Pollutant emission estimation in mixed traffic flow of automated and human-driven vehicles: a case study of a highway segment

This thesis investigates the environmental impact of varying penetration rates of automated vehicles (AVs) in mixed traffic conditions by estimating vehicular emissions along a highway segment in the city of Padova, Italy. The analysis focuses on how different levels of AV integration influence traffic flow characteristics and pollutant output. Pre-generated traffic simulation data from PTV Vissim, representing several AV penetration scenarios, serve as the basis for the study. Emissions are calculated using the EPA MOVES (Motor Vehicle Emission Simulator) software, which models vehicle activity and outputs based on traffic conditions. While some localization is applied, the software’s U.S.-based parameters present certain limitations when applied to the Italian context. The results include statistical and graphical comparisons of key pollutants—such as CO₂, NOₓ, PM, CO, SO₂, N₂O, CH₄, and VOCs—across scenarios. Findings highlight how increased AV presence may affect emission levels through changes in traffic behavior, offering insights into the potential environmental benefits or drawbacks of future AV adoption in urban transport systems.