Driving data processing method and device, storage medium, electronic equipment and vehicle

Abstract

The invention discloses a driving data processing method and device, a storage medium, electronic equipment and a vehicle, and relates to the technical field of data processing, and the method comprises the steps: obtaining first driving data in a current driving cycle, the current driving cycle being a current driving process of the vehicle from a power-on state to a power-off state, the first driving data is single-dimension data; performing integration calculation on the first driving data to obtain second driving data, the second driving data being multi-dimensional data obtained by integrating at least two pieces of first driving data; and synchronously uploading the first driving data and the second driving data to a cloud for storage. The driving data can be synchronously stored at the vehicle end and the cloud end, and meanwhile, the loss of vehicle computing resources is reduced.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, storage medium, electronic device and vehicle for processing driving data. Background Art

[0002] As the level of automobile intelligence continues to increase, the data collected from vehicles during driving continues to increase, and users are highly concerned about the driving status of the vehicle. The use of vehicle-cloud synchronous data sharing can effectively record and utilize vehicle operation information, analyze user usage habits and driving problems, and realize intelligent information exchange and sharing between vehicles, people, and background. It is safe, comfortable, and efficient, and improves traffic and travel efficiency.

[0003] At present, the main method used is to collect data locally in the vehicle and in the cloud. For example, the vehicle collects vehicle data locally through the on-board data collection terminal, such as the collection function in the telematics (Telematics BOX, T-BOX) firmware or a self-written collection program, and the cloud collects vehicle data based on the data collection rules of data analysis. However, this method makes it difficult to ensure the synchronization of data content / collection time of the vehicle-cloud platform, resulting in poor synchronization of vehicle-cloud data. It also consumes computing power at both ends, causing loss of vehicle computing resources. Summary of the invention

[0004] In view of this, the present application provides a driving data processing method, device, storage medium, electronic device and vehicle, which can synchronously store driving data on the vehicle side and the cloud while reducing the loss of vehicle computing resources.

[0005] According to a first aspect of the present application, a method for processing driving data is provided, comprising:

[0006] Acquire first driving data in a current driving cycle, where the current driving cycle is a current driving process of the vehicle from a power-on state to a power-off state, and the first driving data is single-dimensional data;

[0007] Performing integration calculation on the first driving data to obtain second driving data, where the second driving data is multi-dimensional data obtained by integrating at least two of the first driving data;

[0008] The first driving data and the second driving data are synchronously uploaded to cloud storage.

[0009] According to a second aspect of the present application, a driving data processing device is provided, comprising:

[0010] an acquisition module, configured to acquire first driving data in a current driving cycle, wherein the current driving cycle is a current driving process of the vehicle from a power-on state to a power-off state, and the first driving data is single-dimensional data;

[0011] a calculation module, configured to perform integrated calculation on the first driving data to obtain second driving data, where the second driving data is multi-dimensional data obtained by integrating at least two of the first driving data;

[0012] The uploading module is used to synchronously upload the first driving data and the second driving data to cloud storage.

[0013] According to a third aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for processing driving data described in the first aspect is implemented.

[0014] According to a fourth aspect of the present application, an electronic device is provided, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the method for processing driving data described in the first aspect when executing the computer program.

[0015] According to a fifth aspect of the present application, a vehicle is provided, comprising: the electronic device as described in the fourth aspect.

[0016] By means of the above technical scheme, the present application provides a method, device, storage medium, electronic device and vehicle for processing driving data. Compared with the current driving data processing method, the present application can first obtain the first driving data in the current driving cycle, the current driving cycle is the current driving process of the vehicle from the power-on state to the power-off state, and the first driving data is single-dimensional data; the first driving data is integrated and calculated to obtain the second driving data, and the second driving data is multi-dimensional data obtained by integrating at least two first driving data; the first driving data and the second driving data are synchronously uploaded to the cloud for storage. The technical scheme disclosed in the present invention can collect driving data and integrate and calculate the driving data during the vehicle-side driving cycle, and then synchronously upload the collected first driving data and the second driving data obtained by the integrated calculation to the cloud for storage, so as to realize the synchronization of vehicle-cloud data. In addition, the entire driving data acquisition process does not require the cloud to consume computing power, which can reduce the loss of vehicle computing resources.

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 A flowchart of a method for processing driving data provided by an embodiment of the present disclosure;

[0021] Figure 2 A flowchart of a method for processing driving data provided by another embodiment of the present disclosure;

[0022] Figure 3 A system block diagram of driving data processing provided by an embodiment of the present disclosure;

[0023] Figure 4 A schematic diagram of the structure of a driving data processing device provided in an embodiment of the present disclosure;

[0024] Figure 5 A schematic diagram of the structure of a driving data processing device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0025] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0026] The following describes a method, device, storage medium, electronic device, and vehicle for processing driving data according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0027] In the related technologies, the main method of collecting data locally in the vehicle and in the cloud is adopted. For example, the vehicle collects vehicle data locally through the on-board data collection terminal, such as the collection function in the telematics (Telematics BOX, T-BOX) firmware or a self-written collection program, and the cloud collects vehicle data based on the data collection rules of data analysis. However, this method is difficult to ensure the synchronization of data content / collection time of the vehicle-cloud platform, resulting in poor synchronization of vehicle-cloud data. It also consumes computing power at both ends, resulting in loss of vehicle computing resources.

[0028] To solve the above technical problems, the present disclosure provides a driving data processing method, device, storage medium, electronic device and vehicle, which can synchronously store driving data on the vehicle side and the cloud while reducing the loss of vehicle computing resources.

[0029] like Figure 1 As shown, an embodiment of the present disclosure provides a method for processing driving data, including:

[0030] Step 101: Acquire first driving data in a current driving cycle. The current driving cycle is a current driving process of a vehicle from a power-on state to a power-off state. The first driving data is single-dimensional data.

[0031] Among them, the first driving data is the driving data generated during the current driving cycle. The current driving cycle is the current cycle from the vehicle powering on to the vehicle powering off, representing the user's most recent driving use, that is, the process from opening the door to getting in the car to leaving and locking the car. Powering on and off the vehicle is a necessary process to ensure the safe start and shutdown of electric vehicles. The vehicle power-on state means that the vehicle's circuit system is in a powered-on state. The vehicle power-off state means that the entire vehicle is powered off after working for a period of time and stops transmitting power to various devices.

[0032] Specifically, the first driving data is single-dimensional data, that is, it is used to reflect the driving characteristics under a single data dimension, such as the start time of the trip, the end time of the trip, the hybrid driving time, the pure electric driving time, the fuel consumption, the power consumption, the pure electric driving distance, the hybrid driving distance, the discharge inside and outside the vehicle, the power consumption of electrical appliances, etc. In a specific application scenario, the vehicle trajectory, speed and other vehicle state changes can be dynamically obtained through the environmental perception system, such as the Electronic Control Unit (ECU), the infotainment domain controller (Head Unit, HU), the driving recorder, the camera, the sensor, etc., to extract the minimum granularity driving data of the vehicle, that is, the first driving data. The minimum granularity principle can be to divide the system into the smallest possible modules when collecting data, and each module is responsible for the driving characteristic data under a specific data dimension, so as to improve the flexibility of data collection and improve the efficiency of data collection.

[0033] Step 102: integrate and calculate the first driving data to obtain second driving data, where the second driving data is multi-dimensional data obtained by integrating at least two first driving data.

[0034] Among them, the second driving data is multi-dimensional data of the current driving user under various driving conditions, that is, it is used to reflect the driving characteristics under multiple feature dimensions, and the multiple feature dimensions may include time dimension (such as driving days, preset time period indicated by the current driving user, daytime, night, dawn, dusk, rainy days, sunny days, etc.), location dimension (such as city center and suburbs) and vehicle feature dimension (such as fuel consumption, power consumption, etc.). Exemplarily, the average fuel consumption A (i.e., the second driving data) under driving days a1 can be calculated by integrating the driving days a1 (i.e., the first driving data) and the total fuel consumption a2 (i.e., the first driving data): A=a2 / a1, and the time characteristics under the time dimension corresponding to the first driving data a1 and the driving characteristics under the driving dimension corresponding to the first driving data a2 can be reflected in the second driving data A at the same time.

[0035] For the disclosed embodiment, a corresponding preset calculation formula can be selected for data with different calculation requirements, and the first driving data of the corresponding characteristics can be extracted and substituted into the preset calculation formula for calculation to obtain the second driving data under multiple characteristic dimensions, wherein the second driving data can be obtained by integrating at least two first driving data. The preset calculation formula refers to a calculation formula set for a variety of driving characteristic calculation scenarios. For example, when the second driving data needs to be calculated as 100 kilometers of fuel consumption, the corresponding preset calculation formula can be: 100 kilometers of fuel consumption = fuel consumption / driving distance, that is, the first driving data: fuel consumption, driving distance, is substituted into the above-mentioned preset calculation formula of 100 kilometers of fuel consumption, and the 100 kilometers of fuel consumption can be calculated; when the second driving data needs to be calculated as 100 kilometers of electricity consumption, the corresponding preset calculation formula can be: 100 kilometers of electricity consumption = electricity consumption / driving distance, that is, the electricity consumption and driving distance are substituted into the above-mentioned preset calculation formula of 100 kilometers of electricity consumption, and the 100 kilometers of electricity consumption can be calculated.

[0036] Step 103: Synchronously upload the first driving data and the second driving data to cloud storage.

[0037] For the disclosed embodiment, at the end of the current driving cycle, the vehicle side can upload the first driving data and the second driving data to the cloud server through the Internet to realize data storage, backup, sharing and other functions. The cloud virtualizes the server to form a virtual resource pool, which can be transmitted over the network with the vehicle-side database. After receiving the data, the data is stored in a centralized manner on a remote server, which can realize a data storage method that separates data management and storage. Compared with the traditional physical server storage method, this storage method has great advantages in maintenance and management, elastic expansion, data backup and disaster recovery, security, cost-effectiveness and other aspects. By synchronously uploading the first driving data and the second driving data to the cloud storage, data management is facilitated to ensure the reliability and stability of the driving data.

[0038] In summary, according to a driving data processing method provided by the present disclosure, compared with the current driving data processing method, the present application can first obtain the first driving data in the current driving cycle, the current driving cycle is the current driving process of the vehicle from the power-on state to the power-off state, and the first driving data is single-dimensional data; the first driving data is integrated and calculated to obtain the second driving data, and the second driving data is multi-dimensional data obtained by integrating at least two first driving data; the first driving data and the second driving data are synchronously uploaded to the cloud storage. The technical solution in the present disclosure can collect driving data and integrate and calculate the driving data during the vehicle-side driving cycle, and then the collected first driving data and the second driving data obtained by the integrated calculation are synchronously uploaded to the cloud storage, so as to realize the synchronization of vehicle-cloud data. In addition, the entire driving data acquisition process does not require the cloud to consume computing power, which can reduce the loss of vehicle computing resources.

[0039] Further, as a refinement and extension of the above embodiment, in order to fully illustrate the specific implementation process of the method of this embodiment, this embodiment provides the following Figure 2 The specific method shown includes:

[0040] Step 201: Acquire first driving data in a current driving cycle. The current driving cycle is a current driving process of a vehicle from a power-on state to a power-off state. The first driving data is single-dimensional data.

[0041] For the embodiment of the present disclosure, the specific implementation process can refer to the relevant description in step 101 of the embodiment, which will not be repeated here.

[0042] Step 202: integrate and calculate the first driving data to obtain second driving data, where the second driving data is multi-dimensional data obtained by integrating at least two first driving data.

[0043] For the embodiment of the present disclosure, the specific implementation process can refer to the relevant description in step 102 of the embodiment, which will not be repeated here.

[0044] Step 203: Determine a vehicle identifier corresponding to the first driving data and the second driving data.

[0045] In a specific application scenario, the first driving data and the second driving data include a vehicle identifier, respectively. When using the vehicle driving data, the vehicle identifier of the vehicle is first determined. The vehicle identifier refers to a unique identifier for identifying the vehicle, which is equivalent to the vehicle's identity certificate. It is matched with the first driving data and the second driving data to facilitate the storage and query of user data, improve data storage efficiency, and reduce query costs. In a specific application scenario, the vehicle identification number (VIN) can be used as a vehicle identifier. The VIN is a set of fixed codes assigned to the vehicle by the vehicle manufacturer, including the vehicle's manufacturer, year, model, body type and code, engine code, and assembly location, and will not change with external factors.

[0046] Step 204: Synchronously upload the first driving data and the second driving data to the cloud, and store them in a preset storage area corresponding to the vehicle identifier in the cloud.

[0047] In specific application scenarios, different preset storage areas can be allocated to different vehicles in the cloud database according to different vehicle identifiers, and different preset storage areas do not intersect with each other. In this way, driving data can be stored independently on a vehicle basis to ensure the security and privacy of driving data.

[0048] In order to facilitate the understanding of the disclosed technical solution, Figure 3 A complete description of the scheme in this disclosure is provided, such as Figure 3 As shown, the ECU first collects the first driving data, transmits the collected information to the HU, and then the HU stores the first driving data of the vehicle, calculates the second driving data according to the preset calculation formula, and manages all the data according to the vehicle identifier as the index. When the vehicle is powered off, the HU sends a request to upload data to the cloud. The cloud receives the upload request and opens up a corresponding storage space in the cloud with the vehicle identifier as the index. After the connection is successful, the driving cycle data of the corresponding vehicle is uploaded to the storage space. Accordingly, it is possible to download driving data from the cloud according to certain rules, verify the vehicle-side cloud data, ensure the synchronization of vehicle-cloud data, and provide driving data to mobile phone APP or other big data service terminals to provide display warning and other functions.

[0049] Among them, ECU is a microcomputer that receives signals from sensors on the one hand, processes these information on the other hand, and issues corresponding control instructions to control the correct action of the actuators, so as to keep the operation of the engine and the car in the best state. HU has multiple functions, which can receive information input from ECU or other devices, convert the input information into signals that can be received by the microprocessor, and store, calculate, analyze and process the received information. The output information is transmitted to other devices by means of communication with modules and systems through controller area networks, local interconnection networks or Ethernet. The preset storage area is a storage space opened according to the vehicle identifier, and the vehicle identifier can be used as an index to store and read the first driving data and the second driving data.

[0050] In a specific application scenario, in order to ensure the integrity of the driving data uploaded synchronously to the cloud, at the beginning of the current driving process, the HU will detect the first historical driving data after waking up and powering on to determine whether it includes the legacy data that has not been uploaded to the cloud; or, in the long-term driving process without the vehicle being powered off, the historical driving cycle can be periodically detected according to the preset duration to determine whether the first historical driving data that has not been successfully uploaded is included. According to these two detection methods, the problem of data leakage caused by vehicle-side failure or communication interruption can be effectively avoided, and the cloud data can be improved in time to further protect the data. Among them, the first historical driving data is the first driving data and / or the second driving data included in the local database but not included in the cloud database. The preset duration can be set according to the user's usage habits or needs, and is used to periodically trigger the detection mechanism, which is not specifically limited here. Accordingly, the embodiment steps may include: at the beginning of the current driving, detecting whether the historical driving cycle includes the first historical driving data that has not been successfully uploaded; or, periodically detecting whether the historical driving cycle includes the first historical driving data that has not been successfully uploaded according to the preset duration.

[0051] For the embodiment of the present disclosure, when the first driving data and the second driving data are synchronously uploaded to the cloud, as a possible implementation method, in response to detecting that the historical driving cycle includes the first historical driving data that has not been successfully uploaded, the first historical driving data can also be synchronously uploaded from the local database to the cloud and stored in a preset storage area corresponding to the vehicle identifier in the cloud.

[0052] For the disclosed embodiment, the vehicle side confirms whether there is any first historical driving data that has not been successfully uploaded to the cloud in the historical driving cycle. If there is any first historical driving data that has not been successfully uploaded, the vehicle side can retransmit the first historical driving data to the cloud until the upload is successful. This can avoid the loss of uploaded data, ensure the integrity of driving data stored in the cloud, and make it consistent with the data stored in the vehicle side.

[0053] In a specific application scenario, when an unexpected problem occurs (such as a failure or replacement of the HU storing the driving data), resulting in the loss of the driving data stored locally on the vehicle side, in order to ensure the integrity of the driving data stored on the vehicle side, after the HU is powered on, the local database can be compared with the cloud database to detect whether the local database includes the second historical driving data that is missing. If missing data is found, a data acquisition request carrying the vehicle identification code is sent to the cloud to request the download of the second historical driving data. After the connection is successful, the data returned by the cloud is received and stored in the preset storage area corresponding to the vehicle identifier in the vehicle side. The impact of data loss caused by sudden failures on the vehicle side can be effectively avoided, the vehicle side database can be improved in time, the data accuracy can be ensured, and the user experience can be improved. Among them, the second historical driving data is the first driving data and / or the second driving data that are not included in the local database but included in the cloud database. Accordingly, the steps of the embodiment may include: detecting whether the local database includes the second historical driving data that is missing; if so, sending a data acquisition request carrying the vehicle identifier to the cloud; receiving the second historical driving data fed back by the cloud in response to the data acquisition request.

[0054] For the disclosed embodiment, the vehicle side detects whether there is any driving data loss locally. If there is any loss, it can send a data acquisition request to the cloud to obtain the missing driving data in the cloud, thereby recovering the missing data to ensure the integrity of the driving data stored on the vehicle side.

[0055] In a specific application scenario, in order to facilitate the user to understand the driving situation of the current driving cycle, the vehicle end may also display the first driving data and / or the second driving data in a preset display format. The preset display format includes but is not limited to visual graphics, text, audio, etc.

[0056] In addition, in order to improve the user's driving experience and driving safety as much as possible, in addition to synchronizing data between the vehicle and the cloud, corresponding assisted driving strategies can also be added to double guarantee driving safety. As a possible application scenario, the vehicle can receive the driving behavior prediction results sent by the cloud. The driving behavior prediction results are the prediction results for the preset driving behavior obtained by the cloud by analyzing the first driving data and / or the second driving data. Based on the driving behavior prediction results, the vehicle can perform safety warning processing for the driver's driving behavior in the next driving cycle.

[0057] In specific application scenarios, the cloud can conduct a comprehensive analysis of the stored historical data, use the driving behavior prediction model to make predictions, obtain the prediction results for the preset driving behavior, and send the driving behavior prediction results to the vehicle side. Correspondingly, the vehicle side can receive the driving behavior prediction results sent by the cloud. Among them, before the cloud determines the driver's driving behavior prediction results based on the driving behavior prediction model, it is also necessary to pre-train the driving behavior prediction model. After the training is completed, the driving behavior prediction model can be repeatedly applied to subsequent driving behavior prediction tasks. When training the driving behavior prediction model, a training sample can be first constructed. The training sample is driving data configured with preset feature labels; the training sample is input into the driving behavior prediction model, and the driving behavior prediction model is trained for driving ability prediction.

[0058] During the driving ability prediction training process, the preset feature labels are used as training labels to update the model parameters in the driving behavior prediction model until the accuracy of the driving ability prediction of the driving behavior prediction model is greater than the preset threshold, and the driving behavior prediction model training is judged to be completed. Among them, the preset feature label can be a driving behavior label, and the preset threshold can be a value greater than 0 and less than 1. The closer the setting value of the preset threshold is to 1, the higher the evaluation accuracy of the trained driving behavior prediction model is. The specific value can be set according to the actual application scenario and is not specifically limited here.

[0059] After obtaining the driving behavior prediction results, the vehicle side can also provide the driver with personalized driving advice and training programs based on the driving behavior prediction results to help the driver improve his driving skills and safety awareness. When providing personalized driving advice to the driver based on the driving behavior prediction results, as a possible implementation method, the driver can be analyzed based on the driving behavior prediction results to see if he has dangerous driving behavior; if the driver is analyzed to have dangerous driving behavior, a braking instruction matching the dangerous driving behavior is generated; the braking instruction is sent to the vehicle side so that the vehicle side responds to the braking instruction to perform braking control on the vehicle. Among them, dangerous driving behavior refers to bad driving behavior that is likely to cause traffic accidents, and may include: driving that is physically unsuitable such as fatigue driving, drunk driving, inattention, sudden physical conditions, emotional driving such as irritability, and unsafe driving such as crazy driving that endangers oneself and public safety, and other driving behaviors that may or have caused driving hazards; the braking instruction may carry braking information such as braking damping, braking time, braking distance and braking speed, and different braking information indicates different braking strengths, such as the longer the braking time, the lower the braking strength, and the shorter the braking time, the higher the braking strength. For the embodiments of the present disclosure, when the driving behavior prediction results predict that the driver has dangerous driving behavior, the vehicle side can generate corresponding braking instructions for the dangerous driving behavior, so that the vehicle side can perform corresponding braking control on the vehicle based on the braking instructions, thereby ensuring the safety of vehicle driving.

[0060] In summary, according to a driving data processing method provided by the present disclosure, compared with the current driving data processing method, the present application can collect driving data during the driving cycle on the vehicle side, and integrate and calculate the driving data, and then synchronously upload the collected first driving data and the second driving data obtained by the integrated calculation to the cloud storage, so as to achieve the synchronization of vehicle-cloud data, facilitate the double backup of driving data, prevent the storage loss of driving data, and ensure the storage security of driving data. In addition, during the driving data upload process, the driving data upload status of the previous driving cycle can also be detected, and the first historical driving data that has not been successfully uploaded can be re-uploaded, so as to ensure the integrity of the driving data stored in the cloud. The vehicle side can also receive the driving behavior prediction results obtained by analyzing the driving data on the cloud side, and based on the driving behavior prediction results, perform safety warning processing for the driver's driving behavior in the next driving cycle, which can ensure driving safety and improve the user's driving experience.

[0061] Based on the above Figure 1 , Figure 2 The specific implementation of the method shown in the embodiment provides a driving data processing device, such as Figure 4 , the device includes: an acquisition module 31, a calculation module 32, and an upload module 33;

[0062] An acquisition module 31 may be used to acquire first driving data in a current driving cycle, where the current driving cycle is a current driving process of the vehicle from a power-on state to a power-off state, and the first driving data is single-dimensional data;

[0063] A calculation module 32, which can be used to integrate and calculate the first driving data to obtain second driving data, where the second driving data is multi-dimensional data obtained by integrating at least two first driving data;

[0064] The uploading module 33 may be used to synchronously upload the first driving data and the second driving data to a cloud storage.

[0065] In a specific application scenario, the first driving data and the second driving data respectively include a vehicle identifier; the upload module 33 can be specifically used to synchronously upload the first driving data and the second driving data to the cloud, and store them in a preset storage area corresponding to the vehicle identifier in the cloud.

[0066] In specific application scenarios, such as Figure 5 As shown, the device further includes: a first detection module 34;

[0067] The first detection module 34 can be used to detect whether the historical driving cycle includes the first historical driving data that has not been successfully uploaded when the current driving starts; or to periodically detect whether the historical driving cycle includes the first historical driving data that has not been successfully uploaded according to a preset time period.

[0068] In a specific application scenario, the upload module 33 can also be used to synchronously upload the first historical driving data from the local database to the cloud in response to detecting that the historical driving cycle includes first historical driving data that has not been successfully uploaded, and store it in a preset storage area corresponding to the vehicle identifier in the cloud.

[0069] In specific application scenarios, such as Figure 5 As shown, the device further includes: a second detection module 35;

[0070] The second detection module 35 can be used to detect whether the local database includes the second historical driving data that is missing; if so, send a data acquisition request carrying a vehicle identifier to the cloud; and receive the second historical driving data fed back by the cloud in response to the data acquisition request.

[0071] In specific application scenarios, such as Figure 5 As shown, the device further includes: a display module 36;

[0072] The display module 36 may be configured to display the first driving data and / or the second driving data in a preset display format.

[0073] In specific application scenarios, such as Figure 5As shown, the device also includes: a receiving module 37, an early warning module 38;

[0074] The receiving module 37 may be used to receive the driving behavior prediction result sent by the cloud, where the driving behavior prediction result is a prediction result for a preset driving behavior obtained by the cloud by analyzing the first driving data and / or the second driving data;

[0075] The warning module 38 can be used to perform safety warning processing on the driver's driving behavior in the next driving cycle based on the driving behavior prediction result.

[0076] It should be noted that for other corresponding descriptions of the functional units involved in the driving data processing device provided in this embodiment, reference can be made to Figure 1 and Figure 2 The corresponding description in will not be repeated here.

[0077] Based on the above Figure 1 and Figure 2 The method shown in the embodiment also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned Figure 1 and Figure 2 The method shown.

[0078] Based on this understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of the present application.

[0079] Based on the above Figure 1 and Figure 2 The method shown, and Figure 4 and Figure 5 In order to achieve the above-mentioned purpose, the embodiment of the present application also provides an electronic device that can be configured on the vehicle (such as an electric vehicle) side, and the device includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to achieve the above-mentioned Figure 1 and Figure 2 The method shown.

[0080] Optionally, the above-mentioned physical device may also include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, etc. The user interface may include a display, an input unit such as a keyboard, etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface), etc.

[0081] Those skilled in the art will appreciate that the above-mentioned physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or a combination of certain components, or different arrangements of components.

[0082] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the above-mentioned physical device, and supports the operation of the information processing program and other software and / or programs. The network communication module is used to realize the communication between the components inside the storage medium, and the communication with other hardware and software in the information processing physical device.

[0083] Based on the above electronic device, the embodiment of the present application further provides a vehicle, which may specifically include: the above electronic device. The vehicle may specifically be an electric car, etc.

[0084] Through the description of the above implementation methods, the technicians in this field can clearly understand that the present application can be implemented by means of software plus the necessary general hardware platform, or by hardware. The technical solution in the present disclosure can collect driving data and integrate and calculate the driving data during the vehicle-side driving cycle, and then upload the collected first driving data and the second driving data obtained by the integrated calculation to the cloud storage synchronously, so as to achieve the synchronization of vehicle-cloud data, facilitate the double backup of driving data, prevent the storage loss of driving data, and ensure the storage security of driving data. In addition, during the process of uploading driving data, the upload status of the driving data of the previous driving cycle can also be detected, and the first historical driving data that has not been successfully uploaded can be re-uploaded, so as to ensure the integrity of the driving data stored in the cloud. The vehicle side can also receive the driving behavior prediction results obtained by analyzing the driving data in the cloud, and based on the driving behavior prediction results, perform safety warning processing for the driver's driving behavior in the next driving cycle, which can ensure the safety of driving and improve the user's driving experience.

[0085] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0086] The above is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A method for processing driving data, characterized in that: include: Acquire first driving data in a current driving cycle, where the current driving cycle is a current driving process of the vehicle from a power-on state to a power-off state, and the first driving data is single-dimensional data; Performing integration calculation on the first driving data to obtain second driving data, where the second driving data is multi-dimensional data obtained by integrating at least two of the first driving data; The first driving data and the second driving data are synchronously uploaded to cloud storage.

2. The method according to claim 1, characterized in that The first driving data and the second driving data respectively include a vehicle identifier; and the step of synchronously uploading the first driving data and the second driving data to a cloud storage includes: The first driving data and the second driving data are synchronously uploaded to the cloud, and stored in a preset storage area corresponding to the vehicle identifier in the cloud.

3. The method according to claim 1, characterized in that The method further comprises: At the beginning of the current driving, detecting whether the historical driving cycle includes the first historical driving data that has not been successfully uploaded; or, The historical driving cycle is periodically detected according to a preset time period to determine whether it includes the first historical driving data that has not been successfully uploaded.

4. The method according to claim 3, characterized in that The method further comprises: In response to detecting that the historical driving cycle includes first historical driving data that has not been successfully uploaded, the first historical driving data is synchronously uploaded from the local database to the cloud and stored in a preset storage area corresponding to the vehicle identifier in the cloud.

5. The method according to claim 1, characterized in that The method further comprises: detecting whether the local database includes the second historical driving data that is missing from storage; If yes, a data acquisition request carrying a vehicle identifier is sent to the cloud; The second historical driving data fed back by the cloud in response to the data acquisition request is received.

6. The method according to claim 1, characterized in that The method further comprises: The first driving data and / or the second driving data are presented to the user in a preset presentation format.

7. The method according to claim 1, characterized in that The method further comprises: receiving a driving behavior prediction result sent by the cloud, where the driving behavior prediction result is a prediction result for a preset driving behavior obtained by the cloud by analyzing the first driving data and / or the second driving data; Based on the driving behavior prediction result, a safety warning process is performed on the driver's driving behavior in the next driving cycle.

8. A driving data processing device, characterized in that: include: an acquisition module, configured to acquire first driving data in a current driving cycle, wherein the current driving cycle is a current driving process of the vehicle from a power-on state to a power-off state, and the first driving data is single-dimensional data; a calculation module, configured to perform integrated calculation on the first driving data to obtain second driving data, where the second driving data is multi-dimensional data obtained by integrating at least two of the first driving data; The uploading module is used to synchronously upload the first driving data and the second driving data to cloud storage.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

11. A vehicle, characterized in that: include: The electronic device as claimed in claim 10.

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