Improvement in airport operations using optimization schemes has been an active research area in the recent years. Particular attention has been given to improve taxiway and runway queue operations. However, once these operations are improved by an efficient taxiway schedule, its execution relies on the planning of ramp-area aircraft movements. An important step in the integration of the taxiway schedule with the planning of ramp-area aircraft maneuvers is to understand the constraints imposed on the aircraft trajectories due to the geometry of ramp-area and aircraft kinematics. Data for ramp trajectories are usually unavailable. To address this, we use an inexpensive scaled-down robot experiment to collect some critical data about aircraft trajectories. Ramp movement trajectories are then modeled by stochastic processes since they are heavily dependent on the human operator. We use the stochastic model to analyze the relationship between aircraft pushback time intervals and ramp-area conflicts. We then discuss constraints that can be imposed on aircraft pushback intervals to avoid any conflicts among trajectories.

The integration of aircraft maneuver characteristics into an optimal taxiway scheduling solution is challenging due to the uncertainties that are intrinsic to ramp area aircraft trajectories. To address the challenge, we build a stochastic model of ramp area aircraft trajectories that is used to generate a probabilistic measure of conflict within the Charlotte Douglas International Airport (CLT) ramp area. Parameters of the conflict distributions are estimated and passed to a Mixed Integer Linear Program that solves for an optimal taxiway schedule constrained to be conflict free in the presence of trajectory uncertainties. Here we extend our previous research by accounting for departing and arriving aircraft whereas our prior formulation only accounted for departing aircraft.

NASA has been working with the FAA and aviation industry partners to develop and demonstrate new concepts and technologies that integrate arrival, departure, and surface traffic management capabilities. In the fall of 2017, NASA began deployment of their technologies in a phased manner to assist with the integrated surface and airspace operations at Charlotte Douglas International Airport (Charlotte, NC). Initial technologies included a tactical surface metering tool and data exchange elements between the airline-controlled ramp and Federal Aviation Administration controlled ATC Tower. In this paper, we focus on the procedures associated with the tactical surface metering tool used in the ramp control tower. This tool was first calibrated in Human-In-the-Loop simulations and was further developed when it was used in the operational world. This paper describes the collaborative procedures that the users exercised in their respective operational worlds to enable surface metering and how several metrics were used to improve the metering algorithm.

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