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

Abstract

The invention relates to a high-density parking lot scheduling method based on a multidirectional mobile RGV, and belongs to the field of three-dimensional parking. The method comprises the following steps: determining the positions and the number of entrances and exits according to a dynamic entrance and exit strategy when a vehicle parking or taking task exists and an idle RGV exists; then, according to a high-density parking lot task scheduling method, the priority, the allocation scheme and the target position of the task are determined; collision avoidance is carried out according to a high-density parking lot traffic management and control strategy, and when the RGV arrives at a parking space or a parking space, parking or parking is completed according to a parking rule or a parking rule; finally, when the RGV completes the task, idle RGV scheduling is completed according to the idle RGV scheduling rule. According to the method, the problems of low space utilization rate and low carrying efficiency in the scheduling process of single-direction moving RGV transport vehicles in the prior art are solved, and a set of high-efficiency scheduling scheme is provided for a high-density parking lot based on multi-direction moving RGVs.

Description

Technical Field

[0001] The 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] Automatic valet parking technology is an advanced smart parking solution that allows self-driving cars to automatically enter and park in parking lots without human intervention. When the user of the vehicle needs to pick up the car, the vehicle can automatically exit the parking lot by simply issuing a command through a mobile phone or other device. Since these vehicles have the characteristics of unmanned driving and interconnection, the automatic valet parking system can improve the comprehensive utilization efficiency of the parking lot according to different parking strategies. In order to improve the space utilization rate of automatic valet parking lots, studies have proposed a discharge layout in which vehicles are connected end to end, that is, a high-density parking lot. The RGV in a high-density parking lot is mainly used to transport vehicles and transport cars to parking spaces. However, in the existing technology, the RGV can only move in one direction, and the three-dimensional parking garage needs to be arranged with a lateral moving platform or a rotating platform to realize the lateral movement of the RGV. However, the arrangement of a lateral moving platform or a rotating platform will increase the risk of equipment failure and operating costs, and reduce space utilization. On the other hand, the high-density parking lot layout will cause some vehicles to be blocked by other parked vehicles when exiting, thereby reducing the time efficiency and user experience of the parking lot.

[0003] In summary, although high-density parking lot scheduling can improve parking lot utilization, it will also reduce time efficiency. However, after reviewing the existing literature related to parking lot scheduling, there are few studies on the problem of high-density parking lot scheduling, which mainly focus on the parking lot scheduling problem based on a single-position mobile RGV, such as the Chinese invention patent with publication number CN116703260A, while there is no relevant research literature on high-density parking lot scheduling based on multi-position mobile RGV. 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, which utilizes the multi-directional mobile RGV transport vehicle to solve 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, and provides a set of efficient scheduling solutions 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 RGV, comprising the steps of:

[0007] Step 1: Determine whether the high-density parking lot dispatching 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 pickup task. If yes, proceed to step 3; otherwise, proceed to step 1.

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

[0010] Step 4: According to the dynamic entrance and exit strategy of the high-density parking lot scheduling system, determine the number and location of the parking lot entrances and exits;

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

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

[0013] Step 7: Avoid collisions 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 storage / retrieval of the 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 perform the task and go to step 6.

[0017] Step 11: Determine whether the RGV has unfinished tasks. If the RGV continues to execute the task, 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 vehicle storage 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 customer needs.

[0023] Furthermore, the vehicle picking task is to use the 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 picking 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 high-density parking lot scheduling system dynamic entrance and exit strategy includes the following steps:

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

[0027] Step 1.2: Determine whether the number of inlets and outlets needs to be adjusted. If so, proceed to step 1.3, otherwise, end the adjustment.

[0028] Step 1.3: Determine whether the number of inlets / outlets has reached the extreme value. If so, end the adjustment, otherwise proceed to step 1.4;

[0029] Step 1.4: Determine the number of entrances / 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 plan, and end this adjustment.

[0031] Furthermore, the real-time traffic data is information such as vehicle inflow and outflow flow, speed, and retention 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 in 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 comprises the following steps:

[0037] Step 2.1: Determine the number of idle RGVs according to 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 priority, allocation scheme and target location of the task and end the task scheduling.

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

[0040] Step 2.4: Determine whether there is an empty 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 picking up tasks. If so, proceed to step 2.6; otherwise, proceed to step 2.8.

[0042] Step 2.6: The high-density parking lot dispatching system starts to assign 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 according to the parking space selection rule and proceed to step 2.9;

[0044] Step 2.8: The high-density parking lot dispatching system starts to assign the car pickup task to the RGV, according to the customer's waiting time T a Determine the priority of the vehicle pickup task. The longer the waiting time T0 is, the higher the priority is. Go to step 2.9.

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

[0046] Step 2.10: According to 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 according to the task binding method task Binding tasks;

[0049] Step 2.13: Determine G task Is the binding 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 dispatching system includes the parking lot occupancy status, RGV information, task information, user information, and environmental information.

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

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

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

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

[0056] Step 3.2: Travel time T1 for transporting 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 ith free parking space and the parking spot, v is the average speed of the RGV when fully loaded, and 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 a vehicle between the i-th free parking space and the parking spot, t u is the time required for RGV to put down the vehicle each time, S Li is the vertical distance between the ith 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 blocking vehicle in front of the i-th free parking space to the free position, t wi is the congestion time of 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 may be 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.

[0061] Furthermore, the nearest and load balancing rate rule comprises 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, is 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, is the current position of the rth idle RGV and G task The vertical distance from the starting point of the task, is the no-load average 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 corresponding number of RGVs greater than 1? If so, proceed 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 The RGV with the smallest total load is selected 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 the waiting time calculation method are as follows: firstly, 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 car storage tasks and car retrieval tasks in the system. For Task G task The travel time required for the corresponding vehicle to transport the goods from the mission starting point to the mission end point.

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

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

[0076] Step 5.1: Determine the assignment 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-picking tasks in the system to determine whether there is a car-picking task with a task end point of 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 to determine whether there is a parking task with a task end point of 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 from the current location of the task to 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 end point.

[0082] Step 5.5: In Gtask The bound task set Ψ selects a task that makes T4 b The smallest 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 is to select appropriate conflict avoidance methods according to the type of conflict. 1. Overtaking conflict. When the RGV temporarily places the blocking vehicle in front of the parking space on the RGV driving path, an overtaking conflict will occur. First, observe whether there is a lateral route to bypass the blocking vehicle. If not, wait on the spot until the blocking vehicle is moved away. 2. Opposite conflict. Two or more RGVs are traveling in opposite directions in a narrow passage or a specific area, and a collision may occur. It is necessary to use the QR code positioning and semaphore mutual exclusion mechanism to avoid collision in narrow passages or areas where opposite directions may occur. When an RGV approaches, the semaphore becomes 1, preventing the RGV in the other direction from entering, ensuring that only one party can pass. 3. Resource competition. Multiple RGVs need to use the same resources at the same time, such as elevators, intersections, charging facilities, maintenance equipment, etc. The order of use of RGVs can be determined according to priority rules, including but not limited to priority rules such as task priority, first come first served, and vehicle urgency.

[0090] Furthermore, the parking / retrieval rules are as follows: when the RGV reaches 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 in the peak parking 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 in the peak vehicle retrieval period, the RGV will move the blocking vehicles to their original positions.

[0091] Furthermore, the idle RGV scheduling rule is that when the RGV completes the 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 stop 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, which utilizes the multi-directional mobile RGV transport vehicle to solve the problems of low space utilization and low transport efficiency in the scheduling process of using single-directional mobile RGV transport vehicles in the prior art, and provides a set of efficient scheduling solutions for high-density parking lots based on multi-directional mobile RGV. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 It is a flow chart of the high-density parking lot scheduling method based on multi-directional mobile RGV of the present invention;

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

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

[0097] Figure 4 It is a partial schematic diagram of a high-density parking lot of the present invention;

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

[0099] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0100] Since the heterogeneous robot system is relatively complex, the following assumptions are made for 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. The high-density parking lot scheduling method based on multi-directional mobile RGV specifically includes the following steps:

[0106] Step 1: Determine whether the high-density parking lot dispatching 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 RGV, it will first check whether the task triggering conditions are met. When the task triggering conditions are met, the task information in the system is obtained, including 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 around the transported vehicle corresponding to the task, and then enter step 2; when the task triggering conditions are not met, it is necessary to loop the judgment until the task triggering 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 setting up additional mechanisms. The car is placed on the RGV fork frame. When the car is transported, the fork frame is raised. After the RGV moves to a fixed parking space, the fork frame falls and the car is parked on 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 trigger conditions include periodic triggering and event triggering, wherein the periodic triggering is a regular triggering at fixed time intervals, and the event triggering is a scheduling method triggered when a set event occurs. In an embodiment of the present invention, the set event includes the number of tasks in the task set 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 pickup 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 pick-up task. If the system has a parking task or a pick-up task, it goes to step 3; if the system does not have a parking task or a pick-up task, there is no task in the system that requires RGV to move, so no scheduling is required, and it goes to step 1, waiting for the next time the system meets the task triggering conditions.

[0114] In the embodiment of the present invention, the vehicle 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 needs of the customer.

[0115] In the embodiment of the present invention, the vehicle picking task is to use the 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 task of the customer picking up the vehicle.

[0116] Step 3: Determine the idle RGV of the system; 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 idle RGV of the system is determined; if the system has an idle RGV, the system goes to step 4 and starts scheduling; if the system has no idle RGV, there is no idle RGV in the system to execute the new task, so there is no need to schedule, and the system goes to step 1 to wait for the next time the system meets the task triggering condition.

[0118] In the embodiment of the present invention, 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.

[0119] Step 4: According to the dynamic entrance and exit strategy of the high-density parking lot scheduling system, determine the number and location of the parking lot entrances and exits;

[0120] When the system has idle RGVs, it analyzes factors such as the current parking lot's vehicle flow, task distribution, and spatial layout, and based on the high-density parking lot scheduling system's dynamic entrance and exit strategy, 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 scheme and target location are determined, and then the RGV starts to execute the task according to the shortest path;

[0122] After determining the number and location of parking lot entrances and exits, the parking and retrieval tasks in the system are prioritized according to the high-density parking lot task scheduling method to determine which tasks need to be processed first. At the same time, a reasonable allocation plan is formulated based on the location, status and task requirements of the RGV to assign tasks to appropriate RGVs. The target location of each task, that is, the specific parking space corresponding to the parking task, is determined at this time to determine the priority, allocation plan and target location of the task. Finally, the RGV assigned the task starts to execute the task according to the planned shortest path to improve the efficiency of task execution.

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

[0124] Step 6: Determine whether RGV has a conflict in executing the task. 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 lot 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 goes to step 7 to avoid collision; if no conflict occurs during the execution of the task, it goes to step 8.

[0126] Step 7: Avoid collisions according to the high-density parking lot traffic control strategy;

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

[0128] In the embodiment of the present invention, the traffic control strategy of the high-density parking lot is to select a suitable conflict avoidance method according to the type of conflict. 1. Overtaking conflict. When the RGV temporarily places the blocking vehicle in front of the parking space on the RGV driving path, an overtaking conflict will occur. First, observe whether there is a lateral route to bypass the blocking vehicle. If not, wait on the spot until the blocking vehicle is moved away. 2. Opposite conflict. Two or more RGVs are traveling towards each other in a narrow passage or a specific area, and a collision may occur. It is necessary to use the QR code positioning and semaphore mutual exclusion mechanism to avoid collision in narrow passages or areas where opposite driving may occur. When an RGV approaches, the semaphore becomes 1, preventing the RGV in the other direction from entering, ensuring that only one party passes. 3. Resource competition. Multiple RGVs need to use the same resources at the same time, such as elevators, intersections, charging facilities, maintenance equipment, etc. The order of use of RGVs can be determined according to priority rules, including but not limited to priority rules such as 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 the common types of conflicts and proposes corresponding collision avoidance methods for the conflict types. However, other types of conflicts can also be simplified into the above-mentioned 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 storage / retrieval of the vehicle. If so, proceed to step 9. Otherwise, the RGV continues to perform the task and proceeds to step 6.

[0131] Through sensors and positioning systems, the position of the RGV is monitored in real time to determine whether it has reached the designated location next to the parking space corresponding to the parking or pickup. If so, it proceeds to step 9; if not, the RGV continues to perform the task and then proceeds to step 6 to determine again whether a conflict occurs.

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

[0133] When the RGV has reached the designated location next to the parking space corresponding to the parking or retrieval, the RGV completes the parking or retrieval action according to the parking / retrieval rules, and stores the vehicle in the designated parking space or takes the vehicle out of the parking space. During the execution process, ensure the accuracy and safety of the operation, and consider the subsequent operations.

[0134] In the embodiment of the present invention, the parking / retrieving rules are as follows: when the RGV arrives at the target parking space for parking / retrieving, 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 moved by the RGV is parked in the target parking space, the blocking vehicle will be moved to the 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 in the peak parking 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, including the parking lot occupancy status, RGV information, task information, user information, environmental information, etc.; if the system is in the peak period of picking up vehicles, the RGV will move the blocking vehicles to the original position.

[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 perform the task and go to step 6.

[0136] When the RGV reaches the target location and completes the action, it is necessary to check whether the parking or picking-up task performed by the RGV has been completed, including correctly placing the vehicle in the target parking space or delivering it to the user, etc. That is, to determine whether the RGV has completed the task. If the task is completed, the system status is updated, including the parking lot occupancy status, RGV information, task information, user information, environmental information, etc., and then enter step 11; if the task is not completed, the RGV continues to perform the task and enters step 6 again to determine whether a conflict occurs during the execution process.

[0137] Step 11: Determine whether the RGV has unfinished tasks. If the RGV continues to execute the task, 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 tasks 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 the embodiment of the present invention, the idle RGV scheduling rule is that when the RGV completes the task, it is determined whether the RGV power is lower than the 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 parking point and wait for the next task assignment. This ensures that the task target point is reached as quickly as possible when responding to the task while avoiding blocking other RGVs.

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

[0143] Step 1.1: Collect real-time traffic data of high-density parking lot entrances and exits 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 lot entrances and exits is collected, and then the usage of the entrances and exits is analyzed, including the level of busyness, congestion, and the average waiting time of vehicles.

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

[0146] Step 1.2: Determine whether the number of inlets and outlets needs to be adjusted. If so, proceed to step 1.3, otherwise, end the adjustment.

[0147] According to the usage of the entrances and exits, determine whether the number of entrances and exits needs to be adjusted. That is, compare the traffic conditions under the current number of entrances and exits with the preset traffic flow standard. If it is found that the current number of entrances and exits cannot meet the needs of vehicle entry and exit, resulting in serious congestion, long waiting time and other problems, then it is determined that the number of entrances and exits needs to be adjusted, and then go to step 1.3; if the traffic conditions of the entrances and exits are good and can meet the needs of vehicle entry and exit, then there is no need to adjust the number of entrances and exits, and this adjustment is completed.

[0148] Step 1.3: Determine whether the number of inlets / outlets has reached the extreme value. 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 extreme value. If the current number of entrances / exits has reached the extreme value, it is not feasible to increase or decrease the number of entrances / exits, so the adjustment ends. If the number of entrances / exits has not reached the extreme value, go to step 1.4 and continue to adjust.

[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 the actual process, the maximum and minimum values ​​of the number of entrances and exits are determined by considering factors such as the spatial layout of the parking lot, the surrounding road conditions, and the construction cost.

[0152] Step 1.4: Determine the number of entrances / 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 extreme value, the number of entrances / exits is determined according to the real-time traffic information rule;

[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 in 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 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 plan, and end this adjustment.

[0156] Using professional traffic simulation software, input parameters such as the layout of the parking lot, the surrounding road conditions, and the number of entrances and exits determined in step 1.4 to simulate the vehicle entry and exit conditions under different combinations of entrance and exit positions. By analyzing the simulation results, such as the average driving time of vehicles, the degree of congestion, the length of queues and other indicators, the optimal entrance and exit layout plan is determined. This plan can maximize the efficiency of vehicle entry and exit of the parking lot and reduce traffic congestion, while also considering factors such as safety and convenience. After determining the optimal entrance / exit layout plan, end this adjustment.

[0157] In the embodiments 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 according to 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 priority, allocation scheme and target location of the task and end the task scheduling.

[0162] After obtaining the number of idle RGVs, determine 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 to schedule tasks and enter step 2.3; if not, that is, there are no idle RGVs, 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 priority, allocation plan and target location of the task, and end this task scheduling.

[0163] Step 2.3: Determine whether there is a parking task, if so, go to step 2.4, otherwise go 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 empty 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 picking up tasks. If so, proceed to step 2.6; otherwise, proceed to step 2.8.

[0168] When the system has free parking spaces, it determines whether the number of parking tasks is greater than the number of pickup tasks, aiming to balance the workload of parking and pickup. If the number of parking tasks is large, it means that the parking lot may face insufficient capacity, so the parking tasks need to be prioritized and go to step 2.6. If the number of parking tasks is less than or equal to the number of pickup tasks, go to step 2.8.

[0169] Step 2.6: The high-density parking lot dispatching system starts to assign 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 tasks is greater than the number of pickup tasks, the high-density parking lot dispatching system starts to assign 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, ensuring that parking requests with longer waiting times are given priority. This not only improves customer satisfaction, but also optimizes the efficiency of resource use.

[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 current system time, t in The time when the customer arrives at the parking or pick-up point.

[0174] Step 2.7: Determine the optimal parking space according to the parking space selection rule 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 enter 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 dispatching system starts to assign the pick-up task to the RGV according to the customer's waiting time T a Determine the priority of the vehicle pickup task. The longer the waiting time T0 is, the higher the priority is. Go 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 is, the higher the priority is. Go to step 2.9 to ensure that the parking request with a long waiting time is given priority. This not only improves customer satisfaction, but also optimizes the efficiency of resource use. The calculation formula of the customer's waiting time T0 is formula (1).

[0178] Step 2.9: Select the best RGVG from all idle RGVs according to the nearest and load balancing rate 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 ,ensuring efficient use of resources and avoiding some RGVs being in a high load state for a long period of time.

[0180] Step 2.10: According to 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: firstly, 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 car storage tasks and car retrieval 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 to G task The travel time required to start the mission is calculated using the formula (4).

[0185] In the embodiment of the present invention, 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. 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.

[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 estimated customer waiting time T is calculated. Y After that, determine the waiting time T Y Is it equal to or greater than the threshold? If the waiting time T Y If it is equal to or greater than the threshold, go to step 2.14; otherwise, go 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 according to 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, the 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 binding 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 G with the highest priority is determined according to the task binding method, task After the binding task, it is necessary to judge G task Is the bound task of G not empty? task If 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 lot 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 and provide 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 idle parking spaces according to 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, because it directly affects the vehicle access efficiency.

[0198] Step 3.2: Travel time T1 for transporting 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 ith free parking space and the parking spot, v is the average speed of the RGV when fully loaded, and 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 a vehicle between the i-th free parking space and the parking spot, t u is the time required for RGV to put down the vehicle each time, S Li is the vertical distance between the ith 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 blocking vehicle in front of the i-th free parking space to the free position, t wi is the congestion time of 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 screen all free parking spaces, and select the parking space with the shortest travel time, that is, select the travel time T1 from all free parking spaces i The least number of parking spaces is used as the optimal parking space. This not only improves parking efficiency, but also effectively reduces customers' waiting time, thereby optimizing the operating efficiency of the entire parking lot. By selecting the optimal parking space, the system ensures the best use of resources 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, is 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, is 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] At this stage, the system will traverse all idle RGVs and calculate the travel time required for them to reach the starting point of the specified task from their current position one by one. This calculation not only takes into account the horizontal and vertical distances, but also the RGV's no-load speed and the speed of the elevator. In this way, the system can have a more comprehensive understanding of the response time of each RGV, laying the foundation for the subsequent selection of the optimal RGV.

[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, all travel times calculated in the first step are 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 corresponding number of RGVs greater than 1? If so, proceed 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, to determine 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 , we need 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 whole selection process ends immediately.

[0214] Step 4.4: From all the minimum travel times T2 min The RGV with the smallest total load is selected as G RGV , end this selection.

[0215] When multiple RGVs can achieve the same minimum travel time T2 min When the system selects all RGVs that reach the minimum travel time, and further calculates 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 requirements, the use of resources is optimized and the overall operating efficiency 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 assignment 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 next 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-picking tasks in the system to determine whether there is a car-picking task with a task end point of 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 qualifying task is found, go to step 5.8.

[0222] Step 5.3: Search all parking tasks in the system to determine whether there is a parking task with a task end point of 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 pick-up 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 qualifying 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 from the current location of the task to 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 end 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 binding task set Ψ, the system can better evaluate the overall efficiency of the tasks and then select the optimal binding task from the binding task set Ψ.

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

[0229] Calculate all G RGV Complete tasks b and G in the bound task set 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 The smallest task b min As G task The pending binding tasks are checked to ensure that the system selects the optimal binding tasks, thereby improving resource utilization efficiency and reducing the 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 the 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 estimated 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, ending the entire binding process.

[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 a person skilled in the art can make several improvements without departing from the principle of the present invention, and these improvements should also be regarded as within the protection scope of the present invention.

Claims

1. A high-density parking lot scheduling method based on multi-directional mobile RGV, characterized in that: The steps include: Step 1: Determine whether the high-density parking lot dispatching 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 car picking task. If yes, proceed to step 3; otherwise, proceed to step 1. Step 3: Determine the idle RGV of the system; if yes, proceed to step 4, otherwise proceed to step 1; Step 4: According to the dynamic entrance and exit strategy of the high-density parking lot scheduling system, determine the number and location of the parking lot entrances and exits; Step 5: According to the high-density parking lot task scheduling method, the task priority, allocation scheme and target location are determined, and then the RGV starts to execute the task according to the shortest path; Step 6: Determine whether RGV has a conflict in executing the task. If so, proceed to step 7; otherwise, proceed to step 8. Step 7: Avoid collision according to the high-density parking lot traffic control strategy; Step 8: Determine whether the RGV has arrived at the parking space corresponding to the storage / retrieval of the 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 perform the task and go to step 6. Step 11: Determine whether the RGV has unfinished tasks. If the RGV continues to execute the task, 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 high-density parking lot scheduling system dynamic entrance and exit strategy includes the following steps: Step 1.1: Collect real-time traffic data of high-density parking lot entrances and exits and analyze the usage of the entrances and exits; Step 1.2: Determine whether the number of inlets and outlets needs to be adjusted. If so, proceed to step 1.3, otherwise, end the adjustment. Step 1.3: Determine whether the number of inlets / outlets has reached the extreme value. If so, end the adjustment, otherwise proceed to step 1.4; Step 1.4: Determine the number of entrances / 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 plan, and end 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 respectively. 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}, 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. A high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1, characterized in that: The high-density parking lot task scheduling method comprises the following steps: Step 2.1: Determine the number of idle RGVs according to 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 priority, allocation scheme and target location of the task and end the task scheduling. Step 2.3: Determine whether there is a parking task, if so, go to step 2.4, otherwise go to step 2.8; Step 2.4: Determine whether there is an empty 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 picking up tasks. If so, proceed to step 2.6; otherwise, proceed to step 2.

8. Step 2.6: The high-density parking lot dispatching system starts to assign 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 according to the parking space selection rule and proceed to step 2.9; Step 2.8: The high-density parking lot dispatching system starts to assign the car pickup task to the RGV, according to the customer's waiting time T a Determine the priority of the vehicle pickup task. The longer the waiting time T0 is, the higher the priority is. Go to step 2.

9. Step 2.9: Select the best RGV G from all idle RGVs according to the nearest and load balancing rate rules RGV , the highest priority task G task Assigned to G RGV ; Step 2.10: According to 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 according to the task binding method task Binding tasks; Step 2.13: Determine G task Is the binding 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.

5. A high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 4, characterized in that: The parking space selection rule comprises the following steps: Step 3.1: Determine the number N and location of idle parking spaces according to the real-time status of the high-density parking lot scheduling system; Step 3.2: Travel time T1 for transporting 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 ith free parking space and the parking spot, v is the average speed of the RGV when fully loaded, and d i is the number of times the RGV lifts a vehicle between the i-th free parking space and the parking spot, td is the time required for the RGV to lift a vehicle each time, and u i is the number of times the RGV puts down a 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 ith 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 blocking vehicle in front of the i-th free parking space to the free position, t ωi is the congestion time of 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.

6. A high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 4, 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, is 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, is the current position of the rth idle RGV and G task The vertical distance from the starting point of the task, is the no-load average 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 corresponding number of RGVs greater than 1? If so, proceed 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 The RGV with the smallest total load is selected as G RGV , end this selection.

7. A high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 4, 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 car storage tasks and car retrieval tasks in the system. For Task G task The travel time required for the corresponding vehicle to transport the goods from the mission starting point to the mission end point.

8. The high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 4 is characterized in that: The task binding method comprises the following steps: Step 5.1: Determine the assignment 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-picking tasks in the system to determine whether there is a car-picking task with a task end point of 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 to determine whether there is a parking task with a task end point of 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 from the current location of the task to 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 end 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(T4 b ),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.

9. The high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1 is characterized in that: The high-density parking lot traffic control strategy is to select an appropriate conflict avoidance method according to 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 a specific area, and a collision occurs. In narrow passages or areas where opposite-direction driving may occur, the collision avoidance method uses QR code positioning and semaphore mutual exclusion mechanism. When an RGV approaches, the semaphore becomes 1, preventing the RGV in the other direction from entering, ensuring that only one side can pass; 3) Resource competition: Multiple RGVs need to use the same resources at the same time, and the order in which the RGVs use them is determined based on priority rules.

10. A high-density parking lot scheduling method based on multi-directional mobile RGV according to claim 1, characterized in that: The parking / retrieval rules are as follows: 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 in the peak parking 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 in the peak vehicle retrieval period, the RGV will move the blocking vehicles to their original positions. The idle RGV scheduling rule is that when the RGV completes the task, it is determined whether the RGV power is lower than the 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 parking point and wait for the next task assignment.

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