Dynamics of particulate emissions in the presence of autonomous vehicles

Abstract

Around one third of CO2{{\rm{CO}}}_{2} emissions in the atmosphere are linked to vehicular traffic. Pollutant agents have an impact on the environment, in particular, the increased presence of particulate matter (PM) creates negative effects on human health. This article examines how autonomy could positively reduce the emission of air pollutants due to traffic. The methodology involves the analyses of PM emissions as a function of traffic conditions, especially in the presence of autonomous vehicles (AVs) dampening traffic waves. The starting point is traffic measurements that, gathered from real experiments involving a fleet of vehicles moving on a ring track, exhibit the presence of stop-and-go waves that are dampened by control strategies implemented on a unique AV. Using a system of ordinary differential equations modeling the principal chemical reactions in the atmosphere, it is proved that wave dampening implies a significant decrease in PM emissions at ground level. The horizontal diffusion of the pollutants is estimated by partial differential equations combined with the model for chemical reactions. The obtained outcomes show advantages given by the improvements in traffic flows and the mitigation effect of green barriers.

Keywords

• road traffic
• emissions
• particulate matter
• ordinary and partial differential equations
• 34a34
• 35k57
• 62p12