Road selection method, road data processing method, device, equipment and medium

Abstract

The present disclosure relates to a road selection method, a road data processing method, an apparatus, a device and a medium. In at least one embodiment of the present disclosure, a visual table for road service classification is constructed through road attribute items and / or business attribute items, and an operator only needs to select at least one cell in the visual table, so as to generate a road service classification result by using a value of a target road attribute item and / or a value of a target business attribute item corresponding to the at least one cell, so that the road service classification is changed from manual entry of rules by the operator to selection of visual attribute items, not only reducing the participation of the operator, but also reducing the thinking cost of the operator in combination of attribute items, thereby improving the efficiency of road service classification, and therefore the efficiency of determining road sections based on the road service classification result is also improved.

Description

Technical Field

[0001] This disclosure relates to the field of map technology, specifically to a road selection method, a road data processing method, an apparatus, a device, and a medium. Background Technology

[0002] With technological advancements, every road in the real world possesses its own unique characteristics, manifested in various objective dimensions, including road attribute dimensions such as the number of lanes, road grade, traffic flow classification, and city ranking, as well as various subjective dimensions, including business attribute dimensions such as important scenarios and complex scenarios. Therefore, objective dimensions can be used to classify roads, yielding road classification results. Furthermore, subjective dimensions can be used to classify these road classification results into business categories, that is, grouping roads that can adopt the same business processing strategies into the same business layer.

[0003] Different business operations have different classification rules, which usually require a combination of multiple rules. Each rule involves one or more attribute dimensions, which requires operators to have high rule editing capabilities and makes rule editing difficult, resulting in low efficiency in selecting road segments in the road network based on classification rules. Summary of the Invention

[0004] At least one embodiment of this disclosure provides a road selection method, a road data processing method, an apparatus, a device, and a medium.

[0005] In a first aspect, embodiments of this disclosure propose a road selection method, the method comprising:

[0006] Obtain at least one road attribute item and / or at least one business attribute item for road business classification;

[0007] Construct a visualization table for road business classification based on at least one road attribute item and / or at least one business attribute item;

[0008] In response to the selection of at least one cell in the visualization table, determine the value of the target road attribute item and / or the value of the target business attribute item corresponding to at least one cell;

[0009] Generate road business classification results based on the values ​​of target road attribute items and / or target business attribute items;

[0010] At least one target road segment is identified based on the road business classification results.

[0011] Secondly, embodiments of this disclosure provide a road data processing method, the method comprising:

[0012] At least one target road segment is determined based on the road selection method described in the first aspect;

[0013] The same business processing strategy is applied to at least one target road segment.

[0014] Thirdly, embodiments of this disclosure also provide a road selection device, which includes:

[0015] The acquisition unit is used to acquire at least one road attribute item and / or at least one business attribute item for road business classification;

[0016] A building unit for constructing a visual table for road business classification based on at least one road attribute item and / or at least one business attribute item;

[0017] The first determining unit is used to determine the value of the target road attribute item and / or the value of the target business attribute item corresponding to the at least one cell in response to the operation of selecting at least one cell in the visualization table;

[0018] The generation unit is used to generate road business classification results based on the values ​​of target road attribute items and / or target business attribute items;

[0019] The second determining unit is used to determine at least one target road segment based on the road business classification results.

[0020] Fourthly, embodiments of this disclosure also provide an electronic device, comprising a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the steps of the road selection method as described in the first aspect or the steps of the road data processing method as described in the second aspect.

[0021] Fifthly, embodiments of this disclosure also provide a computer-readable storage medium, wherein the computer-readable storage medium stores a program or instructions that cause a computer to perform steps of the road selection method as described in the first aspect or the road data processing method as described in the second aspect.

[0022] In a sixth aspect, embodiments of this disclosure also provide a computer program product, wherein the computer program product includes a computer program stored in a computer-readable storage medium, and at least one processor of a computer reads from and executes the computer program from the computer-readable storage medium, causing the computer to perform steps of the road selection method as described in the first aspect or steps of the road data processing method as described in the second aspect.

[0023] As can be seen, in at least one embodiment of this disclosure, a visual table for road business classification is constructed using road attribute items and / or business attribute items. The operator only needs to select at least one cell in the visual table to generate the road business classification result using the value of the target road attribute item and / or the value of the target business attribute item corresponding to the at least one cell. This transforms the road business classification from manual rule input by the operator to selection of visual attribute items, which not only reduces the operator's involvement but also reduces the operator's thinking cost of combining attribute items, thereby improving the efficiency of road business classification. Therefore, the efficiency of determining road segments based on the road business classification result is also improved. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings.

[0025] Figure 1 This is a schematic diagram of an interface for classifying roads into business categories in related technologies;

[0026] Figure 2 A schematic flowchart illustrating a road selection method provided in an embodiment of this disclosure;

[0027] Figure 3 A flowchart illustrating a process for constructing a visual table for road traffic classification, provided as an embodiment of this disclosure;

[0028] Figure 4 A schematic diagram of a process for generating road traffic classification results provided in an embodiment of this disclosure;

[0029] Figure 5 A schematic diagram of a visual table provided in an embodiment of this disclosure;

[0030] Figure 6 A schematic diagram illustrating a road traffic classification result provided in an embodiment of this disclosure;

[0031] Figure 7 A schematic diagram illustrating a process for selecting at least one target road segment based on road traffic classification results, provided in this embodiment of the disclosure;

[0032] Figure 8 A schematic diagram of a road selection device provided in an embodiment of this disclosure;

[0033] Figure 9 This is an exemplary block diagram of an electronic device provided in an embodiment of the present disclosure. Detailed Implementation

[0034] To better understand the above-described objectives, features, and advantages of this disclosure, the present disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. It is to be understood that the described embodiments are only some, not all, of the embodiments of this disclosure. The specific embodiments described herein are merely for explaining this disclosure and are not intended to limit it. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure are within the scope of protection of this disclosure.

[0035] It should be noted that in this article, relational terms such as “first” and “second” are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0036] Currently, map providers differentiate map processing into various production lines, such as road guidance lines, electronic traffic camera lines, and cycling lines. Each line processes roads differently based on its own business needs. Therefore, most production lines currently classify roads into different business categories to differentiate the collection cycles for related data (e.g., point cloud data, image data). Since different production lines have different business classification strategies, the corresponding classification rules also differ. Even within the same production line, the business classification strategy may be manually adjusted at different times of the year due to factors such as road traffic flow and objective changes. Manual adjustments often require combining multiple rules to form a single business classification strategy, with each rule involving one or more attribute dimensions. This necessitates a deep understanding of rule combinations and requires strong rule editing skills, making rule editing quite difficult and resulting in low efficiency in selecting road segments within the road network based on classification rules.

[0037] Figure 1 This is a schematic diagram of an interface for classifying roads for business purposes in related technologies. Figure 1 The business category interface shown displays the various attribute dimensions of the current business category (the category name is manually entered by the operator) in a flat layout. Each attribute item supports multiple selections or single selections, and the attribute items in the same row constitute a rule. Figure 1 Two rules are shown. Operators can also click the "Add Rule" button to add another rule. These rules form a rule group, which is used together to describe the results of the current business classification. Figure 1In the business classification interface shown, for each rule, the various attribute items included in that rule are cascaded to control the selectable values ​​of subsequent attribute items level by level. The operator selects the value of each attribute item in the order of the attribute items to complete the configuration of that rule. When all rules are configured, the result of the current business classification is obtained, which can be used to select road segments. A road segment (Link) is the smallest unit of a road. A road is composed of multiple road segments. The selected road segment satisfies the values ​​of the attribute items included in the current business classification result.

[0038] It is evident that operators need a deep understanding of rule combinations, require strong rule editing skills, and face significant challenges in rule editing, resulting in low efficiency in selecting road segments from the road network based on classification rules. Furthermore, operators can only ascertain the number of road segments that meet the rules after editing them, further reducing efficiency. Additionally, the large number of rule combinations easily leads to issues such as rule duplication and omissions.

[0039] To address at least one of the aforementioned problems, embodiments of this disclosure provide a road selection method, apparatus, electronic device, or storage medium. This method constructs a visual table for road service classification using road attribute items and / or service attribute items. Operators only need to select at least one cell in the visual table to generate road service classification results using the values ​​of the target road attribute items and / or target service attribute items corresponding to at least one cell. This transforms road service classification from manual rule entry by operators to visual attribute item selection, reducing operator involvement and the cognitive cost of combining attribute items, thereby improving the efficiency of road service classification. Consequently, the efficiency of determining road segments based on the road service classification results is also improved.

[0040] Figure 2 This is a flowchart illustrating a road selection method provided in an embodiment of the present disclosure. The execution subject of the road selection method is an electronic device, including but not limited to in-vehicle devices, smartphones, PDAs, tablets, wearable devices with displays, desktop computers, laptops, all-in-one computers, smart home devices, servers, etc. The server can be an independent server or a cluster of multiple servers, and can include servers built locally and servers set up in the cloud.

[0041] like Figure 2 As shown, the road selection method may include, but is not limited to, steps 201 to 205:

[0042] In step 201, at least one road attribute item and / or at least one business attribute item are obtained for road business classification.

[0043] In this embodiment, the road attribute items used for road business classification include, but are not limited to, road attribute dimensions such as: number of lanes, road grade, traffic flow stratification, and TOP cities (which can be understood as city ranking). The business attribute items used for road business classification include, but are not limited to, business attribute dimensions such as: important scenarios, complex scenarios, etc. For example, for the electronic surveillance production line, highway scenarios have higher traffic flow, so highway scenarios are important scenarios, while non-highway scenarios have lower traffic flow, so non-highway scenarios are unimportant scenarios. As another example, for the road guidance production line, for road scenarios with elevated roads and intersections, various types of road guidance lines are involved, including: intersection boundary lines, guide strips, etc.; therefore, road scenarios with elevated roads and intersections are complex scenarios. For rural road scenarios, there are no complex road relationships, so rural road scenarios are uncomplex scenarios. The production line operator can select at least one road attribute item and / or at least one business attribute item from multiple road attribute items based on the production line's business needs for road business classification. Furthermore, the execution entity in this embodiment can obtain the at least one road attribute item and / or at least one business attribute item selected by the operator for road business classification.

[0044] As can be seen, operators on different production lines can select different road attribute items and / or business attribute items based on the business needs of their respective production lines, in order to achieve differentiated road business classification for each production line. In some embodiments, if the operators on a production line do not select road attribute items and business attribute items, the road attribute items and business attribute items that can be used for road business classification are directly obtained, and the operators on different production lines complete the road selection using the steps shown in steps 202 to 204.

[0045] In step 202, a visualization table for road business classification is constructed based on at least one road attribute item and / or at least one business attribute item.

[0046] In this embodiment, in order to facilitate the classification of road operations by operators, at least one road attribute item and / or at least one business attribute item are constructed into a visual table. The column headers and / or row headers of the visual table are composed of at least one road attribute item and / or at least one business attribute item.

[0047] For example, step 201 only retrieves road attribute items, including: number of lanes, road grade, traffic flow stratification, and top cities. The number of lanes includes values ​​of ≥2 lanes, =1 lane, and no guide lines; the road grade includes values ​​of expressway / city expressway / primary / secondary (i.e., roads are not village roads) and village / small road (i.e., roads are village roads); the top cities include values ​​of Top 18 (i.e., cities ranked 1 to 18), Top 50 (i.e., cities ranked 19 to 50), and others (i.e., cities ranked below 50); the traffic flow stratification includes values ​​of 500-2.5K (i.e., hourly traffic flow of 500 to 2.5K vehicles) and 2.5K+ (i.e., hourly traffic flow of more than 2.5K vehicles). The resulting visualization table is shown below:

[0048] Table 1 Visualization Table 1

[0049]

[0050] As can be seen, in Table 1, the road attribute items and their values ​​constitute the column headers and row headers. In addition, Table 1 adds "indicators," which are road data indicators, such as stock (i.e., the number of road segments that meet the column and row headers) and change rate (i.e., the rate of change of the number of road segments that meet the column and row headers). These road data indicators allow operators to understand the road data more intuitively. For example, when the indicator is stock, operators can know the number of road segments that meet the attribute values ​​before selecting a cell, providing data support for operators to select cells and avoiding blind operation.

[0051] For example, if step 201 only retrieves business attribute items, including important scenarios and complex scenarios, where the values ​​for important scenarios are important and unimportant, and the values ​​for complex scenarios are complex and uncomplicated, then the constructed visualization table two is shown below:

[0052] Table 2 Visualization Table 2

[0053] important unimportant complex Not complicated

[0054] In this embodiment, the important, unimportant, complex and / or uncomplex categories in Table 2 can be further divided into different labels. For example, important can be further divided into high, medium and low, or based on the business needs of the production line, they can be divided into different sub-scenarios.

[0055] For example, step 201 simultaneously acquires road attribute items and business attribute items. The acquired road attribute items include: number of lanes, road grade, traffic flow stratification, and top cities. The number of lanes includes values ​​of ≥2 lanes, =1 lane, and no guide lines; the road grade includes values ​​of expressway, urban expressway, primary and secondary, and village / small; the top cities include values ​​of Top 18, Top 50, and others; and the traffic flow stratification includes values ​​of 500-2.5K and 2.5K+. The acquired business attribute items include: important scenarios, with values ​​of important and unimportant. The constructed visualization table three is shown below:

[0056] Table 3 Visualization Table 3

[0057]

[0058]

[0059] As can be seen, in this embodiment, operators on different production lines can customize the header (including row header and column header) of the visual table to include which attribute items based on the business needs of their respective production lines, thereby enabling the rapid configuration of the required attribute items for different production lines.

[0060] In step 203, in response to the operation of selecting at least one cell in the visualization table, the value of the target road attribute item and / or the value of the target business attribute item corresponding to the at least one cell is determined.

[0061] In this embodiment, a visual table is displayed in the user interface, allowing operators to view the table and select at least one cell based on the production line's business needs. This enables the determination of business classification rules through cell combinations. The operation of selecting at least one cell includes clicking or clicking and swiping. For example, each time an operator clicks a cell, that cell is selected; or, if an operator clicks a cell, that cell is selected, and then the cells intersected by the operator's swiping action in the visual table are also selected.

[0062] In this embodiment, in response to the operation of selecting at least one cell in the visualization table, the selected cell can be determined, and then the row header and column header corresponding to the selected cell can be determined. The value of the target road attribute item and / or the value of the target business attribute item corresponding to the selected cell can be obtained. It can be seen that the value of the target road attribute item and / or the value of the target business attribute item are the values ​​of the attribute items selected by the operator for road business classification based on the business needs of the production line.

[0063] As can be seen, in this embodiment, the use of visual tables frees operators from traditional methods such as... Figure 1The rule editing method shown has been changed to selecting cells from a visual table, which can reduce the thinking cost for operators to edit rules, achieve WYSIWYG, and improve the efficiency of road business classification.

[0064] In step 204, a road business classification result is generated based on the value of the target road attribute item and / or the value of the target business attribute item.

[0065] In this embodiment, road business classification results can be generated based on the values ​​of target road attribute items and / or target business attribute items. No operator involvement is required during the generation process. That is, the operator only needs to select at least one cell in the visual table, and the execution entity of this embodiment can generate road business classification results based on at least one cell selected by the operator.

[0066] Compared to related technologies where operators combine attribute items and edit rules based on attribute items (such as...), Figure 1 The process shown involves editing rules through multiple drop-down combo boxes and generating rule groups from multiple rules as the road business classification result. This transforms the road business classification from a process where operators edit rules through multiple drop-down combo boxes to a process of selecting visual attribute items. This allows operators to focus their attention on the road business classification logic itself (i.e., which attribute items need to be used for business classification) rather than on rule editing. This not only reduces the operator's involvement but also reduces the thinking cost of combining attribute items, thereby improving the efficiency of road business classification.

[0067] In step 205, at least one target road segment is determined based on the road traffic classification results.

[0068] In this embodiment, after generating the road service classification result, at least one target road segment can be determined based on the road service classification result. The target road segment satisfies the values ​​of the target road attribute items and / or the target service attribute items included in the road service classification result. Since the efficiency of road service classification is improved, the efficiency of determining road segments based on the road service classification result is also improved.

[0069] As can be seen, in the above embodiments, a visual table for road business classification is constructed by using road attribute items and / or business attribute items. The operator only needs to select at least one cell in the visual table to generate the road business classification result using the value of the target road attribute item and / or the value of the target business attribute item corresponding to at least one cell. This transforms the road business classification from manual rule input by the operator to selection of visual attribute items, which not only reduces the operator's involvement but also reduces the operator's thinking cost of combining attribute items, thereby improving the efficiency of road business classification. Therefore, the efficiency of determining road segments based on the road business classification result is also improved.

[0070] Based on the above embodiments, Figure 2 Step 202, "Constructing a visual table for road business classification based on at least one road attribute item and / or at least one business attribute item," includes, for example: Figure 3 Steps 301 to 303 are shown below:

[0071] In step 301, the classification priority of at least one road attribute item and / or the classification priority of at least one business attribute item are obtained.

[0072] In this embodiment, the classification priority of road attribute items and the classification priority of business attribute items are parameters that operators can configure based on the business needs of the production line. Classification priority can be understood as the priority of road selection. For example, if the classification priority of attribute item 'a' is higher than that of attribute item 'b', then when selecting roads, road segments satisfying attribute item 'a' are first selected from the candidate road segment set to obtain road segment set A. Then, road segments satisfying attribute item 'b' are selected from road segment set A. Therefore, after selecting at least one road attribute item and / or at least one business attribute item from multiple road attribute items for road business classification based on the business needs of the production line, operators can configure the classification priority for the selected at least one road attribute item and / or at least one business attribute item.

[0073] In some embodiments, if the operator has not configured a classification priority, the default classification priority of at least one road attribute item and / or the default classification priority of at least one business attribute item are obtained, wherein the default classification priority may be a historical classification priority or an initial value set by the operator on the production line.

[0074] In step 302, the column or row position of at least one road attribute item in the visualization table is determined based on the classification priority of at least one road attribute item; and / or, the column or row position of at least one business attribute item in the visualization table is determined based on the classification priority of at least one business attribute item.

[0075] In this embodiment, the classification priority of an attribute item determines its position in the visualization table. The higher the classification priority, the more leftward the column position or the higher the row position of the attribute item in the visualization table; the lower the classification priority, the more rightward the column position or the lower the row position of the attribute item in the visualization table.

[0076] For example, in Table 1 above, the classification priority of traffic flow stratification is higher than that of top cities, so the row containing traffic flow stratification is higher than the row containing top cities; the classification priority of lane number is higher than that of road class, so the column containing lane number is to the left of the column containing road class.

[0077] In step 303, a visualization table for road business classification is constructed based on the column or row position of at least one road attribute item in the visualization table and / or the column or row position of at least one business attribute item in the visualization table.

[0078] In this embodiment, although the position of the attribute item in the visualization table is determined by the classification priority, the position of the attribute item in the visualization table is not fixed. That is, the same classification priority order can determine different attribute item positions. For example, although Table 1 gives a specific attribute item arrangement, as long as the classification priority relationship of each attribute item is satisfied, the attribute item arrangement of Table 1 can be different. For example, if traffic stratification and TOP city are currently used as row headers and lane number and road grade are currently used as column headers in Table 1, it can be transformed into: using traffic stratification and TOP city as column headers and using lane number and road grade as row headers, a new Table 1 with a different layout than Table 1 is generated, and the new Table 1 also satisfies the classification priority relationship.

[0079] As can be seen, in this embodiment, operators on different production lines can quickly configure the required attribute items for different production lines by customizing the position of each attribute item in the header (including row header and column header) of the visual table according to the business needs of their respective production lines and by classifying the priority.

[0080] Based on the above embodiments, Figure 2 Step 204, "generating road business classification results based on the values ​​of target road attribute items and / or target business attribute items," includes, for example: Figure 4 Steps 401 to 403 are shown below:

[0081] In step 401, the relative priority between the values ​​of the target road attribute item and / or the target business attribute item is determined based on their relative positions in the visualization table.

[0082] For example, Figure 5 This is a schematic diagram of a visual table provided in an embodiment of the present disclosure. Figure 5 The visualization table shown only includes road attribute items, which include: number of lanes, road grade, traffic flow stratification, and top cities. The number of lanes includes values ​​for ≥2 lanes and 1 lane; road grade includes values ​​for 0-expressway, 1-city expressway, 2-national highway, 3-provincial highway, 4-main city road, 5-secondary city road, 6-urban management road, and 7-county road; top cities include values ​​for TOP18, TOP50, and others; traffic flow stratification includes values ​​for 2.5K+, 600-2.5K+, and 300-600. It can be seen that although... Figure 5The visualization table shown contains the same road attribute items as the aforementioned visualization table one, but the values ​​for these road attribute items differ, demonstrating that different production lines can customize the values ​​of road attribute items based on their business needs. Figure 5 The visualization table also includes road data indicators: stock and change rate. This allows operators to intuitively understand the stock and change rate data before selecting cells, providing data support for cell selection, avoiding blind operation, and improving the efficiency of cell selection.

[0083] exist Figure 5 In the diagram, the shaded areas correspond to the cells selected by the mouse cursor. This allows us to determine the values ​​of the target road attributes for these cells, including: number of lanes (≥2 lanes), road class (2-national highway, 3-provincial highway, 4-city main, 5-city secondary), traffic flow stratification (2.5K+, 600-2.5K+), and top cities (TOP18, TOP50, and others). Furthermore, based on the values ​​of the target road attributes... Figure 5 The relative positions in the visualization table determine the relative priority of the target road attribute values. A value further to the left in the visualization table has higher relative priority, and a value further to the top has even higher relative priority. For example... Figure 5 In this context, the number of lanes (≥2 lanes) is to the left of the road grade (national highway, provincial highway), indicating that the relative priority of the number of lanes (≥2 lanes) is higher than that of the road grade (national highway, provincial highway), and thus based on... Figure 5 The position of the cell shown in the shaded area can determine a set of values ​​with relative priority from largest to smallest: number of lanes (≥2 lanes), road grade (national highway, provincial highway), traffic flow stratification (2.5K+), and top cities (TOP50 and others). This set of values ​​constitutes a rule for classifying road business.

[0084] In step 402, the values ​​of the target road attribute items and / or the target business attribute items are concatenated in descending order of relative priority to obtain at least one concatenation result.

[0085] For example, in Figure 5 In the process, a set of values ​​with relative priority from largest to smallest are: number of lanes (≥2 lanes), road grade (national highway, provincial highway), traffic flow stratification (2.5K+), and top cities (TOP50, others). This set of values ​​constitutes a rule for road business classification. By cascading this set of values ​​in order of relative priority from largest to smallest, a cascaded result (i.e., a rule) is obtained.

[0086] exist Figure 5In the middle, another set of values ​​with relative priority from largest to smallest are: number of lanes (≥2 lanes), road level (city lord, city queuing), traffic flow stratification (2.5K+), and top cities (others). This set of values ​​constitutes a rule for road business classification. By cascading this set of values ​​in order of relative priority from largest to smallest, a cascaded result (i.e., a rule) is obtained.

[0087] exist Figure 5 In the middle, another set of values ​​with relative priority from largest to smallest are: number of lanes (≥2 lanes), road level (city primary, city secondary), traffic flow stratification (600-2.5K+), and TOP cities (TOP18). This set of values ​​constitutes a rule for road business classification. By cascading this set of values ​​in order of relative priority from largest to smallest, a cascaded result (i.e., a rule) is obtained.

[0088] As can be seen, the above three rules constitute a rule group for road traffic classification. If this rule group were generated using related technologies, the operator would need to manually enter these three rules. However, in this embodiment, the operator only needs to select 16 cells (e.g., ...). Figure 5 As shown in the image, this improves the efficiency of rule generation.

[0089] In step 403, a road business classification result is generated based on at least one cascaded result.

[0090] In this embodiment, the road service classification results include all cascaded results, for example... Figure 5 If there are three corresponding cascading results, then the road service classification results will include these three cascading results as a rule group for road service classification. Furthermore, to identify different road service classification results, classification names can be added to the road service classification results, for example... Figure 5 The corresponding road traffic classification results are named as follows: Multi-lane, High-volume, High-variability classification, such as... Figure 6 As shown.

[0091] In some embodiments, after generating the road traffic classification results, the road traffic classification results are displayed, for example, by... Figure 6 The road traffic classification results shown can be displayed to the operator for verification and confirmation. Furthermore, in response to the operator's confirmation of the road traffic classification results, for example, by clicking the confirmation button, at least one target road segment is determined based on the road traffic classification results.

[0092] Based on the above embodiments, Figure 2 Step 204, "determining at least one target road segment based on road business classification results," includes, for example: Figure 7 Steps 701 and 702 are shown below:

[0093] In step 701, based on at least one cascaded result included in the road business classification result, the values ​​of each attribute item included in each cascaded result and the cascaded order of the values ​​of each attribute item are extracted.

[0094] In step 702, for any cascade result, based on the cascade order of the values ​​of each attribute item included in the cascade result, at least one target road segment that satisfies the values ​​of each attribute item included in the cascade result is selected from the candidate road segment set.

[0095] For example, based on Figure 6 The three cascaded results included in the road service classification results shown can determine the following three cascaded sequences for selecting road segments:

[0096] Number of lanes (≥2 lanes), road grade (national highway, provincial highway), traffic flow stratification (2.5K+), top cities (TOP50, others);

[0097] Number of lanes (≥2 lanes), road grade (primary city, secondary city), traffic flow stratification (2.5K+), top cities (others);

[0098] Number of lanes (≥2 lanes), road grade (primary city, secondary city), traffic flow stratification (600-2.5K+), and top cities (TOP18).

[0099] Based on the above three cascading orders, target road segments that satisfy the values ​​of each attribute item in the above three cascading orders are selected from the candidate road segment set. For example, firstly, road segments with ≥2 lanes are selected to obtain the first road segment set; then, road segments of road level (national highway, provincial highway) are selected from the first road segment set to obtain the second road segment set; road segments of road level (city lord, city vassal) are selected from the first road segment set to obtain the third road segment set; then, road segments that satisfy traffic flow stratification (2.5K+) and TOP cities (TOP50, others) are selected from the second road segment set as target road segments; road segments that satisfy traffic flow stratification (2.5K+) and TOP cities (others) are selected from the third road segment set as target road segments; and road segments that satisfy traffic flow stratification (600-2.5K+) and TOP cities (TOP18) are selected from the third road segment set as target road segments.

[0100] In some embodiments, after selecting at least one target road segment based on the road service classification results, at least one selected cell in the visualization table is marked as selected, for example, by color-filling the cell. This allows operators to know which attribute values ​​have participated in the road service classification. It should be noted that the same selected marker is used for the values ​​of each attribute used in the same road service classification, for example, using the same fill color. Different selected markers are used between different road service classifications to help operators distinguish them. Therefore, adding selected markers helps operators understand the usage of cells and avoids problems such as rule duplication (e.g., two rules using the same values ​​for multiple attribute items) and rule omissions.

[0101] This disclosure also provides a road data processing method, including: determining at least one target road segment based on the aforementioned road selection method embodiments; and processing the at least one target road segment using the same business processing strategy, wherein the business processing strategy is a strategy formulated based on the business needs of the production line. For example, for a traffic camera production line, since the traffic flow on highways is large, the collection cycle of highway traffic cameras can be set to be shorter; while the traffic flow on non-highways is small, the collection cycle of non-highway traffic cameras can be set to be longer.

[0102] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art will understand that the embodiments of this disclosure are not limited to the described order of actions, because according to the embodiments of this disclosure, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art will understand that the embodiments described in the specification are all optional embodiments.

[0103] Figure 8 This is a schematic diagram of a road selection device provided in an embodiment of this disclosure. The road selection device can be applied to electronic devices, including but not limited to in-vehicle devices, smartphones, PDAs, tablets, wearable devices with displays, desktop computers, laptops, all-in-one computers, smart home devices, servers, etc. The server can be a standalone server or a cluster of multiple servers, and can include locally located servers and cloud-based servers. The road selection device provided in this embodiment of the disclosure can execute the processing flow provided in various embodiments of the road selection method, such as... Figure 8 As shown, the road selection device includes, but is not limited to: an acquisition unit 801, a construction unit 802, a first determination unit 803, a generation unit 804, and a second determination unit 805. The functions of each unit are described below:

[0104] The acquisition unit 801 is used to acquire at least one road attribute item and / or at least one business attribute item for road business classification;

[0105] Construction unit 802 is used to construct a visualization table for road business classification based on at least one road attribute item and / or at least one business attribute item;

[0106] The first determining unit 803 is used to determine the value of the target road attribute item and / or the value of the target business attribute item corresponding to the at least one cell in response to the operation of selecting at least one cell in the visualization table;

[0107] The generation unit 804 is used to generate road business classification results based on the values ​​of target road attribute items and / or target business attribute items;

[0108] The second determining unit 805 is used to determine at least one target road segment based on the road business classification results.

[0109] In some embodiments, the construction unit 802 is configured to:

[0110] Obtain the classification priority of at least one road attribute item and / or the classification priority of at least one business attribute item;

[0111] Based on the classification priority of at least one road attribute item, determine the column or row position of at least one road attribute item in the visualization table; and / or, based on the classification priority of at least one business attribute item, determine the column or row position of at least one business attribute item in the visualization table.

[0112] A visualization table for road business classification is constructed based on the column or row position of at least one road attribute item and / or the column or row position of at least one business attribute item in the visualization table.

[0113] In some embodiments, the generating unit 804 is configured to:

[0114] Based on the relative positions of the values ​​of the target road attribute items and / or the target business attribute items in the visualization table, determine the relative priority between the values ​​of the target road attribute items and / or the target business attribute items;

[0115] Concatenate the values ​​of the target road attribute items and / or the target business attribute items in descending order of relative priority to obtain at least one concatenation result;

[0116] The road business classification result is generated based on at least one cascaded result.

[0117] In some embodiments, the road selection device further includes:

[0118] The display unit is used to show the road business classification results;

[0119] The second determining unit 805 responds to the operation of confirming the road traffic classification result and determines at least one target road segment based on the road traffic classification result.

[0120] In some embodiments, the second determining unit 805 is configured to:

[0121] Based on at least one cascaded result included in the road business classification results, extract the values ​​of each attribute item included in each cascaded result and the cascaded order of the values ​​of each attribute item;

[0122] For any cascading result, based on the cascading order of the values ​​of the attribute items included in the cascading result, select at least one target road segment from the candidate road segment set that satisfies the values ​​of the attribute items included in the cascading result.

[0123] In some embodiments, the road selection device further includes:

[0124] A marker cell is used to mark at least one selected cell in a visual table as selected.

[0125] As can be seen, in at least one embodiment of the road selection device disclosed herein, a visual table for road business classification is constructed by road attribute items and / or business attribute items. The operator only needs to select at least one cell in the visual table to generate the road business classification result using the value of the target road attribute item and / or the value of the target business attribute item corresponding to the at least one cell. This transforms the road business classification from manual rule input by the operator to selection of visual attribute items, which not only reduces the operator's involvement but also reduces the operator's thinking cost of combining attribute items, thereby improving the efficiency of road business classification. Therefore, the efficiency of determining road segments based on the road business classification result is also improved.

[0126] Figure 9 This is an exemplary block diagram of an electronic device provided in an embodiment of this disclosure. Figure 9 As shown, the electronic device includes a memory 901, a processor 902, and a computer program stored on the memory 901. It is understood that the memory 901 in this embodiment may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0127] In some implementations, memory 901 stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating systems and applications.

[0128] The operating system includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic tasks and handle hardware-based tasks. The application programs include various applications, such as media players and browsers, used to implement various application tasks. The program implementing the road selection method or road data processing method provided in the embodiments of this disclosure can be included in the application programs.

[0129] In this embodiment of the disclosure, at least one processor 902 executes the steps of the various embodiments of the road selection method or the road data processing method provided in this embodiment by calling a program or instruction stored in at least one memory 901, specifically, a program or instruction stored in an application.

[0130] The road selection method or road data processing method provided in this disclosure can be applied to, or implemented by, processor 902. Processor 902 can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the hardware of processor 902 or by instructions in software form. The processor 902 can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor.

[0131] The steps of the road selection method or road data processing method provided in this disclosure can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory 901, and processor 902 reads the information in memory 901 and combines it with hardware to complete the steps of the method.

[0132] This disclosure also proposes a computer-readable storage medium that stores a program or instructions that cause a computer to perform steps as described in the embodiments of the road selection method or the road data processing method. To avoid repetition, these steps will not be repeated here. The computer-readable storage medium can be a non-transitory computer-readable storage medium.

[0133] This disclosure also proposes a computer program product comprising a computer program stored in a computer-readable storage medium, which may be a non-transitory computer-readable storage medium. At least one processor of a computer reads and executes the computer program from the computer-readable storage medium, causing the computer to perform steps as described in the embodiments of the road selection method or the road data processing method, which will not be repeated here to avoid repetition.

[0134] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0135] Those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of this disclosure and form different embodiments.

[0136] Those skilled in the art will understand that the descriptions of the various embodiments have different focuses, and for parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0137] Although embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and all such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A road selection method, the method comprising: Obtain at least one road attribute item and / or at least one business attribute item for road business classification; Based on the at least one road attribute item and / or the at least one business attribute item, construct a visualization table for road business classification; In response to the operation of selecting at least one cell in the visualization table, determine the value of the target road attribute item and / or the value of the target business attribute item corresponding to the at least one cell; The relative priority between the values ​​of the target road attribute item and / or the target business attribute item is determined based on their relative positions in the visualization table. According to the relative priority from largest to smallest, the values ​​of the target road attribute item and / or the values ​​of the target business attribute item are concatenated to obtain at least one concatenation result; A road business classification result is generated based on at least one of the cascaded results; At least one target road segment is determined based on the road traffic classification results.

2. The method according to claim 1, wherein, The step of constructing a visualization table for road business classification based on the at least one road attribute item and / or the at least one business attribute item includes: Obtain the classification priority of the at least one road attribute item and / or the classification priority of the at least one business attribute item; Based on the classification priority of the at least one road attribute item, determine the column or row position of the at least one road attribute item in the visualization table; and / or, based on the classification priority of the at least one business attribute item, determine the column or row position of the at least one business attribute item in the visualization table. A visualization table for road business classification is constructed based on the column or row position of the at least one road attribute item in the visualization table and / or the column or row position of the at least one business attribute item in the visualization table.

3. The method according to claim 1, wherein, After generating the road service classification results, the method further includes: Display the results of the road service classification; In response to the operation of confirming the road traffic classification result, the step of determining at least one target road segment based on the road traffic classification result is performed.

4. The method according to claim 1, wherein, The step of determining at least one target road segment based on the road traffic classification result includes: Based on the at least one cascaded result included in the road business classification result, extract the values ​​of each attribute item included in each cascaded result and the cascaded order of the values ​​of each attribute item; For any cascading result, based on the cascading order of the values ​​of each attribute item included in the cascading result, at least one target road segment that satisfies the values ​​of each attribute item included in the cascading result is selected from the candidate road segment set.

5. The method according to claim 1, wherein, After determining at least one target road segment based on the road traffic classification result, the method further includes: In the visual table, the selected at least one cell is marked as selected.

6. A road data processing method, the method comprising: At least one target road segment is determined based on the road selection method according to any one of claims 1 to 5; The same business processing strategy is applied to the at least one target road segment.

7. A road selection device, the device comprising: The acquisition unit is used to acquire at least one road attribute item and / or at least one business attribute item for road business classification; A construction unit is used to construct a visualization table for road business classification based on the at least one road attribute item and / or the at least one business attribute item; The first determining unit is configured to, in response to the operation of selecting at least one cell in the visualization table, determine the value of the target road attribute item and / or the value of the target business attribute item corresponding to the at least one cell; A generation unit is configured to determine the relative priority between the values ​​of the target road attribute item and / or the target business attribute item based on their relative positions in the visualization table; concatenate the values ​​of the target road attribute item and / or the target business attribute item in descending order of relative priority to obtain at least one concatenation result; and generate a road business classification result based on the at least one concatenation result. The second determining unit is used to determine at least one target road segment based on the road business classification results.

8. An electronic device, wherein, It includes a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the steps of the road selection method as claimed in any one of claims 1 to 5 or the steps of the road data processing method as claimed in claim 6.

9. A computer-readable storage medium, wherein, The computer-readable storage medium stores a program or instructions that cause a computer to perform the steps of the road selection method as claimed in any one of claims 1 to 5 or the steps of the road data processing method as claimed in claim 6.

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