Development of Generic Vehicles for Fleet-Level Analysis of Noise and Emissions Tradeoffs

A fleet-level analysis of technology impacts on environmental metrics via generic vehicle design is proposed. Vehicles are grouped into “vehicle classes” distinguished by the vehicle-level environmental metrics, which include fuel burn (as a surrogate of CO2 emissions), NOx emissions, and SEL noise contours. These groupings are compared against traditional seat class groupings. Target metrics are established for a subset of 94 airports by designing a series of tests of sequentially increasing complexity, with ideal generic vehicle designs minimizing the error distributions across these airports when vehicle-level performance is aggregated to fleet-levels. Latin hypercube design of experiments are employed to explore the Environmental Design Space (EDS), and Stochastic Multicriteria Acceptability Analysis (SMAA) is used to evaluate potential generic vehicle designs against each other and identify the best designs for simultaneously matching aggregate fuel burn, NOx emissions, and DNL contours. In general, the average generic vehicles provide greater accuracy for each of these metrics across across the 94 airports for a representative six weeks of operations at these airports derived from various sources such as the Bureau of Transportation Statistics (BTS), as compared to the traditional approach of choosing a representative vehicle per class. The average generic vehicle approach works well for both vehicle-class and seat-class groupings, but the former leads to slightly tighter error distributions for all of the metrics.