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The Safety Performance of Airborne Separation (SPAS) study is a suite of Monte Carlo simulation experiments designed to analyze and quantify safety behavior of airborne separation. This paper presents results of preliminary baseline testing. The preliminary baseline scenario is designed to be very challenging, consisting of randomized routes in generic high-density airspace in which all aircraft are constrained to the same flight level. Sustained traffic density is varied from approximately 3 to 15 aircraft per 10,000 square miles, approximating up to about 5 times today's traffic density in a typical sector. Research at high traffic densities and at multiple flight levels are planned within the next two years. Basic safety metrics for aircraft separation are collected and analyzed. During the progression of experiments, various errors, uncertainties, delays, and other variables potentially impacting system safety will be incrementally introduced to analyze the effect on safety of the individual factors as well as their interaction and collective effect. In this paper we report the results of the first experiment that addresses the preliminary baseline condition tested over a range of traffic densities. Early results at five times the typical traffic density in today's NAS indicate that, under the assumptions of this study, airborne separation can be safely performed. In addition, we report on initial observations from an exploration of four additional factors tested at a single traffic density: broadcast surveillance signal interference, extent of intent sharing, pilot delay, and wind prediction error. Nomenclature

The ability to meet a controlled time of arrival during a continuous descent operation will enable environmentally friendly and fuel efficient descent operations while simultaneously maintaining airport throughput. However, if the wind forecast used to compute the initial trajectory plan is not accurate enough, the guidance system will need to correct time deviations from the plan during the execution of the descent. Previous work proposed an on-board guidance strategy based on model predictive control, which repeatedly updates the trajectory plan in real-time from the current aircraft state and for the remainder of the descent. However, the wind conditions downstream, at altitudes not explored yet, were difficult to predict due to the lack of data. This paper shows the potential benefits of using wind observations, broadcast by nearby aircraft, to reconstruct the wind profile downstream. The wind profile in the trajectory optimization problem is modeled as a spline, which control points are updated to fit the observations before re-planning the trajectory. Results from simulations using realistic wind data show that the performance of model predictive control significantly improves when including up-to-date wind observations, in terms of time and energy errors at the metering fix and fuel consumption.

Interval Management (IM) is a concept designed to be used by air traffic controllers and flight crews to more efficiently and precisely manage inter-aircraft spacing. Both government and industry have been working together to develop the IM concept and standards for both ground automation and supporting avionics. NASA contracted with Boeing, Honeywell, and United Airlines to build and flight test an avionics prototype based on NASA's spacing algorithm and conduct a flight test. The flight test investigated four different types of IM operations over the course of nineteen days, and included en route, arrival, and final approach phases of flight. This paper examines the spacing accuracy achieved during the flight test and the rate of speed commands provided to the flight crew. Many of the time-based IM operations met or exceeded the operational design goals set out in the standards for the maintain operations and a subset of the achieve operations. Those operations which did not meet the goals were due to issues that are identified and will be further analyzed.

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