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Technology Commercialization and Partnerships

Compass: Transportation Energy Analysis Model

The Challenge

The transportation sector is rapidly moving to electrification, shared mobility and autonomous vehicles. Such changes eventually will affect how decision-makers (e.g., investors, agencies, fleet managers) make decisions about where to place charging and other infrastructure investments and how to position their service hubs and related activities.

However, current models these investors/agencies use do not capture the interactions over space and time between consumer choices and stakeholders decisions.

What Argonne Offers

Researchers at the U.S. Department of Energy’s Argonne National Laboratory have developed a large‑scale computational model – known as Compass – to capture interactions between consumer choices and stakeholders decisions, helping decision-makers to make investments more efficiently, to better position their vehicle fleets and service hubs, and, eventually, to better serve their customers.

Compass – formerly known as A-TEAM – models the complex behavior and interactions between travelers, agencies and service providers for long-term infrastructure planning, technology adoption and systems optimization (e.g., reducing cost, risk and interruption while increasing benefits).

Compass is made possible by Argonne’s unique combination of world-renowned behavior modeling capabilities, high-performance computing resources, and deep knowledge in vehicle connectivity.

The Benefits

Federal Agencies:

  • Help identify and anticipate what is needed to prepare for and meet different levels of demand as mobility evolves.
  • Help determine how demand can be met most efficiently using domestic energy sources and with minimum infrastructure investment.
  • Balance the adoption of electric vehicles (EVs) with the need to maintain revenue streams that support critical transportation infrastructure.

Utilities:

  • Help determine where to locate chargers to promote usage and EV adoption and maximize associated revenue streams.
  • Model the economic impacts of enabling long-distance travel using EVs.
  • Quantify the social equity impact of transportation electrification and identify mitigation measures.
  • Help identify optimum locations for service hubs for electrified autonomous vehicles.

Transportation Fleets:

  • Help identify impacts of electrified autonomous vehicles on grid infrastructure.
  • Pinpoint locations for service hubs based on users’ short-term travel and shopping behaviors.

Cities:

  • Help sustainability offices understand and anticipate the long term energy and environmental impacts of new trends. In addition, allow for the setting of goals and timelines based on technology affordability and adoption in the future.
  • Help mobility offices develop long‑term zoning requirements (e.g., parking space, density, time) and taxing policies to support electrified and automated vehicle fleets.