Xue M.,University of California at Santa Cruz |
Xue M.,University Affiliated Research Center |
15th AIAA Aviation Technology, Integration, and Operations Conference | Year: 2015
In terminal airspace, integrating arrivals, departures, and surface operations with competing resources provides the potential of improving operational efficiency by removing barriers between different operations. This work develops a centralized stochastic scheduler for operations in a terminal area including airborne and surface operations using a non-dominated sorting genetic algorithm and Monte Carlo simulations. The scheduler handles competing resources between different flows, such as runway allocations, runway crossings, merges at departure fixes, and other interaction waypoints between arrivals and departures. The scheduler takes time-varied uncertainties into account in optimization as well. The scheduler is run sequentially to identify the best robust schedule for the next planning window. Resulting schedules determine routes, speeds or delays, and runway assignments subject to separation constraints at merging diverging waypoints in the air and at runways (including runway crossings) on the surface. The Los Angeles terminal area was used as an example in experiments with a four-hour traffic scenario. The results showed that using stochastic schedulers can reduce flight time delay (airborne and ground) anywhere from 28% to 40% statistically compared to deterministic schedulers. Sensitivity studies on various planning horizons presented that trade-offs exist between planning horizons and achievable minimum delays. A twenty-minute planning horizon was found to be a bad choice because uncertainties increased with the look-ahead time. Eight minutes was promising for planning as it achieved the lowest delay compared to others. However, the results demonstrated that any duration from two minutes to eight minutes could be a good candidate as well. The results on runway usage showed that using the stochastic scheduler, runway makespans and occupancy were usually slightly lower than applying deterministic schedulers. © 2015, American Institute of Aeronautics and Astronautics Inc.
Chen N.Y.,NASA |
Chen N.Y.,Research Aerospace Engineer |
Sridhar B.,NASA |
Ng H.K.,University of California at Santa Cruz |
Ng H.K.,University Affiliated Research Center
Journal of Aircraft | Year: 2012
This paper describes a class of strategies for reducing persistent contrail formation with the capability of trading off between contrails and aircraft-induced emissions. The concept of contrail-frequency index is defined and used to quantify the contrail activities. The contrail-reduction strategies reduce the contrail-frequency index by altering aircraft's cruising altitude with consideration to extra emissions. The strategies use a user-defined factor to trade off between contrail reduction and extra emissions. The analysis shows that contrails can be reduced with extra emissions and without adding congestion to airspace. For a day with high contrail activities, the results show that the maximal contrail-reduction strategy can achieve a contrail reduction of 88%. When a tradeoff factor is used, the strategy can achieve less contrail reduction while emitting less emissions compared to the maximal contrail-reduction strategy. The user-defined tradeoff factor provides a flexible way to trade off between contrail reduction and extra emissions. Better understanding of the tradeoffs between contrails and emissions and their impact on the climate need to be developed to fully use this class of contrail-reduction strategies. The strategies provide a starting point for developing operational policies to reduce the impact of aviation on climate. Copyright © 2011 by the American Institute of Aeronautics and Astronautics, Inc.
Giannakopoulou D.,Carnegie Mellon University |
Bushnell D.H.,NASA |
Schumann J.,NASA |
Erzberger H.,University of California at Santa Cruz |
Heere K.,University Affiliated Research Center
Annals of Mathematics and Artificial Intelligence | Year: 2011
In order to address the rapidly increasing load of air traffic operations, innovative algorithms and software systems must be developed for the next generation air traffic control. Extensive verification of such novel algorithms is key for their adoption by industry. Separation assurance algorithms aim at predicting if two aircraft will get closer to each other than a minimum safe distance; if loss of separation is predicted, they also propose a change of course for the aircraft to resolve this potential conflict. In this paper, we report on our work towards developing an advanced testing framework for separation assurance. Our framework supports automated test case generation and testing, and defines test oracles that capture algorithm requirements. We discuss three different approaches to test-case generation, their application to a separation assurance prototype, and their respective strengths and weaknesses. We also present an approach for statistical analysis of the large numbers of test results obtained from our framework. © 2011 Springer Science+Business Media B.V.
Lee S.M.,University Affiliated Research Center |
2013 Aviation Technology, Integration, and Operations Conference | Year: 2013
In integrating Unmanned Aircraft Systems (UAS) into the National Airspace System, separation assurance is one of the important air traffic services for ensuring safe operations of air traffic. This paper describes an approach to develop a range of operational concepts by describing what functions and technologies are required to maintain safe separation of unmanned aircraft and how those functions are allocated and distributed across primary system elements, such as air traffic controllers, automation systems, aircraft onboard systems, and UAS ground control stations including UAS pilots. A framework proposed in this study identifies key functions and capabilities by decomposing high-level system goals into smaller functions to achieve them hierarchically and also identifies primary system elements to perform the identified functions by decomposing the whole system into smaller systems hierarchically. The framework represents hierarchical functional/physical structure and allocation of functions across system elements at different levels to generate a range of potential separation assurance concepts systematically. The detailed representation of functional decomposition and allocation enables an application of the framework for recommending levels of automation (LOA) developed based on human factors engineering principles. The detailed functional decomposition and allocation framework to develop a concept of operations provides additional analysis capabilities: stability, workflow, and task-load analysis to examine the completeness, correctness, and balance of functional decomposition and allocation schemes for concept development without requiring complex simulations. This paper demonstrates the framework through a case study of providing separation assurance functions for UAS operating in en-route and transition airspace in the Next Generation Air Transportation System (NextGen) timeframe.
Mukherjee A.,University Affiliated Research Center |
Grabbe S.,NASA |
AIAA Guidance, Navigation, and Control Conference 2011 | Year: 2011
Delays caused by uncertainty in weather forecasts can be reduced by improving traffic flow management decisions. This paper presents a methodology for traffic flow management under uncertainty in convective weather forecasts. An algorithm for assigning departure delays and reroutes to aircraft is presented. Departure delay and route assignment are executed at multiple stages, during which, updated weather forecasts and flight schedules are used. At each stage, weather forecasts up to a certain look-ahead time are treated as deterministic and flight scheduling is done to mitigate the impact of weather on fourdimensional flight trajectories. Uncertainty in weather forecasts during departure scheduling results in tactical airborne holding of flights. The amount of airborne holding depends on the accuracy of forecasts as well as the look-ahead time included in the departure scheduling. The weather forecast look-ahead time is varied systematically within the experiments perfomed in this paper to analyze its effect on flight delays. Based on the results, longer look-ahead times cause higher departure delays and additional flying time due to reroutes. However, the amount of airborne holding necessary to prevent weather incursions reduces when the forecast look-ahead times are higher. For the chosen day of traffic and weather, setting the look-ahead time to 90 minutes yields the lowest total delay cost.