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Connected and Automated Vehicles (CAVs)
The continued growth of CAV technologies changes the way vehicles move and travelers achieve mobility. The EEMS Program is identifying the significant impacts CAVs have on energy consumption, as well as other facets of transportation, at scales ranging from the individual vehicle level to the transportation system level.
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Mobility Decision Science (MDS)
MDS examines the underlying identity, preference, personality, lifecycle, geographical, and contextual factors that impact transportation behaviors. Interest includes adoption and use of emerging transportation technologies and services such as vehicle automation, vehicle electrification, ride-hailing, shared modes, and e-commerce.
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Urban Science (US)
US focuses on maximum-mobility and minimum-energy opportunities associated with emerging technologies and transportation-technologies within the urban context, and views cities as living organisms. The urban mobility system consists of a complex network that reaches well beyond roads and vehicles to include public transit, parking reserves, curb management, and more.
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Advanced Fueling Infrastructure (AFI)
AFI initiatives use modeling, simulation, and data analysis tools to investigate tradeoffs in different charging infrastructure network designs for human-driven and fully automated transportation options. It also assesses the potential of charging infrastructure installed to support ride hailing to influence mobility and energy-consumption trends on a national scale.
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Multimodal Freight (MMF)
MMF research and development is used to assess the effectiveness of emerging freight movement technologies and understand the impacts of the growing trends in consumer spending and e-commerce on parcel movement considering mobility, energy, and productivity. This assessment is accomplished by using available data sets and modeling tools to understand trends in freight movement and the associated impact of alternative technologies in the medium-and heavy-duty space.
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SMART Mobility Workflow
The SMART Workflow allows researchers to evaluate the energy, mobility, and affordability outcomes of potential future transportation scenarios. The EEMS Program evaluates these outcomes in terms of vehicle miles traveled, travel time, energy, cost, greenhouse gas emissions, and other metrics. Agent-based modeling frameworks, such as POLARIS, are used to simulate large-scale transportation systems, such as the one in this image. This allows for the development of integrated models to evaluate transportation improvements.
Photo courtesy of ANL