George L. Donohue

Simulating Collision Probabilities of Landing Airplanes at Nontowered Airports

Making greater use of smaller airports is one way that has been proposed to increase the capacity of the National Airspace System. A major difficulty is that many small airports do not have control towers, and thus capacity is severely limited during poor visibility. The authors consider a proposed system in which airplanes self-separate, so they are able to land at higher capacities without a control tower. Before such a system is implemented, it must first be shown to be safe. Safety is a difficult metric to measure and predict because accidents are so rare. Even computer simulation can be slow because of the long time to observe accidents. One methodology that has been successful in assessing aviation safety through simulation is TOPAZ (Traffic Organizer and Perturbation AnalyZer). In this study, the authors apply the methodology to assess the safety of the proposed nontowered system.

Dynamic airspace super sectors (DASS) as high-density highways in the sky for a new US air traffic management system

We evaluate a new sector design called dynamic airspace super sectors (DASS). DASS may be thought of as a network of one-directional, high density highways in the sky, like thin ribbons of airspace stretching over the U.S. and connecting major airports. DASS is a simplification of airspace structure that may decrease air traffic controller (ATC) workload and allow higher densities of aircraft to be safely monitored. DASS would also potentially reduce delay for aircraft using DASS. The team used these two factors, workload and delay, to measure the effectiveness of the DASS Alternatives. We uses total airport and airspace modeller (TAAM) and Arena simulation environments to simulate two aspects of the design alternatives: the effect of varying the number of entrance/exit points to DASS, first, on traffic outside and second, on traffic inside of DASS.

Air transportation systems engineering

Economics of Congestion Airport Operations and Constraints Airspace Operations nd Constraints U.S. and European Comparisons Safety and Free Flight The Changing Role of Air Traffic Controllers Emerging Issues in Aircraft Self-Separation

Runway landing safety analysis: a case study of Atlanta Hartsfield airport

According to historical data, aircraft are subject to a higher accident risk during the landing phase than during other flight phases. With the growth in air traffic volume evaluating safety during the landing phase is an important problem. This article presents an analysis and estimate of two safety metrics at ATL airport: probability of a simultaneous runway occupancy by two landing aircraft and probability of a collision on the runway. We begin with the first order analysis to estimate the simultaneous runway occupancy probability, based on field observations. To obtain a more accurate estimate and to evaluate the runway collision risk, we construct a stochastic model of the aircraft approaching and landing process. The result of Monte Carlo simulation gives an improved estimate for the simultaneous occupancy probability. We then numerically evaluate the runway collision risk using a generalization of the Reich collision model. Finally, we carry out sensitivity analysis to examine the impact on safety and capacity when the separation variance changes.

Turbulence Measurements with a Laser Anemometer Measuring Individual Realizations

A laser Doppler anemometer system is described which operates with a noncontinuous signal and measures the velocity of individual scattering centers. Histograms of the instantaneous individual velocity realizations provide accurate and unambiguous estimates of the mean velocity and rms fluctuation velocity in regions of intense turbulence levels. Measurements are presented for a fully developed two‐dimensional water channel and a deflected jet of air.

Airport terminal-approach safety and capacity analysis using an agent-based model

The consistent growth of air traffic demand is causing the operational volumes at hub airports to approach their maximum capacities. With this growth, delays are increasing, and safety is becoming a more crucial problem. The terminal approaching and landing phases are especially important since the airspace is more crowded and operational procedures are more complicated compared with the en route phase. We have developed an agent-based stochastic simulation model which is useful to analyze the relationship among airport arrival capacity, delay, and safety. We first present a simplified queue model to demonstrate key ideas. Then, we give a detailed agent-based model that is calibrated to Hartsfield Atlanta International Airport. We use the model to evaluate several operational scenarios and examine the trade-offs between system capacity and safety.

A Macroscopic Air Transportation Capacity Model: Metrics and Delay Correlation

The need for a macroscopic air transportation modeling approach is discussed and a recently developed model is applied to the U.S. air transportation system. The new model is designed to estimate the maximum capacity of a national air transportation region. The model is based on empirically observed aircraft arrival rates, government published annual operational rate statistics, and analytically derived airport arrival/departure functions. The underlying premise is that the air transportation system can be modeled as a multi path, steady state network of queues, whose maximum capacity is the sum of the maximum airport operational rates, less airspace human factors limitations. Capacity is defined to be twice the hourly arrival rate (since departures equal arrivals in equilibrium). The validity of the model predictions is tested by: 1) observing reported airport delay values ranked in order of model estimated maximum capacity utilization; and 2) observing historical operational growth rates for airports that are now operating near predicted maximum capacity. A national capacity value is estimated and compared to observed historical and predicted growth rates. All planned runway additions are included in the national capacity estimate and a growing national capacity shortfall is predicted. It is estimated that the US is currently operating at 57% of maximum capacity and will be at 70% national capacity by 2010. It is observed that significant delays begin at about 50% capacity fraction and grow at a hyperbolic rate. The effect of adopting new technology and operational concepts is shown to have a better impact on capacity growth (i.e. up to 30%) than runway construction (i.e. 1% per runway). This work should be of interest to policy makers who are responsible for making investments in national and/or local air transportation systems and for those responsible for measuring the air transportation systems operational capacity.

Optimum Airport Capacity Utilization under Congestion Management: A Case Study of New York LaGuardia Airport

Abstract In the United States, most airports do not place any limitations on airline schedules. At a few major airports, the current scheduling restrictions (mostly administrative measures) have not been sufficiently strict to avoid consistent delays and have raised debates about both the efficiency and the fairness of the allocations. With a forecast of 1.1 billion yearly air travelers within the US by 2015, airport expansion and technology enhancement alone are not enough to cope with the competition-driven scheduling practices of the airline industry. The policy legacy needs to change to be consistent with airport capacities. Flights on US airlines arrived late more often in the first four months of 2007 than in any other year since the government began tracking delays, and flight cancellations increased 91% over 2006. With a forecast of 1.1 billion yearly air travelers within the US by 2015, airport expansion and technology enhancement alone are not enough to cope with the competition-driven scheduling practices of the airline industry. Our research studies how flight schedules might change if airlines were required to restrict their schedules to runway capacity. To obtain these schedules, we model a profit-seeking, single benevolent airline whose goal is to maintain current competitive prices and service as many current passengers as possible, while remaining profitable. Our case study demonstrates that at Instrument Meteorological Conditions (IMC) runway rates, the market can find profitable flight schedules that reduce substantially the average flight delay to less than 6 minutes while simultaneously satisfying virtually all of the current demand with average prices remaining unchanged. This is accomplished through significant upgauging to high-demand markets.

A visionary look at aviation surveillance systems

The FAAs future aviation surveillance systems fall into four categories: Automatic Dependent Surveillance (ADS) will be used in the oceanic environment; ADS-Broadcast (ADS-B) will be used in the domestic en route environment; ADS-B will be used with a secondary radar backup in the terminal area; and ADS-B will be used with primary radar backup within the Airport Surface Traffic Automation (ASTA) system on the airports surface environment. Two other systems introduced in this paper are Cockpit Display of Traffic Information (CDTI) and Traffic Advisory and Collision Avoidance System (TCAS). All these systems will use navigational signals emitted by the Global Positioning System (GPS) constellation of satellites. >

UAS Safety: Unmanned Aerial Collision Avoidance System (UCAS)

Lack of safety and regulatory framework currently prevent the routine use of unmanned aircraft systems (UAS) within the U.S National Airspace System (NAS). Demonstrating a level of safety equivalent to that of manned aircraft will allow UAS to fly and interoperate in civil airspace. An unmanned aerial collision avoidance system (UCAS) designed to communicate and interact with the traffic alert collision avoidance system (TCAS) implemented on manned aircraft is proposed. Considering intruding aircraft equipped with TCAS as cooperating aircraft, UCAS will also be able to sense, detect, and avoid non-cooperative aircraft through the use of sensor technology. Simulation and analysis has been carried out to generate a safety metric quantifying the safety of the UCAS system. A Monte Carlo simulation has been performed for a set of outer loop state variables to generate the probability of a near midair collision. A second encounter model is carried out to show the benefits of incorporating the mitigation strategy selected, in this case the collision avoidance capabilities. An existing case study is analyzed to demonstrate the value of the model and the efficiency of the system