Latest revision as of 18:49, 3 February 2021

Abstract

This paper describes the process of designing a software tool for testing en route air traffic management decision support tool functionalities in a research environment. This effort focused on the development of a scalable, low maintenance software application to replace a legacy en route conflict prediction tool. Previous development efforts provided the lessons learned that guided the development of the new en route conflict prediction tool. This new tool met near term functional requirements while allowing flexibility to support future research objectives both inside and outside of the en route domain. The software process encouraged incremental prototyping and short development intervals. The development team used best practices to increase the reliability and maintainability of the software. The tool was also ported to multiple hardware and operating system platforms to further increase its scalability. When compared to the legacy en route conflict prediction tool, the new application had seven times fewer highly complex functions, while maintaining data integrity to ensure consistent predictions.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.2514/6.2007-7803

• http://pdfs.semanticscholar.org/11c1/171f0076a54d10bacae722420e1d5df35903.pdf

• http://arc.aiaa.org/doi/pdf/10.2514/6.2007-7803,

http://dx.doi.org/10.2514/6.2007-7803

• https://www.aviationsystemsdivision.arc.nasa.gov/publications/enroute/eda/Murphy_AIAA_ATIO_2007_1.pdf,

https://www.aviationsystems.arc.nasa.gov/publications/enroute/upr/Murphy_AIAA_ATIO_2007_1.pdf,

http://www.aviationsystems.arc.nasa.gov/publications/enroute/eda/Murphy_AIAA_ATIO_2007_1.pdf,

https://academic.microsoft.com/#/detail/2116447334