Port logistics dynamic path planning method and system based on multi-source data fusion

Abstract

The invention belongs to the field of traffic control, particularly relates to a port logistics dynamic path planning method and system based on multi-source data fusion, and aims to solve the problem of how to dynamically plan a port logistics path in real time according to multi-source data under massive real-time data. The embodiment of the invention provides a port logistics dynamic path planning method based on multi-source data fusion, and the method comprises the steps: obtaining the road condition data of a port and the task data of an external container truck, and calculating a dynamic road weight; performing dynamic path planning on the external container trucks according to the dynamic road weights, and generating an initial path of each external container truck; the real-time road condition of the port and the execution state of the initial path are monitored in real time, and the driving state of the internal container truck is adjusted according to the execution state; and according to the real-time road condition, obtaining the occurrence condition of the dynamic event, and when the dynamic event occurs, updating the initial path according to the dynamic event to obtain an updated path.

Description

Technical Field

[0001] The present invention relates to the field of traffic control, and more particularly, to a method and system for dynamic path planning of port logistics based on multi-source data fusion. Background Art

[0002] With the continuous development of the global trade economy, ports, as important hubs of international trade, play a crucial role. The efficiency of material distribution and management in ports is of vital importance. Compared with ordinary roads, the road conditions inside ports focus more on supporting efficient logistics operations and the passage of heavy transportation vehicles, and the safety and environmental factors faced are more complex. In addition, the road environment inside ports is closed, dynamic, and dedicated, and involves a large number of special vehicles, equipment, and operation processes. The design logic of ordinary navigation, such as static maps, single transportation vehicles, and low-precision positioning, cannot meet the requirements of dynamics, coordination, high precision, and safety control inside ports. Therefore, a dedicated navigation system is needed inside ports to provide more accurate, efficient, and safe navigation services.

[0003] Port logistics involves multiple types of data such as internal container trucks, external container trucks, and traffic events. The data sources are scattered and the formats are not unified. Therefore, fusing the scattered and non-uniform data sources to generate comprehensive and real-time data, so as to provide a dynamic path planning method for port managers or drivers can significantly improve the efficiency and reliability of port logistics, and also provide strong support for the intelligent management and decision-making of ports. Summary of the Invention

[0004] The problem solved by the present invention: How to perform real-time dynamic planning of the path of port logistics according to multi-source data under a large amount of real-time data.

[0005] To solve the above problems, an embodiment of the present invention provides a method for dynamic path planning of port logistics based on multi-source data fusion. The planning method includes: obtaining the road condition data of the port and the task data of external container trucks, and calculating the dynamic road weights; performing dynamic path planning on the external container trucks according to the dynamic road weights to generate the initial path of each external container truck; real-time monitoring the real-time road conditions of the port and the execution status of the initial path, and adjusting the driving status of the internal container trucks according to the execution status; obtaining the occurrence of dynamic events according to the real-time road conditions, and when a dynamic event occurs, updating the initial path according to the dynamic event to obtain an updated path; recalculating the dynamic road weights according to the updated path, and updating the driving status of the internal container trucks according to the change of the dynamic road weights.

[0006] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: By obtaining the port road condition data to obtain the road weights, the changes in the road weights brought about by the real-time road conditions of the port are fully considered. By using the dynamic road weights and the task data of external container trucks to obtain the initial path, the differences between external container truck tasks are fully considered, making the path planning more reasonable. By real-time monitoring the real-time road conditions of the port, sudden situations can be detected in a timely manner, and the execution status of the initial path is monitored in real time, which helps to respond to road condition changes in a timely manner according to the real-time road conditions, reducing transportation delays and chaos caused by sudden road condition changes. The update of the path helps to uniformly dispatch the affected container trucks, thereby improving the dispatching efficiency. According to the changes in the dynamic road weights, the driving status of internal container trucks is updated, which helps to achieve the reasonable dispatching of internal container trucks in the port, avoid conflicts and congestion between container trucks, and improve the coordination and fluency of internal transportation in the port.

[0007] In an embodiment of the present invention, dynamic path planning is performed on external container trucks according to the dynamic road weights to generate the initial path of each external container truck, which specifically includes: classifying according to the destinations within the port area where the external container trucks are located, and planning the driving path according to the destinations; when there are multiple driving paths, obtaining the vehicle type and vehicle load corresponding to the external container truck according to the task data; calculating the starting rate of the external container truck according to the vehicle type and vehicle load; and allocating the external container truck to the driving path according to the starting rate to obtain the initial path of the external container truck.

[0008] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: Classifying according to the destinations within the port area where the external container trucks are located and planning the driving path accordingly makes the driving route planning of external container trucks more targeted. The acquisition of the vehicle type and vehicle load corresponding to the external container truck fully considers the influence brought by the starting rate of the external container truck during the driving process, realizing the reasonable allocation of road resources.

[0009] In an embodiment of the present invention, the real-time road conditions of the port and the execution status of the initial path are monitored in real time, and the driving status of internal container trucks is adjusted according to the execution status, which specifically includes: real-time monitoring the running trajectory and running speed of external container trucks; when the running trajectory is different from the initial path, predicting the subsequent path of the external container truck according to the road condition data of the port; obtaining the cruise path of the internal container truck, and when there is interference between the cruise path and the subsequent path, calculating the interference time period when the interference occurs according to the running speed; setting virtual traffic lights for the internal container trucks, and adjusting the driving status of the internal container trucks through the virtual traffic lights to change the driving position of the internal container trucks during the interference time period.

[0010] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: The acquisition of the running trajectory and speed of external container trucks can promptly respond to changes during the driving process of external container trucks, adapt to path changes caused by factors such as road conditions and emergencies, calculate the interference time period based on the running speed, and can anticipate in advance the possible conflict points and conflict times between container trucks, so as to take targeted measures. The setting of virtual traffic lights provides clear rules and guidance for the driving of internal container trucks, enabling internal container trucks to orderly adjust their driving states when facing possible interference.

[0011] In an embodiment of the present invention, virtual traffic lights are set for internal container trucks, and the driving states of internal container trucks are adjusted through the virtual traffic lights to change the driving positions of internal container trucks during the interference time period. Specifically, it includes: obtaining the same section of the cruise path and the subsequent path to obtain the overlapping path; determining the influence coefficient of the internal container truck on the overlapping path according to the traffic flow density of the overlapping path; when the influence coefficient is greater than or equal to the interference threshold, controlling the driving of the internal container truck through the virtual traffic lights to ensure that the internal container truck is outside the overlapping path during the interference time period; when the influence coefficient is less than the interference threshold, adjusting the initial time for the internal container truck to enter the overlapping path according to the influence coefficient.

[0012] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: The acquisition of the overlapping path can accurately lock the specific area where interference may occur between internal container trucks and external container trucks. Determining the influence coefficient based on the traffic flow density and comparing it with the interference threshold provides a reasonable basis for the scheduling decision of internal container trucks. Through the real-time monitoring and analysis of the driving data of container trucks, the intelligent scheduling and management of internal container trucks are realized, reducing the uncertainty and error of manual intervention.

[0013] In an embodiment of the present invention, the occurrence of dynamic events is obtained according to the real-time road conditions. When a dynamic event occurs, the initial path is updated according to the dynamic event to obtain an updated path. Specifically, it includes: obtaining the occurrence location and event type of the dynamic event according to the real-time road conditions, and determining the traffic stagnation area of the dynamic event; obtaining the external container trucks that need to pass through the traffic stagnation area, and determining the adjustable paths of the external container trucks according to the road condition data; selecting the corresponding adjustable paths for the external container trucks according to the task data to obtain the updated path.

[0014] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: Timely discovering and demarcating the traffic stagnation area and quickly adjusting the paths of affected container trucks can effectively reduce the negative impact of dynamic events on transportation and improve the port's ability to respond to various emergencies.

[0015] In an embodiment of the present invention, the dynamic road weight is recalculated according to the updated path, and the driving state of the internal container truck is updated according to the change of the dynamic road weight, which specifically includes: obtaining the unit weight value of each driving road in each time period; when the unit weight value is greater than the weight threshold, the time period is recorded as a prohibited driving period, and when the unit weight value is less than or equal to the weight threshold, the time period is recorded as a passable period; calculating the unit traffic volume during the passable period, and adjusting the driving state of the internal container truck according to the unit traffic volume.

[0016] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: By obtaining the unit weight value of each driving road in each time period, the traffic conditions of the road at different times can be clearly understood. According to the comparison between the unit weight value and the weight threshold, the prohibited driving period and the passable period are divided, providing a clear time reference for the driving plan of the internal container truck. Adjusting the driving state of the internal container truck according to the unit traffic volume can ensure the operation efficiency of the external container truck.

[0017] In an embodiment of the present invention, calculating the unit traffic volume during the passable period and adjusting the driving state of the internal container truck according to the unit traffic volume specifically includes: obtaining the traffic demand of the internal container truck during the passable period, and predicting the theoretical traffic volume of the internal container truck during the passable period; when the traffic demand is less than or equal to the theoretical traffic volume, confirming the passing order of the internal container truck according to the current position of the internal container truck; when the traffic demand is greater than the theoretical traffic volume, determining the internal container trucks that need to pass according to the task priority of the internal container truck, and controlling the internal container trucks that do not need to pass to park nearby.

[0018] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: By obtaining the traffic demand of the internal container truck during the passable period and predicting the theoretical traffic volume, the relationship between the road carrying capacity and the traffic demand of the container truck can be accurately evaluated. By screening according to the task priority, it is ensured that the container trucks with key tasks can pass in time and are not blocked by other container trucks with non-key tasks, improving the overall efficiency and service quality of the port operation and ensuring the smooth progress of port production.

[0019] In an embodiment of the present invention, the present invention also provides a planning system. The port logistics dynamic path planning method described in the above embodiment is applied to the planning system. The planning system includes: a data collection module, which is used to collect road condition data and the task data of external container trucks; a data processing module, which is used to perform fusion processing on the road condition data and the task data and calculate the dynamic road weight; a path planning module, which is used to generate an initial path and an updated path; a road monitoring module, which is used to monitor the real-time road conditions. This planning system has all the technical features of the above port logistics dynamic path planning method, and will not be elaborated here one by one. Brief Description of the Drawings

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those skilled in the art, without creative efforts, other drawings can be obtained based on these drawings; Figure 1 One of the flowcharts of the dynamic path planning method for port logistics of the present invention; Figure 2 Another flowchart of the dynamic path planning method for port logistics of the present invention; Figure 3 Another flowchart of the dynamic path planning method for port logistics of the present invention; Figure 4 Another flowchart of the dynamic path planning method for port logistics of the present invention; Figure 5 System schematic diagram of the planning system of the present invention; Explanation of reference numerals in the drawings: 100 - Planning system; 110 - Data acquisition module; 120 - Data processing module; 130 - Path planning module; 140 - Road monitoring module. Detailed Embodiments

[0021] To make the above - mentioned objects, features and advantages of the present invention more obvious and understandable, the following will give a detailed description of the specific embodiments of the present invention with reference to the drawings.

[0022]

First Embodiment

[0023] In step S100, generally, the road network layout within a port is relatively complex and may include multiple areas such as docks, warehouses, and yards. These different functional areas are connected by a complex road system, which can easily lead to traffic congestion or navigation difficulties. To ensure the transportation efficiency of external container trucks, it is necessary to perform real-time dynamic planning on the paths of external container trucks. When performing real-time dynamic planning on the paths of external container trucks, it is usually necessary to obtain the task data of external container trucks and the real-time road conditions within the port. Among them, the task data includes, but is not limited to, task type, cargo information, vehicle type, reservation and scheduling information, operation area, entry and exit times, and task priority, etc., which can be obtained through the port management information system, container operation scheduling system, reservation system, and data sharing between logistics companies and the port. The road condition data of the port usually includes traffic flow, lane information, and traffic events, etc., which can be obtained through sensors and monitoring devices, data sharing platforms, traffic management systems, and manual inspections, etc.

[0024] Generally speaking, lane information usually includes road surface conditions, road repairs, lane width, and lane type, etc. Traffic events generally refer to traffic congestion and traffic accidents, etc. The calculation of dynamic road weights needs to comprehensively consider static road attributes such as lane width, road surface conditions, and lane type, and dynamic traffic conditions such as traffic flow, congestion, and accidents, which can be obtained through various calculation methods.

[0025] Taking the weighted average method as an example, the dynamic road weight formula is: ; ; ; .

[0026] Among them, is the traffic event weight, is the event occurrence determination value, is the event impact coefficient, which can be optimized through fuzzy comprehensive evaluation or grey neural network model, is the traffic flow weight, is the traffic flow of the current road section, is the road capacity, is the lane information weight, is the weight of lane information, is the impact coefficient of lane information, which can be determined through the analytic hierarchy process or rough set theory, is the dynamic road weight, is the basic weight.

[0027] Based on the road surface flatness, road surface damage degree, road surface slipperiness, and the presence of obstacles, fixed weights can be directly assigned. For example, the road surface conditions can be divided into four grades: excellent, good, medium, and poor, and their weight values correspond to 0.1, 0.5, 1, and 1.5 respectively.

[0028] Generally speaking, the basic weights can be preset according to the functional importance of the lanes in the port. For example, the main roads, such as the roads connecting the wharf and the yard, are set to 0.2, the secondary roads, such as the yard loop roads, are set to 0.5, the access roads in the loading and unloading areas are set to 0.8, and the temporary roads, such as the construction detours, are set to 1.2. Also, according to whether the lane is a dedicated lane, the lane types can be divided into dedicated lanes and mixed traffic lanes. For example, the weight of the dedicated lane for container trucks is set to 1, and the weight of the mixed traffic lane is set to 1.5.

[0029] For road maintenance, weights can generally be assigned according to the degree of traffic interruption caused by the maintenance. For example, the weight of normal traffic is set to 0, the weight of one-sided closure is set to 1, and the weight of complete closure can be set to infinity, with forced detours.

[0030] The calculation formula for the weight of the lane width is as follows: ; Among them, is the actual width of the current road, is the maximum width of the internal roads in the port.

[0031] It should be noted that the higher the traffic priority, the lower the weight.

[0032] For example, for a certain road in a port, the dynamic road weight of the road surface condition is 0.55, and the dynamic road weight of another road is 0.6. Then, the traffic priority of the road with a dynamic road weight of 0.55 is higher than that of the road with a dynamic road weight of 0.6.

[0033] Taking the method based on traffic zoning as an example, the dynamic road weight formula is: ; Among them, T is the actual travel time, is the free-flow travel time, and are parameters adjusted according to the actual situation, is the traffic flow of the current road section, is the road capacity.

[0034] For example, assume that the free-flow travel time of a certain road is 10 minutes, the traffic flow is 120 vehicles per hour, the road capacity is 150 vehicles per hour, and the model parameter = 0.15, If it is 4, the actual travel time of this road is approximately: T = 10×(1 + 0.15×0.7776) ≈ 11.16 minutes. Then, it takes about 11.16 minutes to pass through this road, that is, the dynamic road weight of this road is 11.16. If the dynamic road weight of another road is 12, then the road with a dynamic road weight of 11.16 has a higher traffic priority than the road with a dynamic road weight of 12.

[0035] In step S200, the dynamic road weight reveals the traffic efficiency and priority in the current traffic environment. Usually, the container trucks in the port generally have a large volume and a slow driving speed. If they mix with other vehicles, it may cause traffic congestion and low efficiency. Therefore, in many large ports, there are usually dedicated lanes or routes for external container trucks. Therefore, when performing dynamic path planning for external container trucks, it is first necessary to screen out the dedicated lanes for external container trucks.

[0036] Secondly, the selected paths can be determined through the task data of external container trucks. Among them, the task types include: loading and unloading tasks, container transfer tasks, customs inspection tasks, etc. The vehicle types of external container trucks can be classified according to their uses. For example, flatbed container trucks, container trucks, van container trucks, and refrigerated container trucks, etc.

[0037] In step S300, usually, external container truck drivers may choose a driving path different from the initial path due to their driving habits. Therefore, external container trucks usually have two situations: following the path and not following the path. In addition, due to the complexity of the internal paths in the port, there may be a situation where internal container trucks interfere with the driving of external container trucks. Therefore, it is necessary to monitor the real-time road conditions of the port and the execution status of the initial path through detection equipment, and adjust the driving status of internal container trucks according to the road priority of internal container trucks.

[0038] For example, generally speaking, the priority of external container trucks is usually higher than that of internal container trucks. Therefore, when internal container trucks interfere with the driving of external container trucks, virtual traffic lights are generated for internal container trucks to ensure the smooth passage of external container trucks.

[0039] It should be noted that when internal container trucks have an emergency task and interfere with the driving of external container trucks, an instruction can be sent to external container trucks. For example, a voice prompt is sent to remind external container trucks, so as to ensure the smooth passage of internal container trucks.

[0040] In steps S400 and S500, generally speaking, a dynamic event refers to situations such as traffic congestion or bottlenecks, sudden traffic accidents or obstacles, and emergency dispatching or priority transportation that occur in the path of external container trucks. Usually, when a dynamic event occurs, it is necessary to uniformly dispatch the affected container trucks according to the scope of influence of the dynamic event, the total number of vehicles that need to change routes, and the traffic conditions of the updated path, so as to avoid traffic congestion and long-term stagnation.

[0041] Obtaining the road weights through the port road condition data fully considers the changes in road weights brought about by the real-time road conditions of the port. Obtaining the initial path through the dynamic road weights and the task data of external container trucks fully considers the differences between external container truck tasks, making the path planning more reasonable. By real-time monitoring the real-time road conditions of the port, sudden situations can be detected in a timely manner, and the execution status of the initial path is monitored in real time, which helps to respond to road condition changes in a timely manner according to the real-time road conditions, reducing transportation delays and chaos caused by sudden road condition changes. The acquisition of the updated path helps to uniformly dispatch the affected container trucks, thereby improving the dispatching efficiency. Updating the driving status of internal container trucks according to the changes in dynamic road weights helps to achieve reasonable dispatching of internal container trucks in the port, avoid conflicts and congestion between container trucks, and improve the coordination and fluency of internal transportation in the port.

[0042]

Second Embodiment

[0043] In step S210, usually, multiple container truck driving paths are usually set inside the port, and these driving paths lead to different cargo yards or terminal areas. Therefore, first, it is necessary to preliminarily screen out suitable driving paths according to the destinations of the external container trucks, and then select the initial path according to the magnitude of the road dynamic weights of the preliminarily screened suitable driving paths.

[0044] In steps S220 and S230, when there is only one driving path available based on the dynamic road weight and the destination of the external truck, this driving path is the initial path. When there are multiple available driving paths, in order to avoid the situation where external trucks uniformly choose the same path or the transportation efficiency of the driving path is reduced due to the different running speeds of external trucks and other trucks on the driving path, therefore, it is necessary to uniformly schedule the driving paths of external trucks.

[0045] Generally speaking, different types of truck vehicles, such as heavy trucks, medium trucks, and light trucks, differ in load capacity and size, which will affect the driving speed, acceleration ability, and cornering ability of the vehicle. For example, heavy trucks may take more time to accelerate and maintain a slower speed, which may affect traffic flow. In addition, for the same model of truck, its weight is different when it is unloaded and fully loaded. Therefore, it is necessary to plan the driving paths of external trucks according to the vehicle type and vehicle load.

[0046] For example, assume that the average speed of a fully loaded medium truck in the port is 15 kilometers per hour, and in the unloaded case, its average speed is 20 kilometers per hour. The distance from the dock to the container pick-up area in the port area for this medium truck is 2 kilometers. Then, when it is fully loaded, it takes about 6 minutes to travel from the dock to the container pick-up area in the port area, and when it is unloaded, it takes 8 minutes to travel from the dock to the container pick-up area in the port area. Therefore, when planning the driving path, external trucks with the same load are preferentially assigned to the same driving path.

[0047] In step S230, usually, the starting rate is affected by the vehicle type and vehicle load, and can be simply obtained through the following formula: ; where F is the traction force, is the rolling resistance, is the air resistance, is the total weight of the external truck, is the starting rate of the external truck.

[0048] From the above formula, it can be seen that for the same external truck, its starting rate is different in the fully loaded and unloaded conditions.

[0049] In addition, for the lanes with a faster starting speed, the traffic flow will be smoother, while vehicles with a slower starting speed are likely to affect the overall traffic flow and may cause delays for subsequent vehicles. Therefore, when planning roads for external container trucks, in order to improve the overall transportation efficiency within the port, it is necessary to obtain the speed limits and average vehicle speeds on each driving path, arrange those with a higher starting speed on the driving paths with a higher average vehicle speed, and arrange those with a lower starting speed on the driving paths with a lower average vehicle speed.

[0050] Classify according to the destinations of external container trucks within the port area and plan the driving paths accordingly, making the driving route planning of external container trucks more targeted. The acquisition of the vehicle types and vehicle loads corresponding to external container trucks fully considers the impact of the starting speed of external container trucks during driving, achieving a reasonable allocation of road resources.

[0051]

Third Embodiment

[0052] In step S320, generally speaking, the destination of the external container truck can be obtained through the task data, and the paths that the external container truck can drive on can be known through the road condition data of the port. When there is a difference between the running trajectory and the initial path, the subsequent path of the external container truck can be predicted based on the task data of the external container truck, the road condition data of the port, and the current driving path.

[0053] In steps S330 and S340, generally, when there is interference between the cruise path and the subsequent path, the interference time period during which the interference occurs is calculated based on the running speed of the external yard truck on the subsequent path, the length of the vehicle flow of the external yard truck affected by the interference, and the length of the interference section. After obtaining the specific range of the interference time period, the interference situation of the internal yard truck on the external yard truck is judged according to the cruise path of the internal yard truck, and the passing mode of the internal yard truck is controlled according to the virtual traffic lights. The virtual red light can be displayed for the internal yard truck in the open area to stop the internal yard truck from running, and it can continue to execute the cruise path after the interference time period ends. Or when the road conditions permit, virtual street lights can be set to enable the internal yard truck to quickly pass through some intersections and pass through the intersections before the start of the interference time period to avoid interference between the cruise path and the subsequent path. Since the internal yard trucks in the port area all adopt assisted driving technology, the virtual traffic lights have a good effect on the internal yard trucks, but they do not play their due role for the external yard trucks.

[0054] Obtaining the running trajectory and running speed of the external yard truck can timely respond to the changes during the driving process of the external yard truck and adapt to the path changes caused by factors such as road conditions and emergencies. Calculating the interference time period based on the running speed can predict in advance the possible conflict points and conflict times between the yard trucks, so as to take targeted measures. The setting of the virtual traffic lights provides clear rules and guidance for the driving of the internal yard trucks, enabling the internal yard trucks to orderly adjust their driving states when facing possible interference.

[0055]

Fourth Embodiment

[0056] In steps S341 and S342, generally, there may be the same driving sections between the internal yard trucks and the external yard trucks. The traffic flow density has a direct relationship with the smoothness, passing capacity, delay, etc. of the traffic flow. When the traffic flow density is too high, the driving speed of the vehicles will be reduced, thus affecting the transportation efficiency.

[0057] The threshold of traffic flow density can be obtained based on the analysis of historical traffic flow data, denoted as the density threshold. The threshold of traffic flow density represents the upper limit of the number of vehicles per unit length on the road. When the flow density exceeds this value, traffic begins to be significantly disrupted, resulting in a decrease in vehicle speed and traffic efficiency, and ultimately may lead to traffic congestion.

[0058] The influence coefficient of the internal container truck on the overlapping path can be determined according to the traffic flow density of the internal container truck and the traffic flow density of the overlapping path, and usually can be obtained through the following formula: ; Where is the influence coefficient, is the traffic flow density of the overlapping path, is the traffic flow density of the internal container truck, is the density threshold. Usually, the larger it is, the greater the influence of the internal container truck on the overlapping path.

[0059] In steps S343 and S344, usually, the interference threshold can be set according to the urgency of the tasks of the external container trucks.

[0060] For example, when the interference threshold is 1 and the influence coefficient is 1.1, since 1.1 is greater than 1, it is necessary to set virtual traffic lights to ensure that the internal container trucks do not enter the overlapping path during the interference period.

[0061] In step S344, when the influence coefficient is less than the interference threshold, it means that the traffic flow on the road has not reached the level of hindering the normal operation of the external container trucks. Therefore, the initial time for the internal container trucks to enter the overlapping path can be adjusted according to the magnitude of the influence coefficient. The specific methods are as follows: The first one: increase the interval time for the internal container trucks to merge into the overlapping path. For example, the internal container trucks enter the overlapping path in batches to avoid a large number of container trucks entering at the same time; The second one: through real-time traffic, observe the changes in traffic flow and density, and adjust the initial time of the container trucks in a timely manner. For example, if it is found that the traffic flow gradually increases during certain periods, the initial time for the internal container trucks to enter the overlapping path can be adjusted in advance to avoid excessive aggregation.

[0062] The acquisition of the overlapping path can accurately lock the specific area where the internal container trucks and the external container trucks may interfere. Determine the influence coefficient based on the traffic flow density and compare it with the interference threshold, which provides a reasonable basis for the scheduling decision of the internal container trucks. Through the real-time monitoring and analysis of the driving data of the container trucks, the intelligent scheduling and management of the internal container trucks are realized, reducing the uncertainty and error of manual intervention.

[0063]

Fifth Embodiment

[0064] In step S410, generally speaking, it can be predicted whether it is necessary to dynamically adjust the driving path of the external heavy trucks according to the event type of the dynamic event. For example, when there is traffic congestion in the front driving section, if the predicted congestion duration is less than the duration for the external heavy truck to reach the congested section, then there is no need to update the initial path.

[0065] In step S430, in order to avoid a large number of external heavy trucks converging into the same driving path, it is necessary to uniformly allocate the affected external heavy trucks according to the destination, the traffic flow density threshold of the adjustable path, the current traffic flow density of the adjustable path, and the average vehicle speed of the adjustable path, so as to obtain the updated path of the external heavy trucks.

[0066] For example, the calculation method for obtaining the updated path through a multi-objective path allocation model is as follows: ; Among them, is the current traffic flow density of the th alternative path, is the maximum traffic flow density of the th alternative path, is the estimated passing time of the th vehicle, is a weight parameter that can be dynamically adjusted according to requirements When is relatively small, the total passing time is dominant,

[0067] When the task priority of the vehicle of the external heavy truck is relatively high, the driving path that enables the external heavy truck to reach the destination in the shortest time is selected.

[0068] For example, assume that the passing time of section A is 10 minutes, and the maximum traffic flow density is 50 vehicles / km, and the current traffic flow density is 30 vehicles per kilometer, and the travel time of section B = 15 minutes, and the maximum traffic flow density is 100 vehicles per kilometer, and the current traffic flow density is 50 vehicles per kilometer. The total number of affected external container trucks is 100. Let the number of vehicles assigned to section A be x. Then, the number of vehicles assigned to section B is 100 - x. When balanced distribution is required, that is, let = , we can get x = 30. Then, is equal to 1.2, and thus the total cost = 1350 + ×1.2. When extreme distribution is carried out, if all vehicles take section A, then the total cost = 1000 + ×2.6. If all vehicles take section B, then the total cost = 1500 + ×1.5. Finally, it can be known that when is less than 100, then all vehicles take road A. When is greater than 300, then all vehicles take road B. When is greater than or equal to 100 and less than or equal to 300, then balanced distribution is carried out.

[0069] Timely discovering and demarcating the stagnant areas and quickly adjusting the paths of affected container trucks can effectively reduce the negative impacts of dynamic events on transportation and improve the port's ability to respond to various emergencies. Orientedly planning the adjustable paths according to the task data can make the updated paths more in line with the current traffic conditions in the port and make the updated paths more reasonable.

[0070]

Sixth Embodiment

[0071] In step S510, the unit weight values of each driving road in each time period can be obtained according to the updated driving paths of external container trucks and the average speeds of external container trucks. Generally speaking, the unit weight value refers to the traffic flow density of each driving road.

[0072] In step S520, generally, the weight threshold can be set according to the actual situation. For example, in order to ensure the rapid passage of external container trucks, the weight threshold can be set slightly lower. When it is necessary to ensure the overall transportation efficiency, the weight threshold can be set slightly higher. In addition, the weight threshold cannot exceed the traffic flow density threshold at most.

[0073] By obtaining the unit weight value of each driving road in each time period, the traffic conditions of the road at different times can be clearly understood. According to the comparison between the unit weight value and the weight threshold, the prohibited driving period and the passable period are divided, providing a clear time reference for the driving plan of internal container trucks. Adjusting the driving state of internal container trucks according to the unit traffic volume can ensure the operation efficiency of external container trucks.

[0074]

Seventh Embodiment

[0075] In steps S531 to S533, generally, the operation of internal container trucks needs to be reserved in advance. The passing section and passing time period of internal container trucks can be obtained through reservation data. The traffic demand of internal container trucks during the passable period can be obtained according to the passing section and passing time period of internal container trucks. According to the traffic flow density and traffic flow density threshold of the driving road during the passable period, the theoretical traffic volume of internal container trucks during the passable period can be predicted. When the theoretical traffic volume is sufficient, internal container trucks determine the arrival order according to the arrival time of the current position. When there are two or more internal container trucks with similar arrival times, the arrival time can be fine-tuned through virtual traffic lights to ensure that there is no impact between internal container trucks and increase the passing efficiency. When the theoretical traffic volume is insufficient, internal container trucks are made to stop working as much as possible to ensure the smooth passage of external container trucks. After the traffic conditions in the port area improve, then control the internal container trucks to start running. In this state, except for some internal container trucks that will affect the work of external container trucks and need to keep running, other internal container trucks are parked nearby on the roadside without affecting the external container trucks driving on the road.

[0076] By obtaining the traffic demand of internal container trucks during the passable time period and predicting the theoretical traffic volume, the relationship between the road carrying capacity and the traffic demand of container trucks can be accurately evaluated. By screening according to task priorities, it is ensured that the container trucks for key tasks can pass in a timely manner without being blocked by container trucks for other non-key tasks, improving the overall efficiency and service quality of port operations and ensuring the smooth progress of port production.

[0077]

Eighth Embodiment

[0078] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention should be subject to the scope defined by the claims.

Claims

1. A port logistics dynamic path planning method based on multi-source data fusion, characterized in that: The planning method includes: Obtain the port's road condition data and external container truck mission data, and calculate dynamic road weights; Performing dynamic path planning for the external container trucks according to the dynamic road weights to generate an initial path for each of the external container trucks; Monitor the real-time road conditions of the port and the execution status of the initial route in real time, and adjust the driving status of the internal container trucks according to the execution status; Acquire the occurrence of a dynamic event according to the real-time road condition, and when the dynamic event occurs, update the initial path according to the dynamic event to obtain an updated path; The dynamic road weight is recalculated according to the updated path, and the driving state of the internal container truck is updated according to the change of the dynamic road weight.

2. The planning method according to claim 1, characterized in that: The step of performing dynamic path planning on the external container truck according to the dynamic road weight to generate an initial path for each of the external container trucks specifically includes: Classify the external container trucks according to their destinations within the port area, and plan travel routes according to the destinations; When there are multiple driving paths, obtaining the vehicle type and vehicle load corresponding to the external container truck according to the mission data; Calculating the start-up rate of the external container truck according to the vehicle type and the vehicle load; The external container truck is allocated to the driving path according to the starting rate to obtain the initial path of the external container truck.

3. The planning method according to claim 2, characterized in that: The real-time monitoring of the real-time road conditions of the port and the execution status of the initial path, and adjusting the driving status of the internal container truck according to the execution status, specifically includes: Real-time monitoring of the running track and running speed of the external container truck; When the running trajectory differs from the initial path, predicting a subsequent path of the external container truck according to the road condition data of the port; Acquire the cruising path of the internal container truck, and when there is mutual interference between the cruising path and the subsequent path, calculate the interference time period when the interference occurs according to the running speed; A virtual traffic light is set for the internal container truck, and the driving state of the internal container truck is adjusted by the virtual traffic light to change the driving position of the internal container truck within the interference time period.

4. The planning method according to claim 3, characterized in that: The step of setting a virtual traffic light for the internal container truck, adjusting the driving state of the internal container truck by using the virtual traffic light, and changing the driving position of the internal container truck during the interference time period specifically includes: Acquire the same section of the cruise path and the subsequent path to obtain an overlapping path; Determining the influence coefficient of the internal container truck on the overlapping path according to the vehicle flow density of the overlapping path; When the influence coefficient is greater than or equal to the interference threshold, the internal container truck is controlled to travel by the virtual traffic light to ensure that the internal container truck is outside the overlapping path during the interference time period; When the influence coefficient is less than the interference threshold, the initial time for the internal container truck to enter the overlapped path is adjusted according to the influence coefficient.

5. The planning method according to claim 4, characterized in that: The obtaining of the occurrence of a dynamic event according to the real-time road condition, and when the dynamic event occurs, updating the initial path according to the dynamic event to obtain an updated path, specifically includes: Obtaining the occurrence location and event type of the dynamic event according to the real-time traffic conditions, and determining the stagnant area of ​​the dynamic event; Acquire the external container truck that needs to pass through the stagnant area, and determine an adjustable path for the external container truck according to the road condition data; The corresponding adjustable path is selected for the external container truck according to the task data to obtain the updated path.

6. The planning method according to claim 5, characterized in that: The recalculating the dynamic road weight according to the updated path, and updating the driving state of the internal container truck according to the change of the dynamic road weight specifically includes: Obtain the unit weight value of each driving road in each time period; When the unit weight value is greater than the weight threshold, the time period is recorded as a prohibited time period; when the unit weight value is less than or equal to the weight threshold, the time period is recorded as a passable time period; The unit traffic volume within the passable time period is calculated, and the driving state of the internal container truck is adjusted according to the unit traffic volume.

7. The planning method according to claim 6, characterized in that: The calculating of the unit traffic volume within the passable time period and adjusting the driving state of the internal container truck according to the unit traffic volume specifically includes: Obtaining the traffic demand of the internal container truck during the passable period, and predicting the theoretical traffic volume of the internal container truck during the passable period; When the traffic demand is less than or equal to the theoretical traffic volume, determining the traffic order of the internal container trucks according to the current positions of the internal container trucks; When the traffic demand is greater than the theoretical traffic volume, the internal container trucks that need to pass are determined according to their task priorities, and the internal container trucks that do not need to pass are controlled to park nearby.

8. A planning system, characterized in that: The port logistics dynamic path planning method according to any one of claims 1 to 7 is applied to the planning system, and the planning system comprises: A data acquisition module, the data acquisition module is used to collect the road condition data and the mission data of the external container truck; A data processing module, the data processing module is used to fuse the road condition data and the task data, and calculate the dynamic road weight; A path planning module, the path planning module is used to generate the initial path and the updated path; A road monitoring module, wherein the road monitoring module is used to monitor the real-time road conditions.

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