As one of the central components of air traffic management (ATM) automation tools, trajectory predictors have a significant impact on the performance of ATM automation and hence the ATM system. Building on prior efforts, this paper applies a framework to assist in the development of performance metrics for trajectory predictors. Key performance areas are defined for trajectory prediction based upon existing trajectory predictor (TP) performance evaluations. Basic metrics are described within the accuracy key performance area for both input and output metrics. The basic metrics rely on precise definitions of events. Issues associated with the definition of events are discussed and approaches are provided for dealing with these. Specifiers are defined to further refine the definition of metrics in all performance areas. The application of basic metrics, events and specifiers is illustrated by drawing upon examples from the literature. An example of the impact of trajectory prediction accuracy on conflict probe performance is provided to illustrate considerations that must be given to the impact on higher-level systems when developing metrics for TP performance.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Assessing trajectory prediction performance - metrics definition


    Contributors:

    Published in:

    Publication date :

    2005-01-01


    Size :

    330317 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Assessing Trajectory Prediction Performance - Metrics Definition

    Mondoloni, S. / Swierstra, S. / Paglione, M. et al. | British Library Conference Proceedings | 2005




    Implementation and Metrics for a Trajectory Prediction Validation Methodology AIAA Paper

    Paglione, M. / Oaks, R. | British Library Conference Proceedings | 2007


    Estimation of Aircraft Performance Metrics Based on Flight Trajectory Data

    Le, Yang / Meng, Liu / Fei, Liu et al. | IEEE | 2020