A method, system, and medium for zipper-style traffic scheduling at intersections for unmanned container trucks in ports.

Abstract

This invention relates to a method, system, and medium for zipper-style traffic scheduling of unmanned trucks at intersections in ports. The method includes: L1. Based on the port's Time-of-Sight (TOS) system, acquiring task data information of the unmanned truck sequence and map data information of the port. The task data information of the unmanned truck sequence includes the previous task execution status, driving status, and destination location information. The map data information of the port includes the latitude and longitude data of the intersection. L2. Based on the task data information of the unmanned truck sequence and the latitude and longitude data of the intersection, using a Euclidean distance algorithm, determining whether the unmanned truck sequence adopts the zipper-style traffic scheduling algorithm. If the zipper-style traffic scheduling algorithm is adopted, proceed to step L3; otherwise, normal passage through the intersection occurs. This invention not only completes the zipper-style traffic scheduling function at intersections, avoiding congestion caused by unmanned trucks at intersections, but also improves the collective operational efficiency of unmanned trucks in ports.

Description

Technical Field

[0001] The present invention relates to the technical field of port autonomous container trucks, and in particular to a zipper-style passing scheduling method, system and medium for port autonomous container trucks at intersections. Background Art

[0002] With the maturity of driverless technology, port construction has gradually moved from "automation" to "unmanned". Especially in the horizontal transportation operation of port containers, intelligent devices are constantly upgraded. Driverless container trucks that can not only cover high labor costs but also greatly improve operation efficiency are being more widely used. Therefore, the dispatching center and dispatching service supporting driverless container trucks are the key content of the port information system centered on autonomous container trucks and play a crucial role in the success or failure of the transportation efficiency of autonomous container trucks.

[0003] Currently, the industry's autonomous container truck dispatching service makes real-time decisions based on external input information such as the TOS system, map road conditions, and vehicle information, issues tasks to container trucks, and coordinates the orderly passage of container trucks to ensure the efficient operation of the port. Among them, the intersection route dispatching technology accounts for the largest proportion of the content. How to avoid congestion at intersections and enable autonomous container trucks to pass alternately in a zipper style to ensure the overall operation efficiency of the port's autonomous container truck fleet is the current technical difficulty.

[0004] Existing technology one, patent (application number: 202010678234.7) discloses a central control platform system for port autonomous container trucks. The system includes an autonomous container truck cluster, a data transceiver module, a data display module, and a scenario interaction module. The data transceiver module is wirelessly connected to the autonomous container truck cluster. The data display module is electrically connected to the data transceiver module and wirelessly connected to the autonomous container truck cluster. The scenario interaction module is electrically connected to the data transceiver module. The data transceiver module is used to receive the real-time position information and real-time attitude information of the autonomous container trucks and publish the real-time position information and real-time attitude information to the data display module. The data transceiver module is also used to send the destination information of the selected autonomous container truck cluster in the scenario interaction module to the autonomous container trucks. The data display module is used to display the video information transmitted by the autonomous container truck cluster and the video information of the autonomous container truck cluster processed by the data transceiver module. The scenario interaction module is used to process and convey the information specifying the autonomous container truck cluster to a designated destination according to the central control interface to the data transceiver module. The focus of this invention is on the real-time information interaction between vehicles and the background, lacking a scheduling scheme for different operating conditions of port autonomous container trucks.

[0005] Prior art two, patent (application number: 202211235249.1), discloses a zipper-style traffic guidance method, device, terminal, and storage medium. The method involves acquiring various target images, wherein the target images are images of lanes to be merged into; performing vehicle identification on each target image to obtain the license plate number information corresponding to the target image, determining the travel time corresponding to each license plate number; sorting the license plate number information in chronological order according to the travel time corresponding to each license plate number to obtain a time sorting result; obtaining a passage sorting result based on the time sorting result and preset zipper-style traffic rules; and sending the passage sorting result to a display screen for display. However, this zipper-style passage information guidance scheme is used to guide vehicle passage in road traffic, and its engineering applicability is limited, not suitable for unmanned truck dispatching services. Summary of the Invention

[0006] In view of the shortcomings of the prior art, the present invention provides a zipper-style traffic scheduling method, system and medium for unmanned trucks at ports, which not only completes the function of zipper-style traffic at intersections and avoids congestion of unmanned trucks at intersections, but also improves the collective operating efficiency of unmanned trucks at ports.

[0007] To achieve the above and other related objectives, the present invention provides the following technical solution:

[0008] A zipper-style traffic scheduling method for unmanned container trucks at port intersections, the method comprising:

[0009] L1. Based on the port TOS system, acquire task data information of unmanned truck sequence and map data information of the port. The task data information of the unmanned truck sequence includes the previous task execution status, driving status and destination location information. The map data information of the port includes the latitude and longitude data information of the intersection.

[0010] L2. Based on the task data information of the unmanned truck sequence and the latitude and longitude data information of the intersection, the Euclidean distance algorithm is used to determine whether the unmanned truck sequence adopts the zipper passage algorithm. If the zipper passage algorithm is adopted, proceed to step L3; otherwise, pass through the intersection normally.

[0011] L3. The zipper passage algorithm is used to predict the passage priority state vector of the unmanned truck sequence and output the passage priority state vector data information of the unmanned truck sequence;

[0012] L4. Based on the passage priority state vector data information of the unmanned truck sequence, establish the priority passage index function of the unmanned truck sequence to obtain the passage priority data information of the unmanned truck sequence.

[0013] Furthermore, in step L4, the priority passage exponential function for establishing the unmanned truck sequence is:

[0014]

[0015] M=(α1,α2,α3,α4,α5,α6),

[0016] in, Let be the number of vehicles queuing behind the i-th unmanned truck. Let be the number of vehicles queuing in front of the i-th unmanned truck. Let be the distance between the i-th unmanned truck and its destination. Let be the speed of the i-th unmanned truck. Let i be the container priority of the i-th unmanned truck. Let α1, α2, α3, α4, α5 and α6 be the number of times the i-th unmanned truck yields, and let α1, α2, α3, α4, α5 and α6 be the weighting coefficients.

[0017] Furthermore, the constraints on the weighting coefficients α1, α2, α3, α4, α5, and α6 are as follows:

[0018]

[0019] Furthermore, the step of using the Euclidean distance algorithm to determine whether the unmanned truck sequence uses the zipper pass algorithm includes:

[0020] L21. Based on the latitude and longitude data of the intersection and the task data of the unmanned truck sequence, establish a function to measure the distance of the unmanned truck from the intersection.

[0021] Among them, (Jlat) ks Jlog ks ) represents the latitude and longitude data of the s-th intersection of routes k and k+r, (Vlat) ks Vlog ks ) represents the location information of the k-th unmanned truck as it passes through the s-th intersection;

[0022] L22. A function based on the distance of the unmanned truck to the intersection. The minimum distance function F is obtained.

[0023]

[0024] Where m is the number of unmanned truck sequences and n is the number of intersections;

[0025] L23. Set a preset threshold. If the value of the minimum distance function F is less than the preset threshold, the zipper passage algorithm is used. If the value of the minimum distance function F is greater than the preset threshold, the zipper passage algorithm is not used.

[0026] Furthermore, in step L3, the prediction of the passage priority state vector of the unmanned truck sequence using the zipper passage algorithm includes:

[0027] L31. Based on the task data information of the unmanned truck sequence and the latitude and longitude data information of the intersection, the state vector of the i-th unmanned truck passing through the k-th intersection is obtained as follows: The state vector of the (i+p)th unmanned truck passing through the kth intersection is

[0028] L32. Based on the state vectors of the i-th unmanned truck passing through the k-th intersection and the (i+p)-th unmanned truck passing through the k-th intersection, a comparison function is established using a 0-1 algorithm:

[0029]

[0030]

[0031]

[0032] Thus, the passage priority state vector data information of the i-th unmanned truck is obtained as follows:

[0033] in, Let be the number of vehicles queuing behind the i-th unmanned truck. Let be the number of vehicles queuing in front of the i-th unmanned truck. Let be the distance between the i-th unmanned truck and its destination. Let be the speed of the i-th unmanned truck. Let i be the container priority of the i-th unmanned truck. Let represent the number of times the i-th unmanned truck yields to other vehicles.

[0034] Furthermore, the method also includes:

[0035] L5. Based on the passage priority data of the unmanned truck sequence, the number of times the unmanned truck sequence passes through the intersection is recorded. Steps L1-L4 are repeated to schedule the unmanned truck sequence.

[0036] To achieve the above and other related objectives, the present invention also provides a zipper-style traffic scheduling system for unmanned container trucks in ports. The system includes: a TOS system, which is a terminal task planning and allocation system for ports. It is a computer management system for managing and controlling various aspects of terminal operations and issuing tasks for cargo ship berthing, loading and unloading, and container transportation loading and unloading.

[0037] The TMC simulation system is an information system for unmanned container trucks in ports. It is a system that displays tasks, statuses, maps, and resources, and integrates command, dispatch, remote control, simulation, operation and maintenance monitoring, fault handling, big data analysis, and network security strategy settings.

[0038] The unmanned container truck is a horizontal transport device for ports that is not driven by human. The mobile communication gateway mounted on the unmanned container truck, together with the automatic driving controller, completes the reception of the passage instructions issued by the TMC simulation system.

[0039] Furthermore, the TMC simulation system is communicatively connected to the TOS system and is used to receive task information lines and map information of each vehicle in the unmanned truck cluster issued by the TOS system.

[0040] Furthermore, the system also includes a 4G / 5G mobile communication network module for providing wireless communication networks for each component of the system.

[0041] To achieve the above and other related objectives, the present invention also provides a computer-readable storage medium storing a computer program programmed or configured to perform any of the described zipper-style traffic scheduling methods for unmanned container trucks in ports.

[0042] The present invention has the following positive effects:

[0043] 1. This invention addresses the problem of zipper traffic at intersections during the operation of unmanned container trucks in ports. Utilizing vehicle sequence task information and map data from the Vehicle Sequence Information System (TOS), the TMC system runs a zipper traffic algorithm. This algorithm first determines whether the two closest vehicles on different routes at the intersection have activated optimized traffic conditions. If activated, it calculates the priority index of the two vehicles based on the priority state vector and weight coefficient vector. The TMC system then issues stop instructions to the vehicle with lower priority, and only issues a departure instruction after the vehicle with higher priority has passed through the intersection. This completes the zipper traffic function at intersections, preventing congestion caused by unmanned container trucks at intersections and improving the collective operational efficiency of unmanned container trucks in ports.

[0044] 2. This invention is applied to unmanned container trucks in ports, which not only enables efficient scheduling of unmanned container trucks under different operating conditions, but also has a wide range of applications, which is conducive to the promotion and use of unmanned container trucks in ports. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0046] Figure 2 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0047] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0048] Example 1: As Figure 1 As shown, a zipper-style traffic scheduling method for unmanned container trucks at port intersections is described, the method comprising:

[0049] L1. Based on the port TOS system, acquire task data information of unmanned truck sequence and map data information of the port. The task data information of the unmanned truck sequence includes the previous task execution status, driving status and destination location information. The map data information of the port includes the latitude and longitude data information of the intersection.

[0050] L2. Based on the task data information of the unmanned truck sequence and the latitude and longitude data information of the intersection, the Euclidean distance algorithm is used to determine whether the unmanned truck sequence adopts the zipper passage algorithm. If the zipper passage algorithm is adopted, proceed to step L3; otherwise, pass through the intersection normally.

[0051] L3. The zipper passage algorithm is used to predict the passage priority state vector of the unmanned truck sequence and output the passage priority state vector data information of the unmanned truck sequence;

[0052] L4. Based on the passage priority state vector data information of the unmanned truck sequence, establish the priority passage index function of the unmanned truck sequence to obtain the passage priority data information of the unmanned truck sequence.

[0053] In this embodiment, in step L4, the priority passage exponential function for establishing the unmanned truck sequence is:

[0054]

[0055] M=(α1,α2,α3,α4,α5,α6),

[0056] in, Let be the number of vehicles queuing behind the i-th unmanned truck. Let be the number of vehicles queuing in front of the i-th unmanned truck. Let be the distance between the i-th unmanned truck and its destination. Let be the speed of the i-th unmanned truck. Let i be the container priority of the i-th unmanned truck. Let α1, α2, α3, α4, α5 and α6 be the number of times the i-th unmanned truck yields, and let α1, α2, α3, α4, α5 and α6 be the weighting coefficients.

[0057] In this embodiment, the constraints on the weighting coefficients α1, α2, α3, α4, α5, and α6 are as follows:

[0058]

[0059] In this embodiment, the step of using the Euclidean distance algorithm to determine whether the unmanned truck sequence uses the zipper pass algorithm includes:

[0060] L21. Based on the latitude and longitude data of the intersection and the task data of the unmanned truck sequence, establish a function to measure the distance of the unmanned truck from the intersection.

[0061] Among them, (Jlat) ks Jlog ks ) represents the latitude and longitude data of the s-th intersection of routes k and k+r, (Vlat) ks Vlog ks ) represents the location information of the k-th unmanned truck as it passes through the s-th intersection;

[0062] L22. A function based on the distance of the unmanned truck to the intersection. The minimum distance function F is obtained.

[0063]

[0064] Where m is the number of unmanned truck sequences and n is the number of intersections;

[0065] L23. Set a preset threshold. If the value of the minimum distance function F is less than the preset threshold, the zipper passage algorithm is used. If the value of the minimum distance function F is greater than the preset threshold, the zipper passage algorithm is not used.

[0066] In this embodiment, step L3, which involves using the zipper passage algorithm to predict the passage priority state vector of the unmanned truck sequence, includes:

[0067] L31. Based on the task data information of the unmanned truck sequence and the latitude and longitude data information of the intersection, the state vector of the i-th unmanned truck passing through the k-th intersection is obtained as follows: The state vector of the (i+p)th unmanned truck passing through the kth intersection is

[0068] L32. Based on the state vectors of the i-th unmanned truck passing through the k-th intersection and the (i+p)-th unmanned truck passing through the k-th intersection, a comparison function is established using a 0-1 algorithm:

[0069]

[0070]

[0071]

[0072] Thus, the passage priority state vector data information of the i-th unmanned truck is obtained as follows:

[0073] in, Let be the number of vehicles queuing behind the i-th unmanned truck. Let be the number of vehicles queuing in front of the i-th unmanned truck. Let be the distance between the i-th unmanned truck and its destination. Let be the speed of the i-th unmanned truck. Let i be the container priority of the i-th unmanned truck. Let represent the number of times the i-th unmanned truck yields to other vehicles.

[0074] In this embodiment, the method further includes:

[0075] L5. Based on the passage priority data of the unmanned truck sequence, the number of times the unmanned truck sequence passes through the intersection is recorded. Steps L1-L4 are repeated to schedule the unmanned truck sequence.

[0076] Example 2: Based on the zipper-style traffic scheduling method for unmanned container trucks at port in Example 1, the present invention will be further explained and described below.

[0077] like Figure 1 As shown, a zipper-style traffic scheduling method for unmanned container trucks at port intersections is described, the method comprising:

[0078] L1. Based on the port TOS system, acquire task data information of unmanned truck sequence and map data information of the port. The task data information of the unmanned truck sequence includes the previous task execution status, driving status and destination location information. The map data information of the port includes the latitude and longitude data information of the intersection.

[0079] L2. Based on the task data information of the unmanned truck sequence and the latitude and longitude data information of the intersection, the Euclidean distance algorithm is used to determine whether the unmanned truck sequence adopts the zipper passage algorithm. If the zipper passage algorithm is adopted, proceed to step L3; otherwise, pass through the intersection normally.

[0080] L3. The zipper passage algorithm is used to predict the passage priority state vector of the unmanned truck sequence and output the passage priority state vector data information of the unmanned truck sequence;

[0081] L4. Based on the passage priority state vector data information of the unmanned truck sequence, establish the priority passage index function of the unmanned truck sequence to obtain the passage priority data information of the unmanned truck sequence.

[0082] like Figure 2 As shown, this invention provides a zipper-style traffic scheduling system for unmanned container trucks at ports, the system comprising:

[0083] The TOS system is a port terminal task planning and allocation system. It is a computer management system used to manage and control all aspects of terminal operations, and issues tasks for cargo ship berthing, loading and unloading, and container transportation loading and unloading.

[0084] The TMC simulation system is an information system for unmanned container trucks in ports. It is a system that displays tasks, statuses, maps, and resources, and integrates command, dispatch, remote control, simulation, operation and maintenance monitoring, fault handling, big data analysis, and network security strategy settings.

[0085] The unmanned container truck is a horizontal transport device for ports that is not driven by human. The mobile communication gateway mounted on the unmanned container truck, together with the automatic driving controller, completes the reception of the passage instructions issued by the TMC simulation system.

[0086] In this embodiment, the TMC simulation system is communicatively connected to the TOS system and is used to receive task information lines and map information of each vehicle in the unmanned truck cluster issued by the TOS system.

[0087] In this embodiment, the system also includes a 4G / 5G mobile communication network module, which is used to provide wireless communication networks for each component of the system.

[0088] The present invention provides a computer-readable storage medium storing a computer program programmed or configured to perform any of the described zipper-style traffic scheduling methods for unmanned container trucks at ports.

[0089] Any references to memory, storage, database, or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0090] In summary, this invention not only enables zipper-like passage at intersections, preventing unmanned trucks from causing congestion at intersections, but also improves the collective operational efficiency of unmanned trucks at ports.

[0091] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A zipper-style traffic scheduling method for unmanned container trucks at port intersections, characterized in that, The method includes: L1. Based on the port TOS system, acquire task data information of unmanned truck sequence and map data information of the port. The task data information of the unmanned truck sequence includes the current task execution status, driving status and destination location information. The map data information of the port includes the latitude and longitude data information of the intersection. L2. Based on the task data information of the unmanned truck sequence and the latitude and longitude data information of the intersection, the Euclidean distance algorithm is used to determine whether the unmanned truck sequence adopts the zipper passage algorithm. If the zipper passage algorithm is adopted, proceed to step L3; otherwise, pass through the intersection normally. L3. The zipper passage algorithm is used to predict the passage priority state vector of the unmanned truck sequence and output the passage priority state vector data information of the unmanned truck sequence; L4. Based on the passage priority state vector data information of the unmanned truck sequence, establish the priority passage index function of the unmanned truck sequence to obtain the passage priority data information of the unmanned truck sequence; In step L2, the step of using the Euclidean distance algorithm to determine whether the unmanned truck sequence uses the zipper pass algorithm includes: L21. Based on the latitude and longitude data of the intersection and the task data of the unmanned truck sequence, establish a function to measure the distance of the unmanned truck from the intersection. , , Among them, (Jlat) ks Jlog ks ) represents the latitude and longitude data of the s-th intersection of routes k and k+r, (Vlat) ks Vlog ks () represents the location information of the k-th unmanned truck as it passes through the s-th intersection; L22. A function based on the distance of the unmanned truck to the intersection. The minimum distance function F is obtained. ， Where m is the number of unmanned truck sequences and n is the number of intersections; L23. Set a preset threshold. If the value of the minimum distance function F is less than the preset threshold, the zipper passage algorithm is used. If the value of the minimum distance function F is greater than the preset threshold, the zipper passage algorithm is not used. In step L3, the prediction of the passage priority state vector of the unmanned truck sequence using the zipper passage algorithm includes: L31. Based on the task data information of the unmanned truck sequence and the latitude and longitude data information of the intersection, the state vector of the i-th unmanned truck passing through the k-th intersection is obtained as follows: The state vector of the (i+p)th unmanned truck passing through the kth intersection is ; L32. Based on the state vectors of the i-th unmanned truck passing through the k-th intersection and the (i+p)-th unmanned truck passing through the k-th intersection, a comparison function is established using a 0-1 algorithm: ， ， ， Thus, the passage priority state vector data information of the i-th unmanned truck is obtained as follows: ， in, Let be the number of vehicles queuing behind the i-th unmanned truck. Let be the number of vehicles queuing in front of the i-th unmanned truck. Let be the distance between the i-th unmanned truck and its destination. Let be the speed of the i-th unmanned truck. Let i be the container priority of the i-th unmanned truck. Let represent the number of times the i-th unmanned truck yields to other vehicles.

2. The zipper-style traffic scheduling method for unmanned container trucks at ports, as described in claim 1, is characterized in that... In step L4, the priority passage exponential function for establishing the unmanned truck sequence is: , , ， in, Let be the number of vehicles queuing behind the i-th unmanned truck. Let be the number of vehicles queuing in front of the i-th unmanned truck. Let be the distance between the i-th unmanned truck and its destination. Let be the speed of the i-th unmanned truck. Let i be the container priority of the i-th unmanned truck. Let α1, α2, α3, α4, α5 and α6 be the number of times the i-th unmanned truck yields, and let α1, α2, α3, α4, α5 and α6 be the weighting coefficients.

3. The zipper-style traffic scheduling method for unmanned container trucks at ports, as described in claim 2, is characterized in that... The constraints on the weighting coefficients α1, α2, α3, α4, α5, and α6 are as follows: 。 4. The zipper-style traffic scheduling method for unmanned container trucks at ports, as described in claim 1, is characterized in that... The method further includes: L5. Based on the passage priority data of the unmanned truck sequence, the number of times the unmanned truck sequence passes through the intersection is recorded. Steps L1-L4 are repeated to schedule the unmanned truck sequence.

5. A zipper-style traffic dispatching system for unmanned container trucks at ports, characterized in that, The system is used to implement the zipper-style traffic scheduling method for unmanned container trucks at ports as described in any one of claims 1-4, the system comprising: The TOS system is a port terminal task planning and allocation system. It is a computer management system used to manage and control all aspects of terminal operations, and issues tasks for cargo ship berthing, loading and unloading, and container transportation loading and unloading. The TMC simulation system is an information system for unmanned container trucks in ports. It is a system that displays tasks, statuses, maps, and resources, and integrates command, dispatch, remote control, simulation, operation and maintenance monitoring, fault handling, big data analysis, and network security strategy settings. The unmanned container truck is a horizontal transport device for ports that is not driven by human. The mobile communication gateway mounted on the unmanned container truck, together with the automatic driving controller, completes the reception of the passage instructions issued by the TMC simulation system.

6. The zipper-style traffic dispatching system for unmanned container trucks in ports according to claim 5, characterized in that: The TMC simulation system is communicatively connected to the TOS system and is used to receive task information lines and map information of each vehicle in the unmanned truck cluster issued by the TOS system.

7. The zipper-style traffic dispatching system for unmanned container trucks at ports according to claim 5, characterized in that: The system also includes a 4G / 5G mobile communication network module, which is used to provide wireless communication networks for each component of the system.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is programmed or configured to perform the zipper-style traffic scheduling method for unmanned container trucks at ports as described in any one of claims 1 to 4.

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