Autonomous collision avoidance has received numerous attentions in recent years due to the focus on Maritime Autonomous Surface Ships (MASS). As a result, many algorithms have been developed for collision avoidance (CA), and Velocity Obstacle (VO) algorithm or Collision Threat Parameter Area (CTPA) is one popular algorithm for CA in recent years due to its simple form and low communication burden. However, since it does not consider global information, the VO algorithm might lead to deadlocks in congested waters. To solve this problem, a distributed collaboration scheme for multi-ship collision avoidance is proposed. The ships are assumed to share their navigation information including their possible trajectories in the future. Then, each ship calculates its Available Maneuvering Margin (AMM) at present, a potential collision-free course using the VO algorithm, and the expected AMM adopting the collision-free course. Based on the differences between the expected AMM and the original AMM, the priorities of taking evasive actions are determined. By utilizing AMM-ascending and AMM-descending orders to determine the decision-making sequence of ships, the probability of deadlock occurrence can be reduced. To demonstrate the proposed collaboration scheme, some experiments are introduced, and the performance of the original VO algorithm and the VO with the proposed collaboration scheme are compared. The proposed scheme is expected to reduce the deadlock using the original VO algorithm and reduce the communication burden in multi-ship collaborative collision avoidance, which would improve the safety and efficiency of shipping in congested waters.


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    Title :

    Collaboration Scheme for Multi-ship Collision Avoidance using Available Maneuvering Margin


    Contributors:
    Zhang, Jinkun (author) / Huang, Yamin (author) / Du, Lei (author) / Chen, Linying (author) / Tian, Wuliu (author) / Wen, Yuanqiao (author)


    Publication date :

    2023-08-04


    Size :

    573413 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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