Port manned container truck and unmanned container truck intersection mixed scheduling method and system

Abstract

The invention relates to a port manned container truck and unmanned container truck intersection mixed traffic scheduling method and system, and the method comprises the steps: U1, obtaining the data information of the current state of a vehicle in real time in the port operation process; and U2, on the basis of the data information of the current state of the vehicle, identifying the vehicle with the path point in the conflict control area in a preset distance range, entering the step U3 if the number of the identified vehicles is greater than or equal to 2, and normally passing through the conflict control area if the number of the identified vehicles is less than 2. According to the method, the existing informatization infrastructure of a port is fully utilized, V2V equipment does not need to be additionally arranged for a manned container truck, a roadside V2X unit does not need to be built, hardware investment and engineering deployment cost are greatly reduced, potential conflicts can be found earlier and more comprehensively, emergency situations are avoided by controlling ACT in advance, and the method is suitable for popularization and application. And the safety is higher than that of a scheme only depending on bicycle sensing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart port logistics transportation, and in particular to a method and system for mixed driving of manned trucks and unmanned trucks at a port intersection. BACKGROUND

[0002] With the wide application of automation and intelligent technology in ports, unmanned trucks (ACT) have been put into actual operation. However, in a complex port operation environment, ACT usually needs to be mixed with a large number of traditional manned trucks (MCT) for operation. In particular, in the intersection area, the traffic flow is interwoven, and there are many conflict points, which is the bottleneck of safety and efficiency.

[0003] The current common solution mainly relies on two types of technology: one is to rely on the sensing system (such as laser radar, camera) of the unmanned truck itself for local obstacle avoidance, but when facing irregularly driving manned trucks, the sensing has blind spots and misjudgment risks, which often leads to the ACT taking a too conservative emergency stop strategy, seriously affecting the smoothness of operation; the other is to rely on vehicle-road cooperation technology, which realizes information interaction and cooperation by deploying V2X (vehicle-road cooperation) devices on the roadside and adding V2V (vehicle-to-vehicle communication) terminals to manned trucks. However, this solution has high hardware modification and deployment cost, and the maintenance is complex, which is difficult to popularize quickly in existing ports. SUMMARY

[0004] In view of the above problems, the present application provides a method and system for mixed driving of manned trucks and unmanned trucks at a port intersection, which not only makes full use of the existing information infrastructure of the port, does not need to add V2V devices to manned trucks, and does not need to build roadside V2X units, greatly reducing the hardware investment and engineering deployment cost, but also can discover potential conflicts earlier and more comprehensively, and avoid emergencies by controlling ACT in advance, which is safer than relying on single vehicle sensing.

[0005] To achieve the above object and other related objects, the technical solution provided by the present application is as follows: A method for mixed driving of manned trucks and unmanned trucks at a port intersection, the method comprising: U1. During the port operation, real-time acquisition of data information of the current state of the vehicle; U2. Based on the data information of the current state of the vehicle, if the number of vehicles identified within a preset distance range and located in the conflict control area is greater than or equal to two, step U3 is entered, otherwise the vehicle normally passes through the conflict control area; U3. Based on the data information of the current state of the vehicle located in the conflict control area within the preset distance range, a vehicle conflict detection model based on safety margin is used to detect whether there is a conflict on the predicted path of each vehicle, and the detection data information of each vehicle on the predicted path is obtained. U4. Based on the detected data information of the vehicle on the predicted path, a conflict is detected, the system immediately calculates a safe intervention point, and issues a "slow down" or "stop and wait" instruction to the relevant ACT in advance outside the safe distance before the conflict occurs.

[0006] Further, in step U3, the detection of whether there is a conflict for each vehicle on the predicted path based on the vehicle conflict detection model based on the safety margin includes: U31. Based on the data information of the current state of the vehicle whose path point within the preset distance range is located in the conflict control area, the overall length L and the side width M of the vehicle are obtained; U32. Based on the overall length L and the side width M of the vehicle, the safety margin parameter L safe and W safe , , ; U33. According to the safety margin parameter L safe and W safe of the vehicle, the conflict detection function Z ij of the vehicle is established , , where (x ik , y ik , θ ik ) is the kth point mass center coordinate of vehicle i, K j is a safety weight matrix, j=1,2,3 and 4, and the detection of whether there is a conflict for each vehicle on the predicted path is performed to obtain the detected data information of each vehicle on the predicted path.

[0007] Further, the safety weight matrix K1 is , the safety weight matrix K2 is , where L is the overall length of the vehicle, M is the side width, L safe and W safe are the safety margin parameters of the vehicle.

[0008] Further, the safety weight matrix K3 is , the safety weight matrix K4 is , Wherein, L is the length of the vehicle, M is the side width, L safe and W safe are the safety margin parameters of the vehicle.

[0009] Further, the data information of the current state of the vehicle includes data information of the position of the vehicle, a predicted path point, data information of the speed of the vehicle, and data information of the driving direction.

[0010] Further, the method further comprises: Conflict resolution and recovery, the VMS continuously monitors the dynamics of the conflict vehicle, and when the system determines that the conflict vehicle has safely passed through the conflict area or the risk has been eliminated, immediately issues a "resume driving" instruction to the waiting ACT to make it start smoothly and continue to perform the task.

[0011] Further, the preset distance is δ, δ=βv, wherein β is a conflict risk coefficient, and v is the driving speed of the vehicle.

[0012] In order to achieve the above object and other related objects, the present application also provides a system for mixed driving scheduling of manned trucks and unmanned trucks at a port, which is used to realize the method for mixed driving scheduling of manned trucks and unmanned trucks at a port, and the system comprises: A central platform for the existing vehicle monitoring system of the port as a core scheduling center; An unmanned truck for reporting its high-precision positioning information, real-time speed, driving direction, preset path and navigation state to the VMS in real time through the existing vehicle-cloud communication network; A manned truck for reporting its basic state information of position, speed and heading to the VMS through the already equipped vehicle-mounted Beidou / GPS terminal and vehicle-mounted communication unit without the need to install any additional communication or sensing equipment; The scheduling model takes each intersection as the center to virtually establish a "conflict warning area", and the system performs real-time tracking and prediction on all MCTs and ACTs entering the area, specifically including: Trajectory prediction, based on the current position, speed, heading of the vehicle and the intersection topology, the driving trajectory of the vehicle in a future period of time is predicted in real time, wherein the trajectory prediction of the unmanned truck is based on the local path point output by the vehicle control, and the trajectory prediction of the manned truck is based on the vehicle speed to generate a βv meter prediction path point; Space-time conflict detection, the intersection of the predicted trajectories of different vehicles in time and space is calculated, and when it is predicted that two or more vehicles will arrive at the same conflict point at the intersection at a similar time, it is determined that there is a conflict risk.

[0013] Further, the system further comprises a decision principle, and the principle of "ensuring safety, efficiency first" is adopted, and when a conflict is detected, the system defaults the unmanned truck as the controlled object.

[0014] Further, the system also includes early intervention, once the conflict is predicted, the system will immediately calculate the safe intervention point, and issue "slow down" or "stop and wait" instructions to the relevant ACT in advance outside the safe distance before the conflict occurs; The control instruction is issued through the vehicle cloud communication network to the vehicle-mounted control system of the target ACT; Conflict resolution and recovery, VMS continuously monitors the dynamics of the conflict vehicle; When the system judges that the conflict vehicle has safely passed through the conflict area, or the risk has been eliminated, immediately issue "resume driving" instructions to the waiting ACT, so that it starts smoothly and continues to perform the task.

[0015] The present application has the following positive effects: 1. The present application makes full use of the existing information infrastructure of the port, without the need to add V2V equipment to manned trucks, and without the need to build roadside V2X units, greatly reducing the hardware investment and engineering deployment cost.

[0016] 2. The present application can detect potential conflicts earlier and more comprehensively through centralized prediction from the "God's perspective", and avoid emergencies through early control of ACT, with higher safety than solutions that rely only on single vehicle perception.

[0017] 3. The present application is essentially a software function upgrade based on the existing VMS platform, with short implementation period, no interference with the normal operation of existing vehicles, and can be quickly deployed and applied in the port.

[0018] 4. The present application reduces the sudden braking and long-term stagnation of ACT at the intersection through smooth and predictive control, ensuring the orderliness of mixed vehicle traffic and improving the overall logistics turnover efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a method flowchart of the present application; Figure 2 is a working flowchart of the vehicle conflict detection model based on safety margin of the present application; Figure 3 is a schematic diagram of the intersection control area of the present application; Figure 4 is a schematic diagram of the vehicle conflict detection model based on safety margin of the present application. DETAILED DESCRIPTION

[0020] Exemplary embodiments of the present disclosure are described herein below with reference to the accompanying drawings, in which various specific details are set forth to assist in understanding the present disclosure. It should be understood, however, that various changes and modifications can be made to the embodiments described herein, without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted for clarity and conciseness.

[0021] Embodiment 1: As shown in Figure 1 or Figure 3 , a method for scheduling mixed driving of manned trucks and unmanned trucks at a port intersection, the method comprising: U1. During port operation, real-time data information of the current state of a vehicle is obtained; U2. Based on the data information of the current state of the vehicle, if the number of vehicles identified within a preset distance range and located in a conflict control area is greater than or equal to two, step U3 is entered, otherwise the vehicle normally passes through the conflict control area; U3. Based on the data information of the current state of the vehicle located in the conflict control area within the preset distance range, a vehicle conflict detection model based on safety margin is used to detect whether there is a conflict on the predicted path of each vehicle, and data information of the detection on the predicted path of each vehicle is obtained; U4. Based on the data information of the detection on the predicted path of the vehicle, if a conflict is detected, the system will immediately calculate a safe intervention point and issue a "slow down" or "stop and wait" instruction to the relevant ACT in advance outside the safe distance before the conflict occurs.

[0022] In this embodiment, as shown in Figure 2 or Figure 4 , in step U3, the detection of whether there is a conflict on the predicted path of each vehicle using the vehicle conflict detection model based on safety margin comprises: U31. Based on the data information of the current state of the vehicle located in the conflict control area within the preset distance range, the overall length L and the side width M of the vehicle are obtained; U32. Based on the overall length L and the side width M of the vehicle, the safety margin parameters L safe and W safe of the vehicle are obtained; , ; U33. According to the safety margin parameters L safe and W safe of the vehicle, a conflict detection function Z ij of the vehicle is established; , , wherein (x ik ,y ik ,θ ik ) is the kth point mass center coordinate of the vehicle i, K j is a safety weight matrix, j = 1, 2, 3 and 4, and whether there is a conflict on the predicted path of each vehicle is detected to obtain the detected data information of each vehicle on the predicted path.

[0023] In the embodiment, the safety weight matrix K1 is, , the safety weight matrix K2 is, , wherein L is the overall length of the vehicle, M is the side width, L safe and W safe are safety margin parameters of the vehicle.

[0024] In the embodiment, the safety weight matrix K3 is, , the safety weight matrix K4 is, , wherein L is the overall length of the vehicle, M is the side width, L safe and W safe are safety margin parameters of the vehicle.

[0025] In the embodiment, the data information of the current state of the vehicle includes the position of the vehicle, the data information of the predicted path point, the data information of the speed of the vehicle and the data information of the driving direction.

[0026] In the embodiment, the method further comprises: Conflict resolution and recovery, the VMS continuously monitors the dynamics of the conflict vehicle, and when the system judges that the conflict vehicle has safely passed the conflict area or the risk has been eliminated, immediately issues a "resume driving" instruction to the waiting ACT to make it start smoothly and continue to perform the task.

[0027] In the embodiment, the preset distance is δ, δ = βv, wherein β is a conflict risk coefficient and v is the driving speed of the vehicle.

[0028] Embodiment 2: On the basis of the method for scheduling mixed driving of manned and unmanned container trucks at a port intersection in embodiment 1, the present application is further described and explained.

[0029] As Figure 1 or Figure 3As shown, a method for scheduling mixed driving of manned trucks and unmanned trucks at a port intersection, the method comprising: U1. During port operation, real-time data information of the current state of the vehicle is obtained; U2. Based on the data information of the current state of the vehicle, if the number of vehicles identified in the conflict control area within the preset distance range is greater than or equal to two, step U3 is entered, otherwise the vehicle normally passes through the conflict control area; U3. Based on the data information of the current state of the vehicle in the conflict control area within the preset distance range, a safety margin-based vehicle conflict detection model is used to detect whether there is a conflict on the predicted path of each vehicle, and the detection data information of each vehicle on the predicted path is obtained. U4. Based on the detection data information of the vehicle on the predicted path, if a conflict is detected, the system will immediately calculate a safe intervention point and issue a "slow down" or "stop and wait" instruction to the relevant ACT in advance outside the safe distance before the conflict occurs.

[0030] In this embodiment, the present application provides a system for scheduling mixed driving of manned trucks and unmanned trucks at a port intersection, which is used to realize the method for scheduling mixed driving of manned trucks and unmanned trucks at a port intersection, and the system comprises: A central platform for the existing vehicle monitoring system in the port as the core scheduling center; An unmanned truck for reporting its high-precision positioning information, real-time speed, driving direction, preset path and navigation state to the VMS in real time through the existing vehicle-cloud communication network; A manned truck for reporting its position, speed and heading basic state information to the VMS through the onboard Beidou / GPS terminal and vehicle communication unit it has been equipped with, without the need to install any additional communication or sensing equipment; The scheduling model takes each intersection as the center and virtually establishes a "conflict warning area", and the system tracks and predicts all MCTs and ACTs entering this area in real time, specifically including: Trajectory prediction, based on the current position, speed, heading of the vehicle and the intersection topology, the driving trajectory of the vehicle in the future is predicted in real time, wherein the trajectory prediction of the unmanned truck is based on the local path point output by the vehicle control, and the trajectory prediction of the manned truck is based on the vehicle speed to generate a βv meter prediction path point; Space-time conflict detection, the intersection of the predicted trajectories of different vehicles in time and space is calculated, and when it is predicted that two or more vehicles will arrive at the same conflict point at the intersection at a similar time, it is determined that there is a conflict risk.

[0031] In the embodiment, the system further comprises a decision principle, and the principle of "ensuring safety and giving priority to efficiency" is adopted, and when a conflict is detected, the system defaults to taking the unmanned container truck as a controlled object.

[0032] In the embodiment, the system further comprises early intervention, and once a conflict is predicted, the system immediately calculates a safe intervention point, and issues a "slow down" or "stop and wait" instruction to the relevant ACT at a safe distance before the conflict occurs; the instruction is issued, and the control instruction is issued to the vehicle-mounted control system of the target ACT through the vehicle cloud communication network; conflict resolution and recovery, the VMS continuously monitors the dynamics of the conflict vehicle; when the system determines that the conflict vehicle has safely passed through the conflict area or the risk has been eliminated, a "resume driving" instruction is immediately issued to the waiting ACT to make it start smoothly and continue to perform the task.

[0033] In the embodiment, the application provides a computer readable storage medium, and the computer readable storage medium stores a computer program programmed or configured to perform the method for scheduling the intersection of the manned container truck and the unmanned container truck.

[0034] Any reference to memory, storage, databases, or other media in the embodiments provided herein can include non-volatile and / or volatile storage. Non-volatile storage can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile storage can include random access memory (RAM), or external cache memory. By way of illustration, and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus DRAM (RDRAM), direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM).

[0035] In summary, the application not only makes full use of the existing information infrastructure of the port, but also does not need to add V2V equipment to the manned container truck or build roadside V2X units, greatly reducing the hardware investment and engineering deployment cost, and can detect potential conflicts earlier and more comprehensively, and avoid emergency situations by controlling the ACT in advance, which is safer than a solution that only relies on single vehicle perception.

[0036] The above detailed description does not limit the scope of the disclosure. Various modifications, combinations, sub-combinations and alternatives can be made to the detailed description. Any modification, equivalent replacement and improvement etc. made within the spirit and principle of the disclosure shall be included in the scope of the disclosure.

Claims

1. A method for scheduling manned and unmanned trucks at intersections in ports, characterized in that, The method includes: U1. During port operations, real-time data on the current status of vehicles is acquired; U2. Based on the data information of the current status of the vehicle, identify vehicles whose path points are located within the conflict control zone within a preset distance range, and if the number of identified vehicles is greater than or equal to two, proceed to step U3; otherwise, pass through the conflict control zone normally. U3. Based on the data information of the current status of vehicles located within the conflict control zone at the path points within the preset distance range, a vehicle conflict detection model based on safety margin is used to detect whether there is a conflict on the predicted path for each vehicle, and the data information of the detection of each vehicle on the predicted path is obtained. U4. Based on the data information detected by the vehicle on the predicted path, if a conflict is detected, the system will immediately calculate the safety intervention point and issue a "decelerate" or "stop and wait" command to the relevant ACT in advance, at a safe distance before the conflict occurs.

2. The method for scheduling manned and unmanned trucks at port intersections according to claim 1, characterized in that, In step U3, the step of using a vehicle conflict detection model based on safety margin to detect whether there is a conflict for each vehicle on the predicted path includes: U31. Based on the data information of the current status of vehicles located within the conflict control zone at the path points within the preset distance range, obtain the overall length L and side width M of the vehicle; U32. Based on the vehicle's overall length L and side width M, obtain the vehicle's safety margin parameter L. safe and W safe , ， ； U33. Based on the vehicle's safety margin parameter L safe and W safe Establish the vehicle collision detection function Z. ij , ， ， Among them, (x ik ,y ik ,θ ik Let K be the centroid coordinate of the k-th point of vehicle i. j The safety weight matrix is ​​set to j=1,2,3 and4. The system detects whether there is a conflict for each vehicle on the predicted path, and obtains the detection data information of each vehicle on the predicted path.

3. The method for scheduling manned and unmanned trucks at port intersections according to claim 2, characterized in that: The security weight matrix K1 is, ， The security weight matrix K2 is, ， Where L is the overall length of the vehicle, M is the side width, and L safe and W safe These are the safety margin parameters for the vehicle.

4. The method for scheduling manned and unmanned trucks at port intersections according to claim 2, characterized in that: The security weight matrix K3 is, ， The security weight matrix K4 is, ， Where L is the overall length of the vehicle, M is the side width, and L safe and W safe These are the safety margin parameters for the vehicle.

5. The method for scheduling manned and unmanned trucks at port intersections according to claim 1, characterized in that: The data information of the vehicle's current status includes the vehicle's position, predicted path points, speed, and direction of travel.

6. The method for scheduling manned and unmanned trucks at port intersections according to claim 1, characterized in that, The method further includes: In the conflict resolution and recovery process, VMS continuously monitors the dynamics of the conflicting vehicles. When the system determines that the conflicting vehicles have safely passed through the conflict area or the risk has been eliminated, it immediately issues a "resume driving" command to the waiting ACT, enabling it to start smoothly and continue to perform its mission.

7. The method for scheduling manned and unmanned trucks at port intersections according to claim 1, characterized in that: The preset distance is δ, where δ = βv, β is the conflict risk coefficient, and v is the vehicle speed.

8. A system for coordinating manned and unmanned truck traffic at port intersections, characterized in that, The system is used to implement the method for scheduling mixed traffic of manned and unmanned trucks at port intersections as described in any one of claims 1-7, the system comprising: The central platform will be used for the port's existing vehicle monitoring system, serving as the core dispatch hub. Unmanned trucks are used to report their high-precision positioning information, real-time speed, driving direction, preset route and navigation status to VMS in real time through the existing vehicle cloud communication network. Manned trucks can report their basic status information, such as location, speed, and heading, to the VMS through their onboard Beidou / GPS terminals and onboard communication units, without the need to install any additional communication or sensing equipment. The scheduling model establishes a virtual "conflict warning zone" centered on each intersection. The system tracks and predicts all MCTs and ACTs entering this zone in real time, specifically including: Trajectory prediction, based on the vehicle's current position, speed, heading and intersection topology, predicts its driving trajectory in real time over a period of time. For unmanned trucks, trajectory prediction is based on local travel points output by vehicle control, while for manned trucks, βv meters are generated based on vehicle speed to predict path points. Spatiotemporal conflict detection calculates the intersection of the predicted trajectories of different vehicles in time and space. When it is predicted that two or more vehicles will arrive at the same conflict point at the intersection at similar times, it is determined that there is a risk of conflict.

9. The system for scheduling manned and unmanned trucks at port intersections according to claim 8, characterized in that, The system also includes decision-making principles, which adopt the principle of "ensuring safety and prioritizing efficiency". When a conflict is detected, the system defaults to treating the unmanned truck as the controlled object.

10. The port intersection scheduling system for both manned and unmanned trucks according to claim 8, characterized in that, The system also includes advance intervention. Once a conflict is predicted, the system will immediately calculate the safe intervention point and issue a "decelerate" or "stop and wait" command to the relevant ACT at a safe distance before the conflict occurs. The command is issued by sending the control command to the vehicle control system of the target ACT through the vehicle-cloud communication network. In the process of resolving and resuming conflict, VMS continuously monitors the dynamics of the conflicting vehicles. When the system determines that the conflicting vehicles have safely passed through the conflict area or the risk has been eliminated, it immediately issues a "resume driving" command to the waiting ACT, enabling it to start smoothly and continue to perform its mission.

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