Presented at the Canadian Society of Mechanical Engineers Forum 98 Symposium on Recent Advances in Transportation Systems and Technologies

Many people expect that the anticipated near and medium term deployment of intelligent transportation systems (ITS) will produce significant benefits in terms of reduced congestion, increased safety, reduced emissions, and reduced fuel consumption. While these expectations may be realised, limited research has been conducted to-date to explicitly quantify these benefits, particularly in terms of the environmental benefits. Furthermore, there is the expectation that these ITS will enable traffic engineers to implement traffic control strategies that satisfy legislated air quality standards. Unfortunately, the relationships between various traffic management options and the resulting air quality impacts are generally poorly understood. This paper describes the use of a traffic network simulation model to quantify the impact of traffic management strategies on network traffic conditions. The model is capable of estimating spatially and temporally correlated pollutant emissions on the basis of a drive mode elemental emissions sub-model. These emissions are used as input to a Eulerian air quality standards model, in which the dispersion of the pollutants is modelled. In this way, the air quality estimates are sensitive to the implemented traffic management strategies. This approach provides a mechanism by which the impact of different ATMS/ATIS strategies on air quality can be quantified and considered when selecting the desired strategy. The approach is demonstrated on an urban network representative of Detroit, Michigan. The traffic and air quality impacts of a typical ATMS strategy is quantified and discussed. 1