An intelligent traffic management system for ship traffic data classification and identification

Abstract

The present invention relates to the field of intelligent traffic management technology, and in particular, to an intelligent traffic management system for classification and identification of ship traffic data. It includes a classification change unit, a calculation identification unit, and a cutting selection unit. The congestion identification module discretizes the end-to-end edge into countless end-to-end edge points, and records the diameter of the end-to-end edge point and the ship flow data of the end-to-end edge point, as well as the position node of the ship. The diameter of the end-to-end edge point is the channel length of the end-to-end edge point. The congestion point is identified according to the diameter of the end-to-end edge point and the ship flow data of the end-to-end edge point. The identified congestion points are interconnected to form a traffic-intensive area of ​​the end-to-end edge, and the traffic-intensive area is marked as a key node in the graph model. By identifying and connecting the traffic-intensive area, the distribution of the congestion area can be more accurately understood, thereby providing a basis for waterway planning and design, optimizing the waterway layout, avoiding future congestion, and improving the efficiency of waterway management.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent traffic management, and in particular to an intelligent traffic management system for classifying and identifying ship traffic data. Background Art

[0002] With the continuous advancement of technology and the deepening of application needs, intelligent traffic management has broad application prospects in the field of ship traffic management, and can be widely used in port management and shipping companies. When a ship is sailing in a waterway according to a navigation path in the water, the interference factors of ripples and floating objects on the water surface affect the visual or optical measurement of the water area, causing data measurement deviations, resulting in insufficient accuracy of the measurement data and large data calculation errors. During navigation in the water area, due to the large data calculation errors, the influence of the ship's speed is difficult to measure accurately, resulting in the ship's performance at navigation not meeting expectations, increasing the risk of conflict and collision between ships and reducing navigation safety. At the same time, due to the large data calculation errors, it is impossible to accurately identify the congestion points of the waterway and traffic-intensive areas, resulting in reduced waterway management efficiency. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent traffic management system for classifying and identifying ship traffic data to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides an intelligent traffic management system for classifying and identifying ship traffic data, comprising:

[0005] Classification change unit, calculation recognition unit, cutting selection unit;

[0006] The classification change unit acquires multi-source data of ship traffic to establish a graph model and calculates the sailing speed adjusted by the ship in the starting and ending stages;

[0007] The calculation and identification unit is used to receive the data in the classification change unit, calculate the comprehensive congestion volume in the terminal stage, identify the congestion point using the calculated comprehensive congestion volume, and form the traffic intensive area of ​​the starting and ending sides according to the identified congestion point;

[0008] The cutting selection unit is used to receive data from the classification change unit and the calculation identification unit, simulate cutting the edges and key nodes connected to the key nodes in the graph model, and determine whether there is an edge based on the points and intersection nodes between the ship position node and the key node;

[0009] The classification change unit classifies the multi-source data of ship traffic into starting nodes, cross nodes and terminal nodes according to the graph model, connects the starting node with the terminal node to form a beginning and end edge, and transmits the data in the classification change unit to the calculation and identification unit. The calculation and identification unit calculates the comprehensive congestion amount in the terminal stage according to the calculated adjusted sailing speed, and uses the calculated comprehensive congestion amount to determine whether there is congestion on the beginning and end edges. When congestion exists on the beginning and end edges, the beginning and end edge points are discretized, and the diameter of the beginning and end edge points and the position nodes of the ships are recorded. The congestion points are identified according to the diameter of the beginning and end edge points, and the identified congestion points are interconnected to form a traffic-intensive area on the beginning and end edges, and then the traffic-intensive area is marked as a key node in the graph model.

[0010] As a further improvement of the technical solution, the classification change unit includes a classification establishment module, a speed calculation module and a flow change module;

[0011] The classification module is established to obtain multi-source data of ship traffic, a graph model is established based on the obtained multi-source data using graph technology, and channel data is obtained from the obtained multi-source data, and then the starting point, intersection point, and end point are obtained from the channel data, and the starting point, intersection point, and end point are classified into different nodes of the starting node, intersection node, and end node in the graph model, and then connected to each other to form a ship navigation path, and the navigation path is marked as an edge in the graph model;

[0012] The speed calculation module is used to receive the start node, end node, edge, radar, channel, sea condition and weather data in the classification module. There are multiple nodes in the edge of the graph model. The graph model transmits the node and edge data to the ship. The ship sails from the start node to the end node according to the edge data, connects the start node with the end node to form the beginning and end edge, and records the channel length of the beginning and end edge. Then, the navigation speed data of the ship on the beginning and end edge is obtained from the radar data, and the navigation speed adjusted by the ship in the beginning and end edge stage is calculated according to the ship's navigation speed, sea condition and weather data;

[0013] The flow change module is used to receive the channel data in the classification module and the channel length of the beginning and end sides in the speed calculation module, obtain the ship flow data of the beginning and end sides from the channel data, calculate the flow density adjusted by the ship in the beginning and end stages according to the ship flow data of the beginning and end sides and the channel length of the beginning and end sides, and then calculate the flow change of the ship in the set time window in the beginning and end stages according to the ship flow data of the beginning and end sides.

[0014] As a further improvement of the technical solution, the flow change module calculates the flow change of the ship in the set time window in the starting and ending stages to achieve the following principle:

[0015] Collect vessel traffic data all the time Calculate the flow change of the ship in the set time window in the beginning and end stages, and calculate the flow change of the ship at the beginning and end stages , the specific algorithm formula is:

[0016] ;

[0017] in, Refers to the calculation time The change of ship traffic at each moment, Refers to time Vessel traffic data at all times , Refers to the time window.

[0018] As a further improvement of the technical solution, the calculation and identification unit includes a calculation and judgment module and a congestion identification module;

[0019] The calculation and judgment module is used to receive the map model in the classification module and the navigation speed calculated and adjusted in the speed calculation module, and receive the ship flow density and calculation time calculated and adjusted in the flow change module. The ship traffic changes at the moment will calculate the adjusted sailing speed, the adjusted ship traffic density and the calculation time The ship flow changes at each moment are input into the graph model, and the graph model outputs the corresponding weight coefficient. The weight coefficient is calculated based on the adjusted sailing speed, the adjusted ship flow density, and the calculated time. The ship flow changes at each moment and the corresponding weight coefficients are used to calculate the comprehensive congestion of ships in the beginning and end stages, and the calculated comprehensive congestion is used to determine whether there is congestion at the beginning and end. When the calculated comprehensive congestion is greater than the set comprehensive congestion, it is determined that there is congestion at the beginning and end.

[0020] The congestion identification module is used to receive a command from the calculation and judgment module to determine whether there is congestion at the beginning and end edges. The congestion identification module obtains the beginning and end edge data from the speed calculation module and the ship flow data of the beginning and end edges from the flow change module, discretizes the beginning and end edges into beginning and end edge points, and records the diameter of the beginning and end edge points and the ship flow data of the beginning and end edge points, as well as the position nodes of the ships. The diameter of the beginning and end edge points is the channel length of the beginning and end edge points. Congestion points are identified based on the diameter of the beginning and end edge points and the ship flow data of the beginning and end edge points, and the identified congestion points are interconnected to form a traffic-intensive area at the beginning and end edges, and the traffic-intensive area is marked as a key node in the graph model.

[0021] As a further improvement of the technical solution, the calculation and judgment module calculates the comprehensive congestion amount of ships in the starting and ending stages to achieve the following steps:

[0022] Step 1: Calculate the adjusted sailing speed , calculate the adjusted ship traffic density , calculation time Changes in ship traffic at each moment and the corresponding weight coefficients, which contain , , Weight coefficient;

[0023] Step 2: Adjust the sailing speed based on calculation , calculate the adjusted ship traffic density , calculation time Changes in ship traffic at each moment and , , The weight coefficient is used to calculate the comprehensive congestion of ships in the beginning and end stages, and the calculated comprehensive congestion is obtained. , the specific algorithm formula is:

[0024] .

[0025] As a further improvement of the technical solution, the congestion identification module implements the steps of identifying the traffic-intensive areas at the beginning and end edges:

[0026] Step 1: Collect the diameters of the beginning and end points Ship traffic data at the end and end points Calculate the flow density of the ship adjusted at the beginning and end points, and obtain the flow density adjusted at the beginning and end points , the specific algorithm formula is:

[0027] ;

[0028] in, Refers to calculating the The flow density after adjusting the edge points , Refers to the Vessel traffic data for each end point , Refers to the The diameter of the end point ;

[0029] Step 2: Use the calculated flow density to adjust the edge points The flow density of the set edge points Make a judgment to determine each end point Whether it is a congestion point, the specific judgment formula is:

[0030] ;

[0031] in, Refers to the Always point ,when When Always point It is a congestion point. When Always point Not a congestion point.

[0032] As a further improvement of the technical solution, the cutting selection unit includes a cutting judgment module and a comparison selection module;

[0033] The cutting judgment module is used to receive the graph model, intersection nodes and terminal nodes in the classification module, receive the beginning and end edges in the speed calculation module and the key nodes and the ship's position nodes in the congestion identification module, obtain the edges connected to the key nodes from the graph model, and obtain all points between the ship's position node and the key nodes and the intersection nodes from the key nodes to the terminal nodes, and then simulate the cutting of the edges and key nodes connected to the key nodes in the graph model, and use the depth-first search algorithm to judge according to the points and intersection nodes between the ship's position node and the key nodes, and judge whether there are edges between the points between the ship's position node and the key nodes and the intersection nodes from the key nodes to the terminal nodes;

[0034] The comparison and selection module is used to receive the number of intersection edges and the channel lengths of the intersection edges in the cutting judgment module, use the channel lengths of the intersection edges to compare in sequence, select the intersection edge with the shortest channel length as the ship's navigation path, and the ship navigates according to the shortest intersection edge.

[0035] As a further improvement of the technical solution, the specific judgment situations in the cutting judgment module include:

[0036] Case ①: When there is an edge, the edge connecting the point between the ship position node and the key node and the intersection node between the key node and the terminal node is marked as a positional intersection edge in the graph model, and the number of positional intersection edges and the channel length of the positional intersection edges are recorded, and then the edge connected to the key node and the key node are cut off in the graph model;

[0037] Case ②: When there is no edge, the edges connected to the key nodes are restored and the key nodes are simulated cut off in the graph model, and an early warning of congestion at the key nodes is triggered.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. In the intelligent traffic management system for classification and identification of ship traffic data, the congestion identification module discretizes the beginning and end edges into countless beginning and end edge points, and records the diameter of the beginning and end edge points and the ship flow data of the beginning and end edge points, as well as the location nodes of the ships. The diameter of the beginning and end edge points is the channel length of the beginning and end edge points. The congestion points are identified according to the diameter of the beginning and end edge points and the ship flow data of the beginning and end edge points. The identified congestion points are interconnected to form a traffic-intensive area on the beginning and end edges, and the traffic-intensive area is marked as a key node in the graph model. By identifying and connecting the traffic-intensive areas, the distribution of the congested areas can be more accurately understood, thereby providing a basis for waterway planning and design, optimizing the waterway layout, avoiding future congestion, and improving the efficiency of waterway management.

[0040] 2. In the intelligent traffic management system for classification and identification of ship traffic data, the calculation and judgment module calculates the adjusted navigation speed, the adjusted ship flow density and the calculation time. The ship flow changes at each moment are input into the graph model, and the graph model outputs the corresponding weight coefficient. The weight coefficient is calculated based on the adjusted sailing speed, the adjusted ship flow density, and the calculated time. The ship flow changes at each moment and the corresponding weight coefficient are used to calculate the comprehensive congestion of ships in the beginning and end stages. The calculated comprehensive congestion amount and the set comprehensive congestion amount are used to determine whether there is congestion at the beginning and end. When the calculated comprehensive congestion amount is greater than the set comprehensive congestion amount, it is determined that there is congestion at the beginning and end. Calculating the comprehensive congestion amount can help identify areas with severe congestion, thereby formulating more effective navigation strategies, reducing the risk of conflicts and collisions between ships, and improving navigation safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is an overall block diagram of the present invention.

[0042] The meaning of each number in the figure is:

[0043] 1. Classification change unit; 11. Establish classification module; 12. Speed ​​calculation module; 13. Flow change module;

[0044] 2. Calculation and identification unit; 21. Calculation and judgment module; 22. Congestion identification module;

[0045] 3. Cutting selection unit; 31. Cutting judgment module; 32. Comparison selection module. DETAILED DESCRIPTION

[0046] The following will be combined with the accompanying drawings in the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] The present invention provides an intelligent traffic management system for classifying and identifying ship traffic data. Figure 1 , including a classification change unit 1, a calculation and recognition unit 2, and a cutting and selection unit 3;

[0048] The classification change unit 1 obtains multi-source data of ship traffic to establish a graph model and calculates the sailing speed adjusted by the ship in the starting and ending stages;

[0049] The calculation and identification unit 2 is used to receive the data in the classification change unit 1, calculate the comprehensive congestion volume in the terminal stage, identify the congestion point by using the calculated comprehensive congestion volume, and form the traffic intensive area of ​​the starting and ending sides according to the identified congestion point;

[0050] The cutting selection unit 3 is used to receive the data in the classification change unit 1 and the calculation identification unit 2, simulate the cutting of the edges and key nodes connected to the key nodes in the graph model, and judge whether there is an edge according to the points and intersection nodes between the ship position node and the key node;

[0051] The classification change unit 1 classifies the multi-source data of ship traffic into starting nodes, cross nodes and terminal nodes according to the graph model, connects the starting node with the terminal node to form a beginning and end edge, and transmits the data in the classification change unit 1 to the calculation and identification unit 2. The calculation and identification unit 2 calculates the comprehensive congestion in the terminal stage according to the calculated adjusted sailing speed, and uses the calculated comprehensive congestion to determine whether there is congestion on the beginning and end edges. When there is congestion on the beginning and end edges, the beginning and end points of the beginning and end edges are discretized, and the diameter of the beginning and end points and the position nodes of the ships are recorded. The congestion points are identified according to the diameter of the beginning and end points, and the identified congestion points are interconnected to form a traffic-intensive area on the beginning and end edges, and then the traffic-intensive area is marked as a key node in the graph model.

[0052] The following is a refinement of the above units, see Figure 1 ;

[0053] The classification change unit 1 includes a classification establishment module 11, a speed calculation module 12 and a flow change module 13;

[0054] Establish a classification module 11 to obtain multi-source data of ship traffic, and use graph technology to establish a graph model based on the obtained multi-source data. The graph model can reduce the interference factors of ripples and floating objects on the water surface by learning and processing the obtained multi-source data, so as to reduce the data measurement deviation, thereby improving the accuracy of the visual or optical measurement data of the water area, and also reducing the large data calculation error. The channel data is obtained from the obtained multi-source data, and then the starting point, intersection point, and end point are obtained from the channel data. The starting point, intersection point, and end point are classified into different nodes of the starting node, intersection node, and end node in the graph model, and then connected to each other to form a ship navigation path, and the navigation path is marked as an edge in the graph model;

[0055] The multi-source data acquired include AIS data, radar data (including the distance between the ship and different nodes and points, the distance between the ship's position point and the intersection point, and the ship's sailing speed), meteorological data, sea condition data, waterway data (including the sailing path (starting point, intersection point, end point), ship flow data), and port data;

[0056] The speed calculation module 12 is used to receive the start node, end node, edge, radar, channel, sea condition and weather data in the classification module 11. There are multiple nodes on the edge of the graph model. The graph model transmits the node and edge data to the ship. The ship sails from the start node to the end node according to the edge data, connects the start node with the end node to form the beginning and end edge, and records the channel length of the beginning and end edge. Then, the navigation speed data of the ship on the beginning and end edge is obtained from the radar data. The adjusted navigation speed of the ship in the beginning and end edge stage is calculated according to the ship's navigation speed, sea condition and weather data. Due to the large error in data calculation, the ship speed is accurately measured, which accurately reflects that the performance of the ship during navigation is consistent with expectations. Controlling the navigation speed of the ship can reduce the distance between ships, thereby reducing the risk of collision. Appropriate speed control helps to improve navigation safety.

[0057] The principle of calculating the sailing speed adjusted by the ship during the starting and ending phases is as follows:

[0058] Collect ship speed , Sea state data and weather data Calculate the adjusted sailing speed of the ship during the start and end phases, and obtain the calculated adjusted sailing speed , the specific algorithm formula is:

[0059] ;

[0060] Among them, this formula is used to calculate the adjusted sailing speed of the ship in the starting and ending stages. By adjusting the sailing speed, the ship flow in the channel can be balanced to avoid congestion. Appropriate adjustment of the speed can make the ship flow evenly distributed and improve the channel's traffic capacity;

[0061] The flow change module 13 is used to receive the channel data in the classification module 11 and the channel length of the start and end sides in the speed calculation module 12, obtain the ship flow data of the start and end sides from the channel data, calculate the flow density of the ship adjusted in the start and end stages according to the ship flow data of the start and end sides and the channel length of the start and end sides, and then calculate the flow change of the ship in the set time window in the start and end stages according to the ship flow data of the start and end sides. Through reasonable time window management, the waiting time of the ship in the channel can be effectively reduced, the punctuality of the flight can be improved, and delays caused by congestion can be avoided;

[0062] The principle of calculating the flow density adjusted by the ship in the starting and ending stages is as follows:

[0063] Collect vessel traffic data all the time and the length of the channel from the beginning to the end Calculate the adjusted flow density of the ship in the beginning and end stages, and obtain the calculated adjusted ship flow density , the specific algorithm formula is:

[0064] ;

[0065] Among them, this formula is used to calculate the flow density adjusted by ships in the starting and ending stages. Adjusting the flow density can help to reasonably allocate waterway resources and ensure that the ship flow in each area is within an acceptable range, thereby avoiding congestion and over-utilization;

[0066] The flow change module 13 calculates the flow change of the ship in the set time window in the beginning and end stages to achieve the following principle:

[0067] Collect vessel traffic data all the time Calculate the flow change of the ship in the set time window in the beginning and end stages, and calculate the flow change of the ship at the beginning and end stages , the specific algorithm formula is:

[0068] ;

[0069] in, Refers to the calculation time The change of ship traffic at each moment, Refers to time Vessel traffic data at all times , Refers to the time window. This formula is used to calculate the flow change of ships in the set time window during the starting and ending stages. By setting the time window and observing the flow change, the passage arrangement of ships can be adjusted in time to avoid excessive congestion of the waterway in a specific time period, thereby optimizing the overall traffic capacity;

[0070] The calculation and identification unit 2 includes a calculation and judgment module 21 and a congestion identification module 22;

[0071] The calculation and judgment module 21 is used to receive the map model in the classification module 11 and the navigation speed calculated and adjusted in the speed calculation module 12, and receive the ship flow density and calculation time calculated and adjusted in the flow change module 13. The ship traffic changes at the moment will calculate the adjusted sailing speed, the adjusted ship traffic density and the calculation time The ship flow changes at each moment are input into the graph model, and the graph model outputs the corresponding weight coefficient. The weight coefficient is calculated based on the adjusted sailing speed, the adjusted ship flow density, and the calculated time. The ship flow changes at each moment and the corresponding weight coefficients are used to calculate the comprehensive congestion of ships in the beginning and end stages. The calculated comprehensive congestion and the set comprehensive congestion are used to determine whether there is congestion at the beginning and end. When the calculated comprehensive congestion is greater than the set comprehensive congestion, it is determined that there is congestion at the beginning and end. Calculating the comprehensive congestion can help identify areas with severe congestion, thereby formulating more effective navigation strategies, reducing conflicts and collision risks between ships, and improving navigation safety.

[0072] The steps for calculating the comprehensive congestion amount of ships in the starting and ending stages in the calculation and judgment module 21 are as follows:

[0073] Step 1: Calculate the adjusted sailing speed , calculate the adjusted ship traffic density , calculation time Changes in ship traffic at each moment and the corresponding weight coefficients, which contain , , Weight coefficient;

[0074] Step 2: Adjust the sailing speed based on calculation , calculate the adjusted ship traffic density , calculation time Changes in ship traffic at each moment and , , The weight coefficient is used to calculate the comprehensive congestion of ships in the beginning and end stages, and the calculated comprehensive congestion is obtained. , the specific algorithm formula is:

[0075] ;

[0076] Among them, this formula is used to calculate the comprehensive congestion of ships in the starting and ending stages. By calculating the comprehensive congestion, we can understand the congestion degree at different stages, so as to more effectively allocate waterway resources, adjust the passage time or change the waterway use strategy to avoid excessive congestion;

[0077] The congestion identification module 22 is used to receive the command of the calculation and judgment module 21 to judge whether there is congestion at the beginning and end sides. The congestion identification module 22 obtains the beginning and end side data from the speed calculation module 12 and the ship flow data of the beginning and end sides from the flow change module 13, discretizes the beginning and end sides into countless beginning and end side points, and records the diameter of the beginning and end side points and the ship flow data of the beginning and end side points, as well as the position nodes of the ships. The diameter of the beginning and end side points is the channel length of the beginning and end side points. The congestion points are identified according to the diameter of the beginning and end side points and the ship flow data of the beginning and end side points, and the identified congestion points are interconnected to form a traffic-intensive area at the beginning and end sides, and then the traffic-intensive area is marked as a key node in the graph model. By identifying and connecting the traffic-intensive areas, the distribution of the congestion areas can be more accurately understood, thereby providing a basis for waterway planning and design, optimizing the waterway layout, avoiding future congestion, and improving the efficiency of waterway management;

[0078] The congestion identification module 22 implements the steps of identifying the traffic-intensive areas at the beginning and end sides:

[0079] Step 1: Collect the diameters of the beginning and end points Ship traffic data at the end and end points Calculate the flow density of the ship adjusted at the beginning and end points, and obtain the flow density adjusted at the beginning and end points , the specific algorithm formula is:

[0080] ;

[0081] in, Refers to calculating the The flow density after adjusting the edge points , Refers to the Vessel traffic data for each end point , Refers to the The diameter of the end point ;

[0082] Step 2: Use the calculated flow density to adjust the edge points The flow density of the set edge points Make a judgment to determine each end point Whether it is a congestion point, the specific judgment formula is:

[0083] ;

[0084] in, Refers to the Always point ,when When Always point It is a congestion point. When Always point It’s not a congestion point;

[0085] The cutting selection unit 3 includes a cutting judgment module 31 and a comparison selection module 32;

[0086] The cutting judgment module 31 is used to receive the graph model, intersection nodes and terminal nodes in the classification module 11, receive the beginning and end edges in the speed calculation module 12 and the key nodes and the ship's position nodes in the congestion identification module 22, obtain the edges connected to the key nodes from the graph model, and obtain all points between the ship's position node and the key nodes and the intersection nodes from the key nodes to the terminal nodes, and then simulate the cutting of the edges and key nodes connected to the key nodes in the graph model, and use the depth-first search algorithm to judge according to the points and intersection nodes between the ship's position node and the key nodes, and judge whether there are edges between the points between the ship's position node and the key nodes and the intersection nodes from the key nodes to the terminal nodes. Confirming that there are edges between the intersection nodes can help determine the most direct navigation path, improve navigation efficiency and reduce voyage time;

[0087] The implementation steps of using the depth-first search algorithm to determine whether there is an edge between the point between the ship position node and the key node and the intersection node are as follows:

[0088] Step 1: Create a visited tag list visited to record whether each point between the ship position node and the key node and the intersection node from the key node to the end node has been visited. Then create a stack to store the ship position node currently being explored and the intersection node from the key node to the end node. and each point between the ship position node and the key node ;

[0089] Step 2: Push the ship position node into the stack. If the stack is not empty, perform the following operations:

[0090] S1. Pop a point between the ship position node and the key node from the stack ;

[0091] S2, when point It is the intersection node between the ship position node and the key node , and the intersection node from the key node to the terminal node Connected, indicating the existence of the edge;

[0092] Step 3: When the stack is empty and no intersection node is found between the ship position node and the key node , indicating that the edge does not exist;

[0093] The specific judgment situations in the cutting judgment module 31 include:

[0094] Case ①: When there is an edge, the edge connecting the point between the ship position node and the key node and the intersection node between the key node and the terminal node is marked as a positional intersection edge in the graph model, and the number of positional intersection edges and the channel length of the positional intersection edges are recorded, and then the edge connected to the key node and the key node are cut off in the graph model;

[0095] Case ②: When there is no edge, restore the edge connected to the key node and simulate the removal of the key node in the graph model, trigger an early warning of congestion at the key node, and send an early warning instruction to the relevant departments;

[0096] The comparison and selection module 32 is used to receive the number of intersection edges and the channel lengths of the intersection edges in the cutting judgment module 31, and use the channel lengths of the intersection edges to compare in turn, and select the intersection edge with the shortest channel length as the ship's navigation path. The ship navigates according to the shortest intersection edge. Selecting the shortest path means that the ship can cover the least distance during the navigation process, thereby saving time. For commercial ships, reducing navigation time can improve efficiency and reduce operating costs.

[0097] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only preferred examples of the present invention, and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. An intelligent traffic management system for classification and identification of ship traffic data, Features: It includes a classification change unit (1), a calculation and recognition unit (2), and a cutting and selection unit (3); The classification change unit (1) acquires multi-source data of ship traffic to establish a graph model and calculates the sailing speed adjusted by the ship in the starting and ending stages; The calculation and identification unit (2) is used to receive the data in the classification change unit (1), calculate the comprehensive congestion volume in the beginning and end stages, identify the congestion points using the calculated comprehensive congestion volume, and form the traffic intensive area of ​​the beginning and end according to the identified congestion points; The calculation and identification unit (2) comprises a calculation and judgment module (21) and a congestion identification module (22); The calculation and judgment module (21) is used to receive the map model in the classification module (11) and the navigation speed calculated and adjusted in the speed calculation module (12), and receive the ship flow density and calculation time calculated and adjusted in the flow change module (13). The ship traffic changes at the moment will calculate the adjusted sailing speed, the adjusted ship traffic density and the calculation time The ship flow change at each moment is input into the graph model, and the graph model outputs the corresponding weight coefficient. The weight coefficient is calculated based on the adjusted sailing speed, the adjusted ship flow density, and the calculated time. The ship flow changes at each moment and the corresponding weight coefficients are used to calculate the comprehensive congestion of ships in the beginning and end stages, and the calculated comprehensive congestion is used to determine whether there is congestion at the beginning and end. When the calculated comprehensive congestion is greater than the set comprehensive congestion, it is determined that there is congestion at the beginning and end. The congestion identification module (22) is used to receive a command from the calculation and judgment module (21) to determine that congestion exists at the end-to-end edge. The congestion identification module (22) obtains the end-to-end edge data from the speed calculation module (12) and the ship flow data of the end-to-end edge from the flow change module (13), discretizes the end-to-end edge into end-to-end edge points, and records the diameter of the end-to-end edge point and the ship flow data of the end-to-end edge point, as well as the position node of the ship. The diameter of the end-to-end edge point is the channel length of the end-to-end edge point. The congestion point is identified based on the diameter of the end-to-end edge point and the ship flow data of the end-to-end edge point, and the identified congestion points are interconnected to form a traffic-intensive area at the end-to-end edge, and the traffic-intensive area is marked as a key node in the graph model; The cutting selection unit (3) is used to receive data from the classification change unit (1) and the calculation identification unit (2), simulate cutting the edges connected to the key nodes and the key nodes in the graph model, and judge whether the edges exist according to the points between the ship position node and the key nodes and the intersection nodes; in case ①, when the edges exist, the edges connecting the points between the ship position node and the key nodes and the intersection nodes between the key nodes and the terminal nodes are marked as position intersection edges in the graph model, the number of position intersection edges and the channel length of the position intersection edges are recorded, and then the edges connected to the key nodes and the key nodes are cut in the graph model; in case ②, when the edges do not exist, the simulated cutting of the edges connected to the key nodes and the key nodes in the graph model is restored, and an early warning of congestion at the key nodes is triggered; The classification change unit (1) classifies the multi-source data of ship traffic into a starting node, a cross node and an end node according to the graph model, connects the starting node with the end node to form an end-end edge, and then transmits the data in the classification change unit (1) to the calculation and identification unit (2). The calculation and identification unit (2) calculates the comprehensive congestion amount in the end-end edge stage according to the calculated adjusted sailing speed, and uses the calculated comprehensive congestion amount to determine whether there is congestion on the end-end edge. When congestion exists on the end-end edge, the end-end edge is discretized into end-end points, and the diameter of the end-end point and the position node of the ship are recorded. The congestion point is identified according to the diameter of the end-end point, and the identified congestion points are connected to each other to form a traffic-intensive area on the end-end edge, and the traffic-intensive area is marked as a key node in the graph model.

2. According to claim 1, an intelligent traffic management system for classification and identification of ship traffic data, Features: The classification change unit (1) comprises a classification establishment module (11), a speed calculation module (12) and a flow change module (13); The classification module (11) is constructed to obtain multi-source data of ship traffic, and to establish a graph model based on the obtained multi-source data using graph technology, and to obtain channel data from the obtained multi-source data, and then to obtain a starting point, an intersection point, and an end point from the channel data, and to classify the starting point, the intersection point, and the end point in the graph model as different nodes of a starting node, an intersection node, and an end node, and then to interconnect them to form a ship navigation path, and to mark the navigation path as an edge in the graph model; The speed calculation module (12) is used to receive the start node, end node, edge, radar, channel, sea condition and weather data in the classification module (11), the edge in the graph model has multiple nodes, the graph model transmits the node and edge data to the ship, the ship sails from the start node to the end node according to the edge data, the start node is connected to the end node to form an end edge, and the channel length of the end edge is recorded at the same time, and then the navigation speed data of the ship on the end edge is obtained from the radar data, and the navigation speed adjusted by the ship in the end edge stage is calculated according to the ship's navigation speed, sea condition and weather data; The flow change module (13) is used to receive the channel data in the classification module (11) and the channel length of the start and end sides in the speed calculation module (12), obtain the ship flow data of the start and end sides from the channel data, calculate the flow density adjusted by the ship in the start and end stages according to the ship flow data of the start and end sides and the channel length of the start and end sides, and then calculate the flow change of the ship in a set time window in the start and end stages according to the ship flow data of the start and end sides.

3. According to claim 2, an intelligent traffic management system for classification and identification of ship traffic data, Features: The flow change module (13) calculates the flow change of the ship in the set time window in the starting and ending phases to achieve the following principle: Collect vessel traffic data all the time Calculate the flow change of the ship in the set time window in the beginning and end stages, and calculate the flow change of the ship at the beginning and end stages , the specific algorithm formula is: ； in, Refers to the calculation time The change of ship traffic at each moment, Refers to time Vessel traffic data at all times , Refers to the time window.

4. According to claim 1, an intelligent traffic management system for classification and identification of ship traffic data, Features: The calculation and judgment module (21) calculates the comprehensive congestion amount of ships in the starting and ending stages by implementing the following steps: Step 1: Calculate the adjusted sailing speed , calculate the adjusted ship traffic density , calculation time Changes in ship traffic at each moment and the corresponding weight coefficients, which include , , Weight coefficient; Step 2: Adjust the sailing speed based on calculation , calculate the adjusted ship traffic density , calculation time Changes in ship traffic at each moment and , , The weight coefficient is used to calculate the comprehensive congestion of ships in the beginning and end stages, and the calculated comprehensive congestion is obtained. , the specific algorithm formula is: 。 5. According to claim 1, an intelligent traffic management system for classification and identification of ship traffic data, Features: The congestion identification module (22) identifies the traffic-intensive areas at the beginning and end edges to achieve the following steps: Step 1: Collect the diameters of the beginning and end points Ship traffic data at the end and end points Calculate the flow density of the ship adjusted at the beginning and end points, and obtain the flow density adjusted at the beginning and end points , the specific algorithm formula is: ； in, Refers to calculating the The flow density after adjusting the edge points , Refers to the Vessel traffic data for each end point , Refers to the The diameter of the end point ; Step 2: Use the calculated flow density to adjust the edge points The flow density of the set edge points Make a judgment to determine each end point Whether it is a congestion point, the specific judgment formula is: ； in, Refers to the Always point ,when When Always point It is a congestion point. When Always point Not a congestion point.

6. An intelligent traffic management system for classification and identification of ship traffic data according to claim 2, Features: The cutting selection unit (3) comprises a cutting judgment module (31) and a comparison selection module (32); The cutting judgment module (31) is used to receive the graph model, intersection nodes and terminal nodes in the classification module (11), receive the beginning and end edges in the speed calculation module (12) and the key nodes and the ship's position nodes in the congestion identification module (22), obtain the edges connected to the key nodes from the graph model, and obtain the points between the ship's position node and the key nodes and the intersection nodes between the key nodes and the terminal nodes, and then simulate the cutting of the edges connected to the key nodes and the key nodes in the graph model, and use the depth-first search algorithm to judge based on the points and intersection nodes between the ship's position node and the key nodes, and judge whether there are edges between the points between the ship's position node and the key nodes and the intersection nodes between the key nodes and the terminal nodes; The comparison and selection module (32) is used to receive the number of positional intersections and the channel lengths of the positional intersections in the cutting judgment module (31), and use the channel lengths of the positional intersections to perform comparisons in sequence, and select the positional intersection with the shortest channel length as the navigation path of the ship, and the ship navigates according to the shortest positional intersection.

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