Air pollution from traffic has severe human health effects and therefore, it is targeted by environmental policies. To take into account human behavior in this process, we will develop a human component for an air quality model using agent-based simulations. Society is modeled as a complex system with humans represented as agents interacting to reveal new properties of the system as a whole. Agents learn and decide using artificial intelligence (AI). Specifically, we will adapt an agent-based traffic model for Helsinki city, quantify the effect of traffic-related incentives on air quality with direct feedbacks from human behavior, and use AI optimization to identify the most efficient incentives for air quality improvement. With these tools, we will launch a new era in air quality modeling and provide invaluable information for policy makers and city planners on ways to reduce traffic emissions and their health effects, with vast future potential for redeeming polluted mega-cities.
The project is funded by the Academy of Finland.
Assoc. Prof. Nønne Prisle (nonne.prisle (at) oulu.fi)