Ship dangerous situations result from the fact that some ships encounter complex conditions in confined waters and, therefore, ship collision risk assessment is important to support maritime traffic monitoring and control tasks at Vessel Traffic Service (VTS) centres. This paper proposes a ship collision risk assessment method using radar sequential images in inland waterways or congested coastal areas. Specifically, ship targets are separated from radar images using a background subtraction algorithm, as radar echoes have limited colour, texture, and shape features. The ship trajectory is then obtained by predicting and matching the ship’s position in two adjacent frames, which provides the ship’s spatial-temporal dynamic information for collision risk assessment. The ship collision risk is quantified by integrating the Distance and Time at the Closest Point of Approach (DCPA/TCPA) indicators, and the safe and prohibited velocity space of every ship is presented to assist VTS operators in evaluating the traffic conditions and support their decisions for safe navigation. The proposed ship collision risk assessment and visualisation method is tested and verified using radar sequential images collected in the Yangtze River.


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    Titel :

    Ship Collision Risk Assessment and Visualization Using Radar Sequential Images for Intelligent Maritime Supervision


    Beteiligte:
    Xu, Xueqian (Autor:in) / Wu, Bing (Autor:in) / Teixeira, Angelo P. (Autor:in) / Soares, Carlos Guedes (Autor:in)


    Erscheinungsdatum :

    01.06.2025


    Format / Umfang :

    4820257 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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