CN113360588A - Map task processing method and device, electronic equipment and storage medium - Google Patents
Map task processing method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application provides a map task processing method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining a drawing efficiency average value corresponding to each map element of a map and the number of the elements of each map element; determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element; determining the map task difficulty level of the map according to the element number of each map element and the difficulty coefficient of each map element; and outputting the map task of the map according to the map task difficulty level. The method and the device can accurately level the difficulty of the map task of automatic driving.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a map task processing method and apparatus, an electronic device, and a storage medium.
Background
At present, the traditional navigation map and the high-precision unmanned map still adopt a manual drawing method, the map task value needing to be updated in each part of operation is determined fairly, the operation level of an operator is determined, tasks are distributed reasonably, and the like, and how to reasonably and accurately level the difficulty level of the map task becomes an important problem which needs to be solved by the high-precision map making at present.
However, there is no method for accurately ranking the task difficulty level of the map.
Disclosure of Invention
The application provides a map task processing method and device, electronic equipment and a storage medium, which are used for accurately grading the difficulty of an automatic driving map task.
In a first aspect, an embodiment of the present application provides a map task processing method, including:
obtaining a drawing efficiency average value corresponding to each map element of a map and the number of the elements of each map element;
determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element;
determining the map task difficulty level of the map according to the element number of each map element and the difficulty coefficient of each map element;
and outputting the map task of the map according to the map task difficulty level.
In an optional implementation manner, the obtaining of the drawing efficiency average value corresponding to each map element of the map includes:
obtaining the element number and drawing time of each sample map element of each sample map task in a plurality of sample map tasks;
obtaining the total element quantity and the total drawing time of each sample map element according to the element quantity and the drawing time of each sample map element of each sample map task;
and determining the drawing efficiency mean value corresponding to each sample map element according to the total element number and the total drawing time of each sample map element.
In an optional implementation manner, the determining a map task difficulty level of the map according to the number of elements of each map element and the difficulty coefficient of each map element includes:
obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task;
calculating the variance of the drawing efficiency of each sample map element to obtain an efficiency variance;
correcting the drawing efficiency mean value corresponding to each map element through the efficiency variance to obtain a corrected drawing efficiency mean value corresponding to each map element;
and if the corrected drawing efficiency average value corresponding to each map element meets a preset condition, determining the difficulty coefficient of each map element according to the corrected drawing efficiency average value corresponding to each map element.
In an optional implementation manner, the modifying the drawing efficiency average value corresponding to each map element by using the efficiency variance to obtain a modified drawing efficiency average value corresponding to each map element includes:
calculating a quotient value of the element quantity and the total element quantity of each map element; calculating the product of the quotient of the number of the elements of each map element and the total number of the elements and the efficiency variance to obtain an error correction value corresponding to each map element;
and calculating the difference value between the drawing efficiency average value corresponding to each map element and the error correction value to obtain the corrected drawing efficiency average value corresponding to each map element.
In an optional implementation manner, before determining the difficulty coefficient of each map element according to the modified drawing efficiency mean value corresponding to each map element if the modified drawing efficiency mean value corresponding to each map element meets a preset condition, the method further includes:
obtaining a first mean value error of each sample map element for each sample map according to the drawing efficiency mean value corresponding to each map element, the element number and the drawing duration of each sample map element;
obtaining a second mean value error of each sample map element for each sample map according to the corrected drawing efficiency mean value corresponding to each map element, the element number and the drawing duration of each sample map element;
calculating the variance of the first mean error to obtain a first variance, and calculating the variance of the second mean error to obtain a second variance;
and if the first variance is larger than the second variance, determining that the corrected drawing efficiency mean value corresponding to each map element meets a preset condition.
In an optional embodiment, the method further comprises:
and if the first variance is smaller than the second variance, determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element.
In an optional implementation manner, the obtaining a first mean error of each sample map element for each sample map according to the drawing efficiency mean value corresponding to each map element, the element number of each sample map element, and the drawing duration includes:
calculating the product of the drawing efficiency mean value and the drawing time length corresponding to each map element to obtain a mean value calculation value corresponding to each map element;
calculating a difference value between the mean calculation value corresponding to each map element and the element number to obtain a first mean error of each sample map element for each sample map;
correspondingly, the obtaining a second mean error of each sample map element for each sample map according to the corrected drawing efficiency mean value corresponding to each map element, the element number of each sample map element, and the drawing duration includes:
calculating the product of the corrected drawing efficiency average value and the drawing time length corresponding to each map element to obtain a corrected average value calculated value corresponding to each map element;
and calculating the difference value between the corrected average calculated value corresponding to each map element and the element number to obtain a second average error of each sample map element for each sample map.
In an optional embodiment, the method further comprises:
obtaining the drawing efficiency of each drawing person in a plurality of drawing persons;
and carrying out map task allocation on the map according to the drawing efficiency of each drawing person and the map task difficulty level of the map.
In an optional embodiment, the method further comprises:
obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task;
and removing the sample map corresponding to the map element with the drawing efficiency not within the specified efficiency range from the plurality of sample maps.
In a second aspect, an embodiment of the present application provides a map task processing apparatus, including:
the efficiency average value and quantity acquisition module is used for acquiring the drawing efficiency average value corresponding to each map element of the map and the element quantity of each map element;
the difficulty coefficient determining module is used for determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element;
and the difficulty level determining module is used for determining the map task difficulty level of the map according to the element number of each map element and the difficulty coefficient of each map element.
And the output module is used for outputting the map task of the map according to the map task difficulty level.
In an optional implementation manner, the efficiency average and quantity obtaining module includes:
the system comprises a sample acquisition unit, a mapping unit and a mapping unit, wherein the sample acquisition unit is used for acquiring the element number and the drawing time length of each sample map element of each sample map task in a plurality of sample map tasks;
the sample processing unit is used for obtaining the total element quantity and the total drawing time of each sample map element according to the element quantity and the drawing time of each sample map element of each sample map task;
and the efficiency average value determining unit is used for determining the drawing efficiency average value corresponding to each sample map element according to the total element number and the total drawing time length of each sample map element.
In an alternative embodiment, the difficulty level determining module includes:
the drawing efficiency determining unit is used for obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task;
the efficiency variance acquiring unit is used for calculating the variance of the drawing efficiency of each sample map element to obtain the efficiency variance;
the correction unit is used for correcting the drawing efficiency mean value corresponding to each map element through the efficiency variance to obtain a corrected drawing efficiency mean value corresponding to each map element;
and the difficulty system determining unit is used for determining the difficulty coefficient of each map element according to the corrected drawing efficiency mean value corresponding to each map element if the corrected drawing efficiency mean value corresponding to each map element meets a preset condition.
In an optional embodiment, the modification unit is specifically configured to:
calculating a quotient value of the element quantity and the total element quantity of each map element; calculating the product of the quotient of the number of the elements of each map element and the total number of the elements and the efficiency variance to obtain an error correction value corresponding to each map element;
and calculating the difference value between the drawing efficiency average value corresponding to each map element and the error correction value to obtain the corrected drawing efficiency average value corresponding to each map element.
In an alternative embodiment, the correction unit is further configured to:
obtaining a first mean value error of each sample map element for each sample map according to the drawing efficiency mean value corresponding to each map element, the element number and the drawing duration of each sample map element;
obtaining a second mean value error of each sample map element for each sample map according to the corrected drawing efficiency mean value corresponding to each map element, the element number and the drawing duration of each sample map element;
calculating the variance of the first mean error to obtain a first variance, and calculating the variance of the second mean error to obtain a second variance;
and if the first variance is larger than the second variance, determining that the corrected drawing efficiency mean value corresponding to each map element meets a preset condition.
In an alternative embodiment, the correction unit is further configured to:
and if the first variance is smaller than the second variance, determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element.
In an optional embodiment, the modification unit is further specifically configured to:
calculating the product of the drawing efficiency mean value and the drawing time length corresponding to each map element to obtain a mean value calculation value corresponding to each map element;
calculating a difference value between the mean calculation value corresponding to each map element and the element number to obtain a first mean error of each sample map element for each sample map;
calculating the product of the corrected drawing efficiency average value and the drawing time length corresponding to each map element to obtain a corrected average value calculated value corresponding to each map element;
and calculating the difference value between the corrected average calculated value corresponding to each map element and the element number to obtain a second average error of each sample map element for each sample map.
In an optional embodiment, the map task processing device further includes:
the drawing efficiency obtaining module is used for obtaining the drawing efficiency of each drawing person in the plurality of drawing persons;
and the distribution module is used for carrying out map task distribution on the map according to the drawing efficiency of each drawing person and the map task difficulty level of the map.
In an optional embodiment, the map task processing device further includes:
the drawing efficiency obtaining module is used for obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task;
and the elimination module is used for removing the sample map corresponding to the map element of which the drawing efficiency is not in the specified efficiency range from the plurality of sample maps.
In a third aspect, an embodiment of the present application provides an electronic device, including: a memory and a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the method provided by the above embodiment.
In a fourth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the computer-executable instructions are used to implement the method provided by the foregoing embodiment.
In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the computer program implements the method provided in any corresponding embodiment of the first aspect of the present application.
According to the map task processing method, the map task processing device, the electronic equipment and the storage medium, the drawing efficiency mean value corresponding to each map element of the map and the element number of each map element are obtained, the difficulty coefficient of each map element is determined according to the drawing efficiency mean value corresponding to each map element, the drawing efficiency mean value reflects the average efficiency condition when different drawing personnel draw the same map element, the map task difficulty grade of the map is determined according to the element number of each map element and the difficulty coefficient of each map element, and the map task of the map is output according to the map task difficulty grade. That is, the drawing efficiency average value is obtained by comprehensively considering the drawing efficiency of different drawing personnel on map elements, and the drawing efficiency average value can accurately reflect the drawing difficulty of each map element, for example, the lower the drawing efficiency average value of a map element is, the greater the difficulty coefficient of drawing the map element is, and then the difficulty level of a map task can be accurately graded by combining the difficulty coefficient and the number of each map element because the map is composed of a certain number of map elements. And then outputting the map task of the map according to the map task difficulty level so as to distribute the map task to a proper drawing personnel account number, thereby improving the efficiency and accuracy of distributing the map task.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic flowchart of a map task processing method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of another map task processing method according to an embodiment of the present application;
FIG. 3 is a flowchart of step 201 in the embodiment of FIG. 2;
FIG. 4 is a flowchart of step 202 in the embodiment of FIG. 2 of the present application;
FIG. 5 is a flowchart of steps 2024a to 2024d according to the embodiment shown in FIG. 2 of the present application;
fig. 6 is a schematic structural diagram of a map task processing device according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 8 is a block diagram of an electronic device provided in an embodiment of the present application.
With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
With the development of the field of unmanned driving technology, advanced driving assistance maps, namely (high-precision maps) making and real-time updating, have attracted much attention. At present, the traditional navigation map and the high-precision unmanned map still adopt a manual drawing method, the map task value needing to be updated in each part of operation is determined fairly, the operation level of an operator is determined, tasks are distributed reasonably, and the like, and how to reasonably and accurately level the map task difficulty coefficient becomes an important problem which needs to be solved by the high-precision map making at present. For example, how easy it is to distinguish high-precision unmanned mapping in the beijing city district from unmanned mapping in tibetan city.
At present, the map task is graded according to difficulty grades, and the map task is generally graded after being analyzed by drawing personnel with abundant experience.
However, this method of rating the difficulty level of the map task depends on the subjective judgment of a certain plotter, and the set difficulty level is not suitable for each plotter, so that the difficulty level of the map task is not accurately set.
In addition, the map usually includes a plurality of map elements, such as arrows, ground text symbols, guardrails, and the like, and the difficulty level of the map is determined manually, so that the map elements on the map need to be analyzed, which results in low grading efficiency.
The embodiment of the application provides a map task processing method, a map task processing device, electronic equipment and a storage medium, and aims to solve the technical problems in the prior art.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 is a schematic flowchart of a method for processing a map task according to an embodiment of the present application, and as shown in fig. 1, the method according to the embodiment includes:
101. and acquiring the drawing efficiency average value corresponding to each map element of the map and the element number of each map element.
For example, the map task processing method of the present embodiment may be applied to an electronic device, which may be a smartphone, a personal computer, a tablet computer, a server, or the like.
The map is mainly a driving map for automatic driving of the vehicle. The map elements are graphic elements required for constructing the driving map, such as lane lines, lane center lines, barrier strips, arrow indicators, road signs, traffic lights, and poles.
The average drawing efficiency value may be an average drawing efficiency value of different drawing persons drawing the same map element.
In some embodiments, a map drawing work platform may be configured in the electronic device, the work platform is embedded with a timer stopwatch, when a drawing staff draws a map task through the work platform, the background may record the time consumed by the drawing staff to make different map elements, and then calculate the drawing efficiency average value of each map element according to the total time consumed and the total number of each drawing staff to each map element. For example, if the drawing efficiency of the person a drawing the traffic sign is 12 at 5 minutes and the drawing efficiency of the person B drawing the traffic sign is 4 at 8 minutes, the average drawing efficiency may be (12+4)/(8+5) ═ 1.23, that is, the average drawing efficiency of the traffic sign is 1.23 per minute. By analogy, the average drawing efficiency value of different types of map elements such as the isolation belt guardrail and the indication arrow can be calculated.
The map task specifies the type and number of map elements included in the map, for example, the map task includes all or most element scenes of an L4-level autopilot map specified by the national standard, so the electronic device can view the map task of the map to obtain the number of elements of each map element in the map.
102. And determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element.
In some embodiments, the drawing efficiency average value corresponding to each map element may be negatively correlated with the difficulty coefficient thereof, that is, the larger the drawing efficiency average value corresponding to a map element is, the higher the efficiency corresponding to the map element drawn by a plurality of drawing persons as a whole is, the smaller the difficulty is. As an example, the electronic device may use a reciprocal of a mean value of the rendering efficiencies corresponding to the map element as a difficulty coefficient of the map element. As an example, taking map elements as arrows, traffic signs, ground characters, and guardrails as an example, as shown in table 1, if the average drawing efficiency of the guardrails is 0.137, the difficulty factor corresponding to the guardrail is 0.736481694.
TABLE 1
| Map elements | Drawing efficiency mean value (min) | Reciprocal of difficulty coefficient |
| Arrow head | 3.8 | 0.026552103 |
| Ground character symbol | 2.21 | 0.0456552 |
| Guard bar | 0.137 | 0.736481694 |
| Traffic sign board | 1.26 | 0.080077772 |
103. And determining the map task difficulty level of the map according to the element number of each map element and the difficulty coefficient of each map element.
As an example, the electronic device may multiply the number of map elements in the map task by the difficulty coefficient to obtain a plurality of products, and then accumulate the plurality of products, so as to use the accumulated result as the difficulty level of the map task. For example, the map task includes map elements including arrows, guardrails, and traffic signs, and the map has a difficulty rating of the number of arrows + the difficulty coefficient of the number of guardrails + the difficulty coefficient of the number of traffic signs + the difficulty coefficient of the traffic signs.
104. And outputting the map task of the map according to the map task difficulty level.
As one example, the electronic device may output a map task for the map to an account of a suitable mapping person based on a map task difficulty rating, for example. For another example, the electronic device may send the map task of the map directly to a dedicated terminal device of a suitable mapping person according to the map task difficulty level.
In this embodiment, a drawing efficiency mean value corresponding to each map element of the map and the element number of each map element are obtained, and the difficulty coefficient of each map element is determined according to the drawing efficiency mean value corresponding to each map element, where the drawing efficiency mean value reflects an average efficiency situation when different drawing personnel draw the same map element, and then the map task difficulty level of the map is determined according to the element number of each map element and the difficulty coefficient of each map element. That is, the drawing efficiency average value is obtained by comprehensively considering the drawing efficiency of different drawing personnel on map elements, and the drawing efficiency average value can accurately reflect the drawing difficulty of each map element, for example, the lower the drawing efficiency average value of a map element is, the greater the difficulty coefficient of drawing the map element is, and then the difficulty level of a map task can be accurately graded by combining the difficulty coefficient and the number of each map element because the map is composed of a certain number of map elements. In addition, the difficulty grading can be automatically carried out on the map by the method, the problems of inaccurate grading and low grading efficiency caused by manual grading are solved, and then the map task of the map is output according to the difficulty grade of the map task so as to be distributed to a proper drawing personnel account, so that the efficiency and the accuracy of the map task are improved.
Fig. 2 is a schematic flowchart of another map task processing method provided in the embodiment of the present application, and as shown in fig. 2, the method provided in the embodiment includes:
201. and acquiring the drawing efficiency average value corresponding to each map element of the map and the element number of each map element.
In some embodiments, as shown in fig. 3, step 201 may include:
2011. and acquiring the element quantity and the drawing time length of each sample map element of each sample map task in the plurality of sample map tasks.
In some embodiments, the electronic device may allocate a plurality of sample map tasks to a plurality of operators, each sample map task corresponds to one operator, and after the plurality of operators complete all the sample map tasks, the electronic device may count, through the work platform, the number of elements and the drawing time of each sample map element in each sample task. As an example, as shown in table 2, taking a sample map element as a traffic sign as an example, table 2 counts information such as the number of elements and the drawing time of the traffic sign of each sample map task in a plurality of sample map tasks. The plurality of sample tasks can be represented by task numbers, and the sample map task corresponding to each task number is completed by one numbered operator.
TABLE 2
Therefore, the electronic equipment can find the drawing time length and the drawing quantity corresponding to the task number and aiming at the traffic sign according to the task number of the sample map task. For example, the traffic sign of the sample map task with task number 401649 can be found to be drawn for 5.00min and 12 in number. By analogy, the drawing time length and the element number of the traffic sign corresponding to each task number can be found. It is understood that other map elements besides the traffic sign can also be obtained through statistical methods similar to table 2, and the corresponding drawing time lengths and quantities can also be obtained.
2012. And obtaining the total element number and the total drawing time of each sample map element according to the element number and the drawing time of each sample map element of each sample map task.
As an example, taking table 2 as an example, the total drawing time length may be obtained by adding the drawing time lengths of the traffic signs in all the sample map tasks according to table 2, and then the total number of elements, such as 127 elements, of the traffic signs in all the sample map tasks may be obtained by adding the number of elements. It is understood that other map elements besides the traffic sign board can also obtain the corresponding total drawing time length and the total element number in a statistical manner similar to table 2.
2013. And determining the drawing efficiency mean value corresponding to each sample map element according to the total element number and the total drawing time of each sample map element.
By taking the above example, the total element number and the total drawing time of the traffic sign can be calculated, and the drawing efficiency average value (hereinafter, may be referred to as the efficiency average value) corresponding to the traffic sign is obtained. It should be understood that other map elements besides the traffic sign may also be obtained by calculating the average value of the rendering efficiency of the traffic sign, and therefore are not described herein.
202. And determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element.
In some embodiments, as shown in fig. 4, step 202 may comprise:
2021. and obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task.
As an example, taking table 2 as an example, for example, if the drawing time of the 401649 sample map task with the task number is 5.00min and the number is 12, the drawing time may be divided by the number to obtain the drawing efficiency of the traffic sign in the 401649 sample map task with the task number of 2.4 traffic signs per minute, and then the drawing efficiency is taken every 10 units, so that the drawing efficiency may be determined to be 0.24. By analogy, the drawing efficiency of each sample map element in each sample task can be obtained.
2022. And calculating the variance of the drawing efficiency of each sample map element to obtain the efficiency variance.
Taking the above example, the variance of all rendering efficiencies (e.g., 0.25, 0.05 … 0.11.11, 0.10) in table 2 can be calculated, and the resulting variance of the efficiencies is 0.005482347.
2023. And correcting the drawing efficiency mean value corresponding to each map element through the efficiency variance to obtain the corrected drawing efficiency mean value corresponding to each map element.
The specific implementation manner of step 2023 includes: calculating a quotient value of the element quantity and the total element quantity of each map element; calculating the product of the quotient of the number of the elements of each map element and the total number of the elements and the efficiency variance to obtain an error correction value corresponding to each map element; and calculating the difference value between the drawing efficiency average value corresponding to each map element and the error correction value to obtain the corrected drawing efficiency average value corresponding to each map element.
As an example, as shown in table 2, taking a sample map task with task number 401649 as an example, the quotient of the number of elements corresponding to the traffic sign and the total number of elements is 12/127, and then product calculation is performed between 12/127 and the efficiency variance, so that the error correction value corresponding to the traffic sign in the sample map task of 401649 is 0.005482347 × 12/127. The error correction value is subtracted from the efficiency average value in the sample map task with task number 401649, and the corrected drawing efficiency average value is 0.13-0.005482347 × 12/127. It is understood that other map elements may also obtain the modified rendering efficiency average value in the above manner. Therefore, the corrected drawing efficiency average value corresponding to each map element can be obtained.
2024. And if the corrected drawing efficiency average value corresponding to each map element meets a preset condition, determining the difficulty coefficient of each map element according to the corrected drawing efficiency average value corresponding to each map element.
In some embodiments, as shown in fig. 5, before step 2024, the method may further include:
2024a, obtaining a first mean error of each sample map element for each sample map according to the drawing efficiency mean value corresponding to each map element, the number of elements of each sample map element, and the drawing time length.
As one way, a specific implementation of step 2023a may include: calculating the product of the drawing efficiency mean value and the drawing time length corresponding to each map element to obtain a mean value calculation value corresponding to each map element; and calculating the difference value between the mean calculation value corresponding to each map element and the element number to obtain a first mean error of each sample map element for each sample map.
As an example, taking map elements as traffic signs as an example, as shown in table 2, when the average drawing efficiency (0.13 × 10) of the traffic signs in the sample map task with task number 401649 is multiplied by the drawing time (5.00min) minus the number of elements (12), a mean error (-5.5) is obtained and is used as a first mean error, and so on, the first mean error corresponding to the traffic signs in each sample map task can be obtained through the above calculation method.
2024b, obtaining a second mean error of each sample map element for each sample map according to the corrected drawing efficiency mean value corresponding to each map element, the element number of each sample map element and the drawing time length.
As a way, a specific implementation of step 2023b may include: calculating the product of the corrected drawing efficiency average value and the drawing time length corresponding to each map element to obtain a corrected average value calculated value corresponding to each map element; and calculating the difference value between the corrected average calculated value corresponding to each map element and the element number to obtain a second average error of each sample map element for each sample map.
The specific implementation of step 2023b may refer to the specific implementation of step 2023a, and specifically, the drawing efficiency average value is replaced by the corrected drawing efficiency average value.
2024c, calculating the variance of the first mean error to obtain a first variance, and calculating the variance of the second mean error to obtain a second variance.
As an example, as shown in table 2, the number of the first mean errors in table 2 is multiple, and the variance calculation may be performed on the multiple first mean errors to obtain the first variance, for example, the first variance is a discrete value a, i.e., -25.45 in table 2. Accordingly, the number of the second mean errors is also multiple, and the second variance may be obtained by performing variance calculation on the multiple second mean errors, for example, the second variance is a discrete value B.
2024d, if the first variance is greater than the second variance, determining that the modified drawing efficiency mean corresponding to each map element meets a preset condition.
Taking advantage of the above example, if a is greater than B, it indicates that the corrected drawing efficiency average is more reliable than the original drawing efficiency average, and it can be determined that the corrected drawing efficiency average corresponding to each map element satisfies the preset condition.
In some embodiments, the method further comprises: and if the first variance is smaller than the second variance, determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element.
Taking advantage of the above example, if a is smaller than B, the corrected drawing efficiency average value is not reliable, and the difficulty coefficient of each map element may be determined according to the drawing efficiency average value corresponding to each map element, so that the original drawing efficiency average value is used to calculate the difficulty coefficient.
Since variance is a measure of the degree of dispersion when probability theory and statistical variance measure a random variable or a set of data. In the present embodiment, the first variance (i.e., the discrete value a) and the second variance (i.e., the discrete value B) can measure the dispersion degree of the mean efficiency error before the correction and the dispersion degree of the mean efficiency error after the correction, respectively. By comparing the discrete value a with the discrete value B. If A is greater than B, the corrected mean value is more reliable. If A is less than B, the corrected average value is not credible and is not adopted, and the average efficiency before correction is continuously used. Therefore, the reliability of the drawing efficiency mean value of the difficulty coefficient used for calculating the map elements can be ensured, and the accuracy of the difficulty coefficient is improved.
203. And determining the map task difficulty level of the map according to the element number of each map element and the difficulty coefficient of each map element.
204. And acquiring the drawing efficiency of each of a plurality of drawing persons.
As an example, table 1 is an example, and the drawing efficiency corresponding to each drawing person (hereinafter, may be referred to as an operator) may be taken as the drawing efficiency thereof.
205. And carrying out map task allocation on the map according to the drawing efficiency of each drawing person and the map task difficulty level of the map.
As an example, when the operation platform configured by the electronic device runs a corresponding program, the map task may be issued to an adapted operator account according to the difficulty level of the map task and the ranking of the drawing efficiency of the operator, so that the drafter completes the task of difficulty matching. The specific operation flow can be as follows: the program determines the task difficulty level of each map according to the determined difficulty coefficients and the determined number of the elements of each map, and divides the difficulty gradient, wherein the difficulty gradient can be set to be 1-5 or 1-10 and the like, and each user can set the difficulty gradient in proportion. And calculating the drawing efficiency mean value of each drafter according to the time spent by each drafter for completing the map task corresponding to each difficulty gradient, and sequencing the drawing efficiency mean values from high to low in sequence, so that the operation level gradient of the drafter is determined, and the operation level gradient can be matched with the drawing operation difficulty gradient. For example, when a drafter gets a new task, the program automatically issues a map task with a difficulty gradient of 1 to a drafter account with a job level gradient of 1. Alternatively, the work platform may issue map tasks at low difficulty levels to a drafter at a high job level.
In some embodiments, the program may summarize and record the time consumed by the single element of each drafter according to a specified time period (e.g., off duty time every day/every night), and repeat the above steps to calculate the difficulty coefficient of the map element, so as to update the difficulty coefficient of the map element, thereby ensuring that the task difficulty level can be updated in real time as the drafter drafting level is increased, and making the task difficulty calculation more accurate, real and credible.
In some embodiments, the map task processing method of the present embodiment further includes:
206. and removing the sample map corresponding to the map element with the drawing efficiency not within the specified efficiency range from the plurality of sample maps.
As an example, the work platform may be configured with an optimization algorithm that automatically learns and determines an error value for each map element difficulty factor after accumulating a certain amount of computation, for example. The error value of the difficulty coefficient is mainly caused by uneven improvement of the drawing level of the drafter. Therefore, when the difficulty level of the map task is updated every day/every week, invalid sample amount is removed, and the data difficulty reliability is further increased. The specific implementation algorithm is as follows: after the data are accumulated to the fifth week or the tenth week, wherein the user sets the number of weeks by himself, the program calculates, compares and rejects the efficiency values of the maximum 1% and the minimum 1% of the statistical efficiency data in the week to obtain a new average value, and compares the new average value with the data not rejected by using the above steps. After obtaining a new credible efficiency average value, compared with the numerical value of the first 2% and the second 2% after elimination, the repeated and same steps are adopted to establish the new efficiency average value. And stopping comparison after the data of the first 10 percent and the data of the second 10 percent are calculated and eliminated. Alternatively, the number of data samples may be reduced due to excessive culling data, and the maximum value of > 10% culling may be prohibited. Alternatively, the user may want to customize the culling maximum number. And calculating the difficulty level of the new map task by using the efficiency with the minimum discrete degree after comparison, thereby ensuring that the difficulty level of the map task can be accurately graded.
It can be seen that, in this embodiment, by combining the error correction number and the statistical variance of the metrology, when calculating the per-person single-element efficiency of all the operators, the per-person single-element efficiency is corrected by using the error correction number, and the error calculation according to the variance verifies that the corrected single-element efficiency value has a smaller dispersion degree, more real data and higher reliability. In addition, the difficulty coefficient and the number of elements of each map element can be automatically calculated, so that the task difficulty level is determined, the difficulty coefficient value is periodically updated every day or every week, and the accuracy and the credibility of the numerical value are ensured.
Fig. 6 is a schematic structural diagram of a map task processing device according to an embodiment of the present application, and as shown in fig. 6, the device includes:
the average efficiency and number obtaining module 31 is configured to obtain a drawing average efficiency and a number of elements of each map element of the map.
The difficulty coefficient determining module 32 is configured to determine the difficulty coefficient of each map element according to the drawing efficiency average value corresponding to each map element.
The difficulty level determining module 33 is configured to determine a map task difficulty level of the map according to the number of the elements of each map element and the difficulty coefficient of each map element.
And the output module 34 is used for outputting the map task of the map according to the map task difficulty level.
For example, the present embodiment may refer to the above method embodiments, and the principle and the technical effect are similar and will not be described again.
In another schematic structural diagram of a map task processing device provided in the embodiment of the present application, on the basis of the embodiment shown in fig. 4, the efficiency average and quantity obtaining module 31 includes:
and the sample acquiring unit is used for acquiring the element number and the drawing time length of each sample map element of each sample map task in the plurality of sample map tasks.
And the sample processing unit is used for obtaining the total element number and the total drawing time of each sample map element according to the element number and the drawing time of each sample map element of each sample map task.
And the efficiency average value determining unit is used for determining the drawing efficiency average value corresponding to each sample map element according to the total element number and the total drawing time length of each sample map element.
In one example, the difficulty level determining module 33 includes:
and the drawing efficiency determining unit is used for obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task.
And the efficiency variance acquiring unit is used for calculating the variance of the drawing efficiency of each sample map element to obtain the efficiency variance.
And the correcting unit is used for correcting the drawing efficiency mean value corresponding to each map element through the efficiency variance to obtain the corrected drawing efficiency mean value corresponding to each map element.
And the difficulty system determining unit is used for determining the difficulty coefficient of each map element according to the corrected drawing efficiency mean value corresponding to each map element if the corrected drawing efficiency mean value corresponding to each map element meets a preset condition.
In one example, the correction unit is specifically configured to:
calculating a quotient value of the element quantity and the total element quantity of each map element; and performing product calculation on the quotient of the number of the elements of each map element and the total number of the elements and the efficiency variance to obtain an error correction value corresponding to each map element.
And calculating the difference value between the drawing efficiency average value corresponding to each map element and the error correction value to obtain the corrected drawing efficiency average value corresponding to each map element.
In one example, the correction unit is further configured to:
and obtaining a first mean value error of each sample map element for each sample map according to the drawing efficiency mean value corresponding to each map element, the element number and the drawing time of each sample map element.
And obtaining a second mean value error of each sample map element for each sample map according to the corrected drawing efficiency mean value corresponding to each map element, the element number and the drawing time of each sample map element.
And calculating the variance of the first mean error to obtain a first variance, and calculating the variance of the second mean error to obtain a second variance.
And if the first variance is larger than the second variance, determining that the corrected drawing efficiency mean value corresponding to each map element meets a preset condition.
In one example, the correction unit is further configured to:
and if the first variance is smaller than the second variance, determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element.
In an example, the correction unit is further specifically configured to:
and calculating the product of the drawing efficiency mean value and the drawing time length corresponding to each map element to obtain a mean value calculation value corresponding to each map element.
And calculating the difference value between the mean calculation value corresponding to each map element and the element number to obtain a first mean error of each sample map element for each sample map.
And calculating the product of the corrected drawing efficiency average value and the drawing time length corresponding to each map element to obtain a corrected average value calculated value corresponding to each map element.
And calculating the difference value between the corrected average calculated value corresponding to each map element and the element number to obtain a second average error of each sample map element for each sample map.
In one example, the output module includes:
and the drawing efficiency obtaining sub-module is used for obtaining the drawing efficiency of each of the plurality of drawing personnel.
And the distribution submodule is used for carrying out map task distribution on the map according to the drawing efficiency of each drawing person and the map task difficulty level of the map.
In one example, the map task processing apparatus further includes:
and the drawing efficiency obtaining module is used for obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task.
And the elimination module is used for removing the sample map corresponding to the map element of which the drawing efficiency is not in the specified efficiency range from the plurality of sample maps.
For example, the present embodiment may refer to the above method embodiments, and the principle and the technical effect are similar and will not be described again.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 6, the electronic device includes a memory 43 and a processor 42.
A memory 43 for storing instructions executable by the processor 42.
The processor 42 is configured to perform the methods provided by the above embodiments.
The electronic device further comprises a receiver 40 and a transmitter 41. The receiver 40 is used for receiving commands and data transmitted from an external device, and the transmitter 41 is used for transmitting commands and data to the external device.
Fig. 8 is a block diagram of an electronic device, which may be a smart phone, a computer, a digital broadcast terminal, a messaging device, a tablet device, a personal digital assistant, or the like, according to an embodiment of the present disclosure.
The apparatus 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, a sensor component 814, and a communication component 816.
The processing component 802 generally controls overall operation of the device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the apparatus 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The multimedia component 808 includes a screen that provides an output interface between the device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the device 800. For example, the sensor assembly 814 may detect the open/closed status of the device 800, the relative positioning of components, such as a display and keypad of the device 800, the sensor assembly 814 may also detect a change in the position of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration/deceleration of the device 800, and a change in the temperature of the device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communications between the apparatus 800 and other devices in a wired or wireless manner. The device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the device 800 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
The embodiment of the application provides a computer-readable storage medium, in which computer-executable instructions are stored, and the computer-executable instructions are executed by a processor to implement the method provided by the above embodiment.
An embodiment of the present application provides a computer program product, where the computer program product includes: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, the at least one processor executing the computer program causing the electronic device to perform the solution provided by any of the embodiments described above.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (13)
1. A map task processing method is characterized by comprising the following steps:
obtaining a drawing efficiency average value corresponding to each map element of a map and the number of the elements of each map element;
determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element;
determining the map task difficulty level of the map according to the element number of each map element and the difficulty coefficient of each map element;
and outputting the map task of the map according to the map task difficulty level.
2. The method of claim 1, wherein obtaining the average value of the rendering efficiency corresponding to each map element of the map comprises:
obtaining the element number and drawing time of each sample map element of each sample map task in a plurality of sample map tasks;
obtaining the total element quantity and the total drawing time of each sample map element according to the element quantity and the drawing time of each sample map element of each sample map task;
and determining the drawing efficiency mean value corresponding to each sample map element according to the total element number and the total drawing time of each sample map element.
3. The method of claim 2, wherein determining the map task difficulty rating for the map based on the number of elements per map element and the difficulty factor per map element comprises:
obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task;
calculating the variance of the drawing efficiency of each sample map element to obtain an efficiency variance;
correcting the drawing efficiency mean value corresponding to each map element through the efficiency variance to obtain a corrected drawing efficiency mean value corresponding to each map element;
and if the corrected drawing efficiency average value corresponding to each map element meets a preset condition, determining the difficulty coefficient of each map element according to the corrected drawing efficiency average value corresponding to each map element.
4. The method according to claim 3, wherein the correcting the drawing efficiency average value corresponding to each map element through the efficiency variance to obtain a corrected drawing efficiency average value corresponding to each map element includes:
calculating a quotient value of the element quantity and the total element quantity of each map element; calculating the product of the quotient of the number of the elements of each map element and the total number of the elements and the efficiency variance to obtain an error correction value corresponding to each map element;
and calculating the difference value between the drawing efficiency average value corresponding to each map element and the error correction value to obtain the corrected drawing efficiency average value corresponding to each map element.
5. The method according to claim 3, wherein before determining the difficulty coefficient of each map element according to the modified drawing efficiency mean value corresponding to each map element if the modified drawing efficiency mean value corresponding to each map element meets a preset condition, the method further comprises:
obtaining a first mean value error of each sample map element for each sample map according to the drawing efficiency mean value corresponding to each map element, the element number and the drawing duration of each sample map element;
obtaining a second mean value error of each sample map element for each sample map according to the corrected drawing efficiency mean value corresponding to each map element, the element number and the drawing duration of each sample map element;
calculating the variance of the first mean error to obtain a first variance, and calculating the variance of the second mean error to obtain a second variance;
and if the first variance is larger than the second variance, determining that the corrected drawing efficiency mean value corresponding to each map element meets a preset condition.
6. The method of claim 5, further comprising:
and if the first variance is smaller than the second variance, determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element.
7. The method according to claim 5, wherein obtaining a first mean error of each sample map element for each sample map according to the drawing efficiency mean value corresponding to each map element, the number of elements of each sample map element, and the drawing duration comprises:
calculating the product of the drawing efficiency mean value and the drawing time length corresponding to each map element to obtain a mean value calculation value corresponding to each map element;
calculating a difference value between the mean calculation value corresponding to each map element and the element number to obtain a first mean error of each sample map element for each sample map;
obtaining a second mean error of each sample map element for each sample map according to the corrected drawing efficiency mean value corresponding to each map element, the element number of each sample map element, and the drawing duration, including:
calculating the product of the corrected drawing efficiency average value and the drawing time length corresponding to each map element to obtain a corrected average value calculated value corresponding to each map element;
and calculating the difference value between the corrected average calculated value corresponding to each map element and the element number to obtain a second average error of each sample map element for each sample map.
8. The method of any of claims 2-7, wherein outputting the map task for the map based on the map task difficulty rating comprises:
obtaining the drawing efficiency of each drawing person in a plurality of drawing persons;
and carrying out map task allocation on the map according to the drawing efficiency of each drawing person and the map task difficulty level of the map.
9. The method according to any one of claims 2-7, further comprising:
obtaining the drawing efficiency of each sample map element according to the element number and the drawing time of each sample map element of each sample map task;
and removing the sample map corresponding to the map element with the drawing efficiency not within the specified efficiency range from the plurality of sample maps.
10. A map task processing apparatus, comprising:
the efficiency average value and quantity acquisition module is used for acquiring the drawing efficiency average value corresponding to each map element of the map and the element quantity of each map element;
the difficulty coefficient determining module is used for determining the difficulty coefficient of each map element according to the drawing efficiency mean value corresponding to each map element;
the difficulty level determining module is used for determining the map task difficulty level of the map according to the element number of each map element and the difficulty coefficient of each map element;
and the output module is used for outputting the map task of the map according to the map task difficulty level.
11. An electronic device, comprising: a memory and a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to perform the method of any one of claims 1-9.
12. A computer-readable storage medium having computer-executable instructions stored thereon, which when executed by a processor, perform the method of any one of claims 1-9.
13. A computer program product, characterized in that it comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1 to 9.
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