Gis-based Multi-agent Traffic Micro Simulation for Modelling the Local Air Pollution

Air pollution from motor vehicles is one of the most serious and rapidly growing problems in metropolitan areas. It is occurred especially in major arterial streets inside the metropolitan central district because of the heavy traffic congestion suffering. Although transportation networks operate as an integrated system, at a regional level we can safely assume that local urban congestion will not affect other urban areas that are geographically distinct. This suggests a manageable problem, i.e., instead of solving for region-wide congestion patterns, we can augment the current capabilities of logistical air quality management system (AQMS) software with a module to predict localized urban congestion on a special major arterial street and its impacts on the amount of generated air pollution. In this paper, a GIS-based multi-agent traffic micro-simulation decision support approach utilized in order to manage and control navigation under dynamic traffic identification and modelling to determine the air pollution, particularly CO, generated by heavy traffic congestion in one of the major arterial urban streets. Our preliminary work in this area indicates that agent technology can significantly help designers and decision makers in this context. * Corresponding author.