Impact of Arrivals on Departure Taxi Operations at Airports

Aircraft taxi operations are a major source of fuel burn and emissions on the ground. Given rising fuel prices and growing concerns about the contributions of aviation to air pollution and greenhouse gas emissions, recent research aims to develop strategies to reduce fuel burn at airports. In order to develop such strategies, an understanding of taxi operations and the factors that affect taxi-out times is required. This paper describes an analysis of taxi-out times at two major U.S. airports in order to identify the primary causal factors affecting the duration of taxi-out operations. Through an analysis of departures out of John F. Kennedy International Airport and Boston Logan International Airport, several variables affecting taxi-out times were identified, including primarily the number of arrivals and number of departures during the taxi-out operation of an aircraft. Previous literature suggests that the number of arrivals on the surface has limited influence on taxi-out times; however, this analysis demonstrates that the number of arrivals is in fact significantly correlated with taxi-out times. Furthermore, we find that arrivals have a greater impact on taxi-out times under runway configurations where there is increased interaction between arrivals and departures

Impact of Heavy Aircraft Operations on Airport Capacity at Newark Liberty International Airport

Aviation System Performance Metrics (ASPM) departure and arrival rate data is collected for four common airport confi gurations at Newark Liberty International Airport (EWR) under Visual Meteorological Conditions (VMC) for the period 2007-2008. The effect of the number of Heavy (including Boeing 757) operations on overall airport throughput is then investigated. The investigation shows that Heavy departures and arrivals negatively impact overall airport capacity. Mechanisms by which controllers mitigate the e ffects of Heavy arrivals and departures are also identifi ed. A preliminary quanti fication of the impact of operations of Heavy aircraft is performed with a parametric estimation of the capacity of the airport. The findings of this empirical study highlight that Heavy aircraft departures introduce a very small effi ciency loss in terms of airport departure capacity. By contrast, under some runway con figurations, Heavy aircraft arrivals have a more detrimental e ffect on airport departure capacity

Feedback Control of the National Airspace System

This paper proposes a general modeling framework adapted to the feedback control of traffic flows in Eulerian models of the National Airspace System. It is shown that the problems of scheduling and routing aircraft flows in the National Airspace System can be posed as the control of a network of queues with load-dependent service rates. Focus can then shift to developing techniques to ensure that the aircraft queues in each airspace sector, which are an indicator of the air traffic controller workloads, are kept small. This paper uses the proposed framework to develop control laws that help prepare the National Airspace System for fast recovery from a weather event, given a probabilistic forecast of capacities. In particular, the model includes the management of airport arrivals and departures subject to runway capacity constraints, which are highly sensitive to weather disruptions.National Science Foundation (U.S.) (Contract ECCS-0745237)United States. National Aeronautics and Space Administration (Contract NNA06CN24A

Human performance and strategies while solving an aircraft routing and sequencing problem: an experimental approach

As airport resources are stretched to meet increasing demand for services, effective use of ground infrastructure is increasingly critical for ensuring operational efficiency. Work in operations research has produced algorithms providing airport tower controllers with guidance on optimal timings and sequences for flight arrivals, departures, and ground movement. While such decision support systems have the potential to improve operational efficiency, they may also affect users’ mental workload, situation awareness, and task performance. This work sought to identify performance outcomes and strategies employed by human decision makers during an experimental airport ground movement control task with the goal of identifying opportunities for enhancing user-centered tower control decision support systems. To address this challenge, thirty novice participants solved a set of vehicle routing problems presented in the format of a game representing the airport ground movement task practiced by runway controllers. The games varied across two independent variables, network map layout (representing task complexity) and gameplay objective (representing task flexibility), and verbal protocol, visual protocol, task performance, workload, and task duration were collected as dependent variables. A logistic regression analysis revealed that gameplay objective and task duration significantly affected the likelihood of a participant identifying the optimal solution to a game, with the likelihood of an optimal solution increasing with longer task duration and in the less flexible objective condition. In addition, workload appeared unaffected by either independent variable, but verbal protocols and visual observations indicated that high-performing participants demonstrated a greater degree of planning and situation awareness. Through identifying human behavior during optimization problem solving, the work of tower control can be better understood, which, in turn, provides insights for developing decision support systems for ground movement management