@article{GENERAL,
      recid = {11143},
      author = {Zaccone, R and Donnarumma, S and Martelli, M},
      title = {A structured metric approach to compare marine collision  avoidance algorithms},
      journal = {Conference Proceedings of iSCSS},
      address = {2024-11-05},
      number = {GENERAL},
      abstract = {The rapid advancement of technologies enabling autonomous  ship capabilities has outpaced the development of  corresponding legislative and regulatory frameworks,  creating a bottleneck in the global application of  autonomous ships as defined by the four MASS degrees of  autonomy. 
A significant issue is the absence of a  well-defined process for certifying new algorithms and  systems to be installed on board. Recently, a reliable,  open-access structured set of scenarios, including several  challenging COLREG encounter situations, has been  published, intended for testing the numerous path-planning  algorithms developed over the years.
When connected to the  testing framework, the modules must accomplish two primary  tasks: determining the applicable COLREG rules (COLREG  classification) and computing an evasive route. 
This paper  focuses on defining an approach to evaluate the performance  of collision avoidance algorithms through dedicated  metrics. 
These metrics are formulated to quantitatively  compare escape manoeuvres according to relevant performance  indexes, helping a human-based compliance evaluation assess  COLREG adherence.
The operation of the comparison metrics  is demonstrated by testing an existing collision avoidance  algorithm developed by the authors. 
This demonstration  underscores the effectiveness of the analyzed algorithms in  efficiently managing the challenging scenarios proposed in  the literature. 
Finally, the paper provides valuable  suggestions for modifying and improving the testing  scenarios to enhance the robustness of the comparison  metrics.},
      url = {http://library.imarest.org/record/11143},
      doi = {https://doi.org/10.24868/11143},
}