-commerce module required a slightly different approach. So, we are actually well we developed this module to really look at e-commerce in detail this is a very unique feature of our modeling system. So, let's start at the bottom left-hand corner and you'll kind of see how all of these elements tie together. So, we started with the whole traveler data survey data which our partners at Lawrence Berkeley National Lab in Idaho National Lab shared we developed an e-commerce behavioral model using these survey data and these surveys. This survey was very rich in information on social demographics of the respondents the types of trips that they take their levels of say delivery versus brick-and-mortar shopping and so, on. So, we were able to develop a very rich econometric behavioral model using that survey data then on the top left-hand side is where the parcel delivery truck part comes in. So, we provide the household demand e-commerce data to the to our partners at Oak Ridge who estimate parcel delivery tours that are commensurate with this to serve these household e-commerce demands and then finally on the top right you see what ultimately, we get from this process. So, this is an example tour of a parcel delivery truck that starts at its base location its depot heads out to a neighborhood makes roughly 120 stops and then comes back to the base station.
 
So again, you know at this point we are using the model we were already estimating VMT the vehicle miles traveled with the parcel delivery truck and then we use our other tools to estimate the energy consumption. Now I want to say a little more about this household e-commerce demand behavioral model because it's very unique and it's as I mentioned very rich in what it can do now, I mentioned earlier that the e-commerce scenarios involve going from one delivery per week to three to five for each household in the region that's actually just an average with this model we predict the e-commerce demand for every single household in the region and so the actual number for any household could be six deliveries per week it could be three it could be zero and we show on the right hand side that the table with all the parameters that we use in the model and we get a lot of behavioral sensitivity we model categories based on say household income number of children number of adults etc. and actually the model findings were it's a very reasonable model in terms of the parameters that were estimated it estimates that more e-commerce demand is generated by households with higher incomes more children. So, you know busy working parents with you know income that they can use for e-commerce conveniences and at the same time less e-commerce demand by households with say fewer more vehicles because you know those are people that can easily stop at the store on the way home.
 
So that those are the main elements of our approach now I will go into the impacts themselves. The first impact I want to describe is that in the Chicago area today, well today meaning the of you know the study time which was 2018-2019 medium duty trucks and heavy-duty trucks make up about 10% of the MT but one third of energy. So already from the baseline their energy impact is kind of outsized. Household shopping is a big part of that it's about I’m sorry it's a big part of the total vehicle miles traveled which is 300 million miles household shopping being 6% that represents a major opportunity space. So, if e-commerce is more efficient then a lot of energy could be saved. Also, in the in the baseline we estimate and in the future years as well we estimate the regional and long-haul heavy-duty truck. Vehicle miles traveled and this is where that differential commodity flow growth rates come in for the regional and long haul on the medium duty side, we keep track of medium duty trucks that are out there for retail purposes namely the major parcel carriers other than other than mail. We also keep track of medium duty trucks moving for other purposes this would-be landscaping U.S. mail plumbing you know all those all those trucks.
 
Now the whole traveler survey I want to highlight a couple of the unique findings from that one finding is that delivery versus brick-and-mortar shopping actually varies quite a bit by the type of item and some of you may know this or have suspected it but there's actually not a lot of data that quantifies it. So, we were very lucky to have this source to support you know the analysis and kind of show how these how delivery is affecting trip making. So anyway, the type of item that's purchased is really you know looking at clothing is very popular for deliveries whereas you know groceries and prepared meals still tend to be purchased more in person and again this is pre-COVID.
 
Pre-COVID data also today meaning the time of the survey, which was 2018,  one in seven shopping trips has been replaced by a delivery trip. That is a major substitution effect and we found also that errors found that deliveries are also replacing both vehicle trips and non-vehicle trips. So that part is actually very important for the net effect of e-commerce because let's say deliveries are replacing walking and bicycling trips well that's going to be terrible for energy impact right but if they're replacing more car trips then it may actually be a good thing depending on which type of trip is more efficient. The last point I wanted to make on this slide is that households that are using e-commerce are actually shopping a little more each week or rather generating an additional small amount of shopping called events each week and this is called induced demand. So, and this is something that we think is generated by you know the convenience of the extra convenience of online shopping and some you know some cost savings.
 
So now moving into the main e-commerce results at the metropolitan level and by the way I should also mention that the previously in the webinar series the whole traveler survey was covered in a lot of detail by Anna Spurlock. So please you know refer to that if you want to see more information. So now yeah moving into the main e-commerce results. So, we did find actually that an increase in e-commerce lowers the overall system vehicle miles traveled and energy and the reason is as I’ve like hopefully kind of set it up. So, it’s you can see at this point is that the delivery trips that are out there are they're only adding about you know point four miles on average for every additional stop whereas a shopping trip on average is about between seven and eight miles. So, this is a huge difference in vehicle miles traveled and it ends up having you know tremendous implications both for VMT as well as for energy.
Se qualify here the energy savings the VMT and energy savings from the e-commerce system the first bar on this bar chart each of these bar charts shows the baseline where households have one delivery per week then the next two bars are for the five deliveries per week scenario with variations of high and low sharing of passenger vehicles and to hit home the point the VMT savings between the baseline and this future scenario is somewhere between 41 and 56 depending on the you know the level of sharing activity of passenger cars. So that's a that's a huge VMT savings energy similar 29 to 54 energy savings as delivery shifts from one delivery per week to five deliveries per week per household. So, this was this is really the key finding of the e-commerce study and finally this this the looking at the share of vehicle miles traveled in energy by medium duty and heavy-duty trucks this is a where all of that scenario information the parcel delivery trucks the vehicle technologies the commodity flows all that scenario information comes together to show you know kind of what is the overall effect of that of those changes. 
 
So, in the baseline as David went over earlier trucks consume about 33% of transportation energy in the Chicago region on the other hand, in the future their share is projected to be closer to 50% and again it's you know right now the freight vehicle technology is it's really, it's lagging the light duty in terms of especially electrification technologies. So, and not only is the technology itself kind of slower to develop but also the adoption is it's obviously very slow right now you know those electric vehicles are very costly for heavier vehicle types. So, the passenger market is having you know this more rapid adoption. So, both of those factors as well as the increase of freight demand are contributing to this higher share.
So in conclusion we found that yes the retail system with e-commerce it does appear to be more efficient than the one based on household shopping alone it's due to that the different characteristics of those trips also the passenger vehicle technologies are progressing more quickly than freight leading to freight's outsize impacts on the system and then finally just reminder this study reflects pre-COVID trends and definitely we expect a lot of a lot of things to have changed in the last in the last year. So, with that I will also acknowledge and thank the other contributors to this study at both the Argonne National Lab as well as Oak Ridge Lawrence Berkeley and Idaho national labs and I would like to thank you.
 
Thank you, Monique! Thank you for the presentation. I will invite Alicia to also unmute and perhaps share your video if you are no longer hindered in doing so. By sharing your screen and we will have about 10 minutes for Q&A. Thank you both again for your presentations there's a question here which I believe is probably aimed at something that Alicia talked about in in her presentation. “What are the main barriers in realizing the huge potential of platooning on the road?” I have some of my own thoughts on that, but I will let you begin. Yeah, that's a great question and you know we have seen some OEMs come out and say there's not enough savings to be had despite some of what we've shown, and I think some of the biggest barriers are the coordination burdens. Basically, you know what's the incentive for fleets or for truckers from different fleets for example to join a platoon especially if the lead vehicle is going to see much lower savings in the trailing vehicle. So, I think it’s mainly going to be a coordination issue technically there may be folks that maybe there's some folks who have done more the technology deeper dives might have some other thoughts on some of that.
 
Yeah, thanks Alicia yeah, I’ve seen some of some of the results of some of our studies within the consortium talk about the you know the barrier of coordination between drivers. As you've mentioned there are some penalties also in terms of, I guess it comes down to coordination, but you know waiting accelerating trying to join the platoon things like that that actually diminishes some of the benefits that would have otherwise gained another question here. So, you know obviously Monique you mentioned a number of times a lot of our modeling work was done prior to COVID. So the question is “how has COVID impacted the retail freight sector and is this change temporary or permanent per minute?” Yeah, that's a great question and there's definitely been a lot of interest and webinar activity going on you know in the transportation community. Well, you know what the statistics that I hear the main one is that it's accelerated e-commerce by anywhere from three years even up to five years and you know and at the local level we obviously are seeing a you know especially at the beginning saw a huge uptick in grocery e-commerce which was a huge laggard and for years you know it’s such a huge market segment that for years you know the players all wanted to get more grocery commerce going. So that there is some thinking that you know now that a lot of people have tried it for the first time and there's some research to show this too now that people have actually tried it out there is an opinion that it will stick maybe not to the extent that it has been going on during the pandemic but certainly to some extent and I would say the same thing for retail other types of retail deliveries another one that is I mean really interesting is the you know it’s kind of accelerated the decline in brick and mortar. So, there have been you know a lot more vacancies and even say malt there's been talk of trying to convert malls to distribution centers but that I mean when I first heard about that I thought that's a really interesting idea and I mean the space is about right and, but it turns out I mean there they would not be at all cost effective for distribution centers. So, I don't think that's going to work out but those are those are two of the main ones.
 
Yeah, thank you thank you for those thoughts Alicia, I don't know if you have anything to add in terms of, I guess perception of the permanence or temporary nature of changes to the freight sector and in terms of COVID. Yeah, I think Monique summarized it very well you know it's anybody's guess what's going to happen in the future but there's no expectation that things will go back to pre-CODIV that just you know in a lot of ways and in e-commerce especially. Great, thanks!
 
This one is I think primarily targeting Alicia. So how you talked about drone delivery and the efficiency of drone delivery how confident are you in the estimate energy estimates for drone delivery that's a mode that hasn't been widely deployed and doesn't really exist yet. So how confident are we in those estimates that you provided well I think the great thing is that the first time we actually do have empirical data whereas we didn't have it before in even if I don't even know if any of the manufacturers had made any claims to that effect. So, it's a great innovation for us to have that data but obviously we would love to have more data and there's going to be more innovation in in the field of drone design and that sort of thing. So, I think moving forward there are opportunities to improve our knowledge here.
 
Great thanks, took me a second to find my unmute button we have a question for which particular application IRV urban regional line hall etc. Do you see the most advantage of transitioning to hybrid and or full electric trucks? Maybe Alicia will start again with you since you talked a little bit about some of the powertrain technologies and then maybe Monique can weigh in yeah, I think that I think the advantages of the different power trains are different in the different sectors and. So, for instance you know the battery electric AVI obviously has in addition to the energy and carbon emission proposition also has advantages of quiet operation and that sort of thing in city and urban environments that aren't necessarily as much of an advantage elsewhere and also you know the range limitations become less of a concern but of course you know being able to get enough miles to pay back is the potential limitation there. So getting the cost down is important meanwhile in that regional the regional hall you know we saw how varied that that operation can be which maybe makes it makes a an argument for a plug-in hybrid that could give you that flexibility but still maximize your all-electric range on those days when you don't need the diesel engine whether that can be done cost effectively again that's an area for research and then in the longer hall hybridization it's starting to look like it has more benefit than I think we initially thought it might and whether there are even there are obviously there's also fuel cell technologies which we didn't we didn't address but you know I don't think it becomes a one winner case at this point.
 
Yeah, and I would echo that and add you know a couple of you know pretty interesting markets I think are say like the medium haul out and back overnight type trips where you know maybe you can get the full range on one charge. That seems to have very good potential at the medium range and then also I mean that yeah to elaborate a little more on the it was a great point about the quiet operations there are a lot of cities where I mean downtown or you know those deliveries are in in in these downtown environments is capped. So, its people aren't allowed to deliver before say 7-8 a.m. and those can you know releasing that restriction due to noise could really help with off hours delivery which has been shown in other studies that were partnered on to have a good effect. Great thank you both another question that's kind of related to the last one. “Is the industry really interested in adopting more efficient vehicles and using less energy why would they?” So maybe we'll start again with Monique and let Alicia weigh in. yeah, I mean they are, and you know we hear we do hear all the time as we're talking with industry. it's an Alicia's you know leading an effort right now to kind of solicit opinions directly about that which I’m sure she'll talk about, but you know for a long time it's been I think that a decade ago it would have been like yeah, we're interested but you know that's just not you know we'll leave it up to the passenger world right now to kind of like improve. But yeah, sustainability greenhouse gas it comes up all the time and it's very much on their radar.
 
Can you add to that Alicia? I’m sorry yeah absolutely you know not the first thing I would say is that the fleet customer you know fuel is I think like the second largest expense after the driver pay? So, without a doubt fleets are motivated to save money. So, they're motivated to save energy you know the hesitance comes in from it being a fairly risk-averse industry because it is a volatile industry and they and they have very narrow margins. But at the same time yes, it is true that you know beyond the fuel savings and the and the cost savings that that green initiatives and sustainability and images becoming far more and more important and then from the I think from the manufacture perspective we have to keep in mind that most of these manufacturers are global manufacturers and. So, they have to respond to what goes on in other countries as well and if they can harmonize a platform and use it across you know globally it gets their sales volumes up and. So, it's to their advantage. So, there is there's a lot of activity and a lot of motivation yeah if I can mention one just one last point on that I do recall in a few webinars that I was listening to  fleet managers talking about how they they're hearing from their customers too that their customers want more you know energy and environmentally friendly solutions. So, it's also helping to drive it!
 
Awesome well thank you both it is four o'clock eastern time we're at the top of the hour and the end of our webinar. So, thank you Dr. Birky and Dr. Stinson for joining us and thank you to all the attendees for joining us sorry if there are questions that we were unable to get to. I will remind you all that if you are interested in going into some of the more detailed results from our Smart Mobility consortium you can download the six capstone reports that we published in a few months ago at the link shown here on your screen one for each of the five pillars and one for the workflow itself that link is also where you can register for our seventh and final webinar which will take place two weeks from today. Focus on evaluating EV charging infrastructure needs in a Smart Mobility system. So, this one largely comes from our advanced fueling infrastructure filler. Again, thank you for your attendance and your attention. Thank you to our speakers stay safe everyone and we will meet again in two weeks. Thank you