The present invention provides an auxiliary berthing method and system for a vessel. Position information of a vessel relative to a berth is determined by a solar blind ultraviolet imaging method; meanwhile, by a GPS method, an attitude angle of the vessel relative to the berth is determined by at least two GPS receivers. Thus, the vessel can be berthed safely when getting close to the shore at low visibility. Further, in the method and device of the present invention, it can be preferable to integrate coordinate data and angle data received by a solar blind ultraviolet imaging module and GPS signal receiving modules by a normalized correlation algorithm and a data fusion algorithm, so as to improve the positioning accuracy.

A marine propulsion system includes at least one propulsion device and a user input device configured to facilitate input for engaging automatic propulsion control functionality with respect to a docking surface, wherein the user input device includes a direction indicator display configured to visually indicate a direction with respect to the marine vessel. A controller is configured to identify a potential docking surface, determine a direction of the potential docking surface with respect to the marine vessel, and control the direction indicator display to indicate the direction of the potential docking surface with respect to the marine vessel. When a user selection is received via the user input device to select the potential docking surface as a selected docking surface, and propulsion of the marine vessel is automatically controlled by controlling the at least one propulsion device to move the marine vessel with respect to the selected docking surface.

The present invention relates to a method for acquiring an object information, the method comprising: obtaining an input image acquired by capturing a sea; obtaining a noise level of the input image; when the noise level indicates a noise lower than a predetermined level, acquiring an object information related to an obstacle included in the input image from the input image by using a first artificial neural network, and when the noise level indicates a noise higher than the predetermined level, obtaining a noise-reduced image of which the environmental noise is reduced from the input image by using a second artificial neural network, and acquiring an object information related to an obstacle included in the sea from the noise-reduced image by using the first artificial neural network.

The present invention proposes a vessel traffic pattern identification method via data quality control and data compression. Firstly, assort a collection of Automatic Identification system (AIS) data points according to Mobile Service Identify (MMSI) code and sort each collection result by time ascending order, and then delete duplicated vessel AIS data points considering time stamp, latitude, longitude and vessel speed over ground, then segment vessel trajectories. Secondly obtain high-quality AIS data with an AIS data anomaly detection and repair and compress each vessel trajectory with the Douglas-Peucker algorithm. Thirdly, cluster vessel trajectories with the Quick Bundles algorithm, and identify maritime traffic pattern. The invention can efficiently identify vessel traffic patterns, and help maritime traffic management departments to accurately identify a traffic situation.

The present invention proposes a vessel traffic pattern identification method via data quality control and data compression. Firstly, assort a collection of Automatic Identification system (AIS) data points according to Mobile Service Identify (MMSI) code and sort each collection result by time ascending order, and then delete duplicated vessel AIS data points considering time stamp, latitude, longitude and vessel speed over ground, then segment vessel trajectories. Secondly obtain high-quality AIS data with an AIS data anomaly detection and repair and compress each vessel trajectory with the Douglas-Peucker algorithm. Thirdly, cluster vessel trajectories with the Quick Bundles algorithm, and identify maritime traffic pattern. The invention can efficiently identify vessel traffic patterns, and help maritime traffic management departments to accurately identify a traffic situation.

Provided is a replay system of ship collision accidents using a free running model test including a ship collision replay simulation system configured to replay the ship collision accidents by receiving a navigation trajectory of the ship collision accidents; a free running model system configured to perform a free running model test of the collision accident ship using a free running model ship; and a free running control system configured to remotely perform the free running model test, in which the replay of the ship collision accidents is performed by simultaneously performing a simulation in the ship collision replay simulation system and a free running model test in the free running model system.

A periphery recognition support system for a personal watercraft includes processing circuitry. The processing circuitry is configured to: receive position related data related to a positional relation between a personal watercraft and a peripheral object around the personal watercraft; determine based on the position related data whether or not a predetermined warning condition is satisfied; and output a predetermined warning signal when it is determined that the warning condition is satisfied.

A periphery recognition support system for a personal watercraft includes processing circuitry. The processing circuitry is configured to: receive position related data related to a positional relation between a personal watercraft and a peripheral object around the personal watercraft; determine based on the position related data whether or not a predetermined warning condition is satisfied; and output a predetermined warning signal when it is determined that the warning condition is satisfied.

A camera mounted on a seafaring vessel obtains an image showing an object. The distance to the object is computed using, in part, a normal vector of the plane containing the camera and the horizon.

A camera mounted on a seafaring vessel obtains an image showing an object. The distance to the object is computed using, in part, a normal vector of the plane containing the camera and the horizon.