Abstract This chapter proposes a novel method to estimate the collision probabilities of monitoring targets for coastal radar surveillance. Initially, the probability of a monitoring target being a real moving vessel is estimated using the records of manual operations and the Evidential Reasoning (ER) rule. Subsequently, the bridges, piers and other encountering vessels in a waterway are characterized as collision potential fields using an Artificial Potential Field (APF) model, and the corresponding coefficients can be trained in terms of the historical vessel distributions. As a result, the positional collision potential of any monitoring vessel can be obtained through overlapping all the collision potential fields together. The probabilities of authenticity and the collision potential are further formulated as two pieces of evidence on which the Dempster’s rule of combination is used to reason the collision probability of a monitoring target. The vessels associated with high collision probabilities can be highlighted for supervisors’ attention, as they potentially pose high risks to safety. A preliminary field test was conducted to validate the proposed method.


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    Title :

    Probabilistic Assessment of Vessel Collision Risk: An Evidential Reasoning and Artificial Potential Field-Based Method


    Contributors:
    Ma, Feng (author) / Chen, Yu-Wang (author)


    Publication date :

    2017-10-25


    Size :

    27 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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