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Marine collisions with fixed offshore structures—such as oil platforms, abandoned wellheads, and navigational hazards—remain a persistent problem for commercial operators and coastal authorities. These incidents often stem from visibility limitations or human error, leading to costly damage, environmental risks, and, in severe cases, loss of life. As maritime traffic grows and offshore infrastructure expands, seafarers need better tools to identify hazards early and choose the safest maneuver.
Researchers at Texas A&M University have developed SMART-SEA, a decision-support system that blends raw marine radar data with machine learning to provide real-time guidance on avoiding stationary obstacles. Rather than taking control of a vessel, the system functions as an advisory tool: it analyzes the radar feed, classifies nearby objects, evaluates the vessel’s handling characteristics, and suggests an optimal evasive action. The approach keeps decision-making in human hands while augmenting situational awareness during high-pressure navigation.
The system solves a core challenge in maritime safety: radar data can show an obstacle, but the question of how to react—how sharply to turn, when to yield, how quickly to alter course—typically falls entirely on the operator. Human judgment varies with experience, stress, and environmental conditions. The system addresses this by incorporating a tiered maneuverability model informed by real seafarers, hydrodynamic simulations, and machine learning trained on historical vessel motion.
According to TechXplore, once the system identifies a stationary hazard, its algorithm assesses the ship’s maneuvering profile alongside the operator’s selected experience level, then displays a recommended action on a dashboard. The information can be delivered visually, through audio cues, or both, depending on user preference. In trials aboard the research vessel “Trident”, the prototype identified hazards reliably even in poor weather, and initial feedback suggests it could substantially reduce collision risk.
Such technology also carries relevance for defense and homeland security. Naval vessels, coast guard patrols, and security craft often operate in congested or low-visibility environments where navigation errors could jeopardize missions. A system that enhances human decision-making without overriding control offers a practical layer of safety for both routine patrols and complex maritime operations.
Looking ahead, the researchers plan further testing across different vessel types and believe the system’s low cost could eventually make it accessible to recreational boaters, extending advanced collision-avoidance tools far beyond large commercial fleets.
The research was published here.
