1. Background
To successfully transition the trucking industry to low-carbon energy carriers, different stakeholders need to pace investments to meet ambitious targets while minimizing transition risk. Truck manufacturers need to align specifications and production volumes, logistics providers need to prioritize fleets and corridors for transition, and infrastructure providers need to invest in charging and alternative fuel stations at the right time and place.
My last post built on an initial exploration of geospatial freight flow visualization by presenting a preliminary non-interactive geospatial tool designed to help trucking industry stakeholders assess where and how best to transition fleets to alternative energy carriers. The tool combines a range of geospatial data from public sources to visualize decision support layers including regional freight flow densities, emission intensities, planned and available infrastructure, and supporting regulations and incentives.
This update presents an interactive version of the tool, which is now available on the MCSC's DataHub website. The full code base has since been moved to this MCSC GitHub repo. The online interactive tool (code here) is based on openlayers, and most of the custom functionality is encoded in Javascript. Developer Brilant Kasami did awesome work integrating the tool into the DataHub.
2. How to access the tool
The interactive tool can be accessed on the MCSC DataHub website as follows:
Create a username and password on the DataHub website here: https://climatedata.mit.edu/users/register/
Log in with your user credentials here: https://climatedata.mit.edu/users/login/
Access the tool here: https://climatedata.mit.edu/faf5/transportation/
3. User-interactive features
Here's a quick screen video showing some of the tool's layers and interactive features, which are described in more detail below.
Video 1: High-level demo of the tool's interactive features
Size and color gradients
Many of the layers have one or more associated attributes that are useful to visualize with gradients. The method by which these gradients are visualized depends on the layer type.
Layer type | How is the gradient visualized? | Example |
Area | Area color (white to red) | Layer: FAF5 regions Gradient attribute: Total imports and exports  |
Line | Link width | Layer: U.S. interstate network Gradient attribute: Annual tons carried  |
Point | Point size | Layer: Hydrogen production facilities Gradient attribute: Production capacity  |
Dynamically updating legend
The legend displayed at the bottom left shows the names of layers being visualized next to representative icons. For layers with gradient attributes, the legend icon shows the gradient scale, and the name indicates the attribute being visualized along with associated units.
The legend details update dynamically as layers are selected, de-selected and customized.
Dropdown for area layer selection
Area layers can be selected one at a time for visualization using the dropdown menu at the top. The constraint to only view one area feature at a time is imposed to avoid potential confusion from overlapping features blocking each other out.
Figure 1: Using the dropdown menu to visualize the emission intensity of the grid.
Multiple-choice highway and point layer selection
Any number of highway and point layers can be visualized simultaneously, since overlap confusion is less of a concern with these layer types.
Layers to visualize are selected with checkboxes. To avoid cluttering the interface, checkboxes and associated layer names are hidden by default. Different classes of layers (eg. highway flows, planned infrastructure corridors, etc.) can be expanded for viewing and selection by clicking on the associated 'show' button (eg. 'Show Highway Flows').
Figure 2: Using checkboxes to visualize several point and highway layers at once
Pop-up window for data sources and layer gradient customization
Each layer in the interface has a blue 'More' button to the right of it. Clicking the 'More' button next to a given layer opens a pop-up window with the following:
Information on where the data was collected, usually with a link to the original data source.
For some layers, the user can customize details of the displayed gradient attribute. For such layers, the pop-up window includes one or more dropdown menus for this customization. For example, the 'Truck Imports and Exports' gradient can be customized to visualize imports or exports separately, or associated fuel production and combustion emissions (Section 2 of the previous post describes how these emissions are evaluated).
Figure 3: Dropdown menu to customize details of the number of incentives and regulations being visualized as a gradient attribute for U.S. states
4. New layers
Here's a quick summary of new layers added since the last post:
Funded infrastructure projects
These layers visualize regions and highway corridors that have been publicly funded for targeted heavy duty vehicle infrastructure projects.
Figure 4: Selection of funded heavy duty vehicle infrastructure projects funded by the Biden-Harris administration
State-level incentives and regulations
This layer includes a gradient attribute to visualize the number of state-level incentives and regulations by state. The pop-up window viewed by clicking the blue 'More' button provides functionality to customize the following gradient attribute details:
1) the type of fuel being supported (hydrogen, biofuels, electricity, etc.),
2) the type of support (incentives or regulations), and
3) what aspect of adoption the support targets (fuel use, infrastructure installation, or vehicle purchase).
Figure 5: Number of state-level incentives and regulations, for a sample set of gradient attribute options (all fuels -> hydrogen only -> 3. hydrogen incentives only -> 4. hydrogen infrastructure incentives only)
Hydrogen production facilities
These layers visualize the locations and capacities of planned, installed and operating hydrogen production facilities. Facilities shown in shades of green use or plan to use electrolysis, and facilities shown in gray are located at oil and gas refineries, and produce "gray" hydrogen using the natural gas reforming process.
Figure 6: Locations and capacities of hydrogen production facilities
5. Thought experiment: Potential savings from pooled charging infrastructure investment
As a first case study demoing the interactive tool's functionality, a hypothetical thought experiment is developed to visualize potential savings from pooled investments in charging or alternative fueling infrastructure. The thought experiment leverages two of the mapping tool layers: 1) highway flows long the U.S. interstate network and 2) truck stop locations (available under 'Show Other Point Features').
The thought experiment, demoed in the video below, highlights two important points:
Appreciable savings from pooled infrastructure investment are possible in principle, even at the level the entire U.S. trucking fleet.
We can expect the benefits of pooled investments to be most pronounced early in the transition when fleet sizes are small, because smaller fleets can expect to reap higher efficiency gains from combining their numbers with other fleets.
The thought experiment and its underlying assumptions and methodology are detailed in this whitepaper. Huge thanks to Sean Lo, Ph.D student at the MIT Operations Research Center, for his review and constructive feedback to improve the whitepaper.
Video 2: Using the geospatial mapping tool to demonstrate the thought experiment described in this section
6. Next steps
We've received lots of valuable insights from experts in industry and academia on how the tool can evolve to best support decisions around fleet transitions. Huge thanks especially to Philipp Leutiger for his amazing support in facilitating a set of deeply insightful interviews with industry experts from a range of fields.
Case Studies
Currently, the tool offers a convenient interface to visualize a wide range of geospatial data relevant to fleet transition decisions. Building on this, I'd like to develop more case studies like the above thought experiment to demo how the available layers and functionality can be leveraged to anticipate important trends and guide fleet-level decisions.
For example, given the tight profit margins in the trucking industry, stakeholders are keen to identify regions and operating conditions in which they can be confident that fleets can transition to alternative energy carriers without significantly impacting operational reliability or profitability. Moving forward, it would be interesting to combine the mapping layers with a total cost of ownership (TCO) model to help users visualize projected TCO with respect to different regions and operating conditions.
User interface
I'd like to integrate more deliberate guidance into the user interface to support users in leveraging the tool for decision-making and analysis. This could include building in guided template analyses that users can modify to suit details of their fleets or needs.
Other suggestions I've received help refine the user experience include:
Organizing the layers and interface with respect to classes of alternative energy carrier (eg. electricity, hydrogen and biofuels) to help users easily compare between the different carrier options.
Customizing the user experience (eg. gradient attribute options and template analyses) and according to the user's role in the trucking industry (eg. fleet owner, policymaker, shipper, etc.).
Infrastructure planning data
Building on the new layer showing publicly funded infrastructure projects (see figure 6), we've heard interest from a few industry stakeholders in seeing more data on planned infrastructure projects to help them anticipate where there will be sufficient infrastructure to support deployment of alternative fleets. So another next step will be to look into sourcing and adding more infrastructure planning data, ideally from both public and private sources.