A method for predicting the encounter time of intelligent inland waterway vessels

Abstract

This invention relates to a method for predicting the encounter time of intelligent inland waterway vessels. The method comprises: Step 1: Establishing a coordinate system relative to the vessel hull and obtaining the target vessel coordinates TS; Step 2: Obtaining the target vessel velocity using the target vessel coordinates TS and the relative velocity between the vessel hull and the target vessel; Step 3: Establishing a collision prediction line expression using the target vessel coordinates TS; Step 4: Determining the collision intersection point coordinates using the collision prediction expression and the inland waterway vessel safety distance boundary equation; Step 5: Obtaining the encounter time at the intersection of the target vessel's collision prediction line and the vessel safety distance boundary using the collision intersection point coordinates and the relative velocity. This invention provides a method for predicting the encounter time of intelligent inland waterway vessels, which can perform real-time collision prediction and has good stability.

Description

Technical Field

[0001] This invention belongs to the field of ship technology, specifically relating to a method for predicting the encounter time of intelligent inland waterway vessels. Background Technology

[0002] The hazard assessment of the navigation situation of intelligent inland waterway vessels is an important parameter for their navigation decisions, and its results play a crucial role in ensuring the safe navigation of inland waterway vessels.

[0003] However, due to the shielding effect of channel linkage structures, radar scanning noise is excessive, signal distortion is severe, and radar scanning performance is poor. Currently, most ships are equipped with shipborne AIS navigation aids. Existing AIS navigation aids can only interpret AIS signals and calculate the TCPA and DCPA of two ships encountering each other. When the encounter parameters are lower than the set threshold, an automatic alarm is triggered to remind the navigator to take evasive action. Neither of these two main ship navigation aids can assist the navigator in assessing the encounter situation and providing timely warnings. The navigator must rely on information about the surrounding environment to determine whether a collision is likely, which can easily lead to driver fatigue and unstable navigation over time. Summary of the Invention

[0004] To address the issues that the aforementioned ship navigation aids are unable to assist the driver in assessing the encounter situation and provide timely warnings, and that the driver must rely on information about the surrounding environment to determine whether a collision will occur, which can lead to driver fatigue and unstable navigation over time, this invention provides a method for predicting the encounter time of inland waterway intelligent vessels, enabling real-time collision prediction.

[0005] The technical solution of the present invention is as follows: A method for predicting encounter time for intelligent inland waterway vessels, comprising a safety distance boundary equation for inland waterway vessels, wherein the method is as follows: Step 1: Establish a coordinate system relative to the ship hull and obtain the target ship coordinates TS; Step 2: Obtain the target ship's speed using the target ship's coordinates TS, and then measure the relative speed between the ship and the target ship. Step 3: Establish the collision prediction line expression using the target ship coordinates TS; Step 4: Determine the coordinates of the collision intersection point by using the collision prediction expression and the boundary equation for the safe distance of inland waterway vessels; Step 5: Obtain the encounter time of the intersection point between the collision prediction line of the target ship and the safe distance boundary of the ship's domain by using the collision intersection point coordinates and the relative velocity.

[0006] Preferably, step 2 is further specified as follows: the components of the target ship's velocity along the x and y axes are as follows: ;in, This represents the component of the target ship's velocity along the x-axis. This represents the component of the target ship's velocity along the y-axis. The formulas for the relative velocities of the ship and the target ship along the x and y axes are as follows: ;in, This represents the relative velocity component of the ship's hull and the target ship along the x-axis. This represents the relative velocity component of the ship and the target ship along the y-axis.

[0007] Preferably, the equation of the relative course line in the ship's coordinate system is: (Formula 1); Where, k t This represents the slope of the relative course equation in the ship's coordinate system.

[0008] Preferably, step 4 further specifies that: the boundary equation for the safe distance of the inland waterway vessel area is as follows: (Formula 2); Combining formulas 1 and 2, we get: (Formula 3); The discriminant of Formula 3 is: ; when If it is determined that the collision hazard detection line and the safe distance boundary do not intersect, then the target vessel is not at risk of collision. when If one or two points of intersection exist between the collision hazard detection line and the safety distance boundary, a collision hazard is identified. The coordinates of the intersection point can be obtained as follows: ; .

[0009] Preferably, the encounter time at the intersection of the collision prediction line of the target vessel and the safe distance boundary of the vessel domain is: ; ; Among them, T cax1 Let T be the predicted meeting time at coordinate x1. cax2 The predicted meeting time is at coordinate x2; Then it will take time Minimum value, i.e. .

[0010] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a method for predicting the encounter time of intelligent inland waterway vessels. It proposes to determine the intersection of the collision prediction line and the safety distance boundary, and also proposes a method to determine the navigation risk level of the target vessel by using the encounter time parameter of the intersection of the target vessel's collision prediction line and the safety distance boundary of the vessel domain. This method can accurately reflect the navigation risk of the target vessel relative to the vessel itself, and the warning data is stable and has good real-time performance, which can effectively assist the driver in identifying navigation risks. Attached Figure Description

[0011] Figure 1 This is a scatter plot of the target ships in an embodiment of the present invention; Figure 2 This is a ship density map (with scatter plots) in an embodiment of the present invention. Figure 3 This is a ship distribution density map in an embodiment of the present invention; Figure 4 This is a schematic diagram of the target ship domain in an embodiment of the present invention; Figure 5 This is a diagram showing the relative headings of surrounding vessels in an embodiment of the present invention. Figure 6 This is a scatter plot of ships sailing in the same direction in an embodiment of the present invention; Figure 7 This is a density distribution diagram (with scatter dots) of ships sailing in the same direction in an embodiment of the present invention. Figure 8 This is a density distribution diagram of ships sailing in the same direction in an embodiment of the present invention; Figure 9 This is a scatter plot of opposing ships in an embodiment of the present invention; Figure 10 This is a density distribution diagram of opposing ships (with scatter plots) in an embodiment of the present invention. Figure 11 This is a density distribution diagram of opposing ships in an embodiment of the present invention; Figure 12 This is a schematic diagram of an eccentric elliptical inland waterway vessel domain model in an embodiment of the present invention; Figure 13 This is the density curve of ships sailing in the same direction at section x in an embodiment of the present invention; Figure 14 This is the density curve of facing ships at section x in an embodiment of the present invention; Figure 15 This is the density curve of ships sailing in the same direction at section y in an embodiment of the present invention; Figure 16 This is the density curve of facing ships at section y in an embodiment of the present invention; Figure 17 This is a safety zone diagram for vessels traveling in the same direction, as shown in this embodiment of the invention. Figure 18 This is a safety zone diagram of opposing vessels in an embodiment of the present invention; Figure 19 This is a schematic diagram illustrating the collision hazard assessment in an embodiment of the present invention. Detailed Implementation

[0012] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0013] A method for predicting encounter time for intelligent inland waterway vessels, comprising a safety distance boundary equation for inland waterway vessels, wherein the method is as follows: Step 1: Establish a coordinate system relative to the ship hull and obtain the target ship coordinates TS; Step 2: Obtain the target ship's speed using the target ship's coordinates TS, and then measure the relative speed between the ship and the target ship. Step 3: Establish the collision prediction line expression using the target ship coordinates TS; Step 4: Determine the coordinates of the collision intersection point by using the collision prediction expression and the boundary equation for the safe distance of inland waterway vessels; Step 5: Obtain the encounter time of the intersection point between the collision prediction line of the target ship and the safe distance boundary of the ship's domain by using the collision intersection point coordinates and the relative velocity.

[0014] The present invention will be further described below: Because the initial Automatic Identification System (AIS) data contains some anomalies, it is necessary to remove data indicating abnormal vessel positions from the selected AIS data. This includes data that is not within the navigation area, has speed but no change in position, exhibits abnormal speed, or has an abnormal heading. Furthermore, since this invention only considers the vessel's current navigation status, it is necessary to determine the vessel's current navigation status based on its speed and remove AIS data where the speed is less than 0.5 m / s. Simultaneously, considering the size characteristics of inland waterway vessels, vessels within a 1 km radius of the vessel are selected as the calculation objects. The processed AIS data is then used to perform the following density map calculations.

[0015] Using the ship as the center and its course as the longitudinal axis, a coordinate system is established relative to the ship in the surrounding waters. First, at any given moment, the relative distance and true bearing of the target ship can be calculated using the latitude and longitude of the ship and all other ships in the surrounding waters. Second, to ensure that the target ship's heading is always aligned with the longitudinal axis of the grid at all navigation moments, the problem of the constantly changing relative bearings of other ships due to the ship's navigation state must be addressed. This requires converting the true relative bearings of all other ships in the surrounding waters with the ship's course to obtain the relative bearing, ensuring the accuracy of the selected statistical sample. Finally, a scatter plot of all other target ships is drawn based on the calculated relative distances and bearings, as shown below. Figure 1 As shown.

[0016] By observing the scatter distribution map of the target ships, there is indeed a sparse area of ​​ships near the origin, which is the ship's domain space.

[0017] To more accurately describe the distribution of the vessel's location relative to other target vessels in the waters surrounding the vessel, it is necessary to convert the scatter plot of vessels into a density plot. The density plot includes a vessel density plot (such as...). Figure 2 ) and ship distribution density map (such as Figure 3 The analysis was performed. During the transformation process, a unit distance of 5m was selected, and the number of ship points within a unit distance of each coordinate point was counted and divided by the area to obtain the density value of that coordinate.

[0018] The density of each coordinate point of the vessel is statistically analyzed, and different colors are used to fill in the density values ​​to obtain a density map of the vessel. By observing and analyzing this density map and density data, the shape and size of the vessel's domain can be determined. Figure 4 As shown in the diagram, the center of the density map represents a small area of ​​water surrounding the vessel, whose density is significantly lower than that of other surrounding waters. This area can be considered the vessel's territory.

[0019] The vessel's domain is asymmetrically elliptical, with the major axis of the ellipse parallel to the bow. The center of the ellipse in the domain is eccentric to the center of the vessel, i.e., the origin of the coordinate system. The center of the ellipse in the domain is located to the left and rear of the center of the vessel.

[0020] The characteristics of ship navigation in separate lanes allow us to analyze surrounding vessels by categorizing them into two groups: those traveling in the same direction and those traveling in opposite directions. First, we analyze the distribution of surrounding vessels relative to their course, using the ship's own course as a reference. Figure 5 As shown.

[0021] Depend on Figure 5It can be seen that 77.5% of the ships have relative headings between -180° and -160°, -20° and 20°, and 160° and 180°. Therefore, data with relative headings between -20° and 20° are selected as the same-direction data, and data with relative headings between -180° and -160° and 60° and 180° are selected as opposite-direction data, and density statistical analysis is performed on them respectively.

[0022] First, data with a relative heading between -20 degrees and 20 degrees are selected as same-direction data, and a scatter plot of same-direction ships is drawn, such as... Figure 6 As shown.

[0023] Based on the characteristic that the separation of upstream and downstream navigation channels on inland waterways changes from side to side depending on the channel flow conditions, the scatter plot is symmetrically supplemented along x=0 to obtain a distribution map of vessel density in the same direction, as shown below. Figure 7 and Figure 8 As shown.

[0024] Secondly, data with relative headings between -180 and -160 degrees and between 60 and 180 degrees were selected as the data for opposing navigation, and a scatter plot of opposing navigation vessels was drawn, such as... Figure 9 As shown.

[0025] Considering that the separation of upstream and downstream navigation lanes on inland waterways can change depending on the channel flow conditions, the scatter plot is symmetrically supplemented along x=0 to obtain a distribution map of opposing vessel density, as shown below. Figure 10 and Figure 11 As shown.

[0026] In summary, when sailing in the same direction, vessels primarily engage in following or overtaking maneuvers, resulting in a shorter forward and longer rearward berth. This means the center of the berth shifts aft, and the space on either side is relatively narrow due to the width of the lane dividers. Conversely, when sailing in opposite directions, vessels primarily engage in head-on encounters, resulting in a longer forward and shorter rearward berth. This means the center of the berth shifts forward, and the space on either side is generally wider than that of vessels sailing in the same direction due to the width of the lane dividers.

[0027] Currently, ship domain models are mainly constructed through statistical analysis, analytical representation, AIS data, and intelligent technologies. However, regardless of the method used, ship domain models all have certain limitations. This is because there are many factors to consider when constructing a ship domain model, and it is extremely difficult to incorporate all of them into the model.

[0028] Considering the characteristics of ship navigation in inland waterways, an elliptical ship domain is selected as the basic graphic, such as... Figure 12 As shown.

[0029] Establish a coordinate system for the ship with its center as the origin, the positive x-axis as the right-hand transverse direction, and the positive y-axis as the bow direction. The boundary equations for the inland waterway vessel domain under this coordinate system are shown in the equation.

[0030] ; In the formula: a and b are the radii of the elliptical ship-shaped field in the positive and negative x-axis and y-axis directions, respectively, and x0 and y0 are the eccentric coordinates in the x-axis and y-axis directions, respectively.

[0031] First, select the density data at x=0, the center of the same-direction and target vessel navigation density map, and generate the same-direction vessel density curve and the opposite-direction vessel density curve at section x, such as... Figure 13 and Figure 14 As shown.

[0032] Different threshold values ​​were used to observe changes in the ship's domain, thus determining the appropriate threshold value. A 40% threshold was ultimately chosen, determining the coordinates of the eccentric point in the same-direction ship's domain as (0, -140), and the major axis radius b1 as 360 meters. The major axis radius is obtained from the coordinate range; for example, the major axis radius b1 corresponds to the horizontal coordinate of the ship's domain between -500 and 220 meters, so the major axis radius b1 is 720 / 2 = 360 meters. A 15% threshold was chosen, with the coordinates of the eccentric point in the opposing ship's domain as (0, 160), and the horizontal coordinate range of the ship's domain being (-190~510), thus the major axis radius b2 is 350 meters.

[0033] Secondly, density data at the center of the same-direction and opposite-direction vessel density distribution maps at y=-140 and y=160, respectively, and several rows of grid density data along the minor axis direction, were selected to generate the density curves of same-direction vessels at the y-section and the density curves of opposite-direction vessels at the y-section, as follows: Figure 15 and Figure 16 As shown.

[0034] Finally, different threshold values ​​were used to observe changes in the ship domain, thereby determining a suitable threshold value. When the cross-sectional view was cut with 40% of the maximum density as the threshold, the width 'a' of the domain for ships traveling in the same direction was determined to be 30 meters, and the width 'a' of the domain for ships traveling in opposite directions was determined to be 70 meters.

[0035] Considering that relying solely on the vessel's own perimeter to determine the existence of a collision hazard could lead to a tense situation in complex inland waterway encounter scenarios, preventing the two vessels from passing at a safe distance, the inland waterway vessel perimeter is expanded by a factor of k along both the lower x-axis and y-axis to add an external safety distance boundary, thereby improving the safety of vessels during collision avoidance. The boundary equations are as follows: ; Where: K a and Kb Generally, the value is taken between [1, 2]. Through observation and comparison, finally, when determining the field of ships sailing in the same direction, K a = 1.5 and K b = 1; when determining the field of ships sailing in opposite directions, K a = 1.15 and K b = 1.28. Finally, the safe range of the ship's domain includes the safe area of the ship's domain for ships sailing in the same direction and the safe area of the ship's domain for ships sailing in opposite directions, as shown in Figure 17 and Figure 18 shown.

[0036] Considering the characteristics of ship navigation in inland waters, an elliptical ship domain is selected as the basic graph. The eyes of the inland ship domain are respectively expanded by k times along the x-axis and y-axis directions to add an external safety distance boundary, so as to improve the safety during ship collision avoidance. The equation of the safety distance boundary of the inland ship domain is as follows: ; In the formula: a and b are the radius lengths of the elliptical ship domain in the positive and negative directions of the x-axis and the positive and negative directions of the y-axis respectively, and x0 and y0 are the eccentric coordinates in the x-axis direction and the y-axis direction.

[0037] Considering the characteristics of ship navigation in inland waters, an elliptical ship domain is selected as the basic graph. The eyes of the inland ship domain are respectively expanded by k times along the x-axis and y-axis directions to add an external safety distance boundary, so as to improve the safety during ship collision avoidance. The equation of the safety distance boundary of the inland ship domain is as follows: ; In the formula: a and b are the radius lengths of the elliptical ship domain in the positive and negative directions of the x-axis and the positive and negative directions of the y-axis respectively, and x0 and y0 are the eccentric coordinates in the x-axis direction and the y-axis direction.

[0038] In an embodiment of the present invention, in combination with the characteristics of inland ship collision avoidance, when sailing in the same direction, the danger judgment starts when the ship is 1 km away from the target ship; when sailing in the opposite direction, the danger judgment starts when the ship is 1.5 km away from the target ship.

[0039] The method for judging whether there is a collision danger between the ship and the target ship is as follows: with the ship as the center, a collision danger detection circle with a radius of R is constructed. When the target ship enters the collision danger detection circle of the ship, that is, D < R, a collision danger detection line is formed based on the position coordinates and relative course of the target ship. First, judge whether the target ship is a ship sailing in the same direction or in the opposite direction, and then judge whether there is a collision danger between the two ships by whether the collision danger detection line crosses the corresponding safe range of the ship's domain for ships sailing in the same direction or in the opposite direction, as shown in Figure 19 .

[0040] To determine the collision hazard using the above methods, it is necessary to obtain the equation of the collision hazard detection line in the ship's coordinate system, and then solve for the intersection point by simultaneously solving the equation of the collision hazard detection line and the equation of the safe distance boundary of the ship's domain. If an intersection point exists, it indicates that there is a collision hazard.

[0041] Further details are as follows: Establish a coordinate system relative to the ship with the ship's position as the origin and the ship's course as the positive y-axis. With the ship's coordinates OS at time t as (0,0), and its speed... The heading is 0; the relative distance of the target ship at time t is D, and the relative bearing is... That is, the target ship's coordinates TS are (x t ot ,y t ot ), speed relative heading The relative bearing of the target ship and relative heading The range is set to between [-180°, 180°]; ; ; Target ship coordinates TS (x t ot ,y t ot Based on the distance D between our ship and the target ship and their relative bearing, the calculations are as follows: .

[0042] The components of the target ship's velocity along the x and y axes are as follows: ;in, This represents the component of the target ship's velocity along the x-axis. This represents the component of the target ship's velocity along the y-axis.

[0043] The formulas for the relative velocities of the ship and the target ship along the x and y axes are as follows: ;in, This represents the relative velocity component of the ship's hull and the target ship along the x-axis. This represents the relative velocity component of the ship and the target ship along the y-axis.

[0044] when When the slope k of the straight line is: ; when When the slope k of the straight line is: ; Based on the point-slope form of the equation of a straight line, the equation of the relative course line in the ship's coordinate system can be obtained as follows: (Formula 1); By combining the two equations, the intersection of the collision hazard detection line and the safety distance boundary of the ship's domain can be obtained.

[0045] Because the equations for the collision hazard detection line and the safety distance boundary of the inland waterway vessel area are complex to analyze, a quadratic equation discriminant is used to determine the number of intersections between the collision hazard detection line and the two boundaries.

[0046] The equation for the safety distance boundary in the inland waterway vessel sector is: (Formula 2); Combining formulas 1 and 2, we get: (Formula 3); ; Its discriminant is: ; when If it is determined that the collision hazard detection line and the safe distance boundary do not intersect, then the target vessel is not at risk of collision. when If one or two intersection points are found between the collision hazard detection line and the safety distance boundary, a collision hazard is considered to exist; and the x-coordinate of the intersection point is: ; ; The encounter time T at the intersection of the target vessel's collision hazard detection line and the maritime safety distance boundary. ca for: ; ; Meet at the right time Minimum value: .

[0047] Among them, T cax1 Let T be the predicted meeting time at coordinate x1. cax2 The predicted meeting time is at coordinate x2; Depending on the timing of the encounter, the driver is able to take evasive action.

[0048] In summary, the present invention provides a method for predicting the encounter time of intelligent inland waterway vessels. It proposes to determine whether there is an intersection between the collision prediction line and the safe distance boundary, and also proposes the encounter time at the intersection of the collision prediction line of the target vessel and the safe distance boundary of the vessel domain. It can accurately reflect the navigation risk of the target vessel relative to the vessel itself, and the warning data is stable and has good real-time performance, which can effectively assist the driver in identifying navigation risks.

[0049] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for predicting the encounter time of intelligent inland waterway vessels, characterized in that, The method is as follows: Step 1: Establish a model for the inland waterway vessel sector; Step 2: Obtain the external safety distance boundary equation using the inland waterway vessel domain model; Step 3: Establish a coordinate system relative to the ship hull and obtain the target ship coordinates TS; Step 4: Obtain the target ship's speed from the target ship's coordinates TS, and then obtain the relative speed between your ship and the target ship from the target ship's speed; Step 5: Establish a collision hazard detection line expression using the target vessel coordinates TS; Step 6: Determine the coordinates of the collision intersection point using the expression for the collision hazard detection line and the equation for the safe distance boundary; Step 7: Obtain the encounter time of the intersection point between the collision hazard detection line and the safety distance boundary of the target vessel using the collision intersection point coordinates and the relative velocity; Step 1 specifically involves: Step 11: Obtain the initial Automatic Identification System (AIS) data of the vessel, and preprocess the initial AIS data to obtain a scatter plot of the vessel and surrounding vessels using the preprocessed AIS data. Step 12: Obtain the density map of the ship through the scatter plot, and obtain the territory map of the ship through the density map; Step 13: Divide the directions of surrounding ships into same-direction and opposite-direction using the angle data of relative headings, and establish a scatter distribution map of ships sailing in the same direction and a scatter distribution map of ships sailing in opposite directions. Based on the scatter distribution map of ships sailing in the same direction and the scatter distribution map of ships sailing in opposite directions, obtain a density distribution map of ships sailing in the same direction and a density distribution map of ships sailing in opposite directions. Step 14: Establish an inland waterway vessel domain model based on the vessel's domain map; Step 14 specifically involves: selecting an elliptical vessel domain as the basic shape, taking the center of the target vessel as the origin, the right transverse direction as the positive x-axis, and the bow direction as the positive y-axis, to establish the vessel's coordinate system. Within this coordinate system, the boundary equations for the inland waterway vessel domain are established as follows: ； In the formula: a and b are the radii of the elliptical ship in the positive and negative x-axis and y-axis directions, respectively, and x0 and y0 are the eccentric coordinates in the x-axis and y-axis directions, respectively; Step 2 is as follows: Step 21: Select the density data at x=0 from the density distribution maps of ships traveling in the same direction and ships traveling in opposite directions, generate the density curves of ships traveling in the same direction and ships traveling in opposite directions at the x-section, determine the density threshold, and cut the density curves of ships traveling in the same direction and ships traveling in opposite directions at the x-section to obtain and determine the coordinates of the eccentric point and the major axis radius r1 of the eccentric point in the domain of ships traveling in the same direction and the coordinates of the eccentric point and the major axis radius r of the eccentric point in the domain of ships traveling in opposite directions. 2； Step 22: Select the preset density data of the center of the same-direction vessel density distribution map and the opposite-direction vessel density distribution map respectively, generate the same-direction vessel density curve and the opposite-direction vessel density curve of the y-section, determine the threshold value, cut the cross-section map according to the threshold value, and obtain the width of the same-direction vessel domain and the width of the opposite-direction vessel domain. Step 23: Expand the inland waterway vessel domain by a factor of k along both the x-axis and y-axis to add an external safety distance boundary. Determine the K values ​​for the domains of vessels traveling in the same direction and those traveling in opposite directions using the external safety distance boundary equation. a and K b value; The equation for the external safety distance boundary is as follows: ； Among them, K a The value is a coefficient of the safety distance boundary equation, indicating the expansion of k along the x-axis in the inland waterway vessel domain. a times, K b The value is a coefficient of the safety distance boundary equation, referring to the expansion of k along the y-axis in the inland waterway vessel domain. b times; Step 5 specifically involves: The equation for the relative course line in the ship's coordinate system is: (Official 1); Where, k t This represents the slope of the relative course equation in the ship's coordinate system; The equation for the safety distance boundary in the inland waterway vessel sector is: (Formula 2); Combining formulas 1 and 2, we get: (Official 3); The discriminant of Formula 3 is: ； when If it is determined that the collision hazard detection line and the safe distance boundary do not intersect, then the target vessel is not at risk of collision. when If one or two points of intersection exist between the collision hazard detection line and the safety distance boundary, a collision hazard is identified. The coordinates of the intersection point can be obtained as follows: ； ； The target ship coordinates TS are represented as (x t ot ,y t ot ); Step 7 specifically includes: The encounter time at the intersection of the collision prediction line of the target vessel and the boundary of the safe distance of the vessel's domain is: ； ； Among them, T cax1 Let T be the predicted meeting time at coordinate x1. cax2 The predicted meeting time is at coordinate x2; This represents the relative velocity component of the ship's hull and the target ship along the x-axis. Then time T will be encountered ca Pick Minimum value, i.e. .

2. The method for predicting the encounter time of intelligent inland waterway vessels according to claim 1, characterized in that, Step 11 specifically involves: selecting ships within a 1km radius of the ship as the calculation object, and removing AIS data information with a speed of less than 0.5m / s from the ship's data. With the target vessel as the center and its course as the longitudinal axis, a coordinate system is established relative to the target vessel in the surrounding waters. To ensure that the target vessel's heading is always aligned with the longitudinal axis of the grid at all times, the relative true directions of all other vessels in the surrounding waters are converted to the target vessel's course. In other words, the position information of all target vessels is converted to a Cartesian coordinate system with the target vessel as the origin and the heading as the y-axis, to obtain their relative bearing and relative distance. Based on the obtained relative distance and relative bearing, a scatter plot of all other target vessels is drawn.

3. The method for predicting the encounter time of intelligent inland waterway vessels according to claim 2, characterized in that, Step 3 specifically involves: Establish a coordinate system relative to the ship with the ship's position as the origin and the ship's course as the positive y-axis. With the ship's coordinates OS at time t as (0,0), and its speed... The heading is 0; the relative distance of the target ship at time t is D, and the relative bearing is... That is, the target ship's coordinates TS are (x t ot ,y t ot ), speed relative heading The relative bearing of the target vessel and relative heading The range is set to between [-180°, 180°]; ； ； Target ship coordinates TS (x t ot ,y t ot Based on the distance D between our vessel and the target vessel and their relative bearing, the calculations are as follows: 。 4. The method for predicting the encounter time of intelligent inland waterway vessels according to claim 3, characterized in that, Step 4 specifically involves: The components of the target ship's velocity along the x and y axes are as follows: ;in, This represents the component of the target ship's velocity along the x-axis. This represents the component of the target ship's velocity along the y-axis. The formulas for the magnitudes of the x and y components of the relative velocity between the ship and the target ship are as follows: ;in, This represents the relative velocity component of the ship's hull and the target ship along the x-axis. This represents the relative velocity component of the hull and the target vessel along the y-axis.

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