A high-density parking lot scheduling method based on multi-directional mobile RGV

Abstract

The present invention relates to a high-density parking lot scheduling method based on multi-directional mobile RGV, which belongs to the field of three-dimensional parking. The method includes the following steps: when there is a parking or retrieval task and there are idle RGVs, the location and number of entrances and exits are determined according to the dynamic entrance and exit strategy; then, according to the high-density parking lot task scheduling method, the priority, allocation plan and target position of the task are determined; then, according to the high-density parking lot traffic control strategy, collision avoidance is performed, and when the RGV arrives at the parking / retrieval parking space, the parking or retrieval action is completed according to the parking / retrieval rules; finally, when the RGV completes the task, the idle RGV scheduling is completed according to the idle RGV scheduling rules. This method solves the problems of low space utilization and low handling efficiency in the prior art in the process of transport vehicle scheduling using single-directional mobile RGVs, and provides a set of high-efficiency scheduling solutions for high-density parking lots based on multi-directional mobile RGVs.

Description

Technical Field

[0001] The present invention relates to the field of three-dimensional parking, and in particular to a high-density parking lot scheduling method based on multi-directional mobile RGV. Background Art

[0002] Automated valet parking technology is an advanced smart parking solution that allows self-driving vehicles to automatically enter and park in parking lots without a human behind the wheel. When the vehicle user needs to retrieve their vehicle, they simply issue a command via their phone or other device, and the vehicle will automatically exit the parking lot. Because these vehicles are driverless and interconnected, automated valet parking systems can adapt to different parking strategies to improve the overall utilization efficiency of parking lots. To improve the space utilization of automated valet parking lots, research has proposed an end-to-end arrangement of vehicles, known as high-density parking lots. RGVs in high-density parking lots are primarily used to transport vehicles to parking spaces. However, existing technologies only allow RGVs to move in one direction, requiring a horizontally movable or rotating platform in a multi-story parking garage to enable lateral movement. However, the deployment of horizontally movable or rotating platforms increases the risk of equipment failure, increases operating costs, and reduces space utilization. Furthermore, high-density parking lot layouts can cause some vehicles to be blocked by other parked vehicles when exiting, reducing parking efficiency and user experience.

[0003] In summary, while high-density parking scheduling can improve parking utilization, it can also reduce time efficiency. However, a review of existing literature on parking scheduling reveals limited research on this issue. This research primarily focuses on parking scheduling using a single-position mobile RGV, such as the Chinese invention patent publication number CN116703260A. However, there is currently no research on high-density parking scheduling using multi-position mobile RGVs. Summary of the Invention

[0004] In order to solve the technical defects existing in the prior art, the present invention proposes a high-density parking lot scheduling method based on multi-directional mobile RGV. By utilizing the multi-directional mobile RGV transport vehicle, the problems of low space utilization and low transport efficiency existing in the scheduling process of using single-directional mobile RGV transport vehicles in the prior art are solved, and a set of high-efficiency scheduling solutions is provided for high-density parking lots based on multi-directional mobile RGV.

[0005] The present invention is achieved through the following technical solutions:

[0006] A high-density parking lot scheduling method based on multi-directional mobile RGVs includes the following steps:

[0007] Step 1: Determine whether the high-density parking lot scheduling system meets the task triggering conditions. If so, obtain the task information in the system and proceed to step 2. Otherwise, loop judgment;

[0008] Step 2: Determine whether the system has a parking task or a pick-up task. If yes, proceed to step 3; otherwise, proceed to step 1.

[0009] Step 3: Determine whether the system has idle RGVs; if yes, proceed to step 4, otherwise proceed to step 1;

[0010] Step 4: Determine the number and location of parking lot entrances and exits based on the dynamic entrance and exit strategy of the high-density parking lot scheduling system;

[0011] Step 5: According to the high-density parking lot task scheduling method, the task priority, allocation plan and target location are determined, and then the RGV starts to execute the task along the shortest path;

[0012] Step 6: Determine whether RGV has a conflict during task execution. If so, proceed to step 7; otherwise, proceed to step 8.

[0013] Step 7: Perform collision avoidance according to the high-density parking lot traffic control strategy;

[0014] Step 8: Determine whether the RGV has arrived at the parking space corresponding to the parking / retrieval vehicle. If so, proceed to step 9. Otherwise, the RGV continues to perform the task and proceeds to step 6.

[0015] Step 9: According to the parking / retrieval rules, RGV completes the parking or retrieval action;

[0016] Step 10: Determine whether RGV has completed the task. If so, update the system status and go to step 11. Otherwise, RGV continues to execute the task and go to step 6.

[0017] Step 11: Determine whether RGV has unfinished tasks. If RGV continues to execute tasks, go to step 6; otherwise, go to step 12.

[0018] Step 12: According to the idle RGV scheduling rule, complete the idle RGV scheduling, update the system status, and go to step 1.

[0019] Furthermore, the high-density parking lot is a three-dimensional parking lot in which vehicles are arranged end to end.

[0020] Furthermore, the task allocation triggering conditions include periodic triggering and event triggering.

[0021] Furthermore, the task information in the system includes the type of task, the transported vehicle corresponding to the task, the starting point of the task, the task generation time and deadline, and the environment surrounding the transported vehicle corresponding to the task.

[0022] Furthermore, the parking task is to use RGV to move the vehicle from the entrance of the parking lot to a suitable parking space for storage according to customer needs.

[0023] Furthermore, the vehicle pickup task is to use RGV to move the vehicle from the parking space in the parking lot to the selected exit according to the customer's needs, so as to complete the customer's vehicle pickup task.

[0024] Furthermore, the idle RGV is an RGV in the system that has completed the previous round of tasks and has not been assigned a new task.

[0025] Furthermore, the dynamic entrance and exit strategy of the high-density parking lot scheduling system includes the following steps:

[0026] Step 1.1: Collect real-time traffic data at the entrances and exits of high-density parking lots and analyze the usage of the entrances and exits;

[0027] Step 1.2: Determine whether the number of entrances and exits needs to be adjusted. If so, proceed to step 1.3; otherwise, terminate the adjustment.

[0028] Step 1.3: Determine whether the number of inlets and outlets has reached the limit. If so, end the adjustment. Otherwise, proceed to step 1.4.

[0029] Step 1.4: Determine the number of entrances and exits based on real-time traffic information rules;

[0030] Step 1.5: Use traffic simulation software to simulate the new entrance and exit locations, determine the optimal entrance and exit layout, and complete this adjustment.

[0031] Furthermore, the real-time traffic data is information such as vehicle inflow and outflow flow, speed, and detention time at the entrance / exit within a specific time period.

[0032] Furthermore, the specific time period is a time period consisting of a period in the past, present and future.

[0033] Furthermore, the extreme value is the case where the parking lot contains one entrance or exit.

[0034] Furthermore, the real-time traffic information rule is to calculate the vehicle inflow and outflow of the parking lot within a specific time period respectively. When the vehicle inflow is greater than the vehicle exit flow, the number of parking lot exits = max{floor(vehicle exit flow / vehicle inflow and outflow), 1}, and the number of parking lot entrances = the total number of parking lot exits / entrances - the number of parking lot exits, where floor(*) is a rounding-down function; when the vehicle inflow is less than or equal to the vehicle exit flow, the number of parking lot entrances = max{floor(vehicle entrance flow / vehicle inflow and outflow), 1}, and the number of parking lot exits = the total number of parking lot exits / entrances - the number of parking lot entrances.

[0035] Furthermore, the traffic simulation software is a computer application used to simulate and analyze traffic flow and traffic system performance, including but not limited to Plant Simulation, VISSIM, Synchro, etc.

[0036] Furthermore, the high-density parking lot task scheduling method includes the following steps:

[0037] Step 2.1: Determine the number of idle RGVs based on the real-time status of the high-density parking lot scheduling system;

[0038] Step 2.2: Determine whether the number of idle RGVs is greater than or equal to 1. If so, proceed to step 2.3. Otherwise, obtain the task priority, allocation plan, and target location, and end the task scheduling.

[0039] Step 2.3: Determine whether there is a parking task. If so, proceed to step 2.4; otherwise, proceed to step 2.8.

[0040] Step 2.4: Determine whether there is an available parking space. If so, proceed to step 2.5; otherwise, proceed to step 2.8.

[0041] Step 2.5: Determine whether the number of parking tasks is greater than the number of pickup tasks. If so, proceed to step 2.6; otherwise, proceed to step 2.8.

[0042] Step 2.6: The high-density parking lot scheduling system starts assigning parking tasks to RGVs and determines the priority of parking tasks based on the customer's waiting time T0. The longer the waiting time T0, the higher the priority.

[0043] Step 2.7: Determine the optimal parking space based on the parking space selection rules and proceed to step 2.9;

[0044] Step 2.8: The high-density parking lot scheduling system starts assigning car pickup tasks to RGVs based on the customer's waiting time T a Determine the priority of the vehicle pickup task. The longer the waiting time T0, the higher the priority, and proceed to step 2.9;

[0045] Step 2.9: Select the best RGVG from all idle RGVs based on the nearest and load balancing ratio rules RGV , the highest priority task G task Assigned to G RGV ;

[0046] Step 2.10: Based on the allocation plan and waiting time calculation method, estimate the customer's waiting time T Y ;

[0047] Step 2.11: Determine the waiting time T Y Is it equal to or greater than the threshold? If so, go to step 2.14; otherwise, go to step 2.12;

[0048] Step 2.12: Determine the highest priority task G based on the task binding method task Binding tasks;

[0049] Step 2.13: Determine G task Is the bound task of G not empty? If so, task The binding task is also assigned to G RGV , go to step 2.14, otherwise go directly to step 2.14;

[0050] Step 2.14: Update the high-density parking lot scheduling system task information, reduce the number of idle RGVs by 1, and go to step 2.2.

[0051] Furthermore, the real-time status of the high-density parking lot scheduling system includes the parking lot occupancy status, RGV information, task information, user information, and environmental information.

[0052] Furthermore, the calculation formula for the customer's waiting time T0 is:

[0053] T0=|tt in | (7) Where t is the system time at this moment, t in The time when the customer arrives at the parking or pick-up point.

[0054] Furthermore, the parking space selection rule includes the following steps:

[0055] Step 3.1: Determine the number N and location of vacant parking spaces based on the real-time status of the high-density parking lot scheduling system;

[0056] Step 3.2: Travel time T1 to the i-th (i=1, ..., N) free parking space i The calculation formula is

[0057]

[0058] Among them, S i is the horizontal distance between the i-th free parking space and the parking spot, v is the average speed of the fully loaded RGV, d i is the number of times the RGV lifts a vehicle between the i-th free parking space and the parking spot, t d The time required for RGV to lift the vehicle each time, u i is the number of times the RGV puts down the vehicle between the i-th free parking space and the parking spot, t u S is the time required for RGV to put down the vehicle each time. Li is the vertical distance between the i-th free parking space and the parking spot, v l is the average speed of the elevator at full load, j is the number of the vehicle blocking the i-th free parking space, M i is the total number of vehicles blocking the i-th free parking space, Di j is the time required to move the jth blocked vehicle in front of the i-th free parking space to the free position, t wi is the congestion time of the RGV during the transportation process between the i-th free parking space and the parking point.

[0059] Step 3.3: Select travel time T1 from all available parking spaces i The minimum parking space is considered as the optimal parking space.

[0060] Furthermore, the congestion time during the RGV transportation process can be obtained by methods including but not limited to a time window method, a machine learning prediction method, a deep learning prediction method or a simulation method.

[0061] Furthermore, the recent and load balancing rate rule includes the following steps:

[0062] Step 4.1: Based on the current positions of all idle RGVs, calculate the current position of each idle RGV in turn to reach G task The travel time required to start the mission The calculation formula is

[0063]

[0064] in, The current position of the rth idle RGV and G task The horizontal distance from the starting point of the task, is the average no-load speed of RGV, The current position of the rth idle RGV and G task The vertical distance from the starting point of the task, is the average no-load speed of the elevator, R is the number of idle RGVs;

[0065] Step 4.2: Calculate the positions of all idle RGVs to reach G task The travel time required to start the mission The shortest travel time T2 min , the calculation formula is

[0066]

[0067] Step 4.3: Determine the minimum travel time T2 min Is the number of corresponding RGVs greater than 1? If so, go to step 4.4. Otherwise, the minimum travel time is T2. min The corresponding RGV is the optimal RGVG RGV , end this selection;

[0068] Step 4.4: From all the minimum travel times T2 min Among the corresponding RGVs, select the RGV with the smallest total load as G RGV , end this selection.

[0069] Furthermore, the task starting point is the parking point (parking lot entrance) in the parking task or the parking space corresponding to the pick-up task.

[0070] Furthermore, the total load includes but is not limited to the total driving time, the total driving distance and the total number of transport vehicles.

[0071] Furthermore, the allocation scheme and waiting time calculation method are as follows: first, G is obtained according to the allocation scheme. task The starting point, end point, priority and G RGV , then the expected customer waiting time T Y for,

[0072]

[0073] Among them, T3 x is the travel time required for RGV to transport the vehicle corresponding to task x from the task starting point to the task end point, is the horizontal distance between the starting point and the end point of task x, d x is the number of times the RGV lifts the vehicle between the starting point and the end point of task x, u x is the number of times the RGV drops off the vehicle between the starting point and the end point of task x, is the vertical distance between the starting point and the end point of task x, M x Dx is the total number of vehicles blocking the front when task x enters / exits the parking space. j is the time required to move the jth blocking vehicle in front to the free position when task x enters / exits the parking space, t wxis the congestion time of RGV in transporting the vehicle corresponding to task x from the task starting point to the task end point, Ω task is the collection of parking tasks and picking up tasks in the system, For Task G task The travel time required for the corresponding vehicle to transport the goods from the starting point to the end point of the task.

[0074] Furthermore, the task end point is the optimal parking space in the parking task or the pick-up point (parking lot exit) in the pick-up task.

[0075] Furthermore, the task binding method includes the following steps:

[0076] Step 5.1: Determine the value assigned to G RGV The highest priority task G task Is it a parking task? If yes, go to step 5.2; otherwise, go to step 5.3.

[0077] Step 5.2: Search all the car pickup tasks in the system and determine whether there is a car pickup task with the task end point G task The starting point of the task, if so, the task of picking up the car that meets the requirements constitutes G task If the bound task set Ψ is met, go to step 5.4, otherwise go to step 5.8;

[0078] Step 5.3: Search all parking tasks in the system and determine whether there is a parking task with the task end point G task The starting point of the task, if so, the parking task that meets the requirements constitutes G task If the bound task set Ψ is met, go to step 5.4, otherwise go to step 5.8;

[0079] Step 5.4: Assume that in G RGV Execute G task Add G before task The bth task in the bound task set Ψ, then G RGV Complete tasks b and G task The travel time required for the two tasks is T4 b The calculation formula is

[0080]

[0081] in, G RGV The travel time required for the current location to reach the starting point of the bth task in the bound task set Ψ, T3 b G RGV The travel time required to transport the vehicle corresponding to the bth task in the bound task set Ψ from the task starting point to the task ending point.

[0082] Step 5.5: In Gtask The bound task set Ψ selects a task that makes T4 b Minimum task b min As G task pending binding tasks;

[0083] Step 5.6: Calculate G RGV Complete Task B min and G task Two tasks, estimated customer waiting time T Y2 for

[0084] T Y2 =T0+min(T4 b ), b∈Ψ (13);

[0085] Step 5.6: Calculate G RGV Complete Task B min and G task Two tasks, estimated customer waiting time T Y2 for

[0086] Step 5.7: Determine the waiting time T Y2 Is it greater than the threshold? If so, go to step 5.8; otherwise, go to step 5.9;

[0087] Step 5.8: G task There is no binding task, so the binding process ends;

[0088] Step 5.9: Setting b min For G task Bind the task and end the binding process.

[0089] Furthermore, the traffic control strategy for high-density parking lots selects appropriate conflict avoidance methods based on the type of conflict. First, an overtaking conflict occurs when an RGV temporarily places an obstructing vehicle in front of a parking space in the RGV's path. First, the RGV observes whether there is a lateral movement route around the obstructing vehicle. If not, the RGV waits until the obstructing vehicle is removed. Second, an opposing conflict occurs when two or more RGVs are traveling toward each other in a narrow passage or specific area, potentially leading to a collision. This requires utilizing QR code positioning and a semaphore mutual exclusion mechanism to avoid collisions in narrow passages or areas where opposing vehicles may be traveling. When an RGV approaches, the semaphore becomes 1, preventing the RGV in the opposite direction from entering, ensuring that only one vehicle can pass. Third, resource competition occurs when multiple RGVs simultaneously require access to the same resources, such as elevators, intersections, charging facilities, and maintenance equipment. The order in which RGVs are used can be determined based on priority rules, including but not limited to task priority, first-come, first-served, and vehicle urgency.

[0090] Furthermore, the parking / retrieval rules state that when an RGV arrives at a target parking space for parking / retrieval, if there is a blocking vehicle in front of the target parking space, the RGV will first move the blocking vehicle to the nearest driving path so that it does not block the target vehicle's entry / exit. Once the target vehicle being transported by the RGV is parked in the target parking space, the blocking vehicle will be moved back to its original position. If the target vehicle being transported by the RGV needs to be retrieved from the target parking space, the RGV will first move the target vehicle to the nearest driving path. If the system is currently in peak parking hours, the blocking vehicles will be moved in their original order to the currently vacant target parking space and adjacent parking spaces, and the system status will be updated. If the system is currently in peak retrieval hours, the RGV will move the blocking vehicles back to their original positions.

[0091] Furthermore, the idle RGV scheduling rule is that when the RGV completes a task, it determines whether the RGV power is lower than a threshold. If it is lower than the threshold, the RGV goes to a suitable charging area for charging; otherwise, the RGV goes to the nearest elevator to find a docking point and wait for the next task assignment.

[0092] Compared with the prior art, the present invention has at least the following beneficial effects or advantages:

[0093] The present invention proposes a high-density parking lot scheduling method based on multi-directional mobile RGV. By utilizing the multi-directional mobile RGV transport vehicle, the problems of low space utilization and low transport efficiency existing in the scheduling process of using single-directional mobile RGV transport vehicles in the prior art are solved, and a set of high-efficiency scheduling solutions is provided for high-density parking lots based on multi-directional mobile RGV. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 Flowchart of the high-density parking lot scheduling method based on multi-directional mobile RGV of the present invention;

[0095] Figure 2 This is a flow chart of the dynamic entrance and exit strategy of the high-density parking lot scheduling system of the present invention;

[0096] Figure 3 Flowchart of the high-density parking lot task scheduling method of the present invention;

[0097] Figure 4 A partial schematic diagram of a high-density parking lot according to the present invention;

[0098] Figure 5 This is a schematic diagram of the multi-directional mobile RGV structure of the present invention. DETAILED DESCRIPTION

[0099] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0100] Since heterogeneous robot systems are relatively complex, the following assumptions are made about the system:

[0101] 1. During the operation of RGV and hoist, the specific acceleration and deceleration process is not considered, only the average speed is considered;

[0102] 2. Failure issues are not considered during the operation of RGV and hoist;

[0103] 3. The system path network is a one-way single lane and does not support overtaking;

[0104] 4. Once RGV starts charging, it will not stop until charging is completed.

[0105] Figure 1 The flowchart of the high-density parking lot scheduling method based on multi-directional mobile RGV of the present invention is as follows:

[0106] Step 1: Determine whether the high-density parking lot scheduling system meets the task triggering conditions. If so, obtain the task information in the system and proceed to step 2. Otherwise, loop judgment;

[0107] When the high-density parking lot scheduling system calls the high-density parking lot scheduling method based on multi-directional mobile RGVs, it first checks whether the task trigger conditions are met. If the task trigger conditions are met, the system obtains task information, including the task type, the corresponding transported vehicle, the task starting point, task generation time and deadline, and the environment surrounding the corresponding transported vehicle, and then proceeds to step 2. If the task trigger conditions are not met, the system needs to repeat the judgment until the task trigger conditions are met.

[0108] In the embodiment of the present invention, the multi-directional mobile RGV is an RGV that can move horizontally and vertically by itself without the need for additional mechanisms. The car is placed on the RGV fork frame. When transporting the car, the fork frame is raised. After the RGV moves to a fixed parking space, the fork frame is lowered and the car is parked in the fixed parking space.

[0109] In the embodiment of the present invention, the high-density parking lot is a three-dimensional parking lot in which vehicles are arranged end to end.

[0110] In an embodiment of the present invention, the task allocation triggering conditions include periodic triggering and event triggering, wherein the periodic triggering is a regular triggering at a fixed time interval, and the event triggering is triggering the scheduling method when a set event occurs. In an embodiment of the present invention, the set event includes the number of tasks in the set of tasks to be assigned reaching a certain value.

[0111] It should be noted that the task allocation trigger condition may also select only periodic triggering or event triggering, and the set event in the event triggering may not be the set event in the embodiment of the present invention. For example, the set event may also be that the RGV completes a task.

[0112] Step 2: Determine whether the system has a parking task or a pick-up task. If yes, proceed to step 3; otherwise, proceed to step 1.

[0113] When the high-density parking lot scheduling system meets the task triggering conditions, it determines whether the system has a parking task or a retrieval task. If the system has a parking task or a retrieval task, it proceeds to step 3. If the system does not have a parking task or a retrieval task, there is no task in the system that requires RGV to carry, so no scheduling is required, and it proceeds to step 1, waiting for the next time the system meets the task triggering conditions.

[0114] In the embodiment of the present invention, the parking task is to use the RGV to move the vehicle from the entrance of the parking lot to a suitable parking space for storage according to the customer's needs.

[0115] In the embodiment of the present invention, the vehicle pickup task is to use the RGV to transport the vehicle from the parking space in the parking lot to the selected exit according to the customer's needs, so as to complete the customer's vehicle pickup task.

[0116] Step 3: Determine whether the system has idle RGVs; if yes, proceed to step 4, otherwise proceed to step 1;

[0117] When the system has a parking task or a pick-up task, the system determines the idle RGVs. If the system has an idle RGV, it proceeds to step 4 and starts scheduling. If the system has no idle RGVs, there is no idle RGV in the system to execute the new task, so there is no need to schedule. It proceeds to step 1 and waits for the next time the system meets the task triggering conditions.

[0118] In the embodiment of the present invention, an idle RGV is an RGV in the system that has completed the previous round of tasks and has not been assigned a new task.

[0119] Step 4: Determine the number and location of parking lot entrances and exits based on the dynamic entrance and exit strategy of the high-density parking lot scheduling system;

[0120] When the system has idle RGVs, it analyzes factors such as the current parking lot's vehicle flow, task distribution, and spatial layout. Based on the dynamic entrance and exit strategy of the high-density parking lot scheduling system, it comprehensively considers various situations and determines the number and specific locations of parking lot entrances and exits that best suit the current situation, in order to improve the efficiency and smoothness of vehicle entry and exit.

[0121] Step 5: According to the high-density parking lot task scheduling method, the task priority, allocation plan and target location are determined, and then the RGV starts to execute the task along the shortest path;

[0122] After determining the number and locations of parking lot entrances and exits, the system prioritizes parking and retrieval tasks based on high-density parking lot task scheduling methods to determine which tasks deserve priority. Simultaneously, a reasonable allocation plan is developed based on the RGV's location, status, and task requirements, assigning tasks to appropriate RGVs. The target location for each task—the specific parking space corresponding to the parking task—is determined. At this point, the task priority, allocation plan, and target location are determined. Finally, the assigned RGV begins executing the task along the planned shortest path to improve task execution efficiency.

[0123] In the embodiment of the present invention, the shortest path is a shortest transport path determined based on a shortest path planning method, and the shortest path planning method includes but is not limited to an A* algorithm, a Floyd algorithm, and a Dijkstra algorithm.

[0124] Step 6: Determine whether RGV has a conflict during task execution. If so, proceed to step 7; otherwise, proceed to step 8.

[0125] When the system: determines the priority, allocation plan and target location of the task according to the high-density parking task scheduling method, the RGV starts to execute the task according to the task allocation plan and the shortest path plan, and determines whether a conflict occurs during the execution of the task. If a conflict occurs, it enters step 7 to avoid collision; if no conflict occurs during the execution of the RGV, it enters step 8.

[0126] Step 7: Perform collision avoidance according to the high-density parking lot traffic control strategy;

[0127] When RGVs encounter conflicts during mission execution, they need to avoid collisions according to the high-density parking lot traffic control strategy.

[0128] In an embodiment of the present invention, the traffic control strategy for high-density parking lots selects an appropriate conflict avoidance method based on the type of conflict. First, an overtaking conflict occurs when an RGV temporarily places an obstructing vehicle in front of a parking space in the RGV's path. First, the RGV checks to see if there is a lateral route around the obstructing vehicle. If not, the RGV waits until the obstructing vehicle is removed. Second, an opposing conflict occurs when two or more RGVs are traveling toward each other in a narrow passage or specific area, potentially leading to a collision. In narrow passages or areas where opposing vehicles may be traveling, a collision avoidance method using QR code positioning and a semaphore mutual exclusion mechanism is employed. When an RGV approaches, the semaphore becomes 1, preventing the RGV in the opposite direction from entering, ensuring that only one vehicle can pass. Third, resource competition occurs when multiple RGVs simultaneously require access to the same resources, such as elevators, intersections, charging facilities, and maintenance equipment. The order in which the RGVs are used can be determined based on priority rules, including but not limited to task priority, first-come, first-served, and vehicle urgency.

[0129] It should be noted that the high-density parking lot traffic control strategy only describes common conflict types and proposes corresponding collision avoidance methods for these conflict types. However, other types of conflicts can also be simplified into the above conflict types and resolved using the above methods. For example, path capacity conflicts can be resolved using the opposite conflict method.

[0130] Step 8: Determine whether the RGV has arrived at the parking space corresponding to the parking / retrieval vehicle. If so, proceed to step 9. Otherwise, the RGV continues to perform the task and proceeds to step 6.

[0131] Using sensors and a positioning system, the RGV's position is monitored in real time to determine whether it has reached the designated location next to the parking space for parking or retrieval. If so, the system proceeds to step 9. If not, the RGV continues its mission and then proceeds to step 6 to determine whether a conflict has occurred.

[0132] Step 9: According to the parking / retrieval rules, RGV completes the parking or retrieval action;

[0133] When the RGV reaches the designated location next to the parking space for parking or retrieval, it completes the parking or retrieval action according to the parking / retrieval rules, storing the vehicle in the designated parking space or retrieving it from the parking space. During the execution process, the accuracy and safety of the operation are ensured, and subsequent operations are considered.

[0134] In an embodiment of the present invention, the parking / retrieval rules are as follows: when an RGV arrives at a target parking space to park / retrieve a vehicle, if there is a blocking vehicle in front of the target parking space, the RGV will first move the blocking vehicle to the nearest driving path so that it does not block the target vehicle from entering / exiting. After the target vehicle being transported by the RGV is parked in the target parking space, the blocking vehicle will be moved back to its original position. When the target vehicle being transported by the RGV needs to be taken out of the target parking space, the RGV will first move the target vehicle to the nearest driving path. If the system is currently in the peak parking period, the blocking vehicles will be moved in order to the currently vacant target parking space and adjacent parking spaces in the original arrangement order, and the system status will be updated, including the parking lot occupancy status, RGV information, task information, user information, environmental information, etc.; if the system is currently in the peak retrieval period, the RGV will move the blocking vehicles to their original positions.

[0135] Step 10: Determine whether RGV has completed the task. If so, update the system status and go to step 11. Otherwise, RGV continues to execute the task and go to step 6.

[0136] When the RGV reaches the target location and completes its actions, it needs to check whether the parking or retrieval task it performed has been completed, including correctly placing the vehicle in the target parking space or delivering it to the user. This means determining whether the RGV has completed its task. If so, the system status is updated, including parking lot occupancy status, RGV information, task information, user information, and environmental information, and then proceeds to step 11. If not, the RGV continues executing the task and proceeds to step 6 again to determine whether any conflicts occurred during execution.

[0137] Step 11: Determine whether RGV has unfinished tasks. If RGV continues to execute tasks, go to step 6; otherwise, go to step 12.

[0138] Because RGV has bound tasks, when RGV completes a task, it needs to determine whether RGV has unfinished tasks. If RGV has unfinished tasks, RGV continues to execute the task and enters step 6 to avoid conflicts during task execution; if RGV has no unfinished tasks, it enters step 12 to schedule idle RGVs.

[0139] Step 12: According to the idle RGV scheduling rule, complete the idle RGV scheduling, update the system status, and go to step 1.

[0140] When the RGV completes all tasks, it is necessary to complete the idle RGV scheduling according to the idle RGV scheduling rules to avoid the idle RGV causing congestion of other RGVs due to the idle path occupied by the idle RGV, and update the system status, including the parking lot occupancy status, RGV information, task information, user information, environmental information, etc.

[0141] In this embodiment of the present invention, the idle RGV scheduling rule is to determine whether the RGV battery level is below a threshold when the RGV completes a task. If so, the RGV proceeds to a suitable charging area for charging. Otherwise, the RGV seeks a docking point near the nearest elevator and waits for the next task assignment. This ensures that the RGV reaches the task destination as quickly as possible when responding to a task, while avoiding blocking other RGVs.

[0142] In step 4, the dynamic entrance and exit strategy of the high-density parking lot scheduling system includes the following steps:

[0143] Step 1.1: Collect real-time traffic data at the entrances and exits of high-density parking lots and analyze the usage of the entrances and exits;

[0144] By installing sensors, cameras and other equipment at the entrances and exits, real-time traffic data of high-density parking entrances and exits is collected, and then the usage of the entrances and exits is analyzed, including the level of busyness, congestion and average waiting time of vehicles.

[0145] In the embodiment of the present invention, real-time traffic data is information such as vehicle inflow and outflow volume, speed, and dwell time at an entrance / exit within a specific time period. The specific time period is a time period consisting of a period in the past, present, and future.

[0146] Step 1.2: Determine whether the number of entrances and exits needs to be adjusted. If so, proceed to step 1.3; otherwise, terminate the adjustment.

[0147] Based on the usage of the entrances and exits, determine whether the number of entrances and exits needs to be adjusted. This means comparing the traffic conditions under the current number of entrances and exits with the preset traffic flow standard. If the current number of entrances and exits cannot meet the demand for vehicle ingress and egress, resulting in severe congestion and long wait times, then the number of entrances and exits needs to be adjusted, and the process proceeds to step 1.3. If the traffic conditions at the entrances and exits are good and can meet the demand for vehicle ingress and egress, then there is no need to adjust the number of entrances and exits, and the adjustment is complete.

[0148] Step 1.3: Determine whether the number of inlets and outlets has reached the limit. If so, end the adjustment. Otherwise, proceed to step 1.4.

[0149] When the number of entrances / exits needs to be adjusted, determine whether the number of entrances / exits has reached the limit. If the current number of entrances / exits has reached the limit, neither increasing nor decreasing the number of entrances / exits is feasible, and the adjustment ends. If the number of entrances / exits has not reached the limit, proceed to step 1.4 to continue the adjustment.

[0150] In the embodiment of the present invention, the extreme value is the case where the parking lot contains one entrance or exit.

[0151] It should be noted that the extreme value in this implementation case is only one of the cases. In actual practice, the maximum and minimum numbers of entrances and exits are determined by considering factors such as the spatial layout of the parking lot, surrounding road conditions, and construction costs.

[0152] Step 1.4: Determine the number of entrances and exits based on real-time traffic information rules;

[0153] When the number of entrances / exits needs to be adjusted and the number of entrances / exits has not reached the limit, the number of entrances / exits is determined according to the real-time traffic information rules;

[0154] In an embodiment of the present invention, the real-time traffic information rule is to calculate the vehicle inflow and outflow of the parking lot within a specific time period respectively. When the vehicle inflow is greater than the vehicle exit flow, the number of parking lot exits = max{floor(vehicle exit flow / vehicle inflow and outflow), 1}, and the number of parking lot entrances = the total number of parking lot exits / entrances - the number of parking lot exits, where floor(*) is a floor rounding function; when the vehicle inflow is less than or equal to the vehicle exit flow, the number of parking lot entrances = max{floor(vehicle entrance flow / vehicle inflow and outflow), 1}, and the number of parking lot exits = the total number of parking lot exits / entrances - the number of parking lot entrances.

[0155] Step 1.5: Use traffic simulation software to simulate the new entrance and exit locations, determine the optimal entrance and exit layout, and complete this adjustment.

[0156] Using professional traffic simulation software, input parameters such as the parking lot layout, surrounding road conditions, and the number of entrances and exits determined in Step 1.4 to simulate vehicle entry and exit under different combinations of entrance and exit locations. By analyzing the simulation results, such as average vehicle travel time, congestion levels, and queue lengths, the optimal entrance and exit layout is determined. This plan maximizes vehicle entry and exit efficiency, reduces traffic congestion, and also takes into account factors such as safety and convenience. Once the optimal entrance and exit layout is determined, the adjustment process ends.

[0157] In the embodiment of the present invention, traffic simulation software is a computer application used to simulate and analyze traffic flow and traffic system performance, including but not limited to Plant Simulation, VISSIM, Synchro, etc.

[0158] In step 5, the high-density parking lot task scheduling method includes the following steps:

[0159] Step 2.1: Determine the number of idle RGVs based on the real-time status of the high-density parking lot scheduling system;

[0160] According to the real-time status of the high-density parking lot scheduling system, including the parking lot occupancy status, RGV information, task information, user information, and environmental information, the number of idle RGVs (automatic guided vehicles) is determined to allocate subsequent tasks.

[0161] Step 2.2: Determine whether the number of idle RGVs is greater than or equal to 1. If so, proceed to step 2.3. Otherwise, obtain the task priority, allocation plan, and target location, and end the task scheduling.

[0162] After obtaining the number of idle RGVs, it is determined whether the number of idle RGVs is greater than or equal to 1. If so, it means that there are enough RGVs available, and the system will continue with task scheduling and enter step 2.3. If not, that is, there are no idle RGVs, and the customer's needs cannot be met. At this time, the system will collect the scheduling information that has been completed, that is, obtain the task priority, allocation plan and target location, and end this task scheduling.

[0163] Step 2.3: Determine whether there is a parking task. If so, proceed to step 2.4; otherwise, proceed to step 2.8.

[0164] When the number of idle RGVs is greater than or equal to 1, determine whether there is a parking task. If there is a parking task, go to step 2.4; otherwise, jump directly to step 2.8 to start processing the vehicle pickup task.

[0165] Step 2.4: Determine whether there is an available parking space. If so, proceed to step 2.5; otherwise, proceed to step 2.8.

[0166] When there is a parking task, determine whether there is an empty parking space. Confirming the availability of parking spaces is crucial to the success of the parking task. If there is an empty parking space, go to step 2.5, otherwise go to step 2.8 and start processing the pick-up task to avoid processing invalid tasks.

[0167] Step 2.5: Determine whether the number of parking tasks is greater than the number of pickup tasks. If so, proceed to step 2.6; otherwise, proceed to step 2.8.

[0168] When there are available parking spaces, the system determines whether the number of parking tasks exceeds the number of retrieval tasks, aiming to balance the parking and retrieval workloads. If the number of parking tasks is high, it indicates that the parking lot may be facing capacity constraints, so parking tasks should be prioritized, proceeding to step 2.6. If the number of parking tasks is less than or equal to the number of retrieval tasks, proceed to step 2.8.

[0169] Step 2.6: The high-density parking lot scheduling system starts assigning parking tasks to RGVs and determines the priority of parking tasks based on the customer's waiting time T0. The longer the waiting time T0, the higher the priority.

[0170] When the number of parking requests exceeds the number of pickup requests, the high-density parking system begins assigning parking tasks to RGVs. Prioritizing parking tasks is determined based on the customer's waiting time, T0. The longer the waiting time, the higher the priority, ensuring that parking requests with longer waiting times are prioritized. This not only improves customer satisfaction but also optimizes resource utilization.

[0171] In the embodiment of the present invention, the calculation formula of the customer's waiting time T0 is:

[0172] T0=|tt in | (14)

[0173] Among them, t is the system time at this moment, t in The time when the customer arrives at the parking or pick-up point.

[0174] Step 2.7: Determine the optimal parking space based on the parking space selection rules and proceed to step 2.9;

[0175] After completing the priority allocation of parking tasks, the system will determine the optimal parking space based on the parking space selection rules and proceed to step 2.9. The parking space selection rules need to consider distance, waiting time, and other factors to ensure that each car can be stored efficiently and reduce the operational complexity of subsequent car retrieval.

[0176] Step 2.8: The high-density parking lot scheduling system starts assigning car pickup tasks to RGVs based on the customer's waiting time T a Determine the priority of the vehicle pickup task. The longer the waiting time T0, the higher the priority, and proceed to step 2.9;

[0177] When there is no parking task or there is an empty parking space, or the number of parking tasks is greater than the number of pick-up tasks, the high-density parking lot scheduling system starts to assign pick-up tasks to RGVs according to the customer's waiting time T a Determine the priority of the vehicle pickup task. The longer the waiting time T0, the higher the priority. Go to step 2.9 to ensure that parking requests with longer waiting times are processed first. This not only improves customer satisfaction but also optimizes resource utilization efficiency. The customer's waiting time T0 is calculated as formula (1).

[0178] Step 2.9: Select the best RGVG from all idle RGVs based on the nearest and load balancing ratio rules RGV , the highest priority task G task Assigned to G RGV ;

[0179] After determining the priority of the task and the target parking space, the optimal RGVG is selected from all idle RGVs according to the nearest and load balancing rate rules.RGV , the highest priority task G task Assigned to G RGV ,ensure efficient use of resources and avoid some RGVs being in a high load state for a long period of time.

[0180] Step 2.10: Based on the allocation plan and waiting time calculation method, estimate the customer's waiting time T Y ;

[0181] According to the allocation plan and the customer's waiting time calculation method, the system will estimate the customer's waiting time T Y , so that you can consider whether to add binding tasks later.

[0182] In the embodiment of the present invention, the allocation scheme and the waiting time calculation method are as follows: first, G is obtained according to the allocation scheme. task The starting point, end point, priority and G RGV , then the expected customer waiting time T Y for,

[0183]

[0184] Among them, T3 x is the travel time required for RGV to transport the vehicle corresponding to task x from the task starting point to the task end point, is the horizontal distance between the starting point and the end point of task x, d x is the number of times the RGV lifts the vehicle between the starting point and the end point of task x, u x is the number of times the RGV drops off the vehicle between the starting point and the end point of task x, is the vertical distance between the starting point and the end point of task x, M x Dx is the total number of vehicles blocking the front when task x enters / exits the parking space. j is the time required to move the jth blocking vehicle in front to the free position when task x enters / exits the parking space, t wx is the congestion time of RGV in transporting the vehicle corresponding to task x from the task starting point to the task end point, Ω task is the collection of parking tasks and picking up tasks in the system, For Task G task The travel time required for the corresponding vehicle to transport from the task starting point to the task end point, T2 min G RGV Current location arrives at G task The travel time required to start the mission is calculated using the formula (4).

[0185] In this embodiment of the present invention, the starting point of a task is the parking spot (parking lot entrance) in a parking task or the parking space corresponding to a pick-up task. The end point of a task is the optimal parking space in a parking task or the pick-up point (parking lot exit) in a pick-up task.

[0186] Step 2.11: Determine the waiting time T Y Is it equal to or greater than the threshold? If so, go to step 2.14; otherwise, go to step 2.12;

[0187] According to formula (5), the expected customer waiting time T is calculated Y After that, judge the waiting time T Y Is it equal to or greater than the threshold? If the waiting time T Y If the value is equal to or greater than the threshold, proceed to step 2.14; otherwise, proceed to step 2.12.

[0188] It should be noted that the set thresholds are based on historical data and customer feedback, with the aim of finding a balance between customer experience and resource scheduling.

[0189] Step 2.12: Determine the highest priority task G based on the task binding method task Binding tasks;

[0190] According to the task binding method, determine the task with the highest priority G task The task binding method ensures that when a task is executed, related bound tasks can be processed at the same time, thereby improving the overall efficiency of the system.

[0191] Step 2.13: Determine G task Is the bound task of G not empty? If so, task The binding task is also assigned to G RGV , go to step 2.14, otherwise go directly to step 2.14;

[0192] When the task with the highest priority G is determined according to the task binding method, task After the binding task, it is necessary to judge G task Is the bound task not empty? If G task The binding task of G is not empty. task The binding task is also assigned to G RGV , go to step 2.14, otherwise go directly to step 2.14;

[0193] Step 2.14: Update the high-density parking lot scheduling system task information, reduce the number of idle RGVs by 1, and go to step 2.2.

[0194] After completing the above operations, update the task information of the high-density parking scheduling system, because at least one task has been assigned to G RGV , G RGV It is no longer an idle RGV, so the number of idle RGVs in the system is reduced by 1, and the process returns to step 2.2 to continue processing the next round of task scheduling. In addition, the process of updating task information ensures that the system can reflect the resource usage in real time, providing an accurate data basis for the next round of scheduling.

[0195] In step 2.7, the parking space selection rule includes the following steps:

[0196] Step 3.1: Determine the number N and location of vacant parking spaces based on the real-time status of the high-density parking lot scheduling system;

[0197] According to the real-time status of the high-density parking lot scheduling system, the number N and location of idle parking spaces are determined for subsequent parking space selection and task scheduling, as it directly affects the vehicle access efficiency.

[0198] Step 3.2: Travel time T1 to the i-th (i=1, ..., N) free parking space i The calculation formula is

[0199]

[0200] Among them, S i is the horizontal distance between the i-th free parking space and the parking spot, v is the average speed of the fully loaded RGV, d i is the number of times the RGV lifts a vehicle between the i-th free parking space and the parking spot, t d The time required for RGV to lift the vehicle each time, u i is the number of times the RGV puts down the vehicle between the i-th free parking space and the parking spot, t u S is the time required for RGV to put down the vehicle each time. Li is the vertical distance between the i-th free parking space and the parking spot, v l is the average speed of the elevator at full load, j is the number of the vehicle blocking the i-th free parking space, M i is the total number of vehicles blocking the i-th free parking space, Di j is the time required to move the jth blocked vehicle in front of the i-th free parking space to the free position, t wi is the congestion time of the RGV during the transportation process between the i-th free parking space and the parking point.

[0201] In the embodiment of the present invention, the congestion time during the RGV transportation process is obtained by a method including but not limited to a time window method, a machine learning prediction method, a deep learning prediction method or a simulation method.

[0202] Step 3.3: Select travel time T1 from all available parking spaces i The minimum parking space is considered as the optimal parking space.

[0203] The travel time T1 calculated according to formula (17) i , compare and filter all available parking spaces, and select the parking space with the shortest travel time, that is, select the travel time T1 from all available parking spaces i The system selects the optimal parking space with the fewest parking spaces. This not only improves parking efficiency but also effectively reduces customer waiting time, thereby optimizing the overall efficiency of the parking lot. By selecting the optimal parking space, the system ensures optimal resource utilization and provides customers with a better service experience.

[0204] In step 2.9, the nearest and load balancing rate rules include the following steps:

[0205] Step 4.1: Based on the current positions of all idle RGVs, calculate the current position of each idle RGV in turn to reach G task The travel time required to start the mission The calculation formula is

[0206]

[0207] in, The current position of the rth idle RGV and G task The horizontal distance from the starting point of the task, is the average no-load speed of RGV, The current position of the rth idle RGV and G task is the vertical distance from the starting point of the task, is the average no-load speed of the elevator, and R is the number of idle RGVs;

[0208] During this phase, the system iterates through all available RGVs and calculates the travel time required for each one to reach the designated mission's starting point from its current location. This calculation takes into account not only the horizontal and vertical distances but also the RGV's unloaded speed and the speed of the elevator. This gives the system a more comprehensive understanding of each RGV's response time, laying the foundation for subsequent optimal RGV selection.

[0209] Step 4.2: Calculate the positions of all idle RGVs to reach G task The travel time required to start the mission The shortest travel time T2 min , the calculation formula is

[0210]

[0211] In this step, the system calculates all the travel times from the first step. Compare and find the minimum travel time T2 min This calculation result will provide an important basis for subsequent decision-making, helping to determine which RGVs can respond to mission requests more quickly.

[0212] Step 4.3: Determine the minimum travel time T2 min Is the number of corresponding RGVs greater than 1? If so, go to step 4.4. Otherwise, the minimum travel time is T2. min The corresponding RGV is the optimal RGVG RGV , end this selection;

[0213] Get the minimum travel time T2 min After that, the system needs to analyze the minimum travel time T2 min The number of associated RGVs. That is, the minimum travel time T2 min Is the number of corresponding RGVs greater than 1? If so, there are multiple RGVs that can achieve the same minimum travel time T2 min , then it is necessary to further evaluate their load conditions to make a more reasonable choice and proceed to step 4.4. If only one RGV can achieve the minimum travel time T2 min , then the RGV is directly selected as the optimal RGV, that is, the one with the shortest travel time T2 min The corresponding RGV is G RGV , the entire selection process ends.

[0214] Step 4.4: From all the minimum travel times T2 min Among the corresponding RGVs, select the RGV with the smallest total load as G RGV , end this selection.

[0215] When multiple RGVs can achieve the same minimum travel time T2 min When , the system will screen out all RGVs that reach the minimum travel time and further calculate their total load. Finally, the RGV with the smallest load is selected as the optimal RGVG RGV This selection process not only takes into account the shortest travel time, but also comprehensively evaluates the load conditions of each RGV, thereby ensuring that while meeting efficiency, the use of resources is optimized and the overall operational effectiveness of the system is improved.

[0216] In the embodiment of the present invention, the total load includes but is not limited to the total driving time, the total driving distance and the total number of transport vehicles.

[0217] In step 2.12, the task binding method includes the following steps:

[0218] Step 5.1: Determine the value assigned to G RGV The highest priority task G task Is it a parking task? If yes, go to step 5.2; otherwise, go to step 5.3.

[0219] The system first needs to identify the type of task currently received by the RGV to determine whether it is a parking task or a pickup task. RGV The highest priority task G task Is it a parking task? If it is a parking task, go to step 5.2, otherwise go to step 5.3; this judgment will determine the subsequent processing flow, thereby ensuring that the system can adopt appropriate binding strategies for different types of tasks.

[0220] Step 5.2: Search all the car pickup tasks in the system and determine whether there is a car pickup task with the task end point G task The starting point of the task, if so, the task of picking up the car that meets the requirements constitutes G task If the bound task set Ψ is met, go to step 5.4, otherwise go to step 5.8;

[0221] When assigned to G RGV The highest priority task G task When it is a parking task, search all the pick-up tasks in the system to determine whether there is a pick-up task with the task end point G task The starting point of the task, if so, the task of picking up the car that meets the requirements constitutes G task If the bound task set Ψ is found, go to step 5.4. If no matching task is found, go to step 5.8.

[0222] Step 5.3: Search all parking tasks in the system and determine whether there is a parking task with the task end point G task The starting point of the task, if so, the parking task that meets the requirements constitutes G task If the bound task set Ψ is met, go to step 5.4, otherwise go to step 5.8;

[0223] When assigned to G RGV The highest priority task G task When it is a car picking task, search all parking tasks in the system to determine whether there is a parking task with the task end point G task The starting point of the task, if so, the parking task that meets the requirements constitutes G task If the bound task set Ψ is found, go to step 5.4. If no matching task is found, go to step 5.8.

[0224] Step 5.4: Assume that in G RGV Execute G task Add G before taskThe bth task in the bound task set Ψ, then G RGV Complete tasks b and G task The travel time required for the two tasks is T4 b The calculation formula is

[0225]

[0226] in, G RGV The travel time required for the current location to reach the starting point of the bth task in the bound task set Ψ, T3 b G RGV The travel time required to transport the vehicle corresponding to the bth task in the bound task set Ψ from the task starting point to the task ending point.

[0227] In this step, the system will assume that G RGV When executing the bth task in the bound task set Ψ, G is completed by calculation. task Compared with the total travel time of the bth task in the bound task set Ψ, the system can better evaluate the overall efficiency of the tasks and then select the optimal bound task from the bound task set Ψ.

[0228] Step 5.5: In G task The bound task set Ψ selects a task that makes T4 b Minimum task b min As G task pending binding tasks;

[0229] Calculate all G RGV Complete tasks b and G in the bound task set Ψ task The travel time required for the two tasks is T3 b , the system needs to calculate the total travel time T3 of all candidate tasks b in the bound task set Ψ b For comparison, in G task The bound task set Ψ selects a task that makes T4 b Minimum task b min As G task The system selects the optimal bound tasks, thereby improving resource utilization efficiency and reducing overall completion time.

[0230] Step 5.6: Calculate G RGV Complete Task B min and G task Two tasks, estimated customer waiting time T Y2 for

[0231] T Y2 =T0+min(T4 b ), b∈Ψ (21);

[0232] Determine the optimal binding task b min Then calculate G RGV Complete Task B min and G task Two tasks, estimated customer waiting time T Y2 , taking into account all time factors in the task execution process. This calculation will help evaluate the overall timing of task execution for threshold judgment in subsequent steps.

[0233] Step 5.7: Determine the waiting time T Y2 Is it greater than the threshold? If so, go to step 5.8; otherwise, go to step 5.9;

[0234] Estimated customer waiting time T Y2 After that, the system needs to calculate the expected waiting time T Y2 Evaluate and determine the waiting time T Y2 Is it greater than the threshold? If the waiting time T Y2 If the value is greater than the threshold, the client waiting time is long, indicating that the pending binding task is not suitable for insertion into G task Before, by G RGV If both are moved at the same time, proceed to step 5.8; otherwise, proceed to step 5.9 and continue setting up the binding task.

[0235] Step 5.8: G task There is no binding task, so the binding process ends;

[0236] When the waiting time T Y2 When it is greater than the threshold, the system confirms that there is no suitable binding task at present, that is, G task There is no binding task, and the entire binding process ends.

[0237] Step 5.9: Setting b min For G task Bind the task and end the binding process.

[0238] When the waiting time T Y2 When it is less than or equal to the threshold, it means that even if b min As G task Binding tasks, the customer waiting time is also within the tolerable time, so set b min For G task Bind the task and end the binding process. This operation marks the completion of task binding and lays the foundation for subsequent task execution.

[0239] The above description is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements can be made without departing from the principles of the present invention. These improvements should also be regarded as the scope of protection of the present invention.

Claims

1. A high-density parking lot scheduling method based on multi-directional mobile RGV, characterized in that: The steps are as follows: Step 1: Determine whether the high-density parking lot scheduling system meets the task triggering conditions. If so, obtain the task information in the system and proceed to step 2. Otherwise, loop judgment; Step 2: Determine whether the high-density parking lot scheduling system has a parking task or a pick-up task. If yes, proceed to step 3; otherwise, proceed to step 1. Step 3: Determine whether the system has idle RGVs; if yes, proceed to step 4, otherwise proceed to step 1; Step 4: Determine the number and location of parking lot entrances and exits based on the dynamic entrance and exit strategy of the high-density parking lot scheduling system; Step 5: According to the high-density parking lot task scheduling method, the priority, allocation plan and target location of the task are determined, and then the RGV starts to execute the task according to the shortest path; the high-density parking lot task scheduling method includes the following steps: Step 2.1: Determine the number of idle RGVs based on the real-time status of the high-density parking lot scheduling system; Step 2.2: Determine whether the number of idle RGVs is greater than or equal to 1. If so, proceed to step 2.

3. Otherwise, obtain the task priority, allocation plan, and target location, and end the task scheduling. Step 2.3: Determine whether there is a parking task. If so, proceed to step 2.4; otherwise, proceed to step 2.

8. Step 2.4: Determine whether there is an available parking space. If so, proceed to step 2.5; otherwise, proceed to step 2.

8. Step 2.5: Determine whether the number of parking tasks is greater than the number of pickup tasks. If so, proceed to step 2.6; otherwise, proceed to step 2.

8. Step 2.6: The high-density parking lot scheduling system starts assigning parking tasks to RGVs and determines the priority of parking tasks based on the customer's waiting time T0. The longer the waiting time T0, the higher the priority. Step 2.7: Determine the optimal parking space based on the parking space selection rules and proceed to step 2.9; Step 2.8: The high-density parking lot scheduling system starts assigning car pickup tasks to RGVs based on the customer's waiting time T a Determine the priority of the vehicle pickup task. The longer the waiting time T0, the higher the priority, and proceed to step 2.9; Step 2.9: Select the best RGVG from all idle RGVs based on the nearest and load balancing ratio rules RGV , the highest priority task G task Assigned to G RGV ; Step 2.10: Based on the allocation plan and waiting time calculation method, estimate the customer's waiting time T Y ; Step 2.11: Determine the waiting time T Y Is it equal to or greater than the threshold? If so, go to step 2.14; otherwise, go to step 2.12; Step 2.12: Determine the highest priority task G based on the task binding method task Binding tasks; Step 2.13: Determine G task Is the bound task of G not empty? If so, task The binding task is also assigned to G RGV , go to step 2.14, otherwise go directly to step 2.14; Step 2.14: Update the high-density parking lot scheduling system task information, reduce the number of idle RGVs by 1, and go to step 2.2; Step 6: Determine whether RGV has a conflict during task execution. If so, proceed to step 7; otherwise, proceed to step 8. Step 7: Avoid collisions based on the high-density parking lot traffic control strategy; Step 8: Determine whether the RGV has arrived at the parking space corresponding to the parking / retrieval vehicle. If so, proceed to step 9. Otherwise, the RGV continues to perform the task and proceeds to step 6. Step 9: According to the parking / retrieval rules, RGV completes the parking or retrieval action; Step 10: Determine whether RGV has completed the task. If so, update the system status and go to step 11. Otherwise, RGV continues to execute the task and go to step 6. Step 11: Determine whether RGV has unfinished tasks. If RGV continues to execute tasks, go to step 6; otherwise, go to step 12. Step 12: According to the idle RGV scheduling rule, complete the idle RGV scheduling, update the system status, and go to step 1.

2. A high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1, characterized in that: The dynamic entrance and exit strategy of the high-density parking lot scheduling system includes the following steps: Step 1.1: Collect real-time traffic data at the entrances and exits of high-density parking lots and analyze their usage; Step 1.2: Determine whether the number of entrances and exits needs to be adjusted. If so, proceed to step 1.3; otherwise, terminate the adjustment. Step 1.3: Determine whether the number of inlets and outlets has reached the limit. If so, end the adjustment. Otherwise, proceed to step 1.

4. Step 1.4: Determine the number of entrances and exits based on real-time traffic information rules; Step 1.5: Use traffic simulation software to simulate the new entrance and exit locations, determine the optimal entrance and exit layout, and complete this adjustment.

3. A high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 2, characterized in that: The real-time traffic information rule is to calculate the vehicle inflow and outflow of the parking lot in a specific time period. When the vehicle inflow is greater than the vehicle outflow, the number of parking lot exits = max{floor(vehicle exit flow / vehicle inflow and outflow), 1}, and the number of parking lot entrances = the total number of parking lot exits / entrances - the number of parking lot exits, where floor(*) is a rounding function. When the vehicle entry flow is less than or equal to the vehicle exit flow, the number of parking lot entrances = max{floor(vehicle entry flow / vehicle entry and exit flow), 1}, and the number of parking lot exits = the total number of parking lot entrances / exits - the number of parking lot entrances.

4. The high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1 is characterized in that: The parking space selection rule includes the following steps: Step 3.1: Determine the number N and location of vacant parking spaces based on the real-time status of the high-density parking lot scheduling system; Step 3.2: Travel time T1 to the i-th (i=1, ..., N) free parking space i The calculation formula is Among them, S i is the horizontal distance between the i-th free parking space and the parking spot, v is the average speed of the fully loaded RGV, d i is the number of times the RGV lifts a vehicle between the i-th free parking space and the parking spot, t d The time required for RGV to lift the vehicle each time, u i is the number of times the RGV puts down the vehicle between the i-th free parking space and the parking spot, t u S is the time required for RGV to put down the vehicle each time. Li is the vertical distance between the i-th free parking space and the parking spot, v l is the average speed of the elevator at full load, j is the number of the vehicle blocking the i-th free parking space, M i is the total number of vehicles blocking the i-th free parking space, Di j is the time required to move the jth blocked vehicle in front of the i-th free parking space to the free position, t wi is the congestion time of the RGV during the transportation process between the i-th free parking space and the parking point; Step 3.3: Select travel time T1 from all available parking spaces i The minimum parking space is considered as the optimal parking space.

5. The high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1 is characterized in that: The nearest and load balancing rate rules include the following steps: Step 4.1: Based on the current positions of all idle RGVs, calculate the current position of each idle RGV in turn to reach G task The travel time required to start the mission The calculation formula is in, The current position of the rth idle RGV and G task The horizontal distance from the starting point of the task, is the average no-load speed of RGV, The current position of the rth idle RGV and G task The vertical distance from the starting point of the task, is the average no-load speed of the elevator, R is the number of idle RGVs; Step 4.2: Calculate the positions of all idle RGVs to reach G task The travel time required to start the mission The shortest travel time T2 min , the calculation formula is Step 4.3: Determine the minimum travel time T2 min Is the number of corresponding RGVs greater than 1? If so, go to step 4.

4. Otherwise, the minimum travel time is T2. min The corresponding RGV is the optimal RGVG RGV , end this selection; Step 4.4: From all the minimum travel times T2 min Among the corresponding RGVs, select the RGV with the smallest total load as G RGV , end this selection.

6. The high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1 is characterized in that: The allocation scheme and waiting time calculation method are as follows: first, G is obtained according to the allocation scheme. task The starting point, end point, priority and G RGV , then the expected customer waiting time T Y for, Among them, T3 x is the travel time required for RGV to transport the vehicle corresponding to task x from the task starting point to the task end point, is the horizontal distance between the starting point and the end point of task x, d x is the number of times the RGV lifts the vehicle between the starting point and the end point of task x, u x is the number of times the RGV drops off the vehicle between the starting point and the end point of task x, is the vertical distance between the starting point and the end point of task x, M x Dx is the total number of vehicles blocking the front when task x enters / exits the parking space. j is the time required to move the jth blocking vehicle in front to the free position when task x enters / exits the parking space, t wx is the congestion time of RGV in transporting the vehicle corresponding to task x from the task starting point to the task end point, Ω task is the collection of parking tasks and picking up tasks in the system, For Task G task The travel time required for the corresponding vehicle to transport the goods from the starting point to the end point of the task.

7. The high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1 is characterized in that: The task binding method comprises the following steps: Step 5.1: Determine the value assigned to G RGV The highest priority task G task Is it a parking task? If yes, go to step 5.2; otherwise, go to step 5.

3. Step 5.2: Search all the car pickup tasks in the system and determine whether there is a car pickup task with the task end point G task The starting point of the task, if so, the task of picking up the car that meets the requirements constitutes G task If the bound task set Ψ is met, go to step 5.4, otherwise go to step 5.8; Step 5.3: Search all parking tasks in the system and determine whether there is a parking task with the task end point G task The starting point of the task, if so, the parking task that meets the requirements constitutes G task If the bound task set Ψ is met, go to step 5.4, otherwise go to step 5.8; Step 5.4: Assume that in G RGV Execute G task Add G before task The bth task in the bound task set Ψ, then G RGV Complete tasks b and G task The travel time required for the two tasks is T4 b The calculation formula is in, G RGV The travel time required for the current location to reach the starting point of the bth task in the bound task set Ψ, T3 b G RGV The travel time required to transport the vehicle corresponding to the bth task in the bound task set Ψ from the task starting point to the task ending point; Step 5.5: In G task The bound task set Ψ selects a task that makes T4 b Minimum task b min As G task pending binding tasks; Step 5.6: Calculate G RGV Complete Task B min and G task Two tasks, estimated customer waiting time T Y2 for T Y2 =T0+min(T4b),b∈Ψ (6); Step 5.6: Calculate G RGV Complete Task B min and G task Two tasks, estimated customer waiting time T Y2 for Step 5.7: Determine the waiting time T Y2 Is it greater than the threshold? If so, go to step 5.8; otherwise, go to step 5.9; Step 5.8: G task There is no binding task, so the binding process ends; Step 5.9: Setting b min For G task Bind the task and end the binding process.

8. The high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1 is characterized in that: The traffic control strategy for high-density parking lots is to select appropriate conflict avoidance methods based on the type of conflict, including the following situations: 1) Overtaking conflict: When the RGV temporarily places the blocking vehicle in front of the parking space on the RGV's driving path, an overtaking conflict will occur. First, observe whether there is a lateral movement route to bypass the blocking vehicle. If not, wait on the spot until the blocking vehicle is moved away; 2) Opposite-direction collision: Two or more RGVs are traveling towards each other in a narrow passage or specific area, and a collision may occur. In narrow passages or areas where there may be opposite-direction driving, a collision avoidance method using QR code positioning and semaphore mutual exclusion mechanism is used. When an RGV approaches, the semaphore becomes 1, preventing the RGV in the other direction from entering, ensuring that only one RGV can pass. 3) Resource competition: Multiple RGVs need to use the same resources at the same time, and the order in which RGVs use them is determined according to priority rules.

9. The high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1 is characterized in that: The parking / retrieval rule is that when the RGV arrives at the target parking space for parking / retrieval, if there is a blocking vehicle in front of the target parking space, the RGV will first move the blocking vehicle to the nearest driving path so that it does not block the target vehicle from entering / exiting. When the target vehicle moved by the RGV is parked in the target parking space, the blocking vehicle will be moved to its original position. When the target vehicle moved by the RGV needs to be taken out of the target parking space, the RGV will first move the target vehicle to the nearest driving path. If the system is currently in the parking peak period, the blocking vehicles will be moved to the vacant target parking space and adjacent parking spaces in the original arrangement order, and the system status will be updated. If the system is currently in the picking peak period, the RGV will move the blocking vehicles to their original positions. The idle RGV scheduling rule is that when the RGV completes a task, it determines whether the RGV power is lower than a threshold. If it is lower than the threshold, the RGV goes to a suitable charging area for charging. Otherwise, the RGV goes to the nearest elevator to find a docking point and wait for the next task assignment.

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