TRAPSim
A transport-health ABM that simulated commuters’ exposure to non-exhaust PM10 emissions to make a preliminary estimate of their health effects
This model was a transport-health ABM (TRAPSim) that simulated commuters’ exposure to non-exhaust PM10 emissions to make a preliminary estimate of their health effects. In NetLogo, I applied an A-star algorithm to assign the vehicles’ trajectories to their destinations, and a Local Search algorithm to assign pedestrians mobility patterns. The model also had traffic signals to enforce the vehicles to stop and go, and during their acceleration and deceleration, the vehicles produced more particles to the air. The findings of this study indicated that pedestrians who had longer commute hours and more exposure to ambient particulates have had additional health loss compared to the intra-urban drivers, although the emergence of health risk appeared to drivers when 10 was persistently high for a few days. The outcomes were presented as a full proceeding paper at European Social Simulation Conference 2021 (accepted for Springer publication in 2022). I am expecting to find more collaboration opportunities associated with non-exhaust emission as well as broader traffic simulation approaches.