Assessing emissions impacts of automated vehicles
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Assessing emissions impacts of automated vehicles

Filetype[PDF-246.14 KB]


English

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  • NTL Classification:
    NTL-ENERGY AND ENVIRONMENT-Air Quality;NTL-ENERGY AND ENVIRONMENT-Alternative Fuels;NTL-ENERGY AND ENVIRONMENT-ENERGY AND ENVIRONMENT;NTL-ENERGY AND ENVIRONMENT-Environment Impacts;NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION;NTL-PLANNING AND POLICY-PLANNING AND POLICY;NTL-INTELLIGENT TRANSPORTATION SYSTEMS-INTELLIGENT TRANSPORTATION SYSTEMS;NTL-INTELLIGENT TRANSPORTATION SYSTEMS-Driver Assistance Systems (Vehicles);
  • Abstract:
    With their potential for transforming surface transportation, understanding the impacts and benefits of automated vehicles (AVs) with regards to safety, mobility, energy and the environment is a necessary first step for informing policy to aid the successful introduction of AVs into an already complex transportation system. As part of a larger work to develop a framework for assessing impacts of AVs in several different areas of interest, this paper serves as an early implementation proof-of-concept for a methodology to integrate microsimulation runs with MOVES analysis to calculate emissions and fuel consumption for AVs. Four scenarios for a single-lane, 2-mile-long roadway are modeled in a microsimulation model: at-capacity with only human drivers, at-capacity with only automated vehicles, over capacity with only human drivers, over capacity with only automated vehicles. In this study, automated vehicles are only modeled very simply, by removing oscillation in following distance behind other vehicles. The trajectory data is used to calculate and assign operating modes for the vehicles along the roadway. Using MOVES 2014a, this operating mode distribution is used to calculate fuel consumption and emissions for certain pollutants and results are discussed and compared. It was found that automated vehicles oscillate less around a primary operating mode and also, overall, produce less emissions and consume less fuel than a roadway with only human drivers. This study indicates that a proper assessment of emissions and fuel consumption can be calculated from output from a microsimulation model. Later work will investigate a variety of other scenarios that simulate anticipated automated vehicle behavior and vehicle operations.
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