Inefficient surface traffic management may lead to congested taxiways, long departure queues, and excess delay in the air transportation system. To address this problem, NASA researchers have developed optimization algorithms and a concept of operations for an airport surface traffic management tool called the Spot and Runway Departure Advisor (SARDA). Past SARDA research efforts have been focused on the Dallas/Fort Worth International airport. This paper describes the development of SARDA-like schedulers for managing the traffic at an operationally dissimilar airport-Charlotte Douglas International airport, and presents the results of a fast-time simulation-based benefits assessment. Fast-time simulations were conducted to test the benefits of optimized scheduling over a baseline model of current-day operations. In the fast-time simulations, it was observed that optimization schedulers reduced movement area delays by up to 3.1 minutes per departure on average, as compared to the baseline simulation. The movement area delay savings translated to shorter movement area taxi-out times and an average reduction in fuel burn and emissions of approximately 24% per departure. The overall trend observed in the total delay (gate delay + ramp delay + movement area delay) comparison indicated the optimization schedulers were not able to reduce total delay, and runway throughput comparisons suggested the optimization schedulers had little to no effect on throughput.
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