There has recently been an increased interest in exploring potential environmental applications for vehicle telematics and Intelligent Transportation Systems (ITS). Green routing or eco-navigation is one such application, which attempts to direct travelers to the most fuel efficient (or least emissions) route rather than the fastest or shortest route. Implementing such a concept in practice, however, requires computationally-efficient models that can accurately and quickly estimate the likely environmental cost associated with a given trip. In this paper, a simplified, macro-model for estimating fuel consumption, Carbon Monoxide (CO) and Nitrogen Oxides (NOx) emissions is developed and validated with the Burlington metropolitan network in Vermont and Buffalo-Niagara metropolitan network in New York. The model is based on only five, readily available trip attributes, which makes it ideal for implementation on smart phones or GPS navigation devices. The results indicate that the fuel consumption estimates were very close to the detailed MOVES results, whereas the CO and NOx estimates were not as good. Nevertheless, by applying appropriate adjustment factors, to account for environmental differences between Burlington and Buffalo, it was possible to make the CO and NOx emissions estimates made more precise._The results also demonstrate that the green routes appear to favor 1) relatively shorter-distance routes; 2) the lower-profile or ranked road type; and 3) the route with the significantly lower "Dominant Grade " for fuel-savings purposes.
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