Methodology for the generation of air traffic scenarios based on recorded traffic data

This article presents a methodology to generate air traffic scenarios for the support of the testing and analysis of air traffic management decision support tools. This methodology was developed by and is currently being used by the Conflict Probe Assessment Team, a workgroup within the Federal Aviation Administration's Simulation and Modeling Group located at the Federal Aviation Administration's William J. Hughes Technical Center. The individual flights within the scenarios generated by this methodology follow realistic flight routes, yet the air traffic in these scenarios contains aircraft-to-aircraft conflicts and encounters that do not exist in the field. Scenarios with these characteristics are necessary to evaluate decision support tools that predict conflicts. The paper describes each of the three steps that comprise the methodology. The first step is data extraction during which traffic data, available from various sources and recorded in different formats, is extracted and placed into a set of relational database tables. The second step is data modification, where the data in the tables may be manipulated for test purposes. This manipulation may consist of simply culling undesirable flights, or it may involve using a genetic algorithm to time-shift the flights to induce conflicts or encounters. The third step is scenario generation, where scenarios are created based on the traffic data retrieved from the modified database tables. During this final step, the scenarios may be formatted for various target systems. The paper then describes how the Conflict Probe Assessment Team has used this methodology to generate scenarios that have been used for accuracy and risk reduction testing and for a study assessing the effect of weather forecast errors.