Fusion and analysis of data sources for assessing aircraft braking performance on non-dry runways

Aircraft landing safety is among the important concerns in the aviation industry due to accidents related to runway/taxiway excursions. The literature has explored the relationship between adverse weather conditions and braking performance from a qualitative perspective. Factors such as the weather conditions, pavement texture characteristics, and slope can all play critical roles in determining braking performance. While literature has explored how these factors individually may impact braking, no studies have explored the multivariate relationship between such factors and reported braking action by pilots over a wide range of operational landings and considering a variety of data sources. In this paper, the quantitative relationship between different factors that may work to cause or prevent poor braking performance is explored. In order to conduct this analysis, a data fusion framework is developed that is able to collect and fuse sources of data such as runway conditions, runway and airport characteristics, prevailing weather conditions, runway condition codes, and pilot reported braking action. The framework is demonstrated on data collected between the years 2016–2020 at various U.S. airports where field condition reports were available. The analysis indicates that this initial statistical distribution and binning of the data substantiates the value of the Runway Condition Code (RwyCC) modeling in predicting actual braking action. Further investigation and development of more refined models is identified for future work.