CN112948407B

CN112948407B - Data updating method, device, equipment and storage medium

Info

Publication number: CN112948407B
Application number: CN202110232154.3A
Authority: CN
Inventors: 商文胜
Original assignee: Wuxi Cheliantianxia Information Technology Co ltd
Current assignee: Wuxi Cheliantianxia Information Technology Co ltd
Priority date: 2021-03-02
Filing date: 2021-03-02
Publication date: 2024-01-23
Anticipated expiration: 2041-03-02
Also published as: CN112948407A

Abstract

The application provides a data updating method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring driving data sent by a target vehicle according to a preset period in the driving process; judging whether a first difference value between the driving data and the historical driving data acquired in the previous period on a designated attribute is smaller than or equal to a first preset threshold value or not; if the first difference value is smaller than or equal to a first preset threshold value, judging whether the driving data comprise first target driving data or not; if the driving data comprise first target driving data, updating a first data statistics record of the first target driving data in the previous period according to the first target driving data aiming at each first target driving data; by the method, time consumption of calculation of the journey data is reduced, and waiting time of a user is reduced.

Description

Data updating method, device, equipment and storage medium

Technical Field

The present invention relates to the field of vehicle data processing, and in particular, to a data updating method, device, apparatus and storage medium.

Background

With the development of automobile manufacturing industry, various sensors are installed in different hardware parts of a vehicle to acquire data generated during running of the vehicle, and a vehicle travel calculation system installed in the vehicle acquires and stores the data acquired by the sensors on the vehicle.

After the journey is finished, when a user driving the vehicle needs to check journey data of the vehicle in the journey, the vehicle journey calculation system calculates the journey data by using the stored data, and as the vehicle travels longer and longer in the journey, the more data are collected by the sensors stored in the database, so that the more time is consumed for calculating the journey data, the longer the user waits.

Disclosure of Invention

In view of the foregoing, embodiments of the present application provide a data updating method, apparatus, device, and storage medium, which are beneficial to reducing time consumption of calculation of trip data, so as to reduce waiting time of a user.

Mainly comprises the following aspects:

in a first aspect, an embodiment of the present application provides a data updating method, where the method includes:

acquiring driving data sent by a target vehicle according to a preset period in the driving process;

judging whether a first difference value between the driving data and the historical driving data acquired in the previous period is smaller than or equal to a first preset threshold value or not, wherein the designated attribute comprises the time for generating the driving data;

if the first difference value is smaller than or equal to the first preset threshold value, judging whether the driving data comprise first target driving data or not, wherein the first target driving data comprise driving events, driving distances, driving behaviors and driving duration of the target vehicle;

If the driving data comprise the first target driving data, updating a first data statistics record of the first target driving data in a previous period according to the first target driving data for each first target driving data, wherein the first data statistics record of the first target driving data in the previous period is obtained by updating a first data statistics record of the first historical target driving data in the first period according to the first historical target driving data acquired in the previous period, the first historical target driving data and the first target driving data have the same attribute, and the first period is adjacent to the previous period and is earlier than the previous period.

Optionally, if the first difference is less than or equal to the first preset threshold, the method further includes:

judging whether the driving data comprise second target driving data or not, wherein the second target driving data comprise the position of the target vehicle;

if the driving data comprise the second target driving data, judging whether a second difference value between the second target driving data and second historical target driving data acquired in the previous period is smaller than or equal to a second preset threshold value, wherein the second historical target driving data and the second target driving data have the same attribute;

And if the second difference value is smaller than or equal to the second preset threshold value, updating a second data statistics record of the second target driving data in a previous period according to the second target driving data, wherein the second data statistics record of the second target driving data in the previous period is obtained by updating a second data statistics record of the second historical target driving data in the first period according to the second historical target driving data.

Optionally, the method further comprises:

acquiring driving data sent by the target vehicle in a second period;

judging whether a third difference value between the driving data sent in the second period and the historical driving data acquired in the first period on the appointed attribute is smaller than or equal to the first preset threshold value;

if the third difference value is smaller than or equal to the first preset threshold value, judging whether the driving data sent in the second period comprises third target driving data, and if the driving data sent in the second period comprises the third target driving data, counting the third target driving data and third historical target driving data acquired in the first period for each third target driving data to obtain a third data statistical record, wherein the third target driving data comprises driving events, driving distances, driving behaviors and driving duration of the target vehicle, and the third historical target driving data and the third target driving data have the same attribute;

Judging whether the driving data transmitted in the second period comprises fourth target driving data or not if the third difference value is smaller than or equal to the first preset threshold value, judging whether the fourth difference value between the fourth target driving data and fourth historical driving data acquired in the first period is smaller than or equal to the third preset threshold value or not if the fourth difference value is smaller than or equal to the third preset threshold value, and obtaining a fourth data statistical record through statistics of the fourth target driving data and the fourth historical driving data, wherein the fourth target driving data comprises the position of the target vehicle, and the fourth historical driving data and the fourth target driving data have the same attribute.

judging whether the driving data comprise fifth target driving data or not, wherein the fifth target driving data comprise the speed of the target vehicle;

if the driving data comprise the fifth target driving data, judging whether a fifth difference value between the fifth target driving data and fifth historical driving data acquired in the previous period is smaller than or equal to a fourth preset threshold value, wherein the fifth historical driving data and the fifth target driving data have the same attribute;

If the fifth difference value is smaller than or equal to the fourth preset threshold value, analyzing the running state of the target vehicle in the current period according to the fifth target running data and a fifth data statistical record of the fifth target running data in the previous period, wherein the fifth data statistical record comprises the fifth target running data acquired by the target vehicle in each period before the current period;

and updating the corresponding times of the running state in the running process.

Optionally, if the first difference is greater than the first preset threshold, the method further includes:

caching the driving data in a first database;

judging whether candidate driving data with the difference value of the historical driving data on the designated attribute smaller than or equal to the first preset threshold value exists in the first database;

if the candidate driving data exist in the first database, the candidate driving data are used as driving data to be processed;

judging whether the to-be-processed driving data comprise sixth target driving data or not, and if the to-be-processed driving data comprise the sixth target driving data, updating a first data statistical record with the same attribute as the sixth target driving data according to the sixth target driving data aiming at each sixth target driving data, wherein the sixth target driving data comprise driving events, driving distances, driving behaviors and driving duration of the target vehicle;

Judging whether the to-be-processed driving data comprise seventh target driving data or not, if so, judging whether a sixth difference value between the seventh target driving data and the second historical target driving data is smaller than or equal to a second preset threshold value or not, and if so, updating a second data statistical record with the same attribute as the seventh target driving data according to the seventh target driving data, wherein the seventh target driving data comprise the position of the target vehicle;

judging whether the to-be-processed driving data comprise eighth target driving data or not, if so, judging whether a seventh difference value between the eighth target driving data and the fifth historical target driving data is smaller than or equal to the fourth preset threshold value or not, and if so, analyzing the driving state of the target vehicle in the current period according to the seventh target driving data and the fifth data statistical record, and updating the corresponding times of the driving state in the driving process, wherein the fifth target driving data comprise the speed of the target vehicle.

Optionally, if the candidate driving data does not exist in the first database, the method further includes:

adding a label for representing a screening condition after the first data statistics record, wherein the screening condition is that the difference value between the screening condition and the historical driving data on the appointed attribute is smaller than or equal to the first preset threshold value;

and when the selected driving data meeting the screening conditions is obtained, the selected driving data is used as the driving data to be processed.

Optionally, the target difference value includes the second difference value or the fifth difference value, the target preset threshold value includes the second preset threshold value or the fourth preset threshold value, and if the target difference value is greater than the target preset threshold value, the method includes:

when the target difference value is the second difference value, the target preset threshold value is the second preset threshold value, and the second target driving data is changed according to the second data statistical record and the driving data with the same attribute as the second target driving data acquired in the next period;

when the target difference value is the fifth difference value, the target preset threshold value is the fourth preset threshold value, and the fifth target driving data is changed according to the fifth data statistical record and the driving data with the same attribute as the fifth target driving data acquired in the next period.

In a second aspect, an embodiment of the present application provides a data updating apparatus, including:

the first acquisition module is used for acquiring driving data sent by the target vehicle according to a preset period in the driving process;

the first judging module is used for judging whether a first difference value between the driving data and the historical driving data acquired in the previous period is smaller than or equal to a first preset threshold value or not, wherein the designated attribute comprises the time for generating the driving data;

the second judging module is used for judging whether the driving data comprise first target driving data or not if the first difference value is smaller than or equal to the first preset threshold value, wherein the first target driving data comprise driving events, driving distances, driving behaviors and driving duration of the target vehicle;

and the updating module is used for updating a first data statistical record of the first target driving data in a previous period according to the first target driving data if the driving data comprise the first target driving data, wherein the first data statistical record of the first target driving data in the previous period is obtained by updating the first data statistical record of the first historical target driving data in the first period according to the first historical target driving data acquired in the previous period, the first historical target driving data and the first target driving data have the same attribute, and the first period is adjacent to the previous period and is earlier than the previous period.

Optionally, if the first difference is less than or equal to the first preset threshold, the second judging module is further configured to:

Optionally, the data updating device further includes:

the second acquisition module is used for acquiring driving data sent by the target vehicle in a second period;

A third judging module, configured to judge whether a third difference value between the driving data sent in the second period and the historical driving data acquired in the first period on the specified attribute is smaller than or equal to the first preset threshold;

the first statistics module is configured to determine whether the driving data sent in the second period includes third target driving data if the third difference value is smaller than or equal to the first preset threshold value, and obtain a third data statistics record by counting the third target driving data and third historical target driving data acquired in the first period for each third target driving data if the driving data sent in the second period includes the third target driving data, where the third target driving data includes a driving event, a driving distance, a driving behavior and a driving duration of the target vehicle, and the third historical target driving data is identical to the third target driving data in attribute;

and the second statistical module is used for judging whether the driving data transmitted in the second period comprises fourth target driving data or not if the third difference value is smaller than or equal to the first preset threshold value, judging whether the fourth difference value between the fourth target driving data and the fourth historical target driving data acquired in the first period is smaller than or equal to the third preset threshold value or not if the fourth difference value is smaller than or equal to the third preset threshold value, and obtaining a fourth data statistical record through statistics of the fourth target driving data and the fourth historical target driving data, wherein the fourth target driving data comprises the position of the target vehicle, and the fourth historical target driving data is identical to the fourth target driving data in attribute.

Optionally, if the first difference is greater than the first preset threshold, the second judging module is further configured to:

Caching the driving data in a first database;

Optionally, if the candidate driving data does not exist in the first database, the second judging module is further configured to:

Optionally, the target difference value includes the second difference value or the fifth difference value, the target preset threshold value includes the second preset threshold value or the fourth preset threshold value, and if the target difference value is greater than the target preset threshold value, the data updating device further includes:

the first changing module is configured to change, when the target difference is the second difference, the target preset threshold being the second preset threshold, the second target driving data according to the second data statistics record and driving data acquired in a next period and having the same attribute as the second target driving data;

and the second changing module is used for changing the fifth target driving data according to the fifth data statistical record and the driving data with the same attribute as the fifth target driving data acquired in the next period when the target difference value is the fifth difference value and the target preset threshold value is the fourth preset threshold value.

In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the steps of the data updating method according to any one of the first aspects when the processor executes the computer program.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the data updating method of any of the first aspects described above.

The technical scheme provided by the embodiment of the application can comprise the following beneficial effects:

according to the data updating method provided by the embodiment of the application, when the target vehicle sends the driving data acquired in the current period to the cloud computing platform, whether the driving data is effective or not needs to be judged, subsequent computation can be carried out only when the driving data is effective, nonsensical computation by using invalid driving data is avoided, namely: the method comprises the steps of judging whether a first difference value between the driving data and the historical driving data acquired in the previous cycle is smaller than or equal to a first preset threshold value or not, if the first difference value is smaller than or equal to the first preset threshold value, indicating that the driving data are effective, determining that the driving data comprise first target driving data, updating a first data statistics record corresponding to the first target driving data according to the first target driving data, acquiring driving data transmitted by a target vehicle in the last cycle after the current stroke is finished, updating a first data statistics record corresponding to the last second cycle by using the driving data transmitted by the last cycle under the condition that the driving data transmitted by the last cycle are effective, wherein the updated first data statistics record is the stroke data of the target vehicle in the current stroke, and when a user driving the target vehicle needs to check the stroke data of the target vehicle in the current stroke, compared with the method that a large amount of storage data are used for acquiring the first data statistics record corresponding to the first target driving data in the current stroke, the method is more effective, and the time of the user waiting time of the data in the current stroke is reduced in the current stroke is not more than the method.

In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered limiting the scope, and that other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for updating data according to an embodiment of the present application;

fig. 2 is a schematic structural diagram of a data updating device according to a second embodiment of the present application;

fig. 3 shows a schematic structural diagram of a computer device according to a third embodiment of the present application.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, are intended to be within the scope of the present application.

The embodiment of the application provides a data updating method, a device, equipment and a storage medium, and the description is given below through the embodiment.

Example 1

Fig. 1 shows a flowchart of a data updating method according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:

step S101: and acquiring driving data sent by the target vehicle according to a preset period in the driving process.

Specifically, from the start of the target vehicle to the flameout of the target vehicle, the target vehicle transmits the driving data acquired in the current period to the mobile base station through the communication terminal according to the preset period, so as to send the driving data to the cloud computing platform, and the cloud computing platform acquires the driving data, wherein the preset period refers to a time interval for sending the driving data, which is set in advance by people, for example: setting 1s to send driving data once, wherein the driving data refer to vehicle terminal data which can be acquired by a target vehicle, the driving data comprise data such as altitude, oil consumption, speed, position, driving duration, driving distance, ignition event, flameout event, braking event, driving behavior and the like of the target vehicle, each acquired driving data exists in a form that the driving data corresponds to the moment generated by the driving data, the target vehicle sends the driving data through an MQTT (Message Queuing Telemetry Transport, message queue telemetry transport protocol) Internet of things protocol, after the driving data are sent to a cloud computing platform, the acquired driving data are stored in the cloud computing platform through a kafka distributed message queue, and a big data real-time computing engine is used for operating the driving data on the cloud computing platform, so that the speed and the safety for processing the driving data are improved.

Step S102: and judging whether a first difference value between the driving data and the historical driving data acquired in the previous period is smaller than or equal to a first preset threshold value or not, wherein the designated attribute comprises the time of generating the driving data.

Specifically, after the driving data is obtained, the driving data exists in a form of a time when the driving data corresponds to the driving data, so that the time for generating the driving data can be obtained, when the designated attribute is the time for generating the driving data, a first difference value between the time corresponding to the driving data and the time of the historical driving data is calculated, after the first difference value is calculated, whether the first difference value is smaller than or equal to a first preset threshold value is judged, wherein the historical driving data refers to the driving data sent to a cloud computing platform by a target vehicle in a previous period, the previous period is adjacent to the current period and is earlier than the current period, and the first preset threshold value is equal to the interval between two adjacent periods.

Step S103: and if the first difference value is smaller than or equal to the first preset threshold value, judging whether the driving data comprise first target driving data, wherein the first target driving data comprise driving events, driving distances, driving behaviors and driving duration of the target vehicle.

Specifically, if the first difference value is smaller than or equal to the first preset threshold value, it is indicated that the acquired data is the driving data of the current period acquired by the target vehicle, and a subsequent statistical calculation operation may be performed according to the driving data, so as to determine whether the driving data includes first target data, in other words, determine which first target data is included in the driving data, the first target data not included in the driving data is the first target data that is not acquired by the target vehicle or is lost in the sending process of the target vehicle, the driving event of the target vehicle includes an ignition event of the target vehicle, a flameout event of the target vehicle, a braking event of the target vehicle, and the driving distance of the target vehicle is the total driving distance from the purchase to the present of the target vehicle, and the driving behavior of the target vehicle includes the driving behavior of a belting/unbuckled, an on/off steering lamp, an on/off night lamp, and the like.

Step S104: if the driving data comprise the first target driving data, updating a first data statistics record of the first target driving data in a previous period according to the first target driving data for each first target driving data, wherein the first data statistics record of the first target driving data in the previous period is obtained by updating a first data statistics record of the first historical target driving data in the first period according to the first historical target driving data acquired in the previous period, the first historical target driving data and the first target driving data have the same attribute, and the first period is adjacent to the previous period and is earlier than the previous period.

Specifically, for each first target driving data included in the driving data, updating a first data statistics record according to the first target driving data, before updating the first data statistics record, acquiring the first data statistics record, where the acquired first data statistics record is obtained after updating a first data statistics record of a first period according to a first historical target driving record, where the first historical target driving record refers to data with the same attribute as the first target driving record, in other words, the data has the same meaning, and the previous period is adjacent to and earlier than the current period, and the first period is adjacent to and earlier than the previous period, for example: the cycle sequence is third second, fourth second and fifth second, when the current cycle is fifth second, the previous cycle is fourth second, and the first cycle is third second.

It should be noted that, for different first target driving data, the corresponding first data statistics records are different, and the manner of updating the first data statistics records corresponding to the first target driving data is also different, when the first target driving data is a driving event, the first data statistics records corresponding to the driving event are the number of times of the driving event in the current journey, and the update manner corresponding to the driving event is to add one to the number of times of the driving event; when the first target driving data is driving behavior, the first data statistics corresponding to the driving behavior is recorded as the occurrence times of the driving behavior in the current journey, and the updating mode corresponding to the driving behavior is to add one to the occurrence times of the driving behavior; when the first target driving data is the driving distance, the first data corresponding to the driving distance is statistically recorded as the driving distance of the target vehicle in the current journey, and the updating mode corresponding to the driving distance is to use the driving distance to subtract the historical driving distance corresponding to the starting of the vehicle; when the first target driving data is driving duration, the first data statistics corresponding to the driving distance is recorded as the driving duration of the target vehicle in the current journey, and the updating mode corresponding to the driving duration is to use the driving duration to subtract the historical driving duration corresponding to the starting of the vehicle.

According to the data updating method provided by the first drawing, when a target vehicle sends driving data acquired in a current period to a cloud computing platform, whether the driving data is effective or not needs to be judged, and subsequent computation can be performed only when the driving data is effective, so that meaningless computation by using invalid driving data is avoided, namely: the method comprises the steps of judging whether a first difference value between the driving data and the historical driving data acquired in the previous cycle is smaller than or equal to a first preset threshold value or not, if the first difference value is smaller than or equal to the first preset threshold value, indicating that the driving data are effective, determining that the driving data comprise first target driving data, updating a first data statistics record corresponding to the first target driving data according to the first target driving data, acquiring driving data transmitted by a target vehicle in the last cycle after the current stroke is finished, updating a first data statistics record corresponding to the last second cycle by using the driving data transmitted by the last cycle under the condition that the driving data transmitted by the last cycle are effective, wherein the updated first data statistics record is the stroke data of the target vehicle in the current stroke, and when a user driving the target vehicle needs to check the stroke data of the target vehicle in the current stroke, compared with the method that a large amount of storage data are used for acquiring the first data statistics record corresponding to the first target driving data in the current stroke, the method is more effective, and the time of the user waiting time of the data in the current stroke is reduced in the current stroke is not more than the method.

In a possible embodiment, if the first difference is less than or equal to the first preset threshold, the data updating method may further be implemented by:

step S201: and judging whether the driving data comprise second target driving data or not, wherein the second target driving data comprise the position of the target vehicle.

Step S202: and if the driving data comprise the second target driving data, judging whether a second difference value between the second target driving data and the second historical target driving data acquired in the previous period is smaller than or equal to a second preset threshold value, wherein the second historical target driving data and the second target driving data have the same attribute.

Step S203: and if the second difference value is smaller than or equal to the second preset threshold value, updating a second data statistics record of the second target driving data in a previous period according to the second target driving data, wherein the second data statistics record of the second target driving data in the previous period is obtained by updating a second data statistics record of the second historical target driving data in the first period according to the second historical target driving data.

Specifically, if the first difference value is smaller than or equal to the first preset threshold value, it is further required to determine whether the driving data includes second target driving data, where the second target driving data includes a position of the target vehicle acquired in the current period, the position of the target vehicle is used as second target driving data to explain the second target driving data, and the second historical target driving data has the same attribute as the second target driving data, so when the second target driving data is the position of the target vehicle in the current period, the second historical target driving data is the position of the target vehicle in the last period, the second data statistics record is a statistics result of the second driving data acquired in each period before the current period, and when the second target driving data is the position of the target vehicle in the current period, the second data statistics record is a driving track of the target vehicle in the current period, and therefore, the method of updating the second data statistics record in the last period is to supplement the acquired position of the target vehicle in the current period to the driving track acquired in the previous period.

When the driving data comprise the position of the target vehicle, the position of the target vehicle acquired by the cloud computing platform in the previous period is acquired, the distance between the two positions is calculated, the calculated distance is used as a second difference value, after the second difference value is obtained, whether the second difference value is smaller than or equal to a second preset threshold value is judged, the second preset threshold value is smaller than or equal to the maximum distance that the target vehicle can travel in the adjacent period interval, and when the second difference value is smaller than or equal to the second preset threshold value, the second data statistics record is updated according to the position of the target vehicle in the current period.

In a possible embodiment, the data updating method further comprises the steps of:

step S301: and acquiring driving data sent by the target vehicle in a second period.

Step S302: and judging whether a third difference value between the driving data sent in the second period and the historical driving data acquired in the first period on the designated attribute is smaller than or equal to the first preset threshold value.

Specifically, when the target vehicle starts, the target vehicle starts to send data, and the cloud computing platform acquires driving data sent by the target vehicle in a first period, and in a next period of the first period, namely: in the second period, the cloud computing platform acquires the driving data sent by the target vehicle in the second period, then calculates a third difference value between the driving data sent by the second period and the historical driving data acquired in the first period on the appointed attribute, and after the third difference value is acquired, judges that the third difference value is smaller than or equal to the first preset threshold value, and the explanation of the calculating mode of the third difference value and the judging mode according to the third difference value is referred to the explanation of the step S102, and is not repeated here.

Step S303: and if the third difference value is smaller than or equal to the first preset threshold value, judging whether the driving data sent in the second period comprises third target driving data, and if the driving data sent in the second period comprises the third target driving data, counting the third target driving data and third historical target driving data acquired in the first period according to each third target driving data to obtain a third data statistical record, wherein the third target driving data comprises driving events, driving distances, driving behaviors and driving duration of the target vehicle, and the third historical target driving data and the third target driving data have the same attribute.

Specifically, for the description of the third target driving data, the description of the first target driving data is referred to, and details are not repeated herein, and for the relationship between the third historical target driving data and the third target driving data, the relationship between the first historical target driving data and the first target driving data is referred to, and details are not repeated herein.

It should be noted that, for the statistical manner of the third data statistics record, for different third target driving data, the corresponding third data statistics record is different, so that the manner of obtaining the third data statistics record is different, when the third target driving data is a driving event, the third data statistics record corresponding to the driving event is the number of times of the driving event in the current journey, and the manner of obtaining the third data statistics record corresponding to the driving event is to add one to the number of times of the driving event; when the third target driving data is driving behavior, the third data statistics record corresponding to the driving behavior is the number of times of the driving behavior in the current journey, and the mode of obtaining the third data statistics record corresponding to the driving behavior is to add one to the number of times of the driving behavior; when the third target driving data is the driving distance, the third data statistics record corresponding to the driving distance is the driving distance of the target vehicle in the current journey, and the driving distance is obtained by subtracting the historical driving distance of the target vehicle acquired in the first period from the driving distance; when the third target driving data is driving duration, the third data statistics record corresponding to the driving distance is the driving duration of the target vehicle in the current journey, and the mode of obtaining the third data statistics record corresponding to the driving duration is to use the driving duration to subtract the historical driving duration of the target vehicle acquired in the first period.

Step S304: judging whether the driving data transmitted in the second period comprises fourth target driving data or not if the third difference value is smaller than or equal to the first preset threshold value, judging whether the fourth difference value between the fourth target driving data and fourth historical driving data acquired in the first period is smaller than or equal to the third preset threshold value or not if the fourth difference value is smaller than or equal to the third preset threshold value, and obtaining a fourth data statistical record through statistics of the fourth target driving data and the fourth historical driving data, wherein the fourth target driving data comprises the position of the target vehicle, and the fourth historical driving data and the fourth target driving data have the same attribute.

Specifically, for the description of the fourth target driving data, reference is made to the description of the second target driving data, which is not repeated herein, for the relationship between the fourth historical target driving data and the fourth target driving data, reference is not repeated herein, reference is made to the relationship between the second historical target driving data and the second target driving data, and reference is not repeated herein for the description of the third preset threshold, reference is made to the description of the second preset threshold, which is not repeated herein, where the third preset threshold may be equal to the second preset threshold or may not be equal to the second preset threshold.

In the statistical method of the fourth data statistics record, when the fourth target driving data is the position of the target vehicle in the second period, the fourth data statistics record is the driving track of the target vehicle from the first period to the second period, so the driving track of the target vehicle is formed by using the position of the target vehicle acquired in the first period and the position of the target vehicle acquired in the second period, so as to obtain the fourth data statistics record.

step S401: and judging whether the driving data comprise fifth target driving data or not, wherein the fifth target driving data comprise the speed of the target vehicle.

Step S402: and if the driving data comprise the fifth target driving data, judging whether a fifth difference value between the fifth target driving data and the fifth historical driving data acquired in the previous period is smaller than or equal to a fourth preset threshold value, wherein the fifth historical driving data and the fifth target driving data have the same attribute.

Step S403: and if the fifth difference value is smaller than or equal to the fourth preset threshold value, analyzing the running state of the target vehicle in the current period according to the fifth target running data and a fifth data statistical record of the fifth target running data in the previous period, wherein the fifth data statistical record comprises the fifth target running data acquired by the target vehicle in each period before the current period.

Step S404: and updating the corresponding times of the running state in the running process.

Specifically, if the first difference value is smaller than or equal to the first preset threshold value, it is further required to determine whether the driving data includes fifth target driving data, where the fifth target driving data includes a speed of the target vehicle acquired in a current period, the speed of the target vehicle is used as fifth target driving data to explain the fifth target driving data, and the fifth historical driving data has the same attribute as the fifth target driving data, so when the fifth target driving data is the speed of the target vehicle acquired in a current period, the fifth historical driving data is the speed of the target vehicle acquired in a previous period, the fourth preset threshold value is smaller than or equal to a maximum speed difference value that can be reached by the target vehicle in an interval between adjacent periods, and the fifth data statistics record includes the fifth target driving data acquired in each period before the current period, so when the fifth target driving data is a set of speeds of the target vehicles acquired in each period before the current period.

When the fifth target driving data is the speed of the target vehicle acquired in the current period, calculating the acceleration of the target vehicle in the current period and each period before the current period according to the speed of the target vehicle acquired in the current period and the set of the speeds of the target vehicle acquired in each period before the current period, judging the driving state of the target vehicle in the current period according to the calculated change condition of each acceleration, wherein the driving state of the target vehicle comprises uniform driving, acceleration, deceleration, turning and the like, and adding one corresponding times of the driving state in the current driving process after the driving state of the target vehicle is obtained.

In another possible embodiment, the updated number of times corresponding to the driving behavior is displayed.

In a possible embodiment, if the first difference is greater than the first preset threshold, the data updating method may further be implemented by:

step S501: and caching the driving data in a first database.

Step S502: and judging whether candidate driving data with the difference value of the historical driving data on the designated attribute smaller than or equal to the first preset threshold value exists in the first database.

Step S503: and if the candidate driving data exist in the first database, taking the candidate driving data as the driving data to be processed.

Step S504: judging whether the to-be-processed driving data comprise sixth target driving data or not, and if the to-be-processed driving data comprise the sixth target driving data, updating a first data statistical record with the same attribute as the sixth target driving data according to the sixth target driving data aiming at each sixth target driving data, wherein the sixth target driving data comprise driving events, driving distances, driving behaviors and driving duration of the target vehicle.

Step S505: judging whether the to-be-processed driving data comprise seventh target driving data or not, if so, judging whether a sixth difference value between the seventh target driving data and the second historical target driving data is smaller than or equal to a second preset threshold value or not, and if so, updating a second data statistical record with the same attribute as the seventh target driving data according to the seventh target driving data, wherein the seventh target driving data comprise the position of the target vehicle.

Step S506: judging whether the to-be-processed driving data comprise eighth target driving data or not, if so, judging whether a seventh difference value between the eighth target driving data and the fifth historical target driving data is smaller than or equal to the fourth preset threshold value or not, and if so, analyzing the driving state of the target vehicle in the current period according to the seventh target driving data and the fifth data statistical record, and updating the corresponding times of the driving state in the driving process, wherein the fifth target driving data comprise the speed of the target vehicle.

Specifically, the first difference value is larger than a first preset threshold value, which indicates that the driving data acquired in the current period and the historical driving data acquired in the previous period are not adjacent driving data, the driving data are required to be cached in a first database, then whether the difference value between each driving data except the driving data and the historical driving data stored in the first database and on a designated attribute is smaller than or equal to the first preset threshold value is judged respectively, so that only candidate driving data, the difference value between the candidate driving data and the historical driving data on the designated attribute of which is smaller than or equal to the first preset threshold value, is determined, and then the candidate driving data is used as driving data to be processed, wherein the driving data to be processed is the driving data adjacent to the historical driving data acquired in the previous period and the period is later than the previous period.

It should be noted that, after the data to be processed is obtained, the operation in step S504 needs to be performed for the step to be processed, and for the description of the related operation in step S504, reference is made to the descriptions in steps S103 to S104, where for the description of the sixth target driving data, reference is made to the description of the first target driving data, and details thereof are not repeated here; after the data to be processed is obtained, the operation in step S505 needs to be executed in the step to be processed, and for the description of the related operation in step S505, reference is made to the descriptions in steps S201 to S203, where for the description of the seventh target driving data, reference is made to the description of the second target driving data, and details thereof are not repeated herein; after the data to be processed is obtained, the operation in step S506 needs to be executed in the step to be processed, and for the description of the related operation in step S506, reference is made to the description in steps S401 to S404, where for the description of the eighth target driving data, reference is made to the description of the fifth target driving data, and details thereof are not repeated here.

In a possible implementation manner, if the candidate driving data does not exist in the first database, the data updating method may further be implemented by the following steps:

Step S601: and adding a label for representing a screening condition after the first data statistics record, wherein the screening condition is that the difference value between the screening condition and the historical driving data on the appointed attribute is smaller than or equal to the first preset threshold value.

Step S602: and when the selected driving data meeting the screening conditions is obtained, the selected driving data is used as the driving data to be processed.

Specifically, if no candidate driving data is found in the first database, it is indicated that driving data adjacent to the historical driving data acquired in the previous period and having a period later than the previous period is not yet transmitted to the cloud computing platform, so that a tag needs to be added after the first data statistics record, the tag indicates a screening condition for the required driving data, when the driving data is acquired for each period after the current period, whether the driving data meets the screening condition is determined according to the screening condition, and if the selected driving data meeting the screening condition is found, the selected driving data is used as driving data to be processed, so as to perform the operations in the steps S504 to S506.

In a possible embodiment, the target difference value includes the second difference value or the fifth difference value, the target preset threshold value includes the second preset threshold value or the fourth preset threshold value, and if the target difference value is greater than the target preset threshold value, the data updating method further includes:

When the target difference value is the second difference value, the target preset threshold value is the second preset threshold value, and the second target driving data is changed according to the second data statistical record and the driving data with the same attribute as the second target driving data acquired in the next period.

Specifically, if the second difference between the second target driving data and the second historical target driving data is greater than a second preset threshold, indicating that the second target driving data is wrong, caching the second target driving data, when the driving data with the same attribute as the second target driving data is acquired in the next period, changing the second target driving data according to the second data statistics record and the driving data with the same attribute as the second target driving data acquired in the next period, so that the second difference between the second target driving data and the second historical target driving data is smaller than or equal to the second preset threshold, if the second difference between the second target driving data and the second historical target driving data cannot be corrected, discarding the second target driving data, and replacing the second target driving data with the replacement driving data with the second difference between the second target driving data and the second historical target driving data being smaller than or equal to the second preset threshold and having the highest similarity with the second target driving data.

Taking the position of the target vehicle as an example to explain the correction mode of second target driving data, displaying a second data statistical record (driving track) on an A expressway, acquiring driving data with the same attribute as the second target driving data in the next period on the A expressway, changing the second target driving data into position coordinates on the A expressway and close to the driving track, wherein the second target driving data is the position coordinates on a small road beside the A expressway.

If the fifth difference value between the fifth target driving data and the fifth historical driving data is larger than a fourth preset threshold value, the fifth target driving data is indicated to be wrong, the fifth target driving data is cached, when the driving data with the same attribute as the fifth target driving data is acquired in the next period, the fifth target driving data is changed according to the fifth data statistical record and the driving data with the same attribute as the fifth target driving data acquired in the next period, so that the fifth difference value between the fifth target driving data and the fifth historical driving data is smaller than or equal to the fourth preset threshold value, if the fifth difference value between the fifth target driving data and the fifth historical driving data cannot be corrected, the fifth target driving data is discarded, and the fifth target driving data is replaced by the replacement driving data with the fifth difference value between the fifth target driving data and the fifth historical driving data is smaller than or equal to the fourth preset threshold value and the highest in similarity with the fifth target driving data.

The method for correcting the fifth target driving data is explained by taking the speed of the target vehicle as an example, the fifth data is statistically recorded as speed 5, speed 5 and speed 5, the driving data which are acquired in the next period and have the same attribute as the fifth target driving data are also speed 5, the fifth target driving data are speed 30, and the fifth target driving data are corrected to speed 5 if the fifth target driving data do not accord with the conventional method.

In another possible implementation, each data statistics record updated in the current period is displayed, and when a help request sent by the target vehicle is received, each data statistics record is sent to the monitoring system, so that a worker can log in the monitoring system conveniently to check and provide assistance.

In another possible implementation manner, if the first difference value is greater than the first preset threshold value, or the target difference value is greater than the target preset threshold value, the processing may be performed by means of a time window, a message time trigger, a message watermark and other measures, so as to solve the problems of message disorder, travel waiting and the like.

In another possible implementation manner, if the first difference value is smaller than or equal to the first preset threshold value, judging whether the driving data includes ninth target driving data, and if the driving data includes the ninth target driving data, displaying each ninth target driving data included in the driving data, wherein the ninth target driving data includes data such as altitude, oil consumption and the like of the target vehicle.

In another possible implementation manner, if the driving data includes second target driving data, according to a target position of a target vehicle in a current period included in the second target driving data, acquiring first data including weather conditions and road conditions of an area where the target position belongs; the first data is displayed.

In another possible embodiment, the first target driving data includes at least one driving behavior, and for each driving behavior, it is determined whether the driving behavior meets a preset vehicle driving behavior specification; if the vehicle driving behavior is not consistent with the preset deduction rule table, deducting the driving behavior according to the preset deduction rule table for the vehicle driving running specification.

In another possible implementation manner, the driving data sent by the target vehicle and acquired in each period are stored, so that after the vehicle is flameout, each data statistics record is verified according to each stored driving data, and in addition, each data statistics record updated in the current period is stored, so that a user can trace back the history record.

Example two

Fig. 2 is a schematic structural diagram of a data updating device according to a second embodiment of the present application, where, as shown in fig. 2, the data updating device includes:

A first obtaining module 201, configured to obtain driving data sent by a target vehicle according to a preset period during a driving process;

a first judging module 202, configured to judge whether a first difference between the driving data and the historical driving data acquired in the previous period is smaller than or equal to a first preset threshold on a specified attribute, where the specified attribute includes a time of generating the driving data;

a second determining module 203, configured to determine whether the driving data includes first target driving data if the first difference is less than or equal to the first preset threshold, where the first target driving data includes a driving event, a driving distance, a driving behavior, and a driving duration of the target vehicle;

the updating module 204 is configured to update, for each piece of first target driving data, a first data statistics record of a previous period of the first target driving data according to the first target driving data if the driving data includes the first target driving data, where the first data statistics record of the previous period of the first target driving data is obtained by updating, according to the first historical target driving data obtained in the previous period, the first data statistics record of the first historical target driving data in the first period, where the first historical target driving data has the same attribute as the first target driving data, and the first period is adjacent to and earlier than the previous period.

In a possible embodiment, if the first difference is less than or equal to the first preset threshold, the second determining module 203 is further configured to:

In a possible embodiment, the data updating apparatus further includes:

In a possible embodiment, if the first difference is greater than the first preset threshold, the second determining module 203 is further configured to:

caching the driving data in a first database;

In a possible embodiment, if the candidate driving data does not exist in the first database, the second determining module 203 is further configured to:

In a possible embodiment, the target difference value includes the second difference value or the fifth difference value, the target preset threshold value includes the second preset threshold value or the fourth preset threshold value, and if the target difference value is greater than the target preset threshold value, the data updating apparatus further includes:

The apparatus provided by the embodiments of the present application may be specific hardware on a device or software or firmware installed on a device, etc. The device provided in the embodiments of the present application has the same implementation principle and technical effects as those of the foregoing method embodiments, and for a brief description, reference may be made to corresponding matters in the foregoing method embodiments where the device embodiment section is not mentioned. It will be clear to those skilled in the art that, for convenience and brevity, the specific operation of the system, apparatus and unit described above may refer to the corresponding process in the above method embodiment, which is not described in detail herein.

Example III

The embodiment of the present application further provides a computer device 300, and fig. 3 shows a schematic structural diagram of a computer device provided in the third embodiment of the present application, as shown in fig. 3, where the device includes a memory 301, a processor 302, and a computer program stored in the memory 301 and capable of running on the processor 302, where the processor 302 implements the data updating method when executing the computer program.

Specifically, the memory 301 and the processor 302 can be general-purpose memories and processors, which are not limited herein, and when the processor 302 runs a computer program stored in the memory 301, the data updating method can be executed, so that the problems of a large amount of time consumption for calculating travel data and a long waiting time of a user in the prior art are solved.

Example IV

The embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the data updating method described above.

Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, and the like, and when the computer program on the storage medium is executed, the data updating method can be executed, so that the problems of long time consumption for calculating the travel data and long waiting time of a user in the prior art are solved.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments provided in the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

It should be noted that: like reference numerals and letters in the following figures denote like items, and thus once an item is defined in one figure, no further definition or explanation of it is required in the following figures, and furthermore, the terms "first," "second," "third," etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.

Finally, it should be noted that: the foregoing examples are merely specific embodiments of the present application, and are not intended to limit the scope of the present application, but the present application is not limited thereto, and those skilled in the art will appreciate that while the foregoing examples are described in detail, the present application is not limited thereto. Any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or make equivalent substitutions for some of the technical features within the technical scope of the disclosure of the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the corresponding technical solutions. Are intended to be encompassed within the scope of this application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of data updating, the method comprising:

judging whether a first difference value between the driving data and the historical driving data acquired in the previous period is smaller than or equal to a first preset threshold value or not, wherein the designated attribute comprises time for generating the driving data, and the first preset threshold value is used for representing a time difference threshold value between the current period and the previous period of the driving data;

if the driving data comprise the first target driving data, updating a first data statistics record of the first target driving data in a previous period according to the first target driving data for each first target driving data, wherein the first data statistics record of the first target driving data in the previous period is obtained by updating a first data statistics record of the first historical target driving data in the first period according to the first historical target driving data acquired in the previous period, the first historical target driving data and the first target driving data have the same attribute, and the first period is adjacent to the previous period and is earlier than the previous period;

if the first difference is greater than the first preset threshold, the method further includes:

caching the driving data in a first database;

judging whether the to-be-processed driving data comprise seventh target driving data or not, if so, judging whether a sixth difference value between the seventh target driving data and second historical driving data acquired in the previous period is smaller than or equal to a second preset threshold value or not, and if so, updating a second data statistical record with the same attribute as the seventh target driving data according to the seventh target driving data, wherein the seventh target driving data comprise the position of the target vehicle, and the second historical target driving data are the same as the seventh target driving data in attribute;

Judging whether eighth target driving data are included in the driving data to be processed, if so, judging whether a seventh difference value between the eighth target driving data and fifth historical driving data acquired in a previous period is smaller than or equal to a fourth preset threshold value, and if so, analyzing the driving state of the target vehicle in the current period according to the eighth target driving data and fifth data statistics records of the eighth target driving data in the previous period, and updating the corresponding times of the driving state in the driving process, wherein the eighth target driving data comprise the speed of the target vehicle; wherein the fifth historical target driving data has the same attribute as the eighth target driving data; the fifth data statistics record comprises eighth target driving data acquired by the target vehicle in each period before the current period;

the second preset threshold is used for representing a position information difference threshold of the driving data between the current period and the previous period;

The fourth preset threshold is used for representing a speed difference threshold of the driving data between the current period and the last period.

2. The method of claim 1, wherein if the first difference is less than or equal to the first preset threshold, the method further comprises:

3. The method of claim 2, wherein the method further comprises:

acquiring driving data sent by the target vehicle in a second period;

judging whether the driving data transmitted in the second period comprises fourth target driving data or not if the third difference value is smaller than or equal to the first preset threshold value, judging whether the fourth difference value between the fourth target driving data and the fourth historical target driving data acquired in the first period is smaller than or equal to the third preset threshold value or not if the fourth difference value is smaller than or equal to the third preset threshold value, and obtaining a fourth data statistical record by counting the fourth target driving data and the fourth historical target driving data, wherein the fourth target driving data comprises the position of the target vehicle, the fourth historical target driving data is identical with the fourth target driving data in attribute, and the third preset threshold value is used for representing the position information difference threshold value between the current period and the second period of the driving data.

4. The method of claim 3, wherein if the first difference is less than or equal to the first preset threshold, the method further comprises:

if the driving data comprise the fifth target driving data, judging whether a fifth difference value between the fifth target driving data and the fifth historical target driving data acquired in the previous period is smaller than or equal to a fourth preset threshold value; wherein the fifth historical driving data has the same attribute as the fifth driving data;

if the fifth difference value is smaller than or equal to the fourth preset threshold value, analyzing the running state of the target vehicle in the current period according to the fifth target running data and the fifth data statistics record of the fifth target running data in the previous period; the fifth data statistics record comprises fifth target driving data acquired by the target vehicle in each period before the current period;

5. The method of claim 4, wherein if the candidate drive data is not present in the first database, the method further comprises:

6. The method of claim 5, wherein a target difference comprises the second difference or the fifth difference, a target preset threshold comprises the second preset threshold or the fourth preset threshold, and if the target difference is greater than the target preset threshold, the method comprises:

7. A data updating apparatus, comprising:

the first judging module is used for judging whether a first difference value between the driving data and the historical driving data acquired in the previous period is smaller than or equal to a first preset threshold value or not, wherein the specified attribute comprises the time for generating the driving data, and the first preset threshold value is used for representing a time difference threshold value between the current period and the previous period of the driving data;

the updating module is used for updating a first data statistical record of the first target driving data in a previous period according to the first target driving data if the driving data comprise the first target driving data, wherein the first data statistical record of the first target driving data in the previous period is obtained by updating the first data statistical record of the first historical target driving data in the first period according to the first historical target driving data acquired in the previous period, the first historical target driving data and the first target driving data have the same attribute, and the first period is adjacent to the previous period and is earlier than the previous period;

If the first difference is greater than the first preset threshold, then:

caching the driving data in a first database;

8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of the preceding claims 1-6 when the computer program is executed.

9. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor performs the steps of the method of any of the preceding claims 1-6.