Modeling Future Scenarios To Make Airport Travel More Efficient (Text Version)

This is the text version of the video Modeling Future Scenarios To Make Airport Travel More Efficient.

[Narrator speaks]

Airports like Dallas Fort-Worth (or DFW) are busy hubs that coordinate the movement of passengers, goods, and services from surrounding areas.

[Images on screen: Airplane at the center of a map, surrounded by trains, buses, taxis, cars, motorcycles, bicycles, and pedestrians. Roads on map darken and connect.]

ATHENA's aim is to use data and high-performance computing to make all of this activity more affordable and efficient. Here's how it works.

Experts from NREL and Oak Ridge National Lab collect DFW Airport data, including traffic patterns, freight routes, flight schedules, weather forecasts, and other sources.

[Images on screen: NREL logo and Oak Ridge National Laboratory logo connect via the logo for the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy’s Vehicle Technologies Office. Logos are surrounded by icons representing weather forecasts, flight schedules, freight routes, fleet analytics, traffic data, ride-share data, and demographics.]

Then, they leverage the labs' powerful supercomputers to model and optimize the integration of new transportation technologies at the airport.

[Images on screen: Supercomputer appears at center, while the aforementioned icons move into the supercomputer.]

The supercomputers allow the researchers to explore hundreds of thousands of potential future scenarios and optimize the energy cost per trip of the various types of transportation.

[Images on screen: A circular infographic with an airport at the center. Along the top half of the circle are icons representing air traffic, freight, and vendor supplies. Along the bottom half are icons representing light rail, taxis, bus shuttles, connected and automated vehicles, and electric vehicles.]

They're developing a "digital twin" model of DFW Airport that uses traffic and human choice modeling, along with artificial intelligence, to simulate the impacts of future scenarios.

[Images on screen: The airport icon from the center of the infographic is duplicated next to the infographic, with a copy below it, and the words “digital twin” between the two airport icons. These icons are connected to the supercomputer, which is surrounded by text: DFW early wins, technology projections, validation, and HPC simulation.]

An iterative process validates the data to project current and future behaviors, based on expanded mobility choices to and from transportation hubs, increased freight volume, and the anticipated dynamics of airport access.

[Images on screen: A graph shows mobility energy productivity increasing over a 20-year time span, with mobility energy productivity increasing more quickly and dramatically for “optimized scenarios” than for the “status quo,” which remains fairly static.]

The result: Useful, actionable results that help DFW and other ports effectively integrate transformative technologies like autonomous vehicles, shared mobility, grid-connected electric vehicles, and drone transport.

[Images on screen: Icons representing boxed package, large package, forklift, taxi, electric vehicle, autonomous vehicle, freight truck, bus, train.]

Learn more about ATHENA at athena-mobility.org

[Text on screen: This research is funded by the U.S. Department of Energy’s Vehicle Technologies Office.]