Air Navigation Service Providers (ANSPs) need quantitative models of risk to set priorities for research, development, and implementation of Operational Improvements (OIs). Although collision risk is a concern both in flight and on the airport surface, there is a lack of models for collision risk associated with airport surface movement. This paper describes progress at formulating, implementing, and validating a quantitative model for collision likelihood on the airport surface, particularly taxiways, under the sponsorship of the FAA's Office of Aviation Safety (AVS). The model uses detailed surveillance-based analysis of surface movement to measure the number and characteristics of discrete interactions during taxi that represent pre-conditions for collision. The model's estimates of separation consider the relative position of aircraft extremities (nose, wingtips, and tail.) Although the initial model is restricted to movement area collisions between aircraft, the methods may be extended to ramp movement and to aircraft-vehicle interactions. The model addresses collision likelihood and lays the groundwork for integration with a severity model addressing the consequences of collision. Preliminary results obtained from applying the analytical model to surveillance obtained from four ASDE-X airports, and the efforts to calibrate these results against historical accident and incident data, are provided and discussed. These results show that it is feasible to statistically characterize all interactions between aircraft on the airport surface in order to model collision risk. The expected benefits of these methods are improved identification of conditions associated with increased collision likelihood, better prediction of the effect of operational changes on this likelihood, and quantitative inputs to the benefits analysis for operational improvements.


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    Titel :

    Quantifying collision potential in airport surface movement


    Beteiligte:


    Erscheinungsdatum :

    01.04.2013


    Format / Umfang :

    456370 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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