A Statistical Separation Standard and Risk-Throughput Modeling of the Aircraft Landing

A STATISTICAL SEPARATION STANDARD AND RISK-THROUGHPUT MODELING OF THE AIRCRAFT LANDING PROCESS Babak Ghalebsaz Jeddi, Ph.D. George Mason University, 2008 Dissertation Director: Dr. John F. Shortle In the context of a high demand for runways as important scarce resources of the national air transportation system, this dissertation is concerned with the problem of determining the best separation between aircraft to maximize the output of the landing system. The risks of wake vortex hazard on the following aircraft and simultaneous runway occupancy shall be controlled. The following specific questions are addressed: 1. What are the stochastic characteristics of the aircraft landing process? 2. What parameters should a separation standard include? 3. How should the optimal levels of separation standard parameters be decided to maximize the system output? The first question is answered by statistical analysis of aircraft landing track data using “multilateration surveillance system” at Detroit airport (DTW). We present probability distribution functions of Landing Time Intervals to the runway threshold, and aircraft Runway Occupancy Time, among other distributions. We suggest that the current “minimum separation” standards for a given type of follow lead aircraft, e.g. a large aircraft following another large aircraft, (under Instrument Flight Rule) should be replaced by statistical separation standards (SSS). Our proposed standard, for a given type of follow-lead pair, specifies a target separation value, a lower specification limit, and a standard for the variance of the process. The optimal level of target separation, which defines the optimal level of the system output, depends on the cost of avoiding the risks and the benefits gained from closer and more frequent landings. An operational procedure will be proposed to avoid the wake vortex hazard. We present optimization models to maximize the system output given cost and benefit factors. The models also provide a framework to estimate runway landing capacity (defined as average sustainable risk-free/safe landing) taking into account the uncertainty of the landing process. The capacity estimation is critical for planning and scheduling purposes. Estimated effects/benefits of reducing variance, of Landing Time Interval, on landing capacity are presented.