Codification of Good Seamanship in Complex and Congested Waterways

TL;DR

This paper tackles the problem of quantifying good seamanship in multi‑vessel encounters by introducing a risk‑based framework that fuses domain violations, a domain risk index, mutual collision risk, grounding risk, and speed‑change probabilities to compute a scenario risk $SR(t)$. A kinodynamic branch‑and‑bound search identifies the safest feasible maneuvers, yielding a Good Seamanship Score $GSS$ derived from $SR_{\max}$ and $SR_{norm}$ via $J_M = 1-SR_{\max}$, $J_C = 1- \frac{1}{SR_{\max}} \int_{t_s}^{t_f} SR_{norm}(t) \mathrm{d}t$, and $GSS = J_M \bigl(1+\beta(2J_C-1)(1-J_M)\bigr)$. The framework integrates probabilistic speed changes and adjusts for channel geometry to produce a more realistic assessment than deterministic risk alone, and it is validated with historical AIS data and Danish ENC charts. The results indicate improved realism and fairness in seamanship scoring, with practical implications for automated collision avoidance, grounding prevention, and risk‑aware route planning in congested waterways.

Abstract

This paper presents a novel method to quantify seafarers' good seamanship during navigation scenarios with multi-vessel encounters -- in open and confined waters --, and to compute COLREG's-compliant trajectories for avoiding collision and grounding. The quantification of good seamanship requires knowledge about the state of the vessels (position, heading, and speed) and the surrounding sailing environment. Such information is accessible through the AIS system and the electronic nautical chart. The proposed method evaluates mutual collision risk by examining domain violations of each vessel, and comparing them to the seaman's actions. This results in a comprehensive metric of good seamanship. As risk free actions are not always possible in the resolution of a potential collision and grounding, the method adopts a branch-and-bound scheme to identify achievable maneuvers that minimize the risk. Further, the dynamic nature of vessel speed in congested scenarios is considered, recognizing potential changes in both own and target vessels' forward speeds. The proposed method is experimentally evaluated using historical AIS data and sea charts of Danish waters. This research contributes to the field by providing a more realistic perspective on seamanship in complex maritime environments.

Figures (7)

• Figure 1: Scenario #1: A snapshot from AIS data in the Svendborg area (DK) showcases a complex and congested waterway. The zoomed-in view reveals paths with high grounding risk (I) and high collision risk (II), emphasizing the absence of entirely risk-free routes. Scenario #2: In Langelandsbælt's open waterway (DK), a focused display illustrates risk-free paths (III). A unique situation pointed at (IV) where a Pilot boat following a Tanker causing a high collision risk.
• Figure 2: (a.) A scenario of two vessels encounters. (b.) A diagram of how the good seamanship score is quantified.
• Figure 3: (a) Scenarios obtained from the AIS data in Denmark on February 1st and 2nd, 2020 (b) The PDF of vessel's speed change at $t=TDV$ grouped by the vessel's type (from 329492 number of violation).
• Figure 4: An illustration demonstrating the quantification of grounding risk.
• Figure 5: (a.) Illustration of trees for searching the feasible paths with the lowest risk and (b.) Collision, grounding and scenario risk for vessel C in Scenario #1.