Vehicle driving data processing method and device, terminal equipment and medium

Abstract

This invention discloses a method, apparatus, terminal device, and computer-readable storage medium for processing vehicle driving data. The method includes: acquiring vehicle driving data during the driving process of a target vehicle, and aggregating the vehicle driving data according to a preset aggregation granularity to obtain a vehicle trip data stream corresponding to the target vehicle; determining target driving data corresponding to each preset vehicle driving state and target time points corresponding to each target driving data in the vehicle trip data stream; determining driving feature tags for the target vehicle based on each target driving data and each target time point, and randomly integrating the driving feature tags to obtain a target tag system. This invention achieves the technical effect of extracting key data representing each driving stage of the vehicle from a vehicle driving data stream containing underlying driving data, thereby improving the efficiency of data processing and data analysis.

Description

Technical Field

[0001] This invention relates to the field of vehicle networking technology, and in particular to a method, apparatus, terminal device, and computer-readable storage medium for processing vehicle driving data. Background Technology

[0002] With the development of the intelligent vehicle industry, the Internet of Vehicles (IoV) system, which is based on in-vehicle networks, inter-vehicle networks, and in-vehicle mobile internet and is constructed according to preset communication protocols and data interaction standards, is gradually becoming an increasingly important part of the development of intelligent vehicles. It is used for network connection and data transmission between vehicles, between vehicles and people, between vehicles and roads, and between vehicles and service platforms.

[0003] The current vehicle-to-everything (V2X) systems used in intelligent vehicles primarily operate by sending vehicle data generated during driving to a cloud database. This cloud database then filters and cleans the data via a connected cloud computing platform, generating processing results for administrators. However, while this method can process various driving data points, the sheer volume of data generated during vehicle operation can reach billions. Therefore, directly analyzing the underlying data as is currently the case results in extremely low data analysis efficiency and places a heavy burden on servers. Summary of the Invention

[0004] The present invention provides a method, apparatus, terminal device, and computer-readable storage medium for processing vehicle driving data, aiming to extract key data representing each driving stage of the vehicle from a vehicle driving data stream containing various underlying driving data, thereby improving the efficiency of data processing and data analysis.

[0005] This invention provides a method for processing vehicle driving data, the method comprising the following steps:

[0006] Acquire the driving data of each vehicle during the driving process of the target vehicle, and aggregate the driving data of each vehicle according to a preset aggregation granularity to obtain the vehicle trip data stream corresponding to the target vehicle.

[0007] In the vehicle trip data stream, the target driving data corresponding to each preset vehicle driving state and the target time point corresponding to each target driving data are determined.

[0008] Based on the target driving data and the target time points, the driving feature labels of the target vehicles are determined, and the driving feature labels are randomly integrated to obtain the target label system.

[0009] Further, the step of determining the target driving data corresponding to each preset vehicle driving state and the target time point corresponding to each target driving data in the vehicle trip data stream includes:

[0010] In the vehicle travel data stream, a first target data that satisfies a preset first vehicle driving state is determined, and the first target data is determined as power-on start data. At the same time, the time point in the vehicle travel data stream that records the power-on start data is determined as a first time point; wherein, the first vehicle driving state is that the target vehicle is in a high-voltage state and the main positive relay of the target vehicle is in a linked state.

[0011] and / or;

[0012] In the vehicle trip data stream, a second target data that satisfies a preset second vehicle driving state is determined, and the second target data is determined as the driving start data. At the same time, the time point in the vehicle trip data stream that records the driving start data is determined as the second time point; wherein, the second vehicle driving state is that the target vehicle is in a high-voltage state, the target vehicle is in a driving state, and the real-time speed of the target vehicle is greater than 0.

[0013] and / or;

[0014] In the vehicle trip data stream, a third target data that satisfies a preset third vehicle driving state is determined, and the third target data is determined as the driving end data. At the same time, the time point in the vehicle trip data stream that records the driving end data is determined as the third time point; wherein, the third vehicle driving state is that the real-time speed of the target vehicle is equal to 0.

[0015] and / or;

[0016] In the vehicle trip data stream, a fourth target data that satisfies a preset fourth driving stage is determined, and the fourth target data is determined as the power-off start data. At the same time, the time point at which the power-off start data is acquired is determined as the fourth time point. The fourth driving stage is defined as the time during which the target vehicle is in a non-high voltage state and the time during which the target vehicle is in a non-driving state is greater than or equal to a preset time threshold.

[0017] Furthermore, the step of determining the target driving data corresponding to each preset vehicle driving state and the target time point corresponding to each target driving data in the vehicle trip data stream further includes:

[0018] Determine whether the driving speed parameter included in the power-down start data is 0;

[0019] If not, then determine that the power-off start data and the driving end data are the same driving data, and determine that the fourth time point and the third time point are the same time point.

[0020] Furthermore, the method also includes:

[0021] The time interval between each vehicle driving data in the vehicle trip data stream is detected, and each time interval is compared with a preset interval threshold to obtain a comparison result;

[0022] Determine whether each of the comparison results contains a target time interval greater than the interval threshold;

[0023] If the target time interval is determined to be included, then the time point that is determined to be the first in the target time interval is determined as the fourth time point according to the preset order arrangement rules, and the driving data corresponding to the fourth time point is determined as the power-off start data.

[0024] Furthermore, the step of determining the driving feature labels of the target vehicle based on each of the target driving data and each of the target time points includes:

[0025] In the vehicle trip data stream, determine the power-on vehicle data between the first time point and the fourth time point, and integrate the power-on vehicle data to obtain the power-on stage data stream of the target vehicle.

[0026] In the vehicle trip data stream, vehicle data in each driving state between the second time point and the third time point are determined, and the vehicle data in each driving state are integrated to obtain the driving stage data stream of the target vehicle.

[0027] Determine each power supply characteristic data corresponding to the power-on stage data stream and each driving characteristic data corresponding to the driving stage data stream, and determine each driving characteristic label based on each power supply characteristic data and each driving characteristic data.

[0028] Furthermore, the method also includes:

[0029] The driving habit characteristics of the target vehicle are obtained based on the target labeling system described above.

[0030] Based on the driving habit characteristics and a preset user profile database, a target user profile corresponding to the driving habit characteristics is obtained.

[0031] Further, the step of obtaining a target user profile corresponding to the driving habit characteristics based on the driving habit characteristics and a preset user profile database includes:

[0032] Read the user profile database;

[0033] The target user profile is obtained by filtering the target user profile database according to the driving habit characteristics.

[0034] Furthermore, to achieve the above objectives, the present invention also provides a vehicle driving data processing apparatus, the apparatus comprising:

[0035] The data integration module is used to acquire the driving data of each vehicle during the driving process of the target vehicle, and to aggregate the driving data of each vehicle according to a preset aggregation granularity to obtain the vehicle trip data stream corresponding to the target vehicle.

[0036] The node determination module is used to determine the target driving data corresponding to each preset vehicle driving state and the target time point corresponding to each target driving data in the vehicle travel data stream.

[0037] The tag calculation module is used to determine the driving feature tags of the target vehicle based on the target driving data and the target time points, and to randomly integrate the driving feature tags to obtain the target tag system.

[0038] In addition, to achieve the above objectives, the present invention also provides a terminal device, the terminal device comprising: a memory, a processor, and a vehicle driving data processing program stored in the memory and executable on the processor, wherein when the vehicle driving data processing program is executed by the processor, it implements the steps of the vehicle driving data processing method described above.

[0039] In addition, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a vehicle driving data processing program, which, when executed by a processor, implements the steps of the vehicle driving data processing method described above.

[0040] The vehicle driving data processing method, apparatus, terminal device, and computer-readable storage medium provided in this invention acquire vehicle driving data during the driving process of a target vehicle, and aggregate the vehicle driving data according to a preset aggregation granularity to obtain a vehicle trip data stream corresponding to the target vehicle; determine target driving data corresponding to each preset vehicle driving state and target time point corresponding to each target driving data in the vehicle trip data stream; determine driving feature tags of the target vehicle based on each target driving data and each target time point, and randomly integrate each driving feature tag to obtain a target tag system.

[0041] In this embodiment, during operation, the terminal device first receives driving data generated by the target vehicle during its journey and inputs this data into its built-in data processing device. The data processing device aggregates the driving data at the trip granularity to obtain a vehicle trip data stream corresponding to the target vehicle. Then, the terminal device sends this vehicle trip data stream to a data extraction device configured within it. The data extraction device extracts target driving data corresponding to each vehicle's driving state from the vehicle trip data stream according to the developer's preset driving states, and records the target time points for each target driving data point. Finally, the terminal device inputs the target driving data and target time points into a tag calculation device configured within it. The tag calculation device calculates based on the target driving data and target time points to determine the driving feature tags of the target vehicle during its journey, and then integrates these driving feature tags in different combinations to obtain a target tag system.

[0042] Thus, this invention aggregates vehicle travel data generated by vehicles according to the granularity of travel distance to obtain a vehicle travel data stream. Then, it extracts target travel data and target time points that can represent the driving status of each vehicle from the vehicle travel data stream. Based on the target travel data and target time points, it determines the target label system corresponding to the target vehicle. That is, the vehicle travel data stream containing the underlying travel data is filtered according to a preset screening standard to obtain representative travel data of each driving stage of the vehicle. This achieves the technical effect of extracting key data representing each driving stage of the vehicle from the vehicle travel data stream containing the underlying travel data, thereby improving the efficiency of data processing and data analysis. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the structure of the terminal device in the hardware operating environment involved in the embodiments of the present invention;

[0044] Figure 2 This is a flowchart illustrating the first embodiment of the vehicle driving data processing method of the present invention;

[0045] Figure 3 This is a flowchart illustrating the second embodiment of the vehicle driving data processing method of the present invention;

[0046] Figure 4 This is a detailed flowchart illustrating an embodiment of the vehicle driving data processing method of the present invention;

[0047] Figure 5 This is a schematic diagram of the functional modules involved in an embodiment of the vehicle driving data processing method of the present invention.

[0048] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0049] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0050] Please refer to Figure 1 , Figure 1 This is a schematic diagram of the terminal device structure of the hardware operating environment involved in the embodiments of the present invention.

[0051] The terminal device in this embodiment of the invention can be a fixed terminal device that connects to the vehicle transmitter and the cloud server. Of course, the terminal device can also be other fixed terminal devices such as PC (Personal Computer), server, or mobile terminal devices such as mobile phones and tablets that connect to the vehicle transmitter and the cloud server.

[0052] like Figure 1 As shown, the terminal device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0053] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the terminal device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0054] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a data storage module, a network communication module, a user interface module, and a program for processing vehicle driving data.

[0055] exist Figure 1 In the terminal device shown, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the terminal device of the present invention can be set in the terminal device, and the terminal device calls the vehicle driving data processing program stored in the memory 1005 through the processor 1001 and executes the vehicle driving data processing method provided in the embodiment of the present invention.

[0056] Based on the aforementioned terminal device, various embodiments of the vehicle driving data processing method of the present invention are provided.

[0057] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the vehicle driving data processing method of the present invention.

[0058] It should be understood that although the logical order is shown in the flowchart, in some cases, the method for processing vehicle driving data of the present invention may of course perform the steps shown or described in a different order than that shown here.

[0059] In this embodiment, the vehicle driving data processing method of the present invention may include the following steps:

[0060] Step S10: Obtain the driving data of each vehicle during the driving process of the target vehicle, and aggregate the driving data of each vehicle according to the preset aggregation granularity to obtain the vehicle trip data stream corresponding to the target vehicle.

[0061] In this embodiment, during operation, the terminal device first receives the vehicle driving data generated by the target vehicle during its driving process, and inputs each vehicle driving data into the data processing device configured in the terminal device. The data processing device then aggregates each vehicle driving data according to the generation time sequence corresponding to each vehicle driving data at an aggregation granularity preset by the developer, thereby obtaining a vehicle trip data stream corresponding to the target vehicle.

[0062] For example, please refer to Figure 4 , Figure 4This is a detailed flowchart illustrating an embodiment of the vehicle driving data processing method of the present invention. During operation, the terminal device first identifies the target vehicle and links with the target vehicle and the cloud server. Then, during the driving process, the target vehicle generates vehicle driving data including its own speed change signal, real-time motion speed information, and real-time operation command signals of the driver of the target vehicle. The terminal device sends each vehicle driving data to the terminal device. The terminal device inputs the received vehicle driving data to the aforementioned data processing device and determines the aggregation granularity preset by the developer as trip. Finally, after the target vehicle finishes driving, the data processing device aggregates each vehicle driving data with the trip of the target vehicle as the granularity to obtain the aforementioned vehicle trip data stream.

[0063] Step S20: Determine the target driving data corresponding to each preset vehicle driving state and the target time point corresponding to each target driving data in the vehicle travel data stream;

[0064] In this embodiment, the terminal device reads the storage device to obtain the driving status of each vehicle preset by the developer, and inputs the driving status of each vehicle and the obtained vehicle travel data stream to the data extraction device configured in the terminal device. The data extraction device filters the vehicle travel data stream according to the driving status of each vehicle, thereby extracting the target driving data corresponding to each driving status of each vehicle and generating the target time of each target driving data.

[0065] For example, such as Figure 4 As shown, the terminal device reads the aforementioned storage device to obtain the first, second, third, and fourth vehicle driving states preset by the developer. Then, the terminal device inputs the first, second, third, and fourth vehicle driving states and the obtained vehicle trip data stream to the aforementioned data extraction device. The data extraction device sequentially filters the vehicle trip data stream according to the first, second, third, and fourth vehicle driving states to obtain target driving data corresponding to the first, second, third, and fourth vehicle driving states, and generates the target time corresponding to each of the target driving data.

[0066] Furthermore, in a feasible embodiment, step S20 above may specifically include:

[0067] Step S201: Determine the first target data that satisfies the preset first vehicle driving state in the vehicle travel data stream, and determine the first target data as power-on start data. At the same time, determine the time point in the vehicle travel data stream that records the power-on start data as the first time point; wherein, the first vehicle driving state is that the target vehicle is in a high voltage state and the main positive relay of the target vehicle is in a linked state.

[0068] In this embodiment, the terminal device reads the aforementioned storage device to obtain the aforementioned first vehicle driving state, and determines that the first vehicle driving state is that the target vehicle is in a high-voltage state and the main positive relay of the target vehicle is in a connected state. Then, the terminal device inputs the first vehicle driving state to the aforementioned data extraction device, and the data extraction device filters the aforementioned vehicle driving data stream based on the first vehicle driving state to obtain first target data that satisfies the conditions that the target vehicle is in a high-voltage state and the main positive relay is in a connected state. The terminal device determines the first target data as the power-on start data of the target vehicle, and at the same time, determines the time point at which the power-on start data is recorded as the first time point.

[0069] Step S202: Determine the second target data that satisfies the preset second vehicle driving state in the vehicle trip data stream, and determine the second target data as the driving start data. At the same time, determine the time point in the vehicle trip data stream that records the driving start data as the second time point; wherein, the second vehicle driving state is that the target vehicle is in a high-voltage state, the target vehicle is in a driving state, and the real-time speed of the target vehicle is greater than 0.

[0070] In this embodiment, the terminal device reads the aforementioned storage device to obtain the second vehicle driving status of the developer, and determines that the second vehicle driving status is that the target vehicle is in a high-voltage state, the target vehicle is in a driving state, and the real-time speed of the target vehicle is greater than 0. Then, the terminal device inputs the second vehicle driving status to the aforementioned data extraction device, and the data extraction device filters the vehicle driving data stream based on the second vehicle driving status to obtain second target data that satisfies the conditions that the target vehicle is in a high-voltage state, the target vehicle is in a driving state, and the real-time speed of the target vehicle is greater than 0. The terminal device determines the second target data as the driving start data of the target vehicle, and at the same time, determines the time point at which the driving start data is recorded as the second time point.

[0071] Step S203: Determine the third target data that satisfies the preset third vehicle driving state in the vehicle trip data stream, and determine the third target data as the driving end data. At the same time, determine the time point in the vehicle trip data stream that records the driving end data as the third time point; wherein, the third vehicle driving state is that the real-time speed of the target vehicle is equal to 0.

[0072] In this embodiment, the terminal device reads the aforementioned storage device to obtain the third vehicle driving state preset by the developer, and determines that the third vehicle driving state is that the real-time speed of the target vehicle is equal to 0. Then, the terminal device inputs the third vehicle driving state to the aforementioned data extraction device, and the data extraction device filters the vehicle driving data stream based on the third vehicle driving state to obtain the third target data that satisfies the real-time speed of the target vehicle being equal to 0. The terminal device determines the third target data as the driving end data of the target vehicle, and at the same time, determines the time point recorded to the driving end data as the third time point.

[0073] Step S204: Determine the fourth target data that satisfies the preset fourth driving stage in the vehicle trip data stream, and determine the fourth target data as the power-off start data. At the same time, determine the time point at which the power-off start data is acquired as the fourth time point; wherein, the fourth driving stage is the time when the target vehicle is in a non-high voltage state and the target vehicle is in a non-driving state is greater than or equal to a preset time threshold.

[0074] In this embodiment, the terminal device reads the aforementioned storage device to obtain the fourth vehicle driving state preset by the developer, and determines that the fourth vehicle driving state is when the target vehicle is in a non-high voltage state and the target vehicle is in a non-driving state for a time greater than or equal to a preset time threshold. Then, the terminal device inputs the fourth vehicle driving state to the aforementioned data extraction device, which filters the vehicle driving data stream based on the fourth vehicle driving state to obtain fourth target data that satisfies the condition that the target vehicle is in a non-high voltage state and the target vehicle is in a non-driving state for a time greater than or equal to the preset time threshold. The terminal device uses the fourth target data as the power-off start data of the target vehicle, and simultaneously determines the time point recorded to the power-off start data as the fourth time point.

[0075] For example, when the terminal device reads the aforementioned storage device to obtain the first vehicle driving state preset by the developer, and confirms that the first vehicle driving state is that the high voltage status signal data corresponding to the target vehicle is Ready and the connection state of the positive relay corresponding to the target vehicle is On, the terminal device inputs the acquired vehicle driving data stream to the aforementioned data extraction device. The data extraction device filters each vehicle driving data according to the aforementioned time sequence, and determines the first target data that satisfies the condition that the high voltage status signal data corresponding to the target vehicle is Ready and the connection state of the positive relay corresponding to the target vehicle is On from each vehicle driving data. The first target data is then used as the aforementioned power-on start data. At the same time, the terminal device reads the time point recorded to the power-on start data and determines the time point as the aforementioned first time point.

[0076] And / or,

[0077] The terminal device reads the storage device to obtain the second vehicle driving state preset by the developer, and confirms that the second vehicle driving state is when the high voltage status signal data corresponding to the target vehicle is Ready, the driving state corresponding to the target vehicle is Run, and the real-time speed of the target vehicle is greater than 0. The terminal device inputs the obtained vehicle driving data stream to the data extraction device, which reads each vehicle driving data in the order of time, and determines the first data in the sorted order that meets the conditions of the high voltage status signal data corresponding to the target vehicle being Ready, the driving state corresponding to the target vehicle being Run, and the real-time speed of the target vehicle being greater than 0 as the second target data. The second target data is used as the driving start data. At the same time, the terminal device reads the time point recorded when the driving start data is recorded and determines the time point as the second time point.

[0078] And / or,

[0079] The terminal device reads the storage device to obtain the third vehicle driving status preset by the developer, and confirms that the third vehicle driving status is that the real-time speed of the target vehicle is equal to 0. The terminal device inputs the obtained vehicle driving data stream to the data extraction device, which reads each vehicle driving data in the order of time, and determines the first data that satisfies the real-time speed of the target vehicle being equal to 0 in the sorted data as the third target data, and uses the third target data as the driving end data. At the same time, the terminal device reads the time point recorded to the driving end data and determines the time point as the third time point.

[0080] And / or,

[0081] The terminal device reads the storage device to obtain the fourth vehicle driving state preset by the developer. When the fourth vehicle driving state is confirmed to be when the high voltage status signal data corresponding to the target vehicle is Not Ready and the driving state corresponding to the target vehicle is in Not Run for more than 6 seconds, the terminal device inputs the acquired vehicle driving data stream to the data extraction device. The data extraction device reads each vehicle driving data in the order of time and determines the first data in the sorted order that satisfies the condition that the high voltage status signal data of the target vehicle is Not Ready and the driving state corresponding to the target vehicle is in Not Run for more than 6 seconds as the fourth target data. The fourth target data is used as the power-down start data. At the same time, the terminal device reads the time point recorded to the power-down start data and determines the time point as the fourth time point.

[0082] Furthermore, in a feasible embodiment, step S20 above may further include:

[0083] Step S205: Determine whether the driving speed parameter included in the power-down start data is 0;

[0084] In this embodiment, when the terminal device detects the power-down start data, it inputs the power-down start data to the data processing device. The data processing device extracts the information parameters contained in the power-down start data and determines the driving speed parameter from each information parameter. The data processing device then determines whether the driving speed parameter is 0.

[0085] Step S206: If not, determine that the power-down start data and the driving end data are the same driving data, and determine that the fourth time point and the third time point are the same time point;

[0086] In this embodiment, if the terminal device determines through the data processing device that the driving speed parameter is not 0, then the terminal device determines that the target vehicle is in a state of performing a power-down operation without stopping driving, and further determines that the power-down start data and the driving end data are the same data, and determines that the fourth time point and the third time point are the same time point.

[0087] For example, when the terminal device extracts the power-off start data from the vehicle trip data stream, the terminal device inputs the power-off start data to the data processing device, which decomposes the power-off start data to obtain the speed change parameters, real-time motion parameters, and operation signal parameters that make up the power-off start data. Then, it determines the driving speed parameters contained in the power-off start data and determines whether the driving speed parameters are not 0. If the terminal device determines that the driving speed parameters are not 0, the terminal device determines that the driver of the target vehicle performed a power-off operation on the target vehicle without stopping driving. Then, the terminal device determines that the power-off start time is consistent with the driving end time and determines that the fourth time point and the third time point are the same time point.

[0088] Furthermore, in a feasible embodiment, step S20 above may further include:

[0089] Step S207: Detect the time interval between each vehicle driving data in the vehicle trip data stream, and compare each time interval with a preset interval threshold to obtain each comparison result;

[0090] In this embodiment, the terminal device uses the data extraction device to detect the recording time corresponding to each of the vehicle driving data contained in the vehicle trip data stream, and determines the time interval between each of the vehicle driving data according to the time sequence. At the same time, the terminal device inputs the acquired time intervals and the interval threshold preset by the developer into the data comparison device configured in the terminal device. The data comparison device compares each time interval with the interval threshold and obtains each comparison result.

[0091] Step S208: Determine whether each of the comparison results contains a target time interval greater than the interval threshold;

[0092] In this embodiment, the terminal device determines the interval difference between each of the above-mentioned time intervals and the above-mentioned interval threshold based on each of the above-mentioned comparison results, and determines whether there is a target interval difference greater than the interval threshold among each of the interval differences.

[0093] Step S209: If it is determined that the target time interval is included, then the time point with the highest order in the target time interval is determined as the fourth time point according to the preset order arrangement rules, and the driving data corresponding to the fourth time point is determined as the power-off start data;

[0094] In this embodiment, if the terminal device determines that there is a target interval difference among the above interval differences, the terminal device determines the time interval corresponding to the target interval difference as the target time interval. At the same time, the terminal device determines the time point that is ranked earlier in the target time interval according to the above time order, and determines the time point as the fourth time point. At the same time, the vehicle driving data corresponding to the fourth time point is determined as the power-off start data.

[0095] For example, the terminal device invokes the aforementioned data extraction device to detect the recording time corresponding to each of the vehicle travel data in the vehicle trip data stream, and sequentially detects the time interval between each adjacent vehicle travel data according to the aforementioned time sequence. Simultaneously, the terminal device reads the aforementioned storage device to obtain an interval threshold pre-stored by the developer. When the interval threshold is set to 60 seconds by the developer, the terminal device inputs each obtained time interval and the interval threshold 60 seconds to the aforementioned data comparison device, which then compares each time interval with the interval threshold 60 seconds. The terminal device compares the results obtained by 0s and then determines the interval difference between each time interval and the interval threshold of 60s based on each comparison result. It also determines whether each interval difference contains a target interval difference greater than 60s. When the terminal device determines that there is a target interval difference greater than 60s, it determines the time interval corresponding to the target interval difference and determines the time point that is ranked earlier in the target time interval according to the time order. This time point is determined as the fourth time point mentioned above, and the driving data corresponding to the fourth time point is determined as the power-off start data mentioned above.

[0096] Step S30: Determine the driving feature labels of the target vehicle based on the target driving data and the target time points, and randomly integrate the driving feature labels to obtain the target label system;

[0097] In this embodiment, the terminal device inputs the acquired target driving data and target time points of each row into the tag calculation device configured in the terminal device. The tag calculation device calculates the driving feature tags of the target vehicle during the driving process based on the target driving data and target time points, and randomly combines the driving feature tags to obtain the target tag system.

[0098] For example, such as Figure 4As shown, the terminal device inputs the acquired power-on start data, driving start data, driving end data, and power-off start data, along with the target time points corresponding to each of these target data points, into the tag calculation device. The tag calculation device extracts data features such as acceleration features, real-time vehicle speed features, and driver operation features contained in each of the power-on start data, driving start data, driving end data, and power-off start data. Based on these data features and the target time points, it calculates the driving feature tags corresponding to each driving stage of the target vehicle during driving. The terminal device then randomly combines these driving feature tags to obtain the target tag system.

[0099] Furthermore, in a feasible embodiment, step S30 above may specifically include:

[0100] Step S301: Determine the power-on vehicle data between the first time point and the fourth time point in the vehicle trip data stream, and integrate the power-on vehicle data to obtain the power-on stage data stream of the target vehicle.

[0101] In this embodiment, the terminal device first determines the vehicle driving data between the first time point and the fourth time point in the vehicle travel data stream, and aggregates the vehicle driving data according to the stage granularity preset by the developer as the aggregation granularity to obtain the power-on stage data stream of the overall journey of the target vehicle.

[0102] Step S302: Determine the vehicle data in each driving state between the second time point and the third time point in the vehicle travel data stream, and integrate the vehicle data in each driving state to obtain the driving stage data stream of the target vehicle.

[0103] In this embodiment, the terminal device determines the vehicle driving data between the second time point and the third time point by summarizing the vehicle travel data stream, and aggregates the vehicle driving data according to the stage granularity preset by the developer as the aggregation granularity to obtain the driving stage data stream in the overall journey of the target vehicle.

[0104] Step S303: Determine each power supply characteristic data corresponding to the power-on stage data stream and each driving characteristic data corresponding to the driving stage data stream, and determine each driving characteristic label based on each power supply characteristic data and each driving characteristic data;

[0105] In this embodiment, the terminal device extracts the corresponding data feature information from the power-on stage data stream and the driving stage data stream, respectively, and then determines the driving feature data of the target vehicle in each driving stage based on the data feature information. After that, the terminal device performs offline task calculation on the driving feature data through the tag calculation device to obtain the driving feature tags.

[0106] For example, the terminal device first determines the first time point and the fourth time point from the data recording times included in the vehicle trip data stream, and reads the power-on vehicle data between the first time point and the fourth time point in the time sequence. The terminal device aggregates the power-on vehicle data according to the stage granularity preset by the developer as the aggregation granularity to obtain the power-on stage data stream of the target vehicle throughout the entire driving process. At the same time, the terminal device determines the second time point and the third time point from the recording times in the vehicle trip data stream, and reads the data between the first time point and the fourth time point in the time sequence. The terminal device aggregates the vehicle data in each driving state between the second time point and the third time point according to the granularity of the stage to obtain the driving stage data stream. Then, the terminal device inputs the vehicle driving data corresponding to the power-on stage data stream and the vehicle driving data corresponding to the driving stage data stream to the tag computing device. The tag computing device extracts the data feature information of each data in the power-on stage data stream and the data feature information of each data in the driving stage data stream, and performs offline calculation on each data feature information to obtain the driving feature tag corresponding to each driving stage.

[0107] In this embodiment, during operation, the terminal device first receives vehicle driving data generated by the target vehicle during its journey, and inputs this data into a data processing device configured within the terminal device. The data processing device then aggregates the vehicle driving data according to the generation time sequence of each data point, using an aggregation granularity preset by the developer, to obtain a vehicle trip data stream corresponding to the target vehicle. Afterward, the terminal device reads from a storage device to obtain the vehicle driving status preset by the developer, and inputs the vehicle driving status and the obtained vehicle trip data stream into the terminal device. The data extraction device within the terminal device filters the vehicle travel data stream according to the driving status of each vehicle, thereby extracting the target driving data corresponding to each driving status and generating the target time for each target driving data. Finally, the terminal device inputs the acquired target driving data and target time points into the tag calculation device configured within the terminal device. The tag calculation device calculates the driving feature tags of the target vehicle during its driving process based on the target driving data and target time points, and randomly combines the driving feature tags to obtain the target tag system.

[0108] Thus, this invention aggregates vehicle driving data generated by vehicles according to the granularity of the trip to obtain a vehicle trip data stream. Then, it extracts target driving data and target time points that can represent the driving status of each vehicle from the vehicle trip data stream. Based on the target driving data and target time points, it determines the target label system corresponding to the target vehicle. This achieves the technical effect of extracting key data representing each driving stage of the vehicle from the vehicle driving data stream containing the underlying driving data, thereby improving the efficiency of data processing and data analysis.

[0109] Furthermore, based on the first embodiment of the vehicle driving data processing method of the present invention described above, a second embodiment of the vehicle driving data processing method of the present invention is proposed herein.

[0110] Please refer to Figure 3 , Figure 3 This is a flowchart illustrating a second embodiment of the vehicle driving data processing method of the present invention. The vehicle driving data processing method of the present invention may further include:

[0111] Step A10: Obtain the driving habit characteristics corresponding to the target vehicle based on the target label system described above;

[0112] In this embodiment, the terminal device inputs the acquired target tag systems into the user profiling device configured in the terminal device, and the user profiling device determines the driving habit characteristics of the driver of the target vehicle based on the target tag systems.

[0113] Step A20: Obtain the target user profile corresponding to the driving habit characteristics according to the driving habit characteristics and the preset user profile database;

[0114] In this embodiment, the terminal device reads the storage device to obtain the user profile database pre-stored by the developer, and inputs the user profile database into the user profile device. The user profile device then filters the user profile database according to the driving habit characteristics to determine the target user profile corresponding to the driver.

[0115] For example, the terminal device inputs the acquired target tag systems into the user profiling device, which extracts data features that match the vehicle trip data stream from each target tag system and determines the driving style, operating habits, and other feature data of the driver of the target vehicle based on each data feature, thereby obtaining the driving habit features. Then, the terminal device reads the user profile database preset by the developer and inputs it into the user profiling device, which determines the target user profile in the user profile database based on the driving habit features.

[0116] Furthermore, in a feasible embodiment, step A20 above may specifically include:

[0117] Step A201: Read the user profile database;

[0118] Step A202: Filter the target user profile database according to the driving habit characteristics to obtain the target user profile corresponding to the driving habit characteristics;

[0119] For example, the terminal device reads the aforementioned storage device to obtain a user profile database pre-stored by the developer, which includes each user profile and driving habit feature data corresponding to each user profile. Then, the terminal device inputs the aforementioned user profile database and the aforementioned driving habit feature data into the aforementioned user profile device, and the user profile device filters the user profile database according to the driving habit feature data to determine the target user profile corresponding to the driving habit feature data in the user profile database.

[0120] In this embodiment, the terminal device inputs the acquired target tag systems into the user profiling device configured within the terminal device. The user profiling device determines the driving habit characteristics corresponding to the driver of the target vehicle based on each target tag system. Then, the terminal device reads the storage device to obtain the user profile database pre-stored by the developer and inputs the user profile database into the user profiling device. The user profiling device filters the user profile database according to the driving habit characteristics to determine the target user profile corresponding to the driver.

[0121] Thus, this invention uses the method of determining the driving habit characteristics of the driver of the target vehicle according to each target label system, and then filtering the preset user profile database according to the driving habit characteristics to obtain the target user profile corresponding to the driving habit characteristics. This achieves the purpose of determining the user's driving habits based on the collected vehicle information data, thereby improving the user experience.

[0122] In addition, the present invention also provides a vehicle driving data processing device, please refer to... Figure 5 , Figure 5 This is a schematic diagram of the functional modules involved in an embodiment of the vehicle driving data processing method of the present invention, as shown below. Figure 5 As shown, the vehicle driving data processing device of the present invention includes:

[0123] The data integration module 10 is used to acquire the driving data of each vehicle during the driving process of the target vehicle, and to aggregate the driving data of each vehicle according to a preset aggregation granularity to obtain the vehicle trip data stream corresponding to the target vehicle.

[0124] The node determination module 20 is used to determine the target driving data corresponding to each preset vehicle driving state and the target time point corresponding to each target driving data in the vehicle travel data stream.

[0125] The tag calculation module 30 is used to determine the driving feature tags of the target vehicle based on the target driving data and the target time points, and to randomly integrate the driving feature tags to obtain the target tag system.

[0126] Furthermore, the node determination module 20 includes:

[0127] The first filtering unit is used to determine first target data that meets a preset first vehicle driving state in the vehicle travel data stream, and to determine the first target data as power-on start data. At the same time, the time point in the vehicle travel data stream that records the power-on start data is determined as the first time point. The first vehicle driving state is that the target vehicle is in a high-voltage state and the main positive relay of the target vehicle is in a linked state.

[0128] The second filtering unit is used to determine second target data that meets a preset second vehicle driving state in the vehicle travel data stream, and to determine the second target data as driving start data. At the same time, the time point recorded in the vehicle travel data stream to the driving start data is determined as the second time point; wherein, the second vehicle driving state is that the target vehicle is in a high-voltage state, the target vehicle is in a driving state, and the real-time speed of the target vehicle is greater than 0.

[0129] The third filtering unit is used to determine the third target data that meets the preset third vehicle driving state in the vehicle trip data stream, and to determine the third target data as the driving end data. At the same time, the time point recorded in the vehicle trip data stream to the driving end data is determined as the third time point; wherein, the third vehicle driving state is that the real-time speed of the target vehicle is equal to 0.

[0130] The fourth filtering unit is used to determine the fourth target data that meets the preset fourth driving stage in the vehicle travel data stream, and to determine the fourth target data as the power-off start data. At the same time, the time point at which the power-off start data is acquired is determined as the fourth time point. The fourth driving stage is defined as the time when the target vehicle is in a non-high voltage state and the target vehicle is in a non-driving state is greater than or equal to a preset time threshold.

[0131] Furthermore, the node determination module 20 also includes:

[0132] The parameter judgment unit is used to determine whether the driving speed parameter included in the power-down start data is 0;

[0133] The data merging unit is used to determine that the power-off start data and the driving end data are the same driving data if the driving speed parameter contained in the power-off start data is 0, and to determine that the fourth time point and the third time point are the same time point.

[0134] Furthermore, the node determination module 20 also includes:

[0135] An interval detection unit is used to detect the time interval between each vehicle driving data in the vehicle trip data stream, and compare each time interval with a preset interval threshold to obtain a comparison result.

[0136] An interval comparison unit is used to determine whether each of the comparison results contains a target time interval greater than the interval threshold.

[0137] The fifth filtering unit is used to determine the time point with the highest order in the target time interval as the fourth time point if it is determined that the target time interval is included, and to determine the driving data corresponding to the fourth time point as the power-off start data.

[0138] Furthermore, the tag calculation module 30 includes:

[0139] The first integration unit is used to determine the power-on vehicle data between the first time point and the fourth time point in the vehicle trip data stream, and to integrate the power-on vehicle data to obtain the power-on stage data stream of the target vehicle.

[0140] The second integration unit is used to determine the vehicle data of each driving state between the second time point and the third time point in the vehicle travel data stream, and to integrate the vehicle data of each driving state to obtain the driving stage data stream of the target vehicle.

[0141] The tag calculation unit is used to determine each power supply characteristic data corresponding to the power-on stage data stream and each driving characteristic data corresponding to the driving stage data stream, and to determine each driving characteristic tag based on each power supply characteristic data and each driving characteristic data.

[0142] Furthermore, the tag calculation module 30 also includes:

[0143] A habit calculation unit is used to obtain the driving habit features corresponding to the target vehicle based on each of the target label systems;

[0144] The profile determination unit is used to obtain a target user profile corresponding to the driving habit characteristics according to the driving habit characteristics and a preset user profile database.

[0145] Furthermore, the image determination unit includes:

[0146] The data reading subunit is used to read the user profile database;

[0147] The data filtering subunit is used to filter the target user profile database according to the driving habit characteristics to obtain the target user profile corresponding to the driving habit characteristics.

[0148] In addition, the present invention also provides a terminal device having a vehicle driving data processing program that can run on a processor. When the terminal device executes the vehicle driving data processing program, it implements the steps of the vehicle driving data processing method as described in any of the above embodiments.

[0149] The specific embodiments of the terminal device of the present invention are basically the same as the embodiments of the above-described vehicle driving data processing method, and will not be described in detail here.

[0150] Furthermore, the present invention also provides a computer-readable storage medium storing a vehicle driving data processing program thereon, wherein when the vehicle driving data processing program is executed by a processor, it implements the steps of the vehicle driving data processing method as described in any of the above embodiments.

[0151] The specific embodiments of the computer-readable storage medium of this invention are basically the same as the embodiments of the vehicle driving data processing method described above, and will not be repeated here.

[0152] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0153] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0154] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which can be a fixed terminal device connected to a vehicle transmitter and a cloud server; of course, the terminal device can also be a PC (Personal Computer), server, or other fixed terminal device connected to a vehicle transmitter and a cloud server, or a mobile terminal device such as a mobile phone or tablet, etc.) to execute the methods described in the various embodiments of the present invention.

[0155] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method of processing vehicle travel data, characterized by, The processing method of the vehicle driving data comprises the following steps: Obtaining each vehicle driving data in the driving process of a target vehicle, and aggregating each vehicle driving data according to a preset aggregation granularity and a time sequence in which each vehicle driving data is generated to obtain a vehicle travel data stream corresponding to the target vehicle, wherein the aggregation granularity comprises a travel of the target vehicle; Determining, in the vehicle travel data stream, target driving data corresponding to each preset vehicle driving state and target time points corresponding to each target driving data, wherein the target driving data and the target time points are obtained by filtering and extracting the vehicle travel data stream based on the vehicle driving state, and the target driving data is the first data satisfying the vehicle driving state in each vehicle driving data sorted according to the time sequence; Determining each driving feature label of the target vehicle based on each target driving data and each target time point, and randomly integrating each driving feature label to obtain each target label system.

2. The processing method of vehicle travel data according to claim 1, characterized in that, The step of determining, in the vehicle travel data stream, target driving data corresponding to each preset vehicle driving state and target time points corresponding to each target driving data comprises: Determining first target data satisfying a preset first vehicle driving state in the vehicle travel data stream, and determining the first target data as start-up start data, and simultaneously determining a time point recorded in the vehicle travel data stream to the start-up start data as a first time point; wherein the first vehicle driving state is that the target vehicle is in a high-voltage state, and a main positive relay of the target vehicle is in a linked state; And / or; Determining second target data satisfying a preset second vehicle driving state in the vehicle travel data stream, and determining the second target data as driving start data, and simultaneously determining a time point recorded in the vehicle travel data stream to the driving start data as a second time point; wherein the second vehicle driving state is that the target vehicle is in a high-voltage state, the target vehicle is in a driving state, and a real-time vehicle speed of the target vehicle is greater than 0; And / or; Determining third target data satisfying a preset third vehicle driving state in the vehicle travel data stream, and determining the third target data as driving end data, and simultaneously determining a time point recorded in the vehicle travel data stream to the driving end data as a third time point; wherein the third vehicle driving state is that the real-time vehicle speed of the target vehicle is equal to 0; And / or; Determining fourth target data satisfying a preset fourth driving phase in the vehicle travel data stream, and determining the fourth target data as power-down start data, and simultaneously determining a time point at which the power-down start data is obtained as a fourth time point; wherein the fourth driving phase is that the target vehicle is in a non-high-voltage state and a time in which the target vehicle is in a non-driving state is greater than or equal to a preset time threshold.

3. The processing method of vehicle travel data according to claim 2, characterized in that, The step of determining, in the vehicle travel data stream, each preset vehicle driving state corresponding target driving data and each target driving data corresponding target time point further comprises: determining whether the driving speed parameter contained in the power-off start data is 0; if not, determining that the power-off start data and the driving end data are the same driving data, and determining that the fourth time point and the third time point are the same time point.

4. The processing method of vehicle travel data according to claim 3, characterized in that, The method further comprises: detecting the time interval between each vehicle driving data in the vehicle travel data stream, and comparing each time interval with a preset interval threshold to obtain each comparison result; determining whether the comparison result contains a target time interval greater than the interval threshold; if it is determined that the target time interval is contained, arranging the time point determined to be in the front in the target time interval according to a preset arrangement rule to determine the fourth time point, and determining the driving data corresponding to the fourth time point as the power-off start data.

5. The processing method of vehicle travel data according to claim 4, characterized in that, The step of determining each driving feature label of the target vehicle based on each target driving data and each target time point comprises: determining each power-on state vehicle data between the first time point and the fourth time point in the vehicle travel data stream, and integrating each power-on state vehicle data to obtain the power-on stage data stream of the target vehicle; determining each driving state vehicle data between the second time point and the third time point in the vehicle travel data stream, and integrating each driving state vehicle data to obtain the driving stage data stream of the target vehicle; determining each power supply feature data corresponding to the power-on stage data stream and each driving feature data corresponding to the driving stage data stream, and determining each driving feature label according to each power supply feature data and each driving feature data.

6. The processing method of vehicle travel data according to claim 1, characterized in that, The method further comprises: obtaining the driving habit feature corresponding to the target vehicle according to each target label system; obtaining the target user portrait corresponding to the driving habit feature according to the driving habit feature and a preset user portrait database.

7. The processing method of vehicle travel data according to claim 6, characterized in that, The step of obtaining the target user portrait corresponding to the driving habit feature according to the driving habit feature and a preset user portrait database comprises: reading the user portrait database; screening the target user portrait database according to the driving habit feature to obtain the target user portrait corresponding to the driving habit feature.

8. A processing device of vehicle travel data, characterized by, The device comprises: a data integration module configured to obtain each vehicle driving data in the driving process of a target vehicle, and aggregate each vehicle driving data according to a preset aggregation granularity and the time sequence of each vehicle driving data to obtain a vehicle travel data stream corresponding to the target vehicle, wherein the aggregation granularity comprises the travel of the target vehicle. A node determining module is configured to determine, in the vehicle travel data stream, each target travel data corresponding to each preset vehicle travel state and each target time point corresponding to each target travel data, wherein the target travel data and the target time point are obtained by filtering and extracting the vehicle travel data stream based on the vehicle travel state, and the target travel data is the first data satisfying the vehicle travel state in each vehicle travel data sorted in the time sequence; A label calculating module is configured to determine each travel feature label of the target vehicle based on each target travel data and each target time point, and randomly integrate each travel feature label to obtain each target label system.

9. A terminal device, comprising: The terminal device comprises a memory, a processor, and a vehicle travel data processing program stored in the memory and executable on the processor. When the vehicle travel data processing program is executed by the processor, the steps of the vehicle travel data processing method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a vehicle travel data processing program. When the vehicle travel data processing program is executed by the processor, the steps of the vehicle travel data processing method according to any one of claims 1 to 7 are implemented.

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