Method, apparatus, device and storage medium for determining vehicle use

Abstract

The present invention provides a method, device, equipment and storage medium for determining the use of a vehicle, relating to the technical field of vehicles, and is used to improve the efficiency of determining the use of a vehicle, including: a device for determining the use of a vehicle obtains target driving information of a target vehicle within a historical time period; wherein, the target driving information includes a plurality of target transport distances and the fuel consumption and speed corresponding to each target transport distance. Further, the device for determining the use of a vehicle determines the target use of the target vehicle according to the target driving information.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicles, and particularly to a method, device, equipment and storage medium for determining the use of vehicles. Background Art

[0002] Currently, the number of commercial vehicles in the market is huge. However, due to the low level of intelligence of traditional manufacturers of commercial vehicles, there is currently no organization or manufacturer that can comprehensively understand the application scenarios and uses of these vehicles. To maximize the benefits of limited resources, statistical analysis of vehicles for different uses can further clarify the market positioning, target population, configuration parameters, etc. of the vehicles, greatly improving the R & D efficiency of vehicle manufacturers and enhancing the core competitiveness of vehicle manufacturers.

[0003] However, due to the low level of intelligence of traditional vehicle factories that manufacture commercial vehicles, for the identification of vehicle uses, the uses of vehicles are usually determined only by staff through pre-sales inquiries or after-sales return visits to drivers. And using this method to determine vehicle uses requires a large amount of human support, and the scope that can be investigated is small, and the final data obtained is relatively one-sided. Summary of the Invention

[0004] The present invention provides a method, device, equipment and storage medium for determining the use of vehicles, realizing the automated and efficient determination of vehicle uses.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] In the first aspect, a method for determining the use of a vehicle is provided. The method includes: a vehicle use determination device obtains target driving information of a target vehicle within a historical time period; wherein, the target driving information includes a plurality of target driving distances and the fuel consumption and speed corresponding to each target driving distance. Further, the vehicle use determination device determines the target use of the target vehicle according to the target driving information.

[0007] In the method for determining the use of a vehicle provided by the present invention, by means of the vehicle networking technology, by obtaining the vehicle driving information uploaded by in-vehicle devices, the target driving distance of the target vehicle and the fuel consumption and speed corresponding to each driving distance are determined. In this way, the vehicle use can be determined through the driving distance, fuel consumption and speed, realizing the automated, efficient and large-batch determination of vehicle uses, overcoming the dependence on manpower, and being able to be widely promoted and used.

[0008] In a possible design, the above-mentioned determining device for vehicle use determines the target use of the target vehicle according to the target driving information, including: for the first target travel distance, based on a preset mapping relationship, the first target travel distance, and the fuel consumption and speed corresponding to the first target travel distance, determining the candidate uses corresponding to the first target travel distance; the first target travel distance is any one of multiple target travel distances, and the mapping relationship includes the use of the vehicle, the travel distance range, the fuel consumption range, and the speed range. Further, the determining device for vehicle use determines the target use from the candidate uses corresponding to the multiple target travel distances; the target use is the candidate use corresponding to the largest number of travel distances among the candidate uses corresponding to the multiple target travel distances. In this design, the determining device for vehicle use determines the candidate uses corresponding to multiple travel distances and then determines the target use from the multiple candidate uses, which can improve the accuracy of use determination.

[0009] In a possible design, the above-mentioned determining device for vehicle use determines the target use of the target vehicle according to the target driving information, including: the determining device for vehicle use determines the target driving characteristics of the target driving information according to the target driving information; inputting the target driving characteristics into a pre-trained prediction model to obtain a target use identifier; the prediction model includes a convolutional neural network model, and the convolutional neural network model is used to generate a use identifier according to the driving characteristics of the vehicle; further, based on the target use identifier, the target use is determined. In this design, the target use identifier of the target vehicle is determined through the convolutional neural network model. Since the convolutional neural network model is obtained through a large amount of training, the accuracy of determining the target use can be improved.

[0010] In a possible design, the determining device for vehicle use obtains the sample driving information of the sample vehicle and the sample use identifier of the sample vehicle; the sample driving information includes multiple sample travel distances and the fuel consumption and speed corresponding to each sample travel distance. Further, the determining device for vehicle use uses the sample driving characteristics of the sample driving information as features and the sample use identifier as a supervision signal to perform supervised training on a preset model to obtain a prediction model. In this design, it is realized how to train the model for determining the target use of the target vehicle. Training with a large amount of data can improve the accuracy of the model.

[0011] In a second aspect, a determining device for vehicle use is provided, including an obtaining unit and a determining unit. The obtaining unit is used to obtain the target driving information of the target vehicle within a historical time period; the target driving information includes multiple target travel distances and the fuel consumption and speed corresponding to each target travel distance; the determining unit is used to determine the target use of the target vehicle according to the target driving information.

[0012] In a possible design, the determination unit is specifically configured to determine, for a first target travel distance, a candidate use corresponding to the first target travel distance based on a preset mapping relationship, the first target travel distance, and the fuel consumption and speed corresponding to the first target travel distance; the first target travel distance is any one of a plurality of target travel distances, and the mapping relationship includes the use of the vehicle, the travel distance range, the fuel consumption range, and the speed range. The determination unit is further configured to determine a target use from the candidate uses corresponding to the plurality of target travel distances; the target use is the candidate use corresponding to the largest number of travel distances among the candidate uses corresponding to the plurality of target travel distances.

[0013] In a possible design, the apparatus for determining the use of a vehicle further includes a processing unit. The determination unit is specifically configured to determine the target travel characteristics of the target travel information according to the target travel information. The processing unit is configured to input the target travel characteristics into a pre-trained prediction model to obtain a target use identifier; the prediction model includes a convolutional neural network model, and the convolutional neural network model is configured to generate a use identifier according to the travel characteristics of the vehicle. The determination unit is further configured to determine the target use based on the target use identifier.

[0014] In a possible design, the acquisition unit is further configured to acquire the sample travel information of the sample vehicle and the sample use identifier of the sample vehicle; the sample travel information includes a plurality of sample travel distances and the fuel consumption and speed corresponding to each sample travel distance. The processing unit is further configured to use the sample travel characteristics of the sample travel information as features and the sample use identifier as a supervision signal to perform supervised training on a preset model to obtain a prediction model.

[0015] In a third aspect, a device for determining the use of a vehicle is provided. The device for determining the use of a vehicle includes a memory and a processor; the memory and the processor are coupled. The memory is used to store computer program code, and the computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes the method for determining the use of a vehicle as in the first aspect.

[0016] In a fourth aspect, a computer-readable storage medium is provided. Instructions are stored in the computer-readable storage medium. When the instructions run on the device for determining the use of a vehicle, the device for determining the use of a vehicle is caused to execute the method for determining the use of a vehicle as in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 FIG. is a schematic structural diagram of a system for determining the use of a vehicle provided by an embodiment of the present invention;

[0018] Figure 2 FIG. is a schematic flow chart of a method for determining the use of a vehicle provided by an embodiment of the present invention Figure 1 ;

[0019] Figure 3A schematic diagram of location information provided for an embodiment of the present invention Figure 1 ;

[0020] Figure 4 A schematic diagram of location information provided for an embodiment of the present invention Figure 2 ;

[0021] Figure 5 A schematic diagram of location information provided for an embodiment of the present invention Figure 3 ;

[0022] Figure 6 A schematic diagram of a vehicle trajectory provided for an embodiment of the present invention;

[0023] Figure 7 A schematic flow chart of a method for determining the use of a vehicle provided for an embodiment of the present invention Figure 2 ;

[0024] Figure 8 A schematic flow chart of a method for determining the use of a vehicle provided for an embodiment of the present invention Figure 3 ;

[0025] Figure 9 A schematic flow chart of a method for determining the use of a vehicle provided for an embodiment of the present invention Figure 4 ;

[0026] Figure 10 A schematic structural diagram of a device for determining the use of a vehicle provided for an embodiment of the present invention;

[0027] Figure 11 A schematic structural diagram of a device for determining the use of a vehicle provided for an embodiment of the present invention Figure 1 ;

[0028] Figure 12 A schematic structural diagram of a device for determining the use of a vehicle provided for an embodiment of the present invention Figure 2 . Detailed implementation manners

[0029] Next, the technical solutions in the embodiments of the present invention will be described with reference to the accompanying drawings in the embodiments of the present invention.

[0030] In the embodiments of the present invention, words such as "exemplary" or "for example" are used to represent examples, illustrations, or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0031] In the description of the present invention, unless otherwise specified, " / " means "or". For example, A / B may represent A or B. "And / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, "at least one" and "a plurality of" refer to two or more. The words such as "first" and "second" do not limit the quantity and execution order, and the words such as "first" and "second" do not necessarily limit being different.

[0032] In the prior art, due to the low level of intelligence of traditional vehicle manufacturers for commercial vehicles, for the identification of vehicle uses, the uses of vehicles are usually determined only by pre-sales inquiries or after-sales follow-up of drivers by staff. And using this method to determine the vehicle use requires a large amount of human support, and the scope that can be investigated is small, and the finally obtained data is relatively one-sided.

[0033] To solve the above problems, the present invention provides a method, device, equipment and storage medium for determining vehicle uses. The device for determining vehicle uses obtains target driving information of a target vehicle within a historical time period, where the target driving information includes a plurality of target transport distances and the fuel consumption and speed corresponding to each transport distance. Further, the device for determining vehicle uses determines the target use of the target vehicle according to the target driving information. In the method for determining vehicle uses provided by the present invention, by means of the vehicle networking technology, by obtaining the vehicle driving information uploaded by in-vehicle devices, the target transport distance of the target vehicle and the fuel consumption and speed corresponding to each transport distance are determined. In this way, the vehicle use can be determined through the transport distance, fuel consumption and speed, realizing the automation, high efficiency and large batch determination of vehicle uses, overcoming the dependence on manpower, and being able to be widely promoted and used.

[0034] The method for determining vehicle uses provided by the embodiments of the present invention can be applied to a system for determining vehicle uses. The system for determining vehicle uses is used to determine the use of a target vehicle in response to a request from a user after receiving the request from the user to determine the use of the target vehicle. Figure 1 A schematic structural diagram of the system for determining vehicle uses is shown. As Figure 1 shown, the system 10 for determining vehicle uses includes a device 11 for determining vehicle uses, a server 12 and an in-vehicle device 13.

[0035] Among them, the server 12 is respectively connected to the device 11 for determining vehicle uses and the in-vehicle device 13. The connection between the server 12 and the device 11 for determining vehicle uses can be wired or wireless, and the embodiments of the present invention do not limit this; the connection between the server 12 and the in-vehicle device 13 is wireless.

[0036] The vehicle use determination device 11 can be used to obtain the driving information of the target vehicle from the server 12. Among them, the driving information includes data such as the position information, driving mileage, fuel consumption, and speed of the target vehicle.

[0037] The vehicle use determination device 11 can also be used to determine the target driving information based on the driving information. Among them, the target driving information includes a plurality of target transport distances and the fuel consumption and speed corresponding to each transport distance. The transport distance is the farthest straight-line distance after a vehicle completes a transportation task. The fuel consumption corresponding to the transport distance is the average fuel consumption per 100 kilometers of the vehicle in the transportation task corresponding to the transport distance, and the speed corresponding to the transport distance is the average speed of the vehicle in the transportation task corresponding to the transport distance.

[0038] After the vehicle use determination device 11 determines the target driving information of the target vehicle, it can also determine the target use of the target vehicle according to the target driving information of the target vehicle. Among them, the uses of the target vehicle include long-distance transport vehicles, short-distance transport vehicles, medium and long-distance transport vehicles, and dedicated line logistics vehicles, etc.

[0039] It should be noted that the vehicle use determination device 11 stores the mapping relationship between the target driving information and the target use. In this way, after the vehicle use determination device 11 determines the target driving information of the target vehicle, it can determine the target use of the target vehicle according to this mapping relationship.

[0040] The server 12 can be used to receive the vehicle driving information periodically uploaded by the in-vehicle device 13 and store it.

[0041] The in-vehicle device 13 can be a vehicle networking intelligent terminal (Telematics BOX, T-BOX), which is used to periodically upload the vehicle driving information to the server 12.

[0042] Figure 2 It is a flowchart showing a method for determining vehicle use according to some exemplary embodiments. In some embodiments, the above method for determining vehicle use can be applied to the vehicle use determination device 11 of the base station device in the communication system as Figure 1 shown. The method for determining vehicle use provided by the embodiments of the present invention will be described below with reference to the accompanying drawings.

[0043] As Figure 2 shown, the method for determining vehicle use provided by the embodiments of the present invention is applied to the above vehicle use determination system 10, including S201 - S202.

[0044] S201. The vehicle use determination device obtains the target driving information of the target vehicle within the historical time period.

[0045] Among them, the target driving information includes multiple transportation distances and the fuel consumption and speed corresponding to each transportation distance. The transportation distance is the farthest straight-line distance after a vehicle completes a transportation task. The fuel consumption corresponding to the transportation distance is the average fuel consumption per 100 kilometers of the vehicle in the transportation task corresponding to the transportation distance, and the speed corresponding to the transportation distance is the average speed of the vehicle in the transportation task corresponding to the transportation distance.

[0046] As a possible implementation, the vehicle use determination device obtains multiple location information reported by in-vehicle devices from the server, as well as the speed and fuel consumption corresponding to each location information. Further, the vehicle use determination device determines multiple target transportation distances based on the multiple location information, and determines the fuel consumption and speed corresponding to the target transportation distance based on the fuel consumption and speed corresponding to each location information.

[0047] It should be noted that, in order to make the determined target transportation distance more valuable for reference, the above historical time period is a time period including multiple transportation tasks of the vehicle. How the vehicle use determination device determines multiple target transportation distances based on multiple location information can be referred to the following steps S2011 - S2013.

[0048] S2011. The vehicle use determination device performs data processing on the multiple location information obtained.

[0049] As a possible implementation, the vehicle use determination device uses big data distributed technologies such as spark and hive to perform data warehouse technology (Extract-Transform-Load, ETL) operations such as cleaning, filtering, and converting the format on the multiple location information obtained, removing dirty data, and unifying the data format.

[0050] It can be understood that among the multiple location information obtained, there may be situations such as omission, missing, deviation, and inconsistent data format, resulting in the data obtained being unable to be directly used. Therefore, the embodiments of the present invention perform ETL operations such as data cleaning, filtering, and converting the format on the obtained data, which can process the original data to an available degree and avoid the impact of dirty data on subsequent determination of vehicle use.

[0051] S2012. The vehicle use determination device filters multiple target location information from the multiple location information after data processing according to preset rules.

[0052] It should be noted that the preset rules can be set in advance in the vehicle use determination device by the operation and maintenance personnel of the vehicle use determination device. Exemplarily, the preset rules can include: deleting the location information when the vehicle is in a stopped state, deleting the location information whose distance difference between adjacent time location information is greater than the first threshold, and deleting the location information whose distance difference between adjacent time location information is less than the second threshold.

[0053] The first threshold and the second threshold can be pre-set in the vehicle usage determination device by the operation and maintenance personnel of the vehicle usage determination device. The embodiments of the present invention do not limit this.

[0054] In some embodiments, the vehicle reports data even when it is in a stopped state, and such data is meaningless for determining the vehicle travel distance. Therefore, this part of the data needs to be filtered out.

[0055] Exemplarily, as Figure 3 shown, some of the position points A - G among multiple position information are shown. Among them, the speeds of the position points A - G are 30 kilometers per hour (km / h), 50 km / h, 20 km / h, 0 km / h, 2 km / h, 0 km / h, and 20 km / h respectively. The vehicle usage determination device determines that the position points D and F are the points where the vehicle is in a stopped state based on the speed information of the position points A - G. Therefore, the position points D and F are deleted, and the position points A, B, C, E, and G are determined as the target position information, and the position points A, B, C, E, and G are retained for subsequent determination of the travel distance.

[0056] Due to the complex operating environment of the vehicle, the data reported by the in-vehicle device may have errors. The vehicle's shaking causes the in-vehicle device to judge that the vehicle has a speed. To overcome this problem, the vehicle usage determination device deletes the position points with a speed less than 5 km / h. As Figure 3 shown in the respective position information, the vehicle usage determination device determines that the speeds corresponding to the position points D, E, and F are less than 5 km / h based on the speed information of the position points A - G. Therefore, the position points D, E, and F are determined as the points where the vehicle is in a stopped state, and the position points D, E, and F are deleted, and the position points A, B, C, and G are determined as the target position information, and the position points A, B, C, and G are retained for subsequent determination of the travel distance.

[0057] In some embodiments, due to problems in the vehicle operating environment, the position information reported by the in-vehicle device may be incorrect, resulting in an excessive distance difference between the position information reported at adjacent time points. Since this position information is incorrect, this part of the data needs to be filtered out.

[0058] Exemplarily, as Figure 4 shown, some of the position points H - N among multiple position information are shown. Among them, the position points H - N are the position points corresponding to the position information uploaded by the in-vehicle device according to time, and the distances between adjacent position points are 5 kilometers (km), 4 km, 6 km, 2 km, 50 km, and 52 km respectively.

[0059] If the first threshold is 20 km, based on the distance difference between position points H - N and the first threshold, the vehicle use determination device determines that the distance differences between position points L - M and between position points M - N are greater than the first threshold. Therefore, position points L, M, and N are deleted, and position points H, I, J, and K are determined as the target position information, which is retained for subsequent determination of the haulage distance.

[0060] During the above screening process, the distance differences between position points L - M and between position points M - N are greater than the first threshold because the position information of position point M is reported incorrectly, while the position information of position points L and N is normal data but is deleted.

[0061] Therefore, to overcome the misdeletion situation that occurs during the above screening process, in some embodiments, when the vehicle use determination device determines that among three consecutive adjacent position points, if the distance differences between the middle position point and the two end position points are greater than the first threshold and the distance difference between the two end position points is less than the first threshold, only the middle position point is deleted.

[0062] Exemplarily, in the Figure 4 shown position information, since the distance differences between position points L - M and M - N are greater than the first threshold, the vehicle use determination device determines that the distance difference between position points L - N is 4 km, which is less than the first threshold. Therefore, position point M is deleted, and position points H, I, J, K, L, and N are determined as the target position information, which is retained for subsequent determination of the haulage distance.

[0063] In some embodiments, to calculate a higher - precision haulage distance in the shortest possible time and reduce the time and space complexity of data calculation, thinning processing is performed on the position information.

[0064] Exemplarily, as Figure 5 shown, some of the position points O - T among multiple position information are shown. Among them, position points O - T are the position points corresponding to the position information uploaded by the on - vehicle device according to time, and the distances between adjacent position points are 5 km, 2 km, 4 km, 2 km, and 6 km respectively.

[0065] If the second threshold is 3 km, based on the distance differences between position points O - T and the second threshold, the vehicle use determination device determines that the distance differences between position points P - Q and between position points R - S are less than the second threshold. Therefore, position points Q and S are deleted, and position points O, P, R, and T are determined as the target position information, which is retained for subsequent determination of the haulage distance.

[0066] It can be understood that due to the relatively complex actual operating environment of the vehicle, there are some abnormal data in the driving information reported by the in-vehicle device to the server. As a result, although the vehicle usage determination device performs ETL operations on multiple location information, there are still some location information that is useless for determining the vehicle travel distance. At the same time, in order to reduce the time and space complexity of data calculation, the vehicle usage determination device can overcome the above problems by screening the target location information for determining the travel distance according to preset rules.

[0067] S2013. The vehicle usage determination device determines the target travel distance of the target vehicle according to multiple target location information.

[0068] As a possible implementation, the vehicle usage determination device determines the longitude and latitude of the location points corresponding to each location information according to multiple target location information. Further, the vehicle usage determination device calculates the distance between any two location points according to the determined longitude and latitude, and determines the maximum calculated distance as the target travel distance of the target vehicle.

[0069] It should be noted that after the vehicle usage determination device determines the longitude and latitude of the location points corresponding to each location information, it can use the Haversine formula to calculate the distance between any two location points. The Haversine formula is as follows:

[0070]

[0071] where d is the distance between two location points, r is the radius of the earth, is the latitude of the two location points measured in radians, and λ1, λ2 are the longitudes of the two location points measured in radians.

[0072] It can be understood that after the vehicle usage determination device determines the longitude and latitude of multiple location points, substituting the longitude and latitude of any two location points into the above Haversine formula can calculate the distance between these two location points. Then, by traversing all the location points, calculating the distances between all arbitrary two location points, and determining the maximum calculated distance as the target travel distance.

[0073] Exemplarily, as Figure 6 shown, the dotted line is the trajectory of the vehicle, and points A - E are the location points on the vehicle's driving trajectory. After the vehicle usage determination device determines that the distance between location point A and location point E is the maximum distance among the distances between any two points of location points A - E, it determines the distance between location point A and location point E as the target travel distance.

[0074] Optionally, in the case of a high-precision requirement for the transportation distance, in order to improve the accuracy of the calculated distance, the Vincenty formula can also be used to replace the above haversine formula to calculate the distance between any two position points, and then the calculated maximum distance is determined as the target transportation distance.

[0075] S202. The vehicle use determination device determines the target use of the target vehicle according to the target driving information.

[0076] As a possible implementation, the vehicle use determination device pre-stores the driving characteristics of vehicles for each use. After determining the target driving information of the target vehicle, the vehicle use determination device determines the driving characteristics corresponding to the target driving information of the target vehicle, and then compares the driving characteristics of the target vehicle with the driving characteristics of vehicles for each use to determine the target use of the target vehicle.

[0077] Exemplarily, urban construction vehicles often work in or near cities. Therefore, the position points of the vehicles are often within a certain range, and the transportation distance is short. In terms of speed, since most urban construction vehicles drive in cities, the speed is limited to a certain extent, and the average speed is less than the urban road speed limit value. In terms of fuel consumption, since most urban construction vehicles are large-power tractors with a generally large load, and affected by factors such as traffic jams and traffic lights, the average fuel consumption is relatively high. Therefore, according to the empirical value, the driving characteristics of urban construction vehicles can be set as the target transportation distance being less than the third threshold, the speed being less than the fourth threshold, and the fuel consumption being greater than the fifth threshold. When the driving characteristics corresponding to the target driving information of the target vehicle are the same as those of urban construction vehicles, the target use of the target vehicle is determined as the urban construction use.

[0078] In one design, after obtaining the target driving information, in order to implement the determination of the target use of the target vehicle based on the target driving information, as Figure 7 shown, the vehicle use determination method provided in the embodiments of the present invention further includes S301 - S302.

[0079] S301. For the first target transportation distance, the vehicle use determination device determines the candidate uses corresponding to the first target transportation distance based on the preset mapping relationship, the first target transportation distance, the fuel consumption and speed corresponding to the first target transportation distance.

[0080] Wherein, the first target transportation distance is any one of multiple target transportation distances, and the mapping relationship includes the use of the vehicle, the transportation distance range, the fuel consumption range, and the speed range.

[0081] As a possible implementation, the vehicle use determination device substitutes the determined first target transportation distance, and the fuel consumption and speed corresponding to the first transportation distance, into the preset mapping relationship to determine the corresponding candidate uses.

[0082] It should be noted that the mapping relationship between the vehicle use, the range of transportation distance, the range of fuel consumption, and the range of speed can be set by the device for determining vehicle use according to the characteristics of each use. Exemplarily, the mapping relationship between the vehicle use, the range of transportation distance, the range of fuel consumption, and the range of speed is shown in Table 1 below:

[0083] Table 1: Mapping relationship between vehicle use, range of transportation distance, range of fuel consumption, and range of speed

[0084] Use of the vehicle Transportation distance range Fuel consumption range Speed range Urban construction vehicle 20 - 50 km 33-37L 35 - 45 km / h Short - distance transportation vehicle 20 - 50 km 13-16L 46 - 55 km / h Medium - and long - distance transportation vehicle 50 - 200 km 14-17L 56 - 65 km / h Long - distance transportation vehicle 200 - 400 km 15-18L 65 - 75 km / h

[0085] Exemplarily, based on the above preset mapping relationship, if it is determined that the first target transportation distance is 350 km, the fuel consumption corresponding to the first target transportation distance is 17 liters (L), and the corresponding speed is 68 km / h, the device for determining vehicle use substitutes the determined data into the preset mapping relationship to determine that the corresponding vehicle use is a long-distance transportation vehicle, and determines the long-distance transportation vehicle as the candidate use of the target vehicle.

[0086] S302. The device for determining vehicle use determines the target use from the candidate uses corresponding to multiple target transportation distances.

[0087] Among them, the target use is the candidate use with the largest number of corresponding transportation distances among the candidate uses corresponding to multiple target transportation distances.

[0088] As a possible implementation manner, the device for determining vehicle use respectively determines the candidate uses corresponding to each target transportation distance for multiple target transportation distances to obtain multiple candidate uses. Further, the device for determining vehicle use determines the candidate use with the largest number of corresponding transportation distances among the multiple candidate uses as the target use.

[0089] Exemplarily, if it is determined that there are 6 target transportation distances within the historical time period of the target vehicle, the target transportation distances of the target vehicle, and the corresponding fuel consumption and speed for each target transportation distance are shown in Table 2 below:

[0090] Table 2: Target transportation distances, fuel consumption, and speed of the target vehicle

[0091] Transportation distance label Target transportation distance Fuel consumption Speed A 155 km 15L 60 km / h B 142 km 14L 58 km / h C 232 km 16L 68 km / h D 97 km 17L 57 km / h E 133 km 14L 63 km / h F 25 km 15L 54 km / h

[0092] After the device for determining vehicle use determines the 6 target transportation distances shown in Table 2 above, and the fuel consumption and speed corresponding to the target transportation distances, it respectively determines the candidate uses corresponding to each target transportation distance according to each target transportation distance and the corresponding fuel consumption and speed. Thus, among the above target transportation distances, the candidate uses corresponding to transportation distances A, B, D, and E are medium and long-distance transportation vehicles, the candidate use corresponding to transportation distance C is a long-distance transportation vehicle, and the candidate use corresponding to transportation distance F is a short-distance transportation vehicle.

[0093] Furthermore, when the vehicle use determination device determines candidate trips, the number of target travel distances corresponding to medium- and long-distance transport vehicles is 4, which is greater than the number 1 of long-distance transport vehicles and the number 1 of short-distance transport vehicles. Then, the vehicle use determination device determines that the target use of the target vehicle is a medium- and long-distance transport vehicle.

[0094] In some embodiments, the vehicle use determination device obtains the starting position and the ending position of the target vehicle, and further determines the use of the target vehicle based on the starting position and the ending position of the target vehicle.

[0095] Exemplarily, if the frequency that the starting position or the ending position of the target vehicle is around a coal mine production area is greater than 75%, and the target vehicle is a long-distance transport vehicle, then the vehicle use determination device determines that the target vehicle is a long-distance coal transport vehicle.

[0096] In one design, after obtaining the target travel information, in order to determine the target use of the target vehicle based on the target travel information, as Figure 8 shown, the vehicle use determination method provided by the embodiments of the present invention further includes S401 - S403.

[0097] S401. The vehicle use determination device determines the target travel characteristics of the target travel information according to the target travel information.

[0098] As a possible implementation manner, the vehicle use determination device performs a standardization process on the multi-target travel information to generate the target travel characteristics of the target travel information.

[0099] It should be noted that the standardization process refers to converting different data in the same parameter into a preset standard format. Since the parameters included in each target travel information have different types, the present invention uses different standardization methods for different data types.

[0100] Exemplarily, one of the multiple target travel information can specifically be {target travel distance 1, fuel consumption 1, speed 1, target travel distance 2, fuel consumption 2, speed 2..., target travel distance n, fuel consumption n, speed n}.

[0101] Wherein, n is the number of target travel distances included in the target travel information obtained by the vehicle use determination device.

[0102] Correspondingly, the target driving characteristics after the normalization process of a target driving information can specifically be {3, 2, 5, 4, 2, 6, 4, 3, 5}. Among them, the target travel distance 1 is 3, indicating that the target travel distance is within the range of 100 - 150 km; the fuel consumption 1 is 2, indicating that the fuel consumption corresponding to the target travel distance 1 is within the range of 10 - 15 L; the speed 1 is 5, indicating that the speed corresponding to the target travel distance 1 is within the range of 50 - 60 km / h. The target travel distance 2 is 4, indicating that the target travel distance is within the range of 150 - 200 km; the fuel consumption 2 is 2, indicating that the fuel consumption corresponding to the target travel distance 2 is within the range of 10 - 15 L; the speed 2 is 6, indicating that the speed corresponding to the target travel distance 2 is within the range of 60 - 70 km / h. The target travel distance 3 is 4, indicating that the target travel distance is within the range of 150 - 200 km; the fuel consumption 3 is 3, indicating that the fuel consumption corresponding to the target travel distance 3 is within the range of 15 - 20 L; the speed 6 is 5, indicating that the speed corresponding to the target travel distance 3 is within the range of 50 - 60 km / h.

[0103] S402. The device for determining the vehicle use inputs the target driving characteristics into a pre-trained prediction model to obtain the target driving characteristics.

[0104] Among them, the prediction model includes a convolutional neural network model that generates a use identifier based on the driving characteristics of the vehicle.

[0105] As a possible implementation, the device for determining the vehicle use inputs the target driving characteristics into the prediction model, generates a prediction value corresponding to the target driving characteristics, and determines the prediction value as the target use identifier.

[0106] It should be noted that the convolutional neural network model can adopt a regression model, such as various regression models like Linear Regression, Polynomial Regression, Ridge Regression, etc. The embodiments of the present invention do not limit this. Specifically, how to train the prediction model can be referred to the subsequent records of the embodiments of the present invention, and details will not be elaborated here.

[0107] S403. The device for determining the vehicle use determines the target use based on the target use identifier.

[0108] As a possible implementation, after determining the target use identifier, the device for determining the vehicle use determines the target use according to the mapping relationship between the target use and the target use identifier.

[0109] It should be noted that the mapping relationship between the target use and the target use identifier can be pre-set by the operation and maintenance personnel of the device for determining the vehicle use. Exemplarily, the mapping relationship between the target use and the target use identifier can be shown in Table 3.

[0110] Table 3: Mapping Relationship between Target Use and Target Use Identification

[0111] Target use Target use label Urban construction vehicle 1 Short - distance transportation vehicle 2 Medium - and long - distance transportation vehicle 3 Long - distance transportation vehicle 4

[0112] Exemplarily, based on the above mapping relationship between target use and target use identification, if the predicted value determined by the device for determining the vehicle use is 3, then the target use corresponding to the target use identification 3 is determined to be a medium- and long-distance transport vehicle. Furthermore, the device for determining the vehicle use determines that the target use of the target vehicle is a medium- and long-distance transport vehicle.

[0113] In one design, in order to obtain a prediction model for determining the target use of the target vehicle, as Figure 9 shown, the method for determining vehicle use provided by the embodiments of the present invention further includes S501 - S502.

[0114] S501. The device for determining vehicle use obtains the sample driving information of the sample vehicle and the sample use identification of the sample vehicle.

[0115] Among them, the sample driving information includes multiple sample transport distances and the fuel consumption and speed corresponding to each sample transport distance.

[0116] It should be noted that for the device for determining vehicle use to obtain the sample driving information of the sample vehicle, the method described in step S201 of the above embodiments of the present invention can be referred to, and details are not elaborated herein.

[0117] S502. The device for determining vehicle use uses the sample driving characteristics of the sample driving information as features and the sample use identification as a supervision signal to perform supervised training on a preset model to obtain a prediction model.

[0118] Exemplarily, a sample transport distance, the fuel consumption and speed corresponding to the sample transport distance, and the sample use identification in the sample driving information obtained by the device for determining vehicle use can be expressed as (Y, L, S, Z), where Y is the sample transport distance, L is the fuel consumption corresponding to the sample transport distance, S is the speed corresponding to the sample transport distance, Z is the sample use identification corresponding to the sample transport distance, and the fuel consumption and speed corresponding to the sample transport distance. The sample driving information includes n sample transport distances and the fuel consumption and speed corresponding to n sample transport distances.

[0119] Correspondingly, the sample driving characteristics determined by the device for determining vehicle use based on the sample driving information are {Y1, L1, S1, Y2, L2, S2,..., Y n , L n , S n}, and the sample driving characteristics (Y i , L i , S i)As a feature, identify the sample usage Z i As a supervision signal, perform supervised training on a preset model to obtain a prediction model, which can be identified as Z i = f(Y i , L i , S i ), and the output is the sample usage identifier corresponding to the input time.

[0120] The present invention provides a method, device, equipment and storage medium for determining the vehicle usage. In the method for determining the vehicle usage provided by the present invention, by means of the vehicle networking technology, by obtaining the vehicle driving information uploaded by the in-vehicle device, the target driving distance of the target vehicle, as well as the fuel consumption and speed corresponding to each driving distance are determined. In this way, the vehicle usage can be determined through the driving distance, fuel consumption and speed, realizing the automation, high efficiency and large quantity of vehicle usage determination, overcoming the dependence on manpower, and being able to be widely promoted and used.

[0121] The above mainly introduces the solution provided by the embodiments of the present invention from the perspective of the method. To implement the above functions, it includes the corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of the examples described in the embodiments disclosed in this article, the embodiments of the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0122] The embodiments of the present invention can divide the function modules of the user equipment according to the above method examples. For example, each function module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software function modules. Optionally, the division of modules in the embodiments of the present invention is illustrative, only a logical function division, and there may be other division methods in actual implementation.

[0123] Figure 10 This is a schematic structural diagram of a device for determining vehicle usage provided by an embodiment of the present invention. The device for determining vehicle usage is used to execute the above method for determining vehicle usage. As Figure 10 shown, the device 60 for determining vehicle usage includes an acquisition unit 601, a determination unit 602, and a processing unit 603.

[0124] An acquisition unit 601, configured to acquire target driving information of a target vehicle within a historical time period; the target driving information includes a plurality of target driving distances and the fuel consumption and speed corresponding to each target driving distance. For example, as Figure 2 shown, the acquisition unit 601 may be configured to execute S201.

[0125] A determination unit 602, configured to determine a target use of the target vehicle according to the target driving information. For example, as Figure 2 shown, the determination unit 602 may be configured to execute S202.

[0126] Optionally, as Figure 10 shown, in the vehicle use determination device 60 provided in an embodiment of the present invention, the determination unit 602 is specifically configured to, for a first target driving distance, based on a preset mapping relationship, and the first target driving distance, the fuel consumption and speed corresponding to the first target driving distance, determine a candidate use corresponding to the first target driving distance. The first target driving distance is any one of the plurality of target driving distances, and the mapping relationship includes the use of the vehicle, the driving distance range, the fuel consumption range, and the speed range. For example, as Figure 7 shown, the determination unit 602 may be configured to execute S301.

[0127] The determination unit 602 is further configured to determine a target use from the candidate uses corresponding to the plurality of target driving distances; the target use is the candidate use corresponding to the largest number of driving distances among the candidate uses corresponding to the plurality of target driving distances. For example, as Figure 7 shown, the determination unit 602 may be configured to execute S302.

[0128] Optionally, as Figure 10 shown, in the vehicle use determination device 60 provided in an embodiment of the present invention, a processing unit 603 is further included.

[0129] The determination unit 602 is specifically configured to determine a target driving feature of the target driving information according to the target driving information. For example, as Figure 8 shown, the determination unit 602 may be configured to execute S401.

[0130] The processing unit 603 is configured to input the target driving feature into a pre-trained prediction model to obtain a target use identifier; the prediction model includes a convolutional neural network model that generates a use identifier according to the driving feature of the vehicle. For example, as Figure 8 shown, the processing unit 603 may be configured to execute S402.

[0131] The determination unit 602 is further configured to determine a target use based on the target use identifier. For example, as Figure 8 shown, the determination unit 602 may be configured to execute S403.

[0132] Optionally, as Figure 10As shown in the figure, in the vehicle use determination device 60 provided by the embodiment of the present invention, the acquisition unit 601 is further configured to acquire the sample driving information of the sample vehicle and the sample use identifier of the sample vehicle. The sample driving information includes a plurality of sample transport distances and the fuel consumption and speed corresponding to each sample transport distance. For example, as Figure 9 shown, the acquisition unit 601 may be used to execute S501.

[0133] The processing unit 603 is further configured to use the sample driving characteristics of the sample driving information as features and the sample use identifier as a supervision signal to perform supervised training on a preset model to obtain a prediction model. For example, as Figure 9 shown, the processing unit 603 may be used to execute S502.

[0134] In the case of implementing the functions of the above integrated module in the form of hardware, the embodiment of the present invention provides a possible structural schematic diagram of a vehicle use determination device. The vehicle use determination device is used to execute the vehicle use determination method executed by the vehicle use determination device in the above embodiment. As Figure 11 shown, the vehicle use determination device 70 includes a processor 701, a memory 702, and a bus 703. The processor 701 and the memory 702 may be connected through the bus 703.

[0135] The processor 701 is the control center of the vehicle use determination device, which may be a single processor or a collective term for multiple processing elements. For example, the processor 701 may be a general-purpose central processing unit (CPU), or other general-purpose processors, etc. Among them, the general-purpose processor may be a microprocessor or any conventional processor, etc.

[0136] As an embodiment, the processor 701 may include one or more CPUs. For example, Figure 11 the CPUs 0 and CPU 1 shown in

[0137] The memory 702 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium, or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0138] As a possible implementation, the memory 702 can exist independently of the processor 701. The memory 702 can be connected to the processor 701 through the bus 703 and is used to store instructions or program codes. When the processor 701 calls and executes the instructions or program codes stored in the memory 702, the method for determining the use of the vehicle provided by the embodiments of the present invention can be implemented.

[0139] In another possible implementation, the memory 702 can also be integrated with the processor 701.

[0140] The bus 703 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 11 only a thick line is shown in the figure, but it does not mean that there is only one bus or one type of bus.

[0141] It should be noted that, Figure 11 the structure shown does not constitute a limitation on the device 70 for determining the use of the vehicle. Except Figure 11 for the components shown, the device 70 for determining the use of the vehicle can include more or fewer components than Figure 11 shown, or combine some components, or have different component arrangements.

[0142] As an example, in combination with Figure 10 , the functions implemented by the acquisition unit 601, the determination unit 602, and the processing unit 603 in the vehicle use determination device 60 are the same as Figure 11 the functions of the processor 701 in

[0143] Optionally, as Figure 11 shown, the vehicle use determination device provided by the embodiments of the present invention can further include a communication interface 704.

[0144] The communication interface 704 is used to connect to other devices through a communication network. The communication network can be an Ethernet, a wireless access network, a wireless local area networks (WLAN), etc. The communication interface 704 can include a receiving unit for receiving data and a sending unit for sending data.

[0145] In one design, in the vehicle usage determination device provided by the embodiments of the present invention, the communication interface may also be integrated in the processor.

[0146] Figure 12 Another hardware structure of the vehicle usage determination device in the embodiments of the present invention is shown. As Figure 12 shown, the vehicle usage determination device 80 may include a processor 801 and a communication interface 802. The processor 801 is coupled to the communication interface 802.

[0147] The functions of the processor 801 may refer to the description of the above-mentioned processor 701. In addition, the processor 801 also has a storage function, which may refer to the function of the above-mentioned memory 702.

[0148] The communication interface 802 is used to provide data for the processor 801. This communication interface 802 may be an internal interface of the vehicle usage determination device or an external interface of the vehicle usage determination device (equivalent to the communication interface 704).

[0149] It should be noted that Figure 12 the structure shown in Figure 12 does not constitute a limitation on the vehicle usage determination device. Except for

[0150] the components shown, the vehicle usage determination device 80 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0151] The embodiments of the present invention also provide a computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the computer executes the instructions, the computer executes each step in the method flow shown in the above method embodiments.

[0152] The embodiments of the present invention provide a computer program product containing instructions. When the instructions run on a computer, the computer is caused to execute the vehicle usage determination method in the above method embodiments.

[0153] Among them, a computer-readable storage medium can be, for example, but not limited to, a system, device, or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection with one or more wires, a portable computer disk, a hard disk. Random Access Memory (RAM), Read-Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), registers, hard disks, optical fibers, portable compact disc read-only memory (Compact Disc Read-Only Memory, CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above, or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an Application Specific Integrated Circuit (ASIC). In the embodiments of the present invention, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or component.

[0154] Since the devices, equipment, computer-readable storage media, and computer program products in the embodiments of the present invention can be applied to the above methods, the technical effects that can be obtained can also refer to the method embodiments above, and the embodiments of the present invention will not be elaborated here.

[0155] As described above, the above are only the specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for determining the use of a vehicle, characterized in that, The method includes: Obtaining target driving information of a target vehicle within a historical time period; the target driving information includes a plurality of target driving distances and the fuel consumption and speed corresponding to each target driving distance; Determining the target use of the target vehicle according to the target driving information; Wherein, the determining the target use of the target vehicle according to the target driving information includes: For a first target driving distance, based on a preset mapping relationship, the first target driving distance, and the fuel consumption and speed corresponding to the first target driving distance, determining a candidate use corresponding to the first target driving distance; the first target driving distance is any one of the plurality of target driving distances, and the mapping relationship includes the use of the vehicle, the driving distance range, the fuel consumption range, and the speed range; Determining the target use from the candidate uses corresponding to the plurality of target driving distances; the target use is the candidate use corresponding to the largest number of driving distances among the candidate uses corresponding to the plurality of target driving distances.

2. The determination method according to claim 1, wherein The determining the target use of the target vehicle according to the target driving information includes: Determining the target driving characteristics of the target driving information according to the target driving information; Inputting the target driving characteristics into a pre-trained prediction model to obtain a target use identifier; the prediction model includes a convolutional neural network model, and the convolutional neural network model is used to generate a use identifier according to the driving characteristics of the vehicle; Determining the target use based on the target use identifier.

3. The determination method according to claim 2, wherein The method further includes: Obtaining sample driving information of a sample vehicle and the sample use identifier of the sample vehicle; the sample driving information includes a plurality of sample driving distances and the fuel consumption and speed corresponding to each sample driving distance; Using the sample driving characteristics of the sample driving information as features and the sample use identifier as a supervision signal to perform supervised training on a preset model to obtain the prediction model.

4. A device for determining the use of a vehicle, characterized in that Including an obtaining unit and a determining unit; The obtaining unit is configured to obtain target driving information of a target vehicle within a historical time period; the target driving information includes a plurality of target driving distances and the fuel consumption and speed corresponding to each target driving distance; The determining unit is configured to determine the target use of the target vehicle according to the target driving information; Wherein, the determining unit is specifically configured to, for a first target driving distance, based on a preset mapping relationship, the first target driving distance, and the fuel consumption and speed corresponding to the first target driving distance, determine a candidate use corresponding to the first target driving distance; the first target driving distance is any one of the plurality of target driving distances, and the mapping relationship includes the use of the vehicle, the driving distance range, the fuel consumption range, and the speed range; The determining unit is further configured to determine the target use from the candidate uses corresponding to the plurality of target driving distances; the target use is the candidate use corresponding to the largest number of driving distances among the candidate uses corresponding to the plurality of target driving distances.

5. The determination device according to claim 4, wherein The determining device further includes a processing unit; The determining unit is specifically configured to determine the target driving characteristics of the target driving information according to the target driving information; The processing unit is configured to input the target driving feature into a pre-trained prediction model to obtain a target usage identifier; the prediction model includes a convolutional neural network model, and the convolutional neural network model is configured to generate a usage identifier according to the driving feature of the vehicle; The determining unit is further configured to determine the target usage based on the target usage identifier.

6. The determination device according to claim 5, characterized in that, The obtaining unit is further configured to obtain the sample driving information of the sample vehicle and the sample usage identifier of the sample vehicle; the sample driving information includes a plurality of sample transportation distances and the fuel consumption and speed corresponding to each of the sample transportation distances; The processing unit is further configured to use the sample driving feature of the sample driving information as a feature, use the sample usage identifier as a supervision signal to perform supervised training on a preset model to obtain the prediction model.

7. An apparatus for determining a vehicle use, characterized in that, comprising a memory and a processor; The memory is coupled to the processor; The memory is configured to store computer program code, and the computer program code includes computer instructions; When the processor executes the computer instructions, the vehicle usage determination device executes the vehicle usage determination method according to any one of claims 1-3.

8. A computer-readable storage medium storing instructions therein, characterized in that, When the instruction runs on the vehicle usage determination device, the vehicle usage determination device is caused to execute the vehicle usage determination method according to any one of claims 1-3.

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