A traffic cell division method and system, electronic equipment and storage medium

Abstract

The application discloses a traffic cell division method and system, an electronic device and a storage medium, wherein the method comprises the following steps: acquiring bus service area data and boundary data; performing unit division on a to-be-divided area according to the boundary data to obtain a basic unit set; performing clustering processing on the basic unit set according to the bus service area data to obtain an initial traffic cell division result; and performing abnormal correction processing on the initial traffic cell division result to obtain a target traffic cell division result. The application divides the area based on bus service characteristics, takes the bus service characteristics as the division standard, improves the accuracy of bus service area division evaluation, and can be widely applied to the technical field of public transportation planning.

Description

Technical Field

[0001] This invention relates to the field of public transportation planning technology, and in particular to a method, system, electronic device and storage medium for dividing traffic zones. Background Technology

[0002] Public buses, as a sustainable and green mode of transportation, can effectively alleviate traffic congestion caused by the development of private cars. However, due to the mismatch between public bus supply and residents' travel demand, bus occupancy rates are typically low, necessitating consideration of regional traffic characteristics. Traffic analysis cells, often used to divide the entire study area into smaller zones, are fundamental units in traffic planning and play a crucial role. Current technologies, which use regional traffic accident characteristics, land use characteristics, and residents' travel characteristics as criteria for dividing traffic analysis cells, fail to consider the characteristics of regional public transport services, resulting in poor efficiency. Therefore, the technical problems in these technologies urgently need to be addressed. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a traffic zone division method, system, electronic device, and storage medium to improve the efficiency of traffic zone division.

[0004] On one hand, the present invention provides a method for dividing traffic zones, including:

[0005] Obtain bus service area and boundary data;

[0006] The region to be divided is divided into units based on the boundary data to obtain a set of basic units;

[0007] The basic unit set is clustered based on the bus service area data to obtain the initial traffic zone division results;

[0008] The initial traffic zone division result is subjected to anomaly correction processing to obtain the target traffic zone division result.

[0009] Optionally, obtaining public transport service area data and boundary data includes:

[0010] Obtain the bus stops in the area to be divided, and determine the bus service area data based on the area of ​​the bus stops;

[0011] Obtain the street and town boundaries of the area to be divided and determine the boundary data.

[0012] Optionally, the step of dividing the region to be divided into units based on the boundary data to obtain a set of basic units includes:

[0013] The region to be divided is processed into a grid to obtain a gridded region;

[0014] The boundary of the gridded region is reshaped based on the boundary data to obtain a set of basic units.

[0015] Optionally, the step of clustering the basic unit set based on the public transport service area data to obtain the initial traffic zone division result includes:

[0016] The basic unit set is marked to obtain a marked unit set, which includes multiple basic units that are marked and numbered.

[0017] Based on a first preset threshold, the basic units in the set of labeled units are subjected to regional clustering to obtain the initial traffic zone division results.

[0018] Optionally, the step of performing regional clustering processing on the set of marked units according to a first preset threshold to obtain the initial traffic zone division result includes:

[0019] Select the base unit with the smallest number from the set of marked units as the starting unit;

[0020] The starting unit is assigned to a traffic zone, and a basic unit is selected from the set of marked units according to the number value and assigned to the traffic zone, until the public transport service area of ​​the traffic zone is greater than or equal to the first preset threshold or the basic units that can be selected in the set of marked units are empty, thus obtaining a public transport service zone.

[0021] Return to the step of selecting the smallest numbered basic unit from the set of marked units as the starting unit, until the set of marked units is empty, to obtain the initial traffic zone division result, which includes multiple bus service zones.

[0022] Optionally, the step of performing anomaly correction processing on the initial traffic cell division result to obtain the target traffic cell division result includes:

[0023] In the initial traffic zone division results, bus service zones with a bus service area less than a first preset threshold are identified as first abnormal areas.

[0024] When the public transport service area of ​​the first abnormal area is less than the second preset threshold, the first abnormal area is merged with the adjacent public transport service area to obtain the target traffic area division result.

[0025] Optionally, the step of performing anomaly correction processing on the initial traffic cell division result to obtain the target traffic cell division result further includes:

[0026] Compactness calculation is performed on each public transport service zone in the initial traffic zone division results to obtain a compactness result set;

[0027] From the set of compactness results, select bus service areas with a compactness less than a third preset threshold and determine them as the second abnormal area;

[0028] The second abnormal region is subjected to shape cutting and merging processing to obtain the target traffic zone division result.

[0029] On the other hand, embodiments of the present invention also provide a traffic zone division system, including:

[0030] The first module is used to acquire bus service area data and boundary data;

[0031] The second module is used to divide the region to be divided into units based on the boundary data to obtain a set of basic units.

[0032] The third module is used to perform clustering processing on the basic unit set based on the bus service area data to obtain the initial traffic zone division results.

[0033] The fourth module is used to perform anomaly correction processing on the initial traffic zone division results to obtain the target traffic zone division results.

[0034] On the other hand, embodiments of the present invention also disclose an electronic device, including a processor and a memory;

[0035] The memory is used to store programs;

[0036] The processor executes the program to implement the method described above.

[0037] On the other hand, embodiments of the present invention also disclose a computer-readable storage medium storing a program that is executed by a processor to implement the methods described above.

[0038] On the other hand, embodiments of the present invention also disclose a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned method.

[0039] Compared with the prior art, the present invention has the following technical effects: By acquiring public transport service area data and performing clustering processing on the areas to be divided, the present invention can divide the areas based on public transport service characteristics and use public transport service characteristics as the division criteria, thereby improving the accuracy of public transport service zoning evaluation. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart of a traffic zone division method provided in an embodiment of this application;

[0042] Figure 2 This is a schematic diagram of a public transport service area allocation rule provided in an embodiment of this application;

[0043] Figure 3 This is a schematic diagram of a basic unit generation method provided in an embodiment of this application;

[0044] Figure 4 This is a schematic diagram of traffic zone clustering provided in an embodiment of this application;

[0045] Figure 5 This is a flowchart illustrating a clustering algorithm provided in an embodiment of this application;

[0046] Figure 6 This is a schematic diagram of a traffic zone anomaly correction provided in an embodiment of this application;

[0047] Figure 7 This is a schematic diagram of traffic cell compactness under another traffic cell anomaly situation provided in this application embodiment;

[0048] Figure 8 This is a schematic diagram of the abnormal shape of a traffic cell in another traffic cell situation provided in an embodiment of this application;

[0049] Figure 9 This is a schematic diagram of another traffic zone anomaly correction provided in an embodiment of this application;

[0050] Figure 10 This is a schematic diagram of a traffic zone division system provided in an embodiment of this application;

[0051] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0053] In related technologies, methods for generating traffic analysis zones generally divide traffic zones by maximizing homogeneity within and between regions. For example, hierarchical heuristic algorithms are used to cluster grid cells using origin-destination (OD) data to maximize travel similarity between each region; or genetic algorithm-based clustering algorithms are used to cluster cells into traffic zones based on various regional characteristics, including resident travel similarity. However, these related technologies do not divide traffic zones based on the characteristics of regional public transport services.

[0054] In view of this, this application provides a traffic zone division method. This division method can be applied to a terminal, a server, or software running on either a terminal or a server. The terminal can be a tablet, laptop, desktop computer, etc., but is not limited to these. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0055] Reference Figure 1 This invention provides a method for dividing traffic zones, including:

[0056] S101. Obtain bus service area data and boundary data;

[0057] S102. Divide the region to be divided into units according to the boundary data to obtain a set of basic units;

[0058] S103. Cluster the basic unit set according to the bus service area data to obtain the initial traffic zone division result;

[0059] S104. Perform anomaly correction processing on the initial traffic cell division result to obtain the target traffic cell division result.

[0060] This invention proposes a traffic zone delineation method based on public transport service characteristics. This method divides the study area into smaller spatial units, which are named public transport service analysis zones. Unlike other regional delineation methods, this invention uses public transport service characteristics as the delineation standard, improving the accuracy of public transport service zoning evaluation. The basic process of this public transport service characteristic-based traffic zone delineation method involves dividing the study area into small basic units and then clustering them. Therefore, the public transport service characteristic-based traffic zone delineation method has two steps: basic unit generation and clustering. First, public transport service area data and boundary data are acquired. Then, the area to be delineated is divided into units based on the boundary data, resulting in a set of basic units. Public transport service area data includes bus stops, the public transport service area of ​​bus stops, and the public transport service area, etc. The set of basic units includes multiple basic units. Then, the set of basic units is clustered based on the public transport service area data to obtain the initial traffic zone delineation result. Finally, the initial traffic zone delineation result is corrected for anomalies to obtain the target traffic zone delineation result. The traffic zone division method of this invention can make the bus service area of ​​each zone similar based on the service range characteristics of bus stops, thus providing a regional analysis basis for subsequent analysis of bus services in each area.

[0061] As a further optional implementation, in step S101 above, obtaining the public transport service area data and boundary data includes:

[0062] Obtain the bus stops in the area to be divided, and determine the bus service area data based on the area of ​​the bus stops;

[0063] Obtain the street and town boundaries of the area to be divided and determine the boundary data.

[0064] In this embodiment of the invention, public service area data includes bus stops, the bus service area of ​​the bus stops, and the bus service area, etc. By acquiring the bus stops within the area to be divided, where each bus stop may include two stops serving the upstream and downstream vehicles of a bus route respectively, the bus service area of ​​the bus stop is determined to be a circular area with a radius of 300 meters. For example... Figure 2 As shown in the diagram, the black dots represent bus stops (e.g., points A, B, C, D, E), and the circular areas along these points are bus service areas. The size of the circular area for the j-th bus stop is denoted as s. j The area of ​​overlapping regions is calculated only once. For example... Figure 2 As shown, the bus service areas of bus station A and bus station B overlap, and the area of ​​the overlapping area is s. overlap(A,B) Then the bus service area size of bus station A and bus station B is s. A +s B -soverlap(A,B) If a bus service area falls within multiple bus service zones, then the bus service area is divided accordingly, and the size of the bus service area of ​​the j-th station in zone z is represented as... like Figure 2 As shown, the bus service area of ​​bus stop C is divided into two parts, namely bus service area 1 and bus service area 2, with areas of 1 and 2 respectively. and The bus service area located within bus service zone 1 is: The bus service area located within Bus Service Community 2 is In this embodiment, bus service zone 1 and bus service zone 2 represent two different bus service analysis zones. Additionally, when dividing traffic zones, this embodiment also considers boundary data, which can be the street / township boundaries. Boundary data is obtained by acquiring the street / township boundaries of the area to be divided.

[0065] As a further optional implementation, in step S102 above, the step of dividing the region to be divided into units based on the boundary data to obtain a set of basic units includes:

[0066] The region to be divided is processed into a grid to obtain a gridded region;

[0067] The boundary of the gridded region is reshaped based on the boundary data to obtain a set of basic units.

[0068] In this embodiment of the invention, the region to be divided is partitioned into units based on the boundary data, resulting in multiple basic units, which can be of any shape. To facilitate generation, searching, and clustering, this embodiment uses a grid as the basic unit to generate the region. (Refer to...) Figure 3 Using a grid as the basic unit, the region to be divided is processed into a gridded region, and the grid located on the boundary of the partition is reshaped based on the boundary to obtain a set of basic units.

[0069] As a further optional implementation, in step S103 above, the step of clustering the basic unit set based on the public transport service area data to obtain the initial traffic zone division result includes:

[0070] The basic unit set is marked to obtain a marked unit set, which includes multiple basic units that are marked and numbered.

[0071] Based on a first preset threshold, the basic units in the set of labeled units are subjected to regional clustering to obtain the initial traffic zone division results.

[0072] In this embodiment of the invention, the basic unit set is labeled, and each basic unit in the set is numbered from southwest to northeast, with each number representing the ID of the basic unit. (Refer to...) Figure 4 This embodiment of the invention provides an example containing 25 basic units. First, the basic units are numbered according to step 1. Unit 1 is located in the southwest corner of the area, and Unit 2 is located to the north of Unit 1. After all the basic units in the first column have been numbered, i.e., no more basic units can be found to the north of Unit 5, the process moves to the bottom of the second column, i.e., the southwest corner of the remaining basic units, and continues numbering. These steps are repeated until all basic units have been numbered. Then, the basic units in the set of marked units are subjected to regional clustering processing according to a first preset threshold to obtain the initial traffic zone division results. The first preset threshold is the standard area for public transport service, which can be set to 0.9 km² in this embodiment of the invention. 2 It is approximately the size of the bus service area at the station (0.3km). 2 The first preset threshold can be set according to the needs of the bus operator.

[0073] Further, as an optional implementation, the step of performing regional clustering processing on the set of marked units according to a first preset threshold to obtain the initial traffic zone division result includes:

[0074] Select the base unit with the smallest number from the set of marked units as the starting unit;

[0075] The starting unit is assigned to a traffic zone, and a basic unit is selected from the set of marked units according to the number value and assigned to the traffic zone, until the public transport service area of ​​the traffic zone is greater than or equal to the first preset threshold or the basic units that can be selected in the set of marked units are empty, thus obtaining a public transport service zone.

[0076] Return to the step of selecting the smallest numbered basic unit from the set of marked units as the starting unit, until the set of marked units is empty, to obtain the initial traffic zone division result, which includes multiple bus service zones.

[0077] In this embodiment of the invention, the smallest-numbered basic unit is selected from the set of marked units as the starting unit. This starting unit is the starting point for one aggregation in the divided traffic zones. Then, the starting unit is assigned to a traffic zone, and basic units are selected from the set of marked units according to their number values ​​and assigned to the traffic zone. The selection rule is to select basic units adjacent to the traffic zone one by one according to their number values ​​from smallest to largest, until the public transport service area of ​​the traffic zone is greater than or equal to the first preset threshold, or the set of marked units is empty. At this point, clustering stops, and a public transport service zone is obtained. Then, the process returns to selecting the starting unit and repeats the above steps until the set of marked units has been completely divided, resulting in the initial traffic zone division result. (Refer to...) Figure 4 Begin region clustering. To cluster the first region, cell 1, select the smallest unselected basic unit with the smallest ID, i.e., cell 1, as the starting point and add it to the cell cluster. Within the basic unit set. Because the area of ​​the public transport service area in Community 1 is smaller than the previously defined standard area δ = 0.9 km². 2 Therefore, the unselected basic units surrounding cell 1, namely units 2, 6, and 7, are selected and added to the set of basic units to be added (B). 待选 Because after adding units 2, 6, and 7 to Community 1, the public transport service area is still smaller than the standard size δ, and unit 2 has the smallest ID, so we first select to add them, and then select units 6 and 7. Now, B 待选 Leave it empty, then select a new basic unit. That is, select units 3, 8, 11, 12, and 13. When adding unit 3, the area of ​​the bus service area in cell 1 is greater than the standard δ, at which point the clustering of cell 1 is complete. The clustering of the next bus service cell begins with the smallest unselected basic unit, unit 4, and then units 5, 8, 9, and 10 are selected sequentially to cluster cell 2. Figure 4 In the process, each starting unit is marked with a pentagram, and clusters are performed on cell 1 (units 1, 2, 3, 6, 7), cell 2 (units 4, 5, 8, 9, 10), cell 3 (units 11, 12, 13, 16, 17, 18, 21, 22), and cell 4 (units 14, 15, 19, 20, 23, 24, 25) based on a given clustering algorithm.

[0078] Reference Figure 5The clustering algorithm of this invention comprises the following steps: Cells are labeled using basic unit numbers, followed by initialization, which initializes a candidate unit set and a set of units to be added. The candidate unit set consists of basic units adjacent to the traffic cell, and the set of units to be added is the labeled unit set. Next, a standard check is performed, i.e., basic unit clustering is performed according to defined partitioning criteria. In this invention, a first preset threshold is set as the partitioning criterion for clustering basic units. Basic units are selected to complete the clustering of one traffic cell. The above steps are then repeated for the next traffic cell until all units are clustered. This invention also corrects for cells with anomalous shapes, proposing two special cases, A and B. By correcting these special cases, the output is the public transport service cell.

[0079] As a further optional implementation, the step of performing anomaly correction processing on the initial traffic cell division result to obtain the target traffic cell division result includes:

[0080] In the initial traffic zone division results, bus service zones with a bus service area less than a first preset threshold are identified as first abnormal areas.

[0081] When the public transport service area of ​​the first abnormal area is less than the second preset threshold, the first abnormal area is merged with the adjacent public transport service area to obtain the target traffic area division result.

[0082] In this embodiment of the invention, special case A occurs when the public transport service area of ​​a traffic cell in the initial traffic cell division result is not greater than a first preset threshold. In this case, the aggregation process for that area will stop, and the traffic cell will be identified as a first abnormal area. For example, ... Figure 6 As shown, after forming cell 4, cell 22 is selected to form the next cell, whose public transport service area is smaller than a first preset threshold, but there are no unselected basic cells around it. This embodiment of the invention allows the size of the public transport service area of ​​a traffic cell to be smaller than the first preset threshold, but the deviation cannot be too large. Therefore, this embodiment of the invention sets a second preset threshold μδ. When the public transport service area of ​​a traffic cell is smaller than μδ, the traffic cell will be merged with its adjacent areas. μ is a scaling factor ranging from 0 to 1, which can be set according to the analysis needs, and δ represents the first standard threshold.

[0083] As a further optional implementation, the step of performing anomaly correction processing on the initial traffic cell division result to obtain the target traffic cell division result further includes:

[0084] Compactness calculation is performed on each public transport service zone in the initial traffic zone division results to obtain a compactness result set;

[0085] From the set of compactness results, select bus service areas with a compactness less than a third preset threshold and determine them as the second abnormal area;

[0086] The second abnormal region is subjected to shape cutting and merging processing to obtain the target traffic zone division result.

[0087] In this embodiment of the invention, reference is made to Figures 7-9 Special case B is the existence of a banded region (such as...) Figure 7 (3) This particular form reduces area compactness and may distort the impact of transit stops. To illustrate this, the compactness ratios are as follows.

[0088]

[0089] In the formula, A i A' is the area of ​​community i (unit: square kilometers), while A' is... i It is the area of ​​the smallest circumcircle of cell i (in square kilometers). A larger τ i This implies a higher degree of compactness. Figure 7 In the diagram, community 3 has a large circumcircle region marked by a colored dashed line, exhibiting low compactness. To address the issue arising from special case B, this embodiment of the invention can set a third preset threshold, which can be set according to actual conditions, such as 0.5. By calculating the compactness of each public transport service community in the initial traffic community division results, public transport service communities with a compactness less than the third preset threshold are identified as second abnormal regions. This second abnormal region may have a strip-like shape, in which case that region is selected. For example, Figure 8 S′2 in medium-sized area 3 is a strip-shaped portion. w It is the length of the shorter side of the strip region, x l It is the length of the longer side of the strip region. This embodiment of the invention considers modifying cell 3 (if x...). w ≤2α and x l ≥10α), where α represents the side length of the basic unit. This condition can be changed according to the analysis requirements. This modification divides cell 3 into two parts, S′1 and S′2, and merges S′2 with the neighboring area that shares the longest side of cell 3 and has the smallest area. In this example, the selected neighboring area is cell 3, and this embodiment combines S′2 with cell 2. The modification is as follows: Figure 9 As shown. During the modification process, A1, A′1, and A′2 remain unchanged. A2 increases, and τ2 increases. A3 and A′3 both decrease, but the change in A′3 is much larger. Therefore, τ3 increases, meaning the area compactness improves. Finally, by performing shape cutting and merging processing on the second abnormal region, the traffic cell is corrected to obtain the corrected traffic cell, thus determining the final target traffic cell division result.

[0090] Reference Figure 10 This invention also provides a traffic zone division system, comprising:

[0091] The first module 1001 is used to acquire bus service area data and boundary data;

[0092] The second module 1002 is used to divide the region to be divided into units based on the boundary data to obtain a set of basic units.

[0093] The third module 1003 is used to perform clustering processing on the basic unit set based on the bus service area data to obtain the initial traffic zone division result.

[0094] The fourth module 1004 is used to perform anomaly correction processing on the initial traffic zone division result to obtain the target traffic zone division result.

[0095] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0096] and Figure 11 Corresponding to the method described above, this embodiment of the invention also provides an electronic device, including a processor 1101 and a memory 1102; the memory is used to store a program; the processor executes the program to implement the method described above.

[0097] and Figure 1 Corresponding to the method described above, embodiments of the present invention also provide a computer-readable storage medium storing a program that is executed by a processor to implement the method described above.

[0098] This invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to perform... Figure 1 The method shown.

[0099] In summary, the embodiments of the present invention have the following advantages: The embodiments of the present invention can ensure that each community has bus stop service area coverage, facilitating the calculation of stop density and improving the fitting degree of the relationship diagram between bus service features. Furthermore, by correcting for abnormal situations, the embodiments of the present invention can increase the compactness of the area, avoid the generation of narrow and elongated areas, and better reflect the actual situation of bus services.

[0100] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is altered and sub-operations described as part of a larger operation are executed independently.

[0101] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the described functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0102] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0103] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0104] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0105] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0106] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0107] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0108] The above is a detailed description of the preferred embodiments of the present invention, but the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A traffic cell division method, characterized by, The method comprises: acquiring bus service area data and boundary data; unit dividing the to-be-divided area according to the boundary data to obtain a basic unit set; performing clustering processing on the basic unit set according to the bus service area data to obtain an initial traffic subdistrict division result; performing abnormal correction processing on the initial traffic subdistrict division result to obtain a target traffic subdistrict division result; the clustering processing on the basic unit set according to the bus service area data to obtain the initial traffic subdistrict division result comprises: performing marking processing on the basic unit set to obtain a marked unit set, the marked unit set comprising a plurality of marked basic units; performing area clustering processing on the basic units in the marked unit set according to a first preset threshold to obtain the initial traffic subdistrict division result; the first preset threshold is a bus service standard area; the area clustering processing on the marked unit set according to the first preset threshold to obtain the initial traffic subdistrict division result comprises: selecting a basic unit with the smallest number from the marked unit set as a starting unit; dividing the starting unit into a traffic subdistrict, and selecting a basic unit from the marked unit set according to a number value and dividing it into the traffic subdistrict until the bus service area of the traffic subdistrict is greater than or equal to the first preset threshold or the available basic units in the marked unit set are empty, thereby obtaining a bus service subdistrict; returning to the step of selecting the basic unit with the smallest number from the marked unit set as the starting unit until the marked unit set is empty, thereby obtaining the initial traffic subdistrict division result, the initial traffic subdistrict division result comprising a plurality of bus service subdistricts; the abnormal correction processing on the initial traffic subdistrict division result to obtain the target traffic subdistrict division result comprises: acquiring a bus service subdistrict with a bus service area smaller than a first preset threshold in the initial traffic subdistrict division result, and determining it as a first abnormal area; when the bus service area of the first abnormal area is smaller than a second preset threshold, merging the first abnormal area with an adjacent bus service subdistrict to obtain the target traffic subdistrict division result; performing compactness calculation on each bus service subdistrict in the initial traffic subdistrict division result to obtain a compactness result set; acquiring a bus service subdistrict with a compactness smaller than a third preset threshold from the compactness result set, and determining it as a second abnormal area; performing shape cutting and merging processing on the second abnormal area to obtain the target traffic subdistrict division result.

2. The method of claim 1, wherein, the acquiring of the bus service area data and the boundary data comprises: acquiring bus stations of the to-be-divided area, and determining the bus service area data according to the area of the bus stations; acquiring the street town boundary of the to-be-divided area to determine the boundary data.

3. The method of claim 1, wherein, the unit dividing the to-be-divided area according to the boundary data to obtain the basic unit set comprises: performing grid processing on the to-be-divided area to obtain a grid area; According to the boundary data, boundary remodeling is performed on the meshed region to obtain a basic unit set.

4. A traffic zone dividing system characterized by, The system comprises: A first module for obtaining bus service area data and boundary data; A second module for performing unit division on a region to be divided according to the boundary data to obtain a basic unit set; A third module for performing clustering processing on the basic unit set according to the bus service area data to obtain an initial traffic subdistrict division result; A fourth module for performing abnormal correction processing on the initial traffic subdistrict division result to obtain a target traffic subdistrict division result; The clustering processing on the basic unit set according to the bus service area data to obtain an initial traffic subdistrict division result comprises: Performing marking processing on the basic unit set to obtain a marked unit set, wherein the marked unit set comprises a plurality of basic units marked with numbers; Performing regional clustering processing on the basic units in the marked unit set according to a first preset threshold to obtain an initial traffic subdistrict division result, wherein the first preset threshold is a bus service standard area; The regional clustering processing on the marked unit set according to the first preset threshold to obtain an initial traffic subdistrict division result comprises: Selecting a basic unit with the smallest number from the marked unit set as a starting unit; Dividing the starting unit into a traffic subdistrict, and selecting a basic unit from the marked unit set according to a number value and dividing it into the traffic subdistrict until the bus service area of the traffic subdistrict is greater than or equal to the first preset threshold or the basic units available for selection in the marked unit set are empty, thereby obtaining a bus service subdistrict; Returning to the step of selecting a basic unit with the smallest number from the marked unit set as a starting unit until the marked unit set is empty, thereby obtaining an initial traffic subdistrict division result, wherein the initial traffic subdistrict division result comprises a plurality of bus service subdistricts; The abnormal correction processing on the initial traffic subdistrict division result to obtain a target traffic subdistrict division result comprises: Obtaining a bus service subdistrict with a bus service area smaller than a first preset threshold in the initial traffic subdistrict division result, and determining it as a first abnormal region; When the bus service area of the first abnormal region is smaller than a second preset threshold, performing merging processing on the first abnormal region and an adjacent bus service subdistrict to obtain a target traffic subdistrict division result; Performing compactness calculation on each bus service subdistrict in the initial traffic subdistrict division result to obtain a compactness result set; Obtaining a bus service subdistrict with a compactness smaller than a third preset threshold in the compactness result set, and determining it as a second abnormal region; Performing shape cutting and merging processing on the second abnormal region to obtain a target traffic subdistrict division result.

5. An electronic device, comprising: The electronic device comprises a memory and a processor; The memory is configured to store a program; The processor executes the program to implement the method of any one of claims 1 to 3.

6. A computer readable storage medium, the storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by a processor, implements the method of any one of claims 1 to 3.

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