A parking space automatic layout method and system based on network flow algorithm

Abstract

The present invention discloses a method and system for automatic parking space layout based on a network flow algorithm. The method comprises: identifying the layoutable intervals of parking spaces and passages based on the framework structure of an underground parking lot, and dividing the layoutable intervals into a plurality of grids; treating each screened grid as a node in a graph theory, and the connectivity relationship between each parking space node and its adjacent passage node as an edge, with the direction of the edge pointing from the parking space node to the passage node, and the weight of the edge being the maximum number of parking spaces that the parking space can accommodate, thereby obtaining a weighted directed graph of the underground parking lot; using a network flow algorithm to calculate the maximum flow from the entrance to the exit, and after repeated iterations, obtaining a layout scenario that maximizes the parking space capacity; and finally, determining the direction of the parking space exit based on constraints to complete the placement of the parking spaces. The method proposed by the present invention realizes the automatic layout of parking spaces, increases the flexibility of the layout, and shortens the parking space design cycle.

Description

Technical Field

[0001] The present invention relates to the technical field of parking lot design, and in particular to a parking space automatic layout method and system based on a network flow algorithm. Background Art

[0002] With the continued rapid development of China's economy, the number of cars in Chinese cities has increased rapidly, but parking resources are seriously insufficient. To solve the problem of severe shortage of urban parking spaces, underground parking lots have become a new development trend.

[0003] However, compared to the rapidly growing number of underground parking lots, research on underground parking layouts has lagged significantly behind. In practical applications, underground parking lot layout design relies entirely on the designer's experience. However, underground parking lots have complex contours and internal obstacles, and numerous factors influence parking layout. The flexible arrangement of parking spaces makes layout design difficult, manual design is time-consuming, and the accuracy of the results is limited by the designer's experience.

[0004] In summary, existing technologies generally still have problems such as low design efficiency, limited layout options, and high manual participation, which urgently need to be solved through improved technology. Summary of the Invention

[0005] In response to the problem of insufficient space utilization in parking space design in the prior art, the present invention provides a parking space automatic layout method and system based on a network flow algorithm, which can fully improve the space utilization rate, parking space design efficiency and layout flexibility of the parking lot.

[0006] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] A parking space automatic layout method based on a network flow algorithm, comprising:

[0008] Step 1: Identify the layout range of parking spaces and passages based on the underground parking structure, divide the layout range into several grids, and select the grids where parking spaces or passages can be laid out;

[0009] Step 2: Take each grid screened in step 1 as a node in the graph theory, and take the entrance node of the underground parking lot as the source node and the exit node as the sink node. Under the constraints of the conditions, randomly generate a directed path from the source node to the sink node as a channel; the nodes passed by the channel are all channel nodes, and the remaining nodes are parking space nodes; the connectivity between each parking space node and its adjacent channel node is regarded as an edge, with the direction of the edge pointing from the parking space node to the channel node, and the weight of the edge is the maximum number of parking spaces that the parking space can accommodate. In this way, a weighted directed graph of the underground parking lot is obtained;

[0010] The constraint condition is: the adjacent nodes of each parking space node include at least one channel node;

[0011] Step 3: Use the network flow algorithm to calculate the maximum flow from the source node to the sink node;

[0012] Step 4: Determine whether there are other directed paths from the source node to the sink node in the graph. If so, execute steps 2 and 3; otherwise, execute step 5.

[0013] Step 5: Find the maximum value among all the maximum flows from the source node to the sink node, determine the exit direction of each parking space based on the parking space layout information corresponding to the maximum value and the underground parking lot framework structure constraints, and finally realize the placement of the parking spaces.

[0014] Furthermore, the underground parking lot frame structure is a building element including columns and walls.

[0015] Furthermore, in the step 1, irregular grids are eliminated by judging the shape, length, and width of the grid and finding the intersection within the grid, thereby obtaining a grid that can be used to layout parking spaces or passages.

[0016] Furthermore, the network flow algorithm is any one of the Ford-Fulkerson algorithm, the Dinic algorithm or the Edmonds-Karp algorithm.

[0017] Furthermore, in step 2, the specific sub-steps of randomly generating a directed path from the source node to the sink node under the constraints are as follows:

[0018] First, the source node and the sink node are both channel nodes. The source node is the first channel node on the directed path. Starting from the first channel node, an adjacent node close to the sink node is selected from the adjacent nodes of the first channel node as the second channel node. Then, an adjacent node close to the sink node is selected from the adjacent nodes of the second channel node as the third channel node. And so on, all the channel nodes are obtained, thus obtaining a directed path from the source node to the sink node.

[0019] Furthermore, the Euclidean distance is used to determine the proximity between the adjacent nodes and the sink node.

[0020] An automatic parking space layout system based on a network flow algorithm, the system comprising:

[0021] An identification module is used to identify the layout intervals of parking spaces and passages based on the framework structure of the underground parking lot, divide the layout intervals into a number of grids, and screen out the grids where parking spaces or passages can be laid out;

[0022] The graph construction module is used to treat each filtered grid as a node in graph theory, with the underground parking lot entrance node as the source node and the exit node as the sink node. Under the constraints, a directed path from the source node to the sink node is randomly generated as a channel; the nodes passed by the channel are regarded as channel nodes, and the remaining nodes are regarded as parking space nodes; the connectivity between each parking space node and its adjacent channel node is regarded as an edge, with the direction of the edge pointing from the parking space node to the channel node, and the weight of the edge is the maximum number of parking spaces that the parking space can accommodate, so as to construct a weighted directed graph of the underground parking lot; the constraints are: the adjacent nodes of each parking space node contain at least one channel node;

[0023] A calculation module, used to calculate the maximum flow from the source node to the sink node;

[0024] The placement module is used to extract the maximum value of all the maximum flows from the source node to the sink node, determine the exit direction of each parking space based on the parking space layout information corresponding to the maximum value and the structural constraints of the underground parking lot framework, and finally realize the placement of the parking spaces.

[0025] The beneficial effects of the present invention are:

[0026] The network flow algorithm-based automatic parking space layout method and system of the present invention can quickly and easily implement the automatic layout of underground parking lots. It is simple to operate, does not require extensive human intervention, avoids tedious and repetitive design processes, and effectively improves parking space design efficiency. It also fully improves parking space utilization, reduces designer workload, and allows for adjustments and changes to parking lot plans based on different scenarios and needs, increasing parking lot flexibility and adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flowchart of the automatic parking space layout method based on the network flow algorithm.

[0028] Figure 2 This is a schematic diagram of the framework structure of an underground parking lot.

[0029] Figure 3 This is a grid diagram of an underground parking lot after automatic identification.

[0030] Figure 4 This is a schematic diagram of an underground parking lot layout scenario that can provide maximum parking space capacity.

[0031] Figure 5 This is a structural diagram of the automatic parking space layout system based on the network flow algorithm. DETAILED DESCRIPTION

[0032] The present invention will be further described below with reference to the following examples. The following examples are provided only to facilitate understanding of the present invention. It should be noted that, without departing from the principles of the present invention, a number of improvements and modifications may be made to the present invention by those skilled in the art, and such improvements and modifications fall within the scope of the claims of the present invention.

[0033] The present invention's automatic parking space layout method, based on a network flow algorithm, first identifies the layout intervals of parking spaces and passageways based on the underground parking structure. It then constructs these layout intervals into a weighted directed graph. A maximum flow algorithm is used to calculate the maximum flow from entrance to exit. After repeated iterations, a layout scenario that maximizes parking capacity is obtained. Finally, the parking spaces are arranged based on constraints to determine the exit direction. This method improves parking space utilization, enhances parking space design efficiency, reduces designer workload, and enhances layout flexibility.

[0034] Figure 1 FIG. 1 is a flow chart of a method for automatic parking space layout based on a network flow algorithm according to an embodiment of the present invention. Figure 1 As shown, including:

[0035] Step 101 : Identify the layout range of parking spaces and passages according to the framework structure of the underground parking lot, divide the layout range into a plurality of grids, and select the grids where parking spaces or passages can be laid out.

[0036] The frame structure of the underground parking lot is a building element including columns and walls. The columns are regularly arranged in the horizontal or vertical direction and exist in the form of rectangles. The walls exist in the form of straight lines or polylines, such as Figure 2 shown.

[0037] In the drawing, the area enclosed by every four columns can determine a rectangular layout interval. By traversing all the columns, all the layout intervals in the drawing can be obtained. These rectangular layout intervals are arranged like a grid. Each grid represents a parking space or a passage, such as Figure 3 shown.

[0038] In the above-mentioned process of extracting layout intervals, this method can automatically exclude irregular layout intervals in the drawing by judging the grid shape, length, and width and intersecting the grid internally. For example, there are obstacles in the grid, or the length and width of the grid do not meet the space for at least one parking space, or the grid shape affects vehicle parking.

[0039] When executing the following steps, these irregular layout intervals will be automatically ignored.

[0040] In step 102, each grid is treated as a node in a graph, with the underground parking lot entrance node S as the source node and the exit node T as the sink node. A constraint is given: each parking space node's adjacent nodes must include at least one access node. Based on this constraint, a directed path from S to T is randomly generated as a access node. All nodes passed through by the access node are access nodes, and the remaining nodes are parking space nodes. The connectivity between each parking space node and its adjacent access node is represented as an edge, with the direction of the edge pointing from the parking space node to the access node. The weight of the edge is the maximum number of parking spaces that the space can accommodate (greater than or equal to 1). This yields a weighted directed graph for the underground parking lot.

[0041] Here, we only consider underground parking lots with a single entrance and exit. Based on the maximum number of rows (m) and columns (n) of the grid graph, we define the position index of each grid as (i, j), where i represents the row of the grid and j represents the column of the grid, where i∈{1, 2...m} and j∈{1, 2,...n}.

[0042] Node S and node T are both channel nodes, and node S is the first channel node on the directed path. Starting from the channel node, select an adjacent node close to node T from the adjacent nodes of the channel node as the second channel node, and then select an adjacent node close to node T from the adjacent nodes of the second channel node as the third channel node. And so on, all channel nodes are obtained, thus obtaining a directed path from node S to node T.

[0043] As one implementation method, Euclidean distance is used to determine the proximity between the adjacent node and the T node.

[0044] Step 103: Calculate the maximum flow value from the inlet node (S) to the outlet node (T).

[0045] The process of calculating the maximum flow from S to T may be solved using the Ford-Fulkerson algorithm, the Dinic algorithm, or the Edmonds-Karp algorithm, but is not limited to these three methods.

[0046] Step 104, determine whether there are other directed paths from S to T in the graph. If so, execute steps 102 and 103 again; otherwise, execute step 105.

[0047] For the weighted directed graph constructed based on the underground parking lot, the directed paths from S to T are limited, so step 105 must be executed after multiple iterations.

[0048] Step 105, find the maximum value of these maximum flow values ​​Value, recorded as MaxV; according to the parking space layout information corresponding to MaxV and the underground parking lot framework structure constraints, determine the exit direction of each parking space, and finally realize the placement of the parking spaces.

[0049] Among them, the parking space layout scenario corresponding to MaxV can maximize the parking space capacity, such as Figure 4 shown. Figure 4 Schematic diagram of underground parking lot layout scenario that can provide maximum parking space capacity.

[0050] Among them, the process of judging the parking space exit direction not only depends on the parking space layout information corresponding to MaxV, but also needs to consider constraints such as obstacles in the underground parking lot. Figure 4 For example, a parking space node in the example has an adjacent channel node on the upper side and an adjacent channel node on the right side. However, since there is a solid wall between it and the adjacent channel node on the upper side, the exit direction of this parking space node can only point to the adjacent channel node on the right side.

[0051] On the other hand, the present invention provides a parking space automatic layout system based on network flow algorithm, such as Figure 5 Shown, including:

[0052] The identification module 201 is used to identify the layout range of parking spaces and passages according to the framework structure of the underground parking lot, divide the layout range into a number of grids, and select the grids where parking spaces or passages can be laid out.

[0053] The graph construction module 202 is used to treat each filtered grid as a node in the graph theory, the underground parking entrance node as the source node, the exit node as the sink node, and randomly generate a directed path from the source node to the sink node as a channel under the constraints of the constraints; the nodes passed by the channel are used as channel nodes, and the remaining nodes are used as parking space nodes; the connectivity relationship between each parking space node and its adjacent channel node is used as an edge, the direction of the edge is from the parking space node to the channel node, and the weight of the edge is the maximum number of parking spaces that the parking space can accommodate, so as to construct a weighted directed graph of the underground parking lot; the constraint condition is: the adjacent nodes of each parking space node contain at least one channel node.

[0054] The calculation module 203 is used to calculate the maximum flow from the source node to the sink node.

[0055] The placement module 204 is used to extract the maximum value of all the maximum flows from the source node to the sink node, determine the exit direction of each parking space based on the parking space layout information corresponding to the maximum value and the underground parking lot framework structure constraints, and finally realize the placement of the parking spaces.

[0056] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0057] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A parking space automatic layout method based on network flow algorithm, characterized in that: include: Step 1: Identify the layout range of parking spaces and passages based on the underground parking structure, divide the layout range into several grids, and select the grids where parking spaces or passages can be laid out; Step 2: Take each grid screened in step 1 as a node in the graph theory, and take the entrance node of the underground parking lot as the source node and the exit node as the sink node. Under the constraints of the conditions, randomly generate a directed path from the source node to the sink node as a channel; the nodes passed by the channel are all channel nodes, and the remaining nodes are parking space nodes; the connectivity between each parking space node and its adjacent channel node is regarded as an edge, with the direction of the edge pointing from the parking space node to the channel node, and the weight of the edge is the maximum number of parking spaces that the parking space can accommodate. In this way, a weighted directed graph of the underground parking lot is obtained; The constraint condition is: the adjacent nodes of each parking space node include at least one channel node; Step 3: Use the network flow algorithm to calculate the maximum flow from the source node to the sink node; Step 4: Determine whether there are other directed paths from the source node to the sink node in the graph. If so, execute steps 2 and 3; otherwise, execute step 5. Step 5: Find the maximum value among all the maximum flows from the source node to the sink node, determine the exit direction of each parking space based on the parking space layout information corresponding to the maximum value and the underground parking lot framework structure constraints, and finally realize the placement of the parking spaces.

2. The automatic parking space layout method based on network flow algorithm according to claim 1 is characterized in that: The underground parking frame structure is a building element including columns and walls.

3. The automatic parking space layout method based on network flow algorithm according to claim 1 is characterized in that: In the step 1, irregular grids are eliminated by determining the shape, length, and width of the grid and intersecting the grid internally, thereby obtaining a grid suitable for arranging parking spaces or passages.

4. The automatic parking space layout method based on network flow algorithm according to claim 1 is characterized in that: The network flow algorithm is any one of the Ford-Fulkerson algorithm, the Dinic algorithm or the Edmonds-Karp algorithm.

5. The automatic parking space layout method based on network flow algorithm according to claim 1 is characterized in that: In step 2, the specific sub-steps of randomly generating a directed path from the source node to the sink node under the constraints are as follows: First, both the source node and the sink node are channel nodes. The source node is the first channel node on the directed path. Starting from the first channel node, an adjacent node close to the sink node is selected from the adjacent nodes of the first channel node as the second channel node. Then, an adjacent node close to the sink node is selected from the adjacent nodes of the second channel node as the third channel node. And so on, all the channel nodes are obtained, thus obtaining a directed path from the source node to the sink node.

6. The automatic parking space layout method based on network flow algorithm according to claim 1 is characterized in that: The Euclidean distance is used to determine the proximity between the adjacent nodes and the sink node.

7. A parking space automatic layout system based on network flow algorithm, characterized in that: The system includes: An identification module is used to identify the layout intervals of parking spaces and passages based on the framework structure of the underground parking lot, divide the layout intervals into a number of grids, and select the grids where parking spaces or passages can be laid out; The graph construction module is used to treat each filtered grid as a node in graph theory, with the underground parking lot entrance node as the source node and the exit node as the sink node. Under the constraints, a directed path from the source node to the sink node is randomly generated as a channel; the nodes passed by the channel are regarded as channel nodes, and the remaining nodes are regarded as parking space nodes; the connectivity between each parking space node and its adjacent channel node is regarded as an edge, with the direction of the edge pointing from the parking space node to the channel node, and the weight of the edge is the maximum number of parking spaces that the parking space can accommodate, so as to construct a weighted directed graph of the underground parking lot; the constraints are: the adjacent nodes of each parking space node contain at least one channel node; A calculation module, used to calculate the maximum flow from the source node to the sink node; The placement module is used to extract the maximum value of all the maximum flows from the source node to the sink node, determine the exit direction of each parking space based on the parking space layout information corresponding to the maximum value and the structural constraints of the underground parking lot framework, and finally realize the placement of the parking spaces.

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