Vehicle trip information determination method, device and electronic equipment

Abstract

The application provides a vehicle travel information determination method, device and electronic equipment, the method comprising: obtaining at least two standard vehicle data of a target vehicle, the standard vehicle data being vehicle data uploaded by the target vehicle according to a data reporting standard protocol; determining at least one motion data set based on each standard vehicle data, the motion data set comprising corresponding data when the target vehicle is in a driving state; extracting at least one value corresponding to a target category in the motion data set, the target category comprising a data category related to travel information in the standard vehicle data; and determining travel information of the target vehicle based on the at least one value corresponding to the target category. Based on the value corresponding to the target category extracted from the motion data set, the vehicle travel information corresponding to the target category can be determined, and the generality of the vehicle travel information determination method can be improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, and electronic device for determining vehicle trip information. Background Technology

[0002] With the rapid development of data applications, users' demands for vehicle data applications are also increasing. For example, vehicle operating companies need to have real-time access to the trip information of each operating vehicle in order to implement practical applications such as transportation planning, transportation status dispatching, and vehicle maintenance planning. Therefore, it is necessary to determine various types of trip information for vehicles in a timely and accurate manner.

[0003] When using existing methods to determine vehicle trip information, the vehicle operation data collected or calculated at the vehicle's terminal is usually directly used as the trip information. Since the type of vehicle operation data collected or calculated at the vehicle's terminal is set by the vehicle manufacturer when the vehicle leaves the factory, the trip information determined by existing methods may not be the type of trip information expected by the user. In other words, the existing methods for determining vehicle trip information have low versatility and cannot be applied to different user needs. Summary of the Invention

[0004] This invention provides a method, apparatus, and electronic device for determining vehicle trip information, which addresses the shortcomings of existing methods for determining vehicle trip information due to their low versatility, thereby improving the versatility of the method and enabling the determined vehicle trip information to be applicable to different user needs.

[0005] This invention provides a method for determining vehicle trip information, comprising:

[0006] Obtain at least two standard vehicle data sets for the target vehicle, wherein the standard vehicle data sets are the vehicle data uploaded by the target vehicle in accordance with the data reporting standard protocol;

[0007] Based on the standard vehicle data, at least one set of motion data is determined, the set of motion data including data corresponding to when the target vehicle is in a driving state;

[0008] Extract at least one value corresponding to a target category from the motion data set, wherein the target category includes data categories related to trip information in the standard vehicle data;

[0009] The travel information of the target vehicle is determined based on at least one value corresponding to the target category.

[0010] According to a method for determining vehicle travel information provided by the present invention, determining at least one set of motion data based on the standard whole vehicle data includes:

[0011] Based on the aforementioned standard vehicle data, at least one motion data is determined, wherein the motion data is the standard vehicle data in which the vehicle speed is not zero and / or the latitude and longitude change in real time.

[0012] Motion data that are continuous in time and have a first time interval less than a first time threshold are grouped into the same data set to determine at least one motion data set, wherein the first time interval is the time interval between two adjacent motion data.

[0013] According to a method for determining vehicle travel information provided by the present invention, the step of dividing motion data that are continuous in time and whose time interval is less than a first time threshold into the same data set to determine at least one motion data set includes:

[0014] Based on the standard vehicle data, at least one stationary data is determined, wherein the stationary data is the standard vehicle data in which the vehicle speed is zero and / or the latitude and longitude remain unchanged in real time.

[0015] Each static data point that is continuous in time and has a second time interval less than a second time threshold is grouped into the same data set to determine at least one static data set, wherein the second time interval is the time interval between two adjacent static data points.

[0016] In the case where there is stationary data or stationary data set between two adjacent motion data sets, the stationary data or stationary data set with a third time interval less than a third time threshold is merged with the two adjacent motion data sets to obtain at least one merged data set, wherein the third time interval is the time interval between the stationary data or stationary data set and the two adjacent motion data sets.

[0017] Based on each of the merged data sets, at least one motion data set is determined.

[0018] According to a method for determining vehicle trip information provided by the present invention, the target category includes data collection time, cumulative mileage and vehicle speed, and the trip information includes trip duration, trip mileage and trip speed;

[0019] Extracting at least one value corresponding to the target category from the motion data set includes:

[0020] Extract the first data acquisition time value corresponding to the data acquisition time of the first motion data in the motion data set, the first cumulative mileage value corresponding to the cumulative mileage of the first motion data in the motion data set, the second data acquisition time value corresponding to the data acquisition time of the last motion data in the motion data set, the second cumulative mileage value corresponding to the cumulative mileage of the last motion data in the motion data set, and the first vehicle speed value corresponding to the vehicle speed of each motion data in the motion data set;

[0021] Determining the trip information of the target vehicle based on at least one value corresponding to the target category includes:

[0022] The travel time of the target vehicle is determined based on the first data acquisition time value and the second data acquisition time value; the travel mileage of the target vehicle is determined based on the first cumulative mileage value and the second cumulative mileage value; and the travel speed of the target vehicle is determined based on the first speed value corresponding to the speed of each of the motion data.

[0023] According to a method for determining vehicle trip information provided by the present invention, the target category includes data acquisition time, total current and total voltage, and the trip information includes trip energy consumption;

[0024] Extracting at least one value corresponding to the target category from the motion data set includes:

[0025] Extract the third data acquisition time value, the first total current value, and the first total voltage value corresponding to each motion data in the motion data set;

[0026] Determining the trip information of the target vehicle based on at least one value corresponding to the target category includes:

[0027] Based on the third data acquisition time values, the first travel duration value corresponding to the motion data set is determined, and the travel energy consumption of the target vehicle is determined by formula (1):

[0028]

[0029] Where E represents the travel energy consumption of the target vehicle, and S i_I1 S represents the first total current value corresponding to the i-th motion data in the motion data set. i_V1 Let t1 represent the first total voltage value corresponding to the i-th motion data in the motion data set, t1 represent the first travel duration value corresponding to the motion data set, and dt represent the integral over time.

[0030] According to a method for determining vehicle trip information provided by the present invention, the target category includes data acquisition time, total current and total voltage, and the trip information includes trip recovery energy;

[0031] Extracting at least one value corresponding to the target category from the motion data set includes:

[0032] Extract the fourth data acquisition time value, the second total current value, and the second total voltage value corresponding to each of the motion data in the motion data set;

[0033] Determining the trip information of the target vehicle based on at least one value corresponding to the target category includes:

[0034] Based on the fourth data acquisition time values, the second travel duration value corresponding to the motion data set is determined, and the travel recovery energy of the target vehicle is determined by formula (2):

[0035]

[0036] Where E_recovery represents the energy recovered during the trip of the target vehicle, S i_I2 S represents the second total current value corresponding to the i-th motion data in the motion data set. i_V2 t2 represents the second total voltage value corresponding to the i-th motion data in the motion data set, t2 represents the second travel duration value corresponding to the motion data set, and dt represents the integral over time.

[0037] According to a method for determining vehicle travel information provided by the present invention, the target category includes data acquisition time, vehicle speed, total current and total voltage, and the travel information includes travel idling energy consumption;

[0038] Extracting at least one value corresponding to the target category from the motion data set includes:

[0039] Extract the fifth data acquisition time value, the second vehicle speed value, the third total current value, and the third total voltage value corresponding to each of the motion data in the motion data set;

[0040] Determining the trip information of the target vehicle based on at least one value corresponding to the target category includes:

[0041] Based on the fifth data acquisition time values, the third travel duration value corresponding to the motion data set is determined, and the travel idling energy consumption of the target vehicle is determined by formula (3):

[0042]

[0043] Where E_idle represents the target vehicle's idle energy consumption, S i_I3 S represents the third total current value corresponding to the i-th motion data in the motion data set. i_V3 S represents the third total voltage value corresponding to the i-th motion data in the motion data set. i_speed2 t3 represents the second vehicle speed value corresponding to the i-th motion data in the motion data set, t3 represents the third travel duration value corresponding to the motion data set, and dt represents the integral over time.

[0044] According to a method for determining vehicle travel information provided by the present invention, determining at least one set of motion data based on the standard whole vehicle data includes:

[0045] Based on the standard vehicle data, remove the standard vehicle data with missing data and / or remove the standard vehicle data whose total voltage value is not within the preset voltage range to obtain the cleaned standard vehicle data.

[0046] Based on the standard vehicle data after each cleaning, at least one set of motion data is determined.

[0047] The present invention also provides a vehicle trip information determination device, comprising:

[0048] The acquisition module is used to acquire at least two standard vehicle data of the target vehicle, wherein the standard vehicle data is the vehicle data uploaded by the target vehicle in accordance with the data reporting standard protocol;

[0049] The determination module is used to determine at least one set of motion data based on the standard vehicle data, wherein the set of motion data includes data corresponding to when the target vehicle is in a driving state;

[0050] The extraction module is used to extract at least one value corresponding to a target category from the motion data set, wherein the target category includes data categories related to travel information in the standard vehicle data;

[0051] The determining module is further configured to determine the travel information of the target vehicle based on at least one value corresponding to the target category.

[0052] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the vehicle trip information determination method as described above.

[0053] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the vehicle trip information determination method as described above.

[0054] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the vehicle trip information determination method as described above.

[0055] The present invention provides a method, apparatus, and electronic device for determining vehicle trip information. The method involves acquiring at least two standard vehicle data sets for a target vehicle, where the standard vehicle data is the vehicle data uploaded by the target vehicle according to a data reporting standard protocol. Based on each standard vehicle data set, at least one motion data set is determined, including data corresponding to when the target vehicle is in motion. At least one value corresponding to a target category is extracted from the motion data set, where the target category includes data categories related to trip information in the standard vehicle data. Based on the at least one value corresponding to the target category, the trip information of the target vehicle is determined. Therefore, since the acquired standard vehicle data is the vehicle data uploaded by the target vehicle according to the data reporting standard protocol, data values ​​for all data categories specified in the standard protocol can be obtained, improving the comprehensiveness and universality of the acquired data. Furthermore, the determined motion data set includes data corresponding to when the target vehicle is in motion, which is the data set corresponding to the trip. The target category includes data categories related to trip information in the standard vehicle data. Based on the value corresponding to the target category extracted from the motion data set, vehicle trip information conforming to the type of vehicle trip information can be determined, improving the universality of the vehicle trip information determination method and meeting different user needs. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0057] Figure 1 This is a flowchart illustrating the method for determining vehicle trip information provided in an embodiment of the present invention;

[0058] Figure 2 This is a flowchart of the vehicle trip information determination method provided in an embodiment of the present invention;

[0059] Figure 3 This is a schematic diagram of the vehicle trip information determination device provided in an embodiment of the present invention;

[0060] Figure 4 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0062] It should be noted that the serial numbers assigned to the objects described in this invention, such as "first" and "second", are only used to distinguish the objects being described and do not have any sequential or technical meaning.

[0063] With the continuous development of the vehicle industry, users' demand for vehicle data information is constantly increasing, especially the need for timely and accurate acquisition of various types of vehicle trip information. Taking electric vehicles as an example, with the development of electric vehicles, in terms of determining vehicle trip information, electric vehicles still use the data calculation and statistical methods of fuel vehicles. After the vehicle's controller calculates the vehicle's operating data, it is transmitted to the vehicle's central control screen for display to show the trip information to the occupants. However, this method of determining vehicle trip information has low universality.

[0064] For example, when a vehicle leaves the factory, the manufacturer only sets it to display the real-time calculated current speed and current battery level as vehicle operating data to the user. The driver can obtain the vehicle's current speed and current battery level during the trip, but the operator of the vehicle cannot determine more types of vehicle trip information such as trip mileage, trip time, and trip energy consumption remotely. Therefore, the operator cannot manage the vehicle more deeply and cannot meet the user's needs.

[0065] To address the aforementioned problems, this invention provides a method for determining vehicle trip information. This method acquires at least two standard vehicle data sets for a target vehicle. These standard vehicle data sets are the vehicle data uploaded by the target vehicle according to a data reporting standard protocol. Since the acquired standard vehicle data is uploaded according to the standard protocol, data values ​​for all data categories specified in the standard protocol can be obtained, improving the comprehensiveness and versatility of the acquired data and providing a data foundation for determining various types of vehicle trip information. Furthermore, based on each standard vehicle data set, at least one motion data set is determined. This motion data set includes data corresponding to when the target vehicle is in motion; thus, the determined motion data set, including data corresponding to when the target vehicle is in motion, is the data set corresponding to the trip information. At least one value corresponding to a target category is extracted from the motion data set. The target category includes data categories related to trip information in the standard vehicle data. Based on the value corresponding to the target category extracted from the motion data set, vehicle trip information conforming to that type can be determined, improving the versatility of the vehicle trip information determination method and meeting different user needs.

[0066] The following is combined with Figure 1 and Figure 2 The method for determining vehicle trip information provided in the embodiments of the present invention will be described. Figure 1 This is a flowchart illustrating the vehicle trip information determination method provided in this embodiment of the invention. The method is applicable to various application scenarios involving the determination of vehicle trip information for multiple types of vehicles. For example, it can determine the trip information of electric vehicles such as small electric vehicles or electric heavy trucks, as well as the trip information of fuel vehicles and clean fuel vehicles capable of reporting standard vehicle data for each trip. It can also determine the trip information of other similar vehicles. The executing entity of this method can be an electronic device such as a tablet computer, mobile phone, computer, server, server cluster, or a specially designed vehicle trip information determination device. Alternatively, it can be a vehicle trip information determination device installed in such an electronic device, which can be implemented through software, hardware, or a combination of both. Figure 1 As shown, the method for determining vehicle trip information includes steps 110 to 140.

[0067] Step 110: Obtain at least two standard vehicle data sets for the target vehicle. The standard vehicle data sets are the vehicle data uploaded by the target vehicle in accordance with the data reporting standard protocol.

[0068] In this step, the target vehicle is the vehicle whose travel information needs to be determined. This vehicle can be, for example, a gasoline-powered car, an electric sedan, or an electric heavy-duty truck. Standard vehicle data refers to the vehicle data uploaded by the target vehicle according to the data reporting standard protocol. For example, standard vehicle data can be the vehicle data uploaded by the target vehicle according to the standard protocol of the national standard GB32960 for new energy vehicles.

[0069] For example, according to the national standard GB32960 for new energy, domestically produced electric vehicles need to collect data on the whole vehicle, drive motor, fuel cell, engine, vehicle location, extreme values, alarms, voltage data of rechargeable energy storage devices, and temperature data of rechargeable energy storage devices, and upload them to the national new energy monitoring platform to enable data transmission between various enterprise platforms.

[0070] For example, after real-time collection of vehicle data, the target vehicle packages this data into standard vehicle data. This standard vehicle data can then be transmitted to a vehicle networking platform via a communication network using an onboard telematics box (TBox), or transmitted to the vehicle manufacturer's server using the onboard TBox. By reading the standard vehicle data stored in the vehicle networking platform or server, at least two sets of standard vehicle data for the target vehicle can be obtained.

[0071] Step 120: Based on the standard vehicle data, determine at least one set of motion data, which includes data corresponding to when the target vehicle is in motion.

[0072] In this step, the motion dataset can be a collection of standard vehicle data corresponding to the same journey. A single journey can be understood as a complete trip undertaken by the target vehicle from the start to the end of its journey. A single motion dataset can represent a single journey and may include multiple standard vehicle data sets.

[0073] For example, when determining at least one set of motion data based on various standard vehicle data, one could sort the acquired standard vehicle data in chronological order to obtain ordered standard vehicle data. Based on this ordered standard vehicle data, data attributes could be partitioned. For instance, data attributes representing the target vehicle being in motion could be partitioned into motion points, and data attributes representing the target vehicle being in a prohibited state could be partitioned into stationary points. Data attribute partitioning can be performed using any method that determines whether the standard vehicle data corresponds to a target vehicle in a moving or stationary state.

[0074] Furthermore, time-continuous motion points can be divided into a motion data set; or time-quasi-continuous motion points can be divided into a motion data set, where quasi-continuous can be understood as the presence of one or fewer stationary points interspersed among multiple motion points. Alternatively, at least one motion data set can be determined based on standard vehicle data using other methods.

[0075] For example, when sorting the acquired standard vehicle data in chronological order, the sorting can be based on the data acquisition time of the standard vehicle data, where the data acquisition time can be understood as the timestamp or time tag of the standard vehicle data.

[0076] Step 130: Extract at least one value corresponding to the target category from the motion data set. The target category includes data categories related to travel information in the standard vehicle data.

[0077] In this step, the data category can be any data category specified in the data reporting standard protocol. For example, when the target vehicle uploads standard vehicle data according to the national standard GB32960 for new energy vehicles, it must upload data values ​​for all data categories specified in the standard protocol, including data collection time, vehicle speed, longitude, latitude, cumulative mileage, total voltage, total current, state of charge (SOC), vehicle status, charging status, and driving mode.

[0078] For example, target categories include data categories related to trip information in standard vehicle data. For instance, if the trip information is related to vehicle speed, the target category could include vehicle speed, etc.; if the trip information is related to trip energy consumption, the target category could include total voltage, total current, and SOC, etc.

[0079] For example, when extracting at least one value corresponding to a target category from a motion dataset, it can be based on the target category, extracting all values ​​corresponding to that target category in the motion dataset; or it can be based on the target category, extracting the values ​​of that target category corresponding to motion points in the motion dataset that meet predetermined conditions. These predetermined conditions can be, for example, conditions preset by an algorithm. For instance, when the trip information is trip mileage, if the predetermined condition preset by the algorithm is: extract the cumulative mileage values ​​corresponding to the start and end points of the trip, then based on this predetermined condition, the cumulative mileage values ​​corresponding to motion points in the motion dataset that meet the predetermined conditions are extracted. One or more predetermined conditions can be preset according to the algorithm, and this invention does not limit this.

[0080] Step 140: Determine the trip information of the target vehicle based on at least one value corresponding to the target category.

[0081] In this step, the travel information of the target vehicle can be determined by analyzing or calculating the values ​​corresponding to the target categories related to the travel information. For example, for travel information with different user needs, corresponding analysis algorithms or calculation models can be preset. The data of the values ​​corresponding to the target categories can be processed based on the preset analysis algorithms or calculation models to determine the travel information of the target vehicle.

[0082] For example, after determining the trip information of the target vehicle, the trip information of the target vehicle can be output on applications such as user systems or vehicle networking platforms.

[0083] The vehicle trip information determination method provided in this invention involves acquiring at least two standard vehicle data sets for a target vehicle. These standard vehicle data sets are the vehicle data uploaded by the target vehicle according to a data reporting standard protocol. Based on each standard vehicle data set, at least one motion data set is determined, including data corresponding to when the target vehicle is in motion. At least one value corresponding to a target category is extracted from the motion data set, where the target category includes data categories related to trip information in the standard vehicle data. Based on the at least one value corresponding to the target category, the trip information of the target vehicle is determined. Therefore, since the acquired standard vehicle data is the vehicle data uploaded by the target vehicle according to the data reporting standard protocol, data values ​​for all data categories specified in the standard protocol can be obtained, improving the comprehensiveness and universality of the acquired data. Furthermore, the determined motion data set includes data corresponding to when the target vehicle is in motion, which is the data set corresponding to the trip. The target category includes data categories related to trip information in the standard vehicle data. Based on the value corresponding to the target category extracted from the motion data set, vehicle trip information matching the type of vehicle trip information can be determined, improving the universality of the vehicle trip information determination method and meeting different user needs.

[0084] In practical applications, in order to improve the timeliness of determining at least one set of motion data, the non-zero vehicle speed and / or real-time changes in latitude and longitude can be used as the judgment conditions for classifying the data attributes of each standard vehicle data, which can achieve the goal of quickly and accurately determining the set of motion data.

[0085] In one embodiment, at least one set of motion data is determined based on various standard vehicle data, which can be achieved in the following way:

[0086] Based on the standard vehicle data, at least one motion data is determined. The motion data is the standard vehicle data in which the vehicle speed is not zero and / or the latitude and longitude change in real time. The motion data that are continuous in time and whose first time interval is less than the first time threshold are divided into the same data set to determine at least one motion data set. The first time interval is the time interval between two adjacent motion data.

[0087] Specifically, for the vehicle speed values ​​in each standard vehicle data set, it can be determined whether the corresponding vehicle speed is zero. A non-zero speed indicates that the target vehicle is in motion, and therefore, standard vehicle data with a non-zero speed can be identified as motion data, meaning that the standard vehicle data is a moving point.

[0088] For example, real-time changes in latitude and longitude can be understood as follows: in ordered standard vehicle data, when the latitude and longitude of two adjacent standard vehicle data are different, the latitude and longitude are changing in real time. In this case, both adjacent standard vehicle data can be motion data.

[0089] For example, when determining at least one motion data point based on various standard vehicle data sets, the determination can be made simultaneously based on two conditions: the vehicle speed is not zero and the latitude and longitude change in real time. For instance, one can first determine whether a standard vehicle data set is a candidate motion data point by checking whether the latitude and longitude of adjacent standard vehicle data sets change in real time within an ordered set of data. If the latitude and longitude change in real time, then it is a candidate motion data point. Based on the vehicle speed of each candidate motion data point, it is determined whether the speed is not zero. If the speed is not zero, then the candidate motion data point is considered a motion data point, meaning that the standard vehicle data set is a motion point. Latitude and longitude can be understood as an array composed of longitude and latitude.

[0090] For example, motion data that are continuous in time and whose first time interval is less than a first time threshold can be grouped into the same data set to determine at least one motion data set. The first time interval is the time interval between two adjacent motion data sets. The first time threshold can be any preset duration, such as 10 seconds, 3 minutes, or 10 minutes. It is understood that if the first time interval between two adjacent motion data sets is greater than or equal to the first time threshold, then the two adjacent motion data sets belong to two different data sets, i.e., they belong to two different journeys.

[0091] In this embodiment, based on standard vehicle data, at least one motion data point is determined. This motion data point consists of standard vehicle data where the vehicle speed is not zero and / or the latitude and longitude change in real time. Motion data points that are time-continuous and whose first time interval is less than a first time threshold are grouped into the same data set, thus determining at least one motion data set. The first time interval is the time interval between two adjacent motion data points. Based on this, the motion data set can be determined quickly and accurately, improving determination efficiency and thus enhancing the timeliness of determining vehicle travel information.

[0092] In practical applications, the target vehicle may experience brief periods of stillness during a journey, meaning it is not constantly in motion. For example, when a vehicle stops to avoid an obstacle or waits at a traffic light, a brief period of stillness occurs within the journey. Dividing the driving state before and after this brief stillness into two separate journeys could lead to an unreasonable journey division. To avoid this, the brief stillness and the two preceding and following journeys can be combined into a single journey, improving the applicability of the journey division scenario.

[0093] In one embodiment, motion data that are continuous in time and whose time interval is less than a first time threshold are grouped into the same data set to determine at least one motion data set. This can be achieved in the following way:

[0094] Based on standard vehicle data, at least one stationary data point is determined. Stationary data refers to standard vehicle data where the vehicle speed is zero and / or the latitude and longitude remain constant in real time. Stationary data points that are time-continuous and have a second time interval less than a second time threshold are grouped into the same data set to determine at least one stationary data set. The second time interval is the time interval between two adjacent stationary data points. If stationary data points or sets exist between two adjacent motion data sets, stationary data points or sets with a third time interval less than a third time threshold are merged with the two adjacent motion data sets to obtain at least one merged data set. The third time interval is the time interval between the stationary data points or sets and the two adjacent motion data sets. Based on each merged data set, at least one motion data set is determined.

[0095] Specifically, contrary to the method of judging motion data in the above embodiments, standard vehicle data with zero speed and / or unchanged latitude and longitude can be determined as stationary data. Zero speed indicates that the target vehicle is stationary, so standard vehicle data with zero speed can be determined as stationary data, i.e., this standard vehicle data is a stationary point. Unchanged latitude and longitude can be understood as follows: in the ordered standard vehicle data, when two adjacent standard vehicle data have the same latitude and longitude, then the latitude and longitude are unchanged in real time. In this case, both adjacent standard vehicle data can be considered stationary data. Stationary data can be determined by at least one of the two judgment conditions: zero speed and unchanged latitude and longitude. A stationary point can be, for example, standard vehicle data sent by the target vehicle at a non-charging stop point or a charging point.

[0096] For example, static data points that are continuous in time and whose second time interval is less than a second time threshold can be grouped into the same data set to determine at least one static data set. The second time interval is the time interval between two adjacent static data points. The second time threshold can be any preset duration, such as 10 seconds, 3 minutes, or 10 minutes. The second time threshold can be the same as the first time threshold, or they can be different.

[0097] For example, when there is stationary data or a set of stationary data between two adjacent sets of motion data, the stationary data or set of stationary data with a third time interval less than a third time threshold can be merged with the two adjacent sets of motion data to obtain at least one merged data set. The third time interval is the time interval between the stationary data or set of stationary data and the two adjacent sets of motion data. The third time threshold can be any preset duration, such as 10 seconds, 3 minutes, or 10 minutes. The third time threshold can be the same as the first time threshold and the second time threshold, or they can be different.

[0098] In this step, two adjacent motion data sets can be understood as the data sets corresponding to two consecutive journeys in which the target vehicle is briefly stationary. Here, "adjacent" can be understood as indirect adjacency, meaning that two motion data sets are interspersed with stationary points or sets of stationary data. These stationary sets are data sets containing multiple time-continuous stationary points, representing the target vehicle in a brief state of stationary motion. The stationary data or sets of stationary data with a third time interval less than a third time threshold are merged with the two adjacent motion data sets to obtain a merged data set. This merged data set can represent a journey that includes stationary points or sets of stationary points.

[0099] For example, at least one motion data set is determined based on each merged data set. For instance, each merged data set could be determined as a separate motion data set.

[0100] In this embodiment, by determining static data and static data sets, when static data or static data sets exist between two adjacent motion data sets, static data or static data sets with a third time interval less than a third time threshold are merged with the two adjacent motion data sets to obtain at least one merged data set. The third time interval is the time interval between the static data or static data set and the two adjacent motion data sets. Based on each merged data set, at least one motion data set is determined. Therefore, a small number of static points interspersed among multiple motion points can also be considered as data points within the same motion set, and the merged data set can be considered as a complete journey, thereby improving the scenario applicability of journey segmentation.

[0101] For example, when determining travel information for a merged dataset, the value corresponding to the target category of the static data or the static dataset can be used, or the value corresponding to the target category of the static data or the static dataset can be left unused. The decision to use the value corresponding to the target category of the static data or the static dataset can be based on a specific analysis algorithm or calculation model.

[0102] The following describes, through exemplary embodiments, how to determine the travel information of a target vehicle based on at least one value corresponding to the target category.

[0103] In one embodiment, the target category includes data collection time, cumulative mileage, and vehicle speed, and the trip information includes trip duration, trip mileage, and trip speed;

[0104] Extract at least one value corresponding to the target category in the motion dataset, specifically: extract the first data acquisition time value corresponding to the data acquisition time of the first motion data in the motion dataset, the first cumulative mileage value corresponding to the cumulative mileage of the first motion data in the motion dataset, the second data acquisition time value corresponding to the data acquisition time of the last motion data in the motion dataset, the second cumulative mileage value corresponding to the cumulative mileage of the last motion data in the motion dataset, and the first vehicle speed value corresponding to the vehicle speed of each motion data in the motion dataset;

[0105] Based on at least one value corresponding to the target category, the travel information of the target vehicle is determined, specifically: the travel duration of the target vehicle is determined based on the first data acquisition time value and the second data acquisition time value; the travel mileage of the target vehicle is determined based on the first cumulative mileage value and the second cumulative mileage value; and the travel speed of the target vehicle is determined based on the first vehicle speed value corresponding to the speed of each motion data.

[0106] Specifically, the data acquisition time can be the time when the target vehicle collects the corresponding standard vehicle data, or the time when the target vehicle sends the corresponding standard vehicle data. For example, each standard vehicle data sent by the target vehicle contains a timestamp corresponding to that standard vehicle data, and this timestamp is the data acquisition time. Accordingly, in the motion dataset, the specific value of the timestamp in each standard vehicle data is the data acquisition time value corresponding to the data acquisition time of the motion data.

[0107] For example, the set of motion data determined based on ordered standard vehicle data is also an ordered set of motion data. Therefore, the first motion data in the ordered set of motion data is the starting motion data of the corresponding journey, i.e., the starting point of the journey; correspondingly, the last motion data in the ordered set of motion data is the ending motion data of the corresponding journey. For example, by reading database data, the first data acquisition time value corresponding to the data acquisition time of the first motion data, the first cumulative mileage value corresponding to the cumulative mileage of the first motion data, the second data acquisition time value corresponding to the data acquisition time of the last motion data, the second cumulative mileage value corresponding to the cumulative mileage of the last motion data, and the first vehicle speed value corresponding to the vehicle speed of each motion data in the set can be extracted.

[0108] For example, suppose the extracted motion data set can be represented by X = [x1, x2, ..., xm], where xi represents the i-th motion data point, i.e., the i-th motion point; m represents the number of motion data points in the motion set. At least one value corresponding to the target category can form a data set S, S = [s1, s2, ..., sn], where si represents the value corresponding to the target category of motion point xi, and n represents the number of values ​​in the motion data set. For example, when the target category is vehicle speed, S = [s1, s2, ..., sn], where s1 represents the first vehicle speed value of the first motion data point in the motion data set, s2 represents the first vehicle speed value of the second motion data point in the motion data set, and so on.

[0109] For example, the travel time of the target vehicle can be determined based on the first data acquisition time value and the second data acquisition time value, for example, by the following formula (4):

[0110] T = S m_time -S 1_time (4)

[0111] Where T represents the travel time of the target vehicle, and S m_timeThis represents the value at the data acquisition time of the last motion data point in the motion dataset, i.e., the value at the second data acquisition time; S 1_time This represents the data acquisition time of the first motion data point in the motion dataset, i.e., the first data acquisition time value. The travel time of the target vehicle can then be obtained by subtracting the first data acquisition time value from the second data acquisition time value.

[0112] For example, the travel mileage of the target vehicle can be determined based on the first cumulative mileage value and the second cumulative mileage value, for example, by the following formula (5):

[0113] MILE=S m_mile -S 1_mile (5)

[0114] Where MILE represents the target vehicle's travel mileage, S m_mile This represents the cumulative mileage value of the last motion data point in the motion dataset, i.e., the second cumulative mileage value; S 1_mile This represents the cumulative mileage value of the first motion data point in the motion dataset, i.e., the first cumulative mileage value. The target vehicle's journey distance can then be the length value obtained by subtracting the first cumulative mileage value from the second cumulative mileage value.

[0115] For example, the travel speed of the target vehicle can be determined based on the first vehicle speed value corresponding to the vehicle speed of each motion data, for example, by the following formula (6):

[0116]

[0117] in, S represents the average speed of the target vehicle during its journey, i.e., the average speed of the vehicle during the journey. i_speed1 Let represent the first vehicle speed value of the i-th motion data point in the motion dataset; m represents the number of motion data points in the motion dataset. Then, by calculating the average of the first vehicle speed values ​​of the m motion data points in the motion dataset, this average value can be determined as the travel speed of the target vehicle.

[0118] Alternatively, the maximum value of the first vehicle speed of the m motion data in the motion dataset can be determined as the maximum travel speed of the target vehicle, denoted as Vmax.

[0119] In this embodiment, at least one value corresponding to the target category is extracted from the motion data set. This at least one value includes a first data acquisition time value, a first cumulative mileage value, a second data acquisition time value, a second cumulative mileage value, and a first vehicle speed value corresponding to the speed of each motion data point in the motion data set. Based on the first and second data acquisition time values, the travel time of the target vehicle can be determined; based on the first and second cumulative mileage values, the travel mileage of the target vehicle can be determined; and based on the first vehicle speed value corresponding to the speed of each motion data point, the travel speed of the target vehicle can be determined. Therefore, the travel information of the target vehicle can be quickly determined, improving the timeliness of travel information determination and meeting user needs for rapid output of travel information.

[0120] In one embodiment, the target categories include data acquisition time, total current, and total voltage, and the travel information includes travel energy consumption;

[0121] Extract at least one value corresponding to the target category from the motion dataset, specifically: extract the third data acquisition time value, the first total current value, and the first total voltage value corresponding to each motion data in the motion dataset;

[0122] Based on at least one value corresponding to the target category, the travel information of the target vehicle is determined, specifically: the first travel duration value corresponding to the motion data set is determined based on the values ​​of each third data collection time, and the travel energy consumption of the target vehicle is determined by formula (1):

[0123]

[0124] Where E represents the target vehicle's travel energy consumption, S i_I1 S represents the first total current value corresponding to the i-th motion data in the motion data set. i_V1 Let t1 represent the first total voltage value corresponding to the i-th motion data in the motion data set, t1 represent the first travel duration value corresponding to the motion data set, and dt represent the integral over time.

[0125] Specifically, the third data acquisition time value is the value of the data acquisition time corresponding to each motion data in the motion data set. The first travel duration value can be the travel duration T of the target vehicle, for example, it can be determined by the above formula (4).

[0126] After determining the first travel duration, the first total current value corresponding to each motion data, and the first total current value corresponding to each motion data, the travel energy consumption of the target vehicle can be determined using the above formula (1). This travel energy consumption represents the total electrical energy consumed by the target vehicle during the travel.

[0127] In this embodiment, after determining the first travel duration value corresponding to the motion data set based on the third data acquisition time value, the travel energy consumption of the target vehicle can be determined by formula (1), thereby achieving the purpose of quickly and accurately determining the vehicle travel information.

[0128] In one embodiment, the target category includes data acquisition time, total current, and total voltage, and the travel information includes travel-recovered energy;

[0129] Extract at least one value corresponding to the target category from the motion dataset, specifically: extract the fourth data acquisition time value, the second total current value, and the second total voltage value corresponding to each motion data in the motion dataset;

[0130] Based on at least one value corresponding to the target category, the travel information of the target vehicle is determined, specifically: the second travel duration value corresponding to the motion data set is determined based on the values ​​of each fourth data acquisition time, and the travel recovery energy of the target vehicle is determined through formula (2):

[0131]

[0132] Where E_recovery represents the energy recovered during the target vehicle's journey, S i_I2 S represents the second total current value corresponding to the i-th motion data in the motion data set. i_V2 t2 represents the second total voltage value corresponding to the i-th motion data in the motion data set, t2 represents the second travel duration value corresponding to the motion data set, and dt represents the integral over time.

[0133] Specifically, the fourth data acquisition time value is the value of the data acquisition time corresponding to each motion data in the motion data set. The second travel duration value can be the travel duration T of the target vehicle, for example, it can be determined by the above formula (4).

[0134] As shown in formula (2) above, when the second total current value of the i-th motion data is greater than or equal to 0, the recovered energy is 0 and is not included in the stroke recovery energy; when the second total current value of the i-th motion data is less than 0, the calculated value is included in the stroke recovery energy.

[0135] After determining the second travel duration, the second total current value corresponding to each motion data point, and the second total current value corresponding to each motion data point, the recovered energy of the target vehicle can be determined using the above formula (2). This recovered energy represents the total amount of electrical energy recovered by the battery of the target vehicle during this travel.

[0136] In this embodiment, after determining the second travel duration value corresponding to the motion data set based on each fourth data acquisition time value, the travel recovery energy of the target vehicle can be determined by formula (2), thereby achieving the purpose of quickly and accurately determining the vehicle travel information.

[0137] In one embodiment, the target categories include data acquisition time, total current, and total voltage, and the travel information includes travel idling energy consumption;

[0138] Extract at least one value corresponding to the target category from the motion data set, specifically: extract the fifth data acquisition time value, the second vehicle speed value, the third total current value, and the third total voltage value corresponding to each motion data in the motion data set;

[0139] Based on at least one value corresponding to the target category, the travel information of the target vehicle is determined, specifically: the third travel duration value corresponding to the motion data set is determined based on the fifth data collection time value, and the travel idling energy consumption of the target vehicle is determined by formula (3):

[0140]

[0141] Where E_idle represents the target vehicle's idle energy consumption, S i_I3 S represents the third total current value corresponding to the i-th motion data in the motion data set. i_V3 S represents the third total voltage value corresponding to the i-th motion data in the motion data set. i_speed2 t3 represents the second vehicle speed value corresponding to the i-th motion data in the motion dataset, t3 represents the third travel duration value corresponding to the motion dataset, and dt represents the integral over time.

[0142] Specifically, the fifth data acquisition time value is the value of the data acquisition time corresponding to each motion data in the motion data set. The third travel duration value can be the travel duration T of the target vehicle, for example, it can be determined by the above formula (4).

[0143] As shown in formula (3) above, when the second speed value of the i-th motion data is equal to 0, the idling energy consumption of the target vehicle is calculated; when the second speed value of the i-th motion data is greater than 0, the idling energy consumption is 0 and is not included in the idling energy consumption of the target vehicle.

[0144] After determining the third stroke duration, the third total current value corresponding to each motion data, and the third total current value corresponding to each motion data, the idle energy consumption of the target vehicle can be determined using the above formula (3). This idle energy consumption represents the idle energy consumption of the target vehicle during this stroke.

[0145] In this embodiment, after determining the third travel duration value corresponding to the motion data set based on the fifth data acquisition time value, the travel idling energy consumption of the target vehicle can be determined by formula (3), thereby achieving the purpose of quickly and accurately determining the vehicle travel information.

[0146] In practical applications, the standard vehicle data transmitted in real time by electric heavy-duty trucks or other types of vehicles includes data such as data acquisition time, charging status, vehicle speed, cumulative mileage, total voltage, and total current. During data acquisition, outliers and missing values ​​are inevitable. To prevent these erroneous data from affecting the final determination of trip information, data cleaning is necessary.

[0147] In one embodiment, at least one set of motion data is determined based on each standard vehicle data set. This can be achieved by: removing standard vehicle data sets with missing data from each standard vehicle data set, and / or removing standard vehicle data sets whose total voltage value is not within a preset voltage range from each standard vehicle data set, to obtain cleaned standard vehicle data sets; and determining at least one set of motion data sets based on each cleaned standard vehicle data set.

[0148] For example, when a standard vehicle dataset contains missing data, i.e., when there are missing sampling points, the standard vehicle dataset can be discarded. This means removing the standard vehicle datasets with missing data. These missing values ​​have minimal impact on trip information determination, data analysis, and battery fault diagnosis, and can be directly deleted. This avoids the influence of defective standard vehicle datasets on trip information determination, thereby improving the accuracy of the determined trip information.

[0149] For example, the preset voltage range can be a preset battery voltage range value. For instance, the preset voltage range for an electric heavy truck is V1-V2, where V1 is a voltage value less than V2. If the total voltage value in the standard vehicle data is not within this preset voltage range, it may be due to a problem caused by sensor acquisition or other reasons. In this case, the standard vehicle data can be discarded, that is, the standard vehicle data whose total voltage value is not within the preset voltage range can be removed. Based on this, the cleaned standard vehicle data can be obtained; based on each cleaned standard vehicle data set, at least one set of motion data can be determined.

[0150] In this embodiment, data cleaning is performed on the standard vehicle data to improve the reliability of the basic data, thereby improving the accuracy of the trip information of the determined target vehicle.

[0151] Below, in conjunction with Figure 2 The exemplary embodiments provided by the present invention will be further described below. Figure 2This is a flowchart of a vehicle trip information determination method provided in this embodiment of the invention. To accurately determine vehicle trip information, the data categories that can be selected in this embodiment include, but are not limited to, data collection time, vehicle speed, longitude, latitude, cumulative mileage, total voltage, total current, SOC, vehicle status, charging status, and motion mode. The standard vehicle data collection cycle can be once every T time intervals. When determining trip information, data acquisition and analysis can be performed on standard vehicle data compliant with national standard GB32960 uploaded from the vehicle terminal to achieve vehicle trip segmentation and trip information determination on the platform. For example, this includes analyzing and determining the time period, mileage, energy consumption, charging power, speed, and trajectory of segmented trips.

[0152] like Figure 2 As shown, after the process begins, standard vehicle data uploaded by the vehicle can be obtained via network communication. This data can be cleaned to filter out errors or inaccuracies. Further, moving and stationary points are identified, and the journey is divided based on these points. The journey information is then calculated and determined using algorithms or formulas. The journey information and related data can then be written to a database, including, for example, the target vehicle's VIN, date, journey start time, journey end time, journey duration, journey energy consumption, driving time, driving energy consumption, journey start longitude, journey start latitude, journey end longitude, journey end latitude, journey start SOC, journey end SOC, journey feedback battery level, and maximum journey speed. Afterward, the journey information can be applied, such as displaying journey data and journey trajectory, enabling journey viewing and analysis on the platform. The journey trajectory display can include, for example, a playback of the journey trajectory or loading the location from the start point to the end point of the journey into map software and displaying it sequentially.

[0153] For example, vehicle operating companies can require vehicle manufacturers to forward platform data according to national standards. The method of this invention can then be used to determine vehicle trip information, enabling data analysis and application. Since each OEM uses a unified national standard protocol to report data, the method of this invention can be used simply by accessing standard vehicle data, making it easy to use and highly applicable to various scenarios. Secondly, the method of this invention can determine trip information on computers, servers, or other platforms, without being limited by the vehicle's hardware computing capabilities, offering the advantage of convenient application. Furthermore, when algorithm optimization or changes in requirements occur, the algorithm can be adjusted promptly on the platform, with minimal adjustment difficulty and low operating costs, resulting in economic advantages.

[0154] The vehicle trip information determination device provided in the embodiments of the present invention is described below. The vehicle trip information determination device described below can be referred to in correspondence with the vehicle trip information determination method described above.

[0155] Figure 3 This is a schematic diagram of the vehicle trip information determination device provided in an embodiment of the present invention, with reference to... Figure 3 As shown, the vehicle trip information determination device 300 includes:

[0156] The acquisition module 310 is used to acquire at least two standard vehicle data of the target vehicle. The standard vehicle data is the vehicle data uploaded by the target vehicle in accordance with the data reporting standard protocol.

[0157] The determination module 320 is used to determine at least one motion data set based on various standard vehicle data. The motion data set includes data corresponding to when the target vehicle is in a driving state.

[0158] Extraction module 330 is used to extract at least one value corresponding to a target category from the motion data set, wherein the target category includes data categories related to travel information in the standard vehicle data;

[0159] The determination module 320 is also used to determine the travel information of the target vehicle based on at least one value corresponding to the target category.

[0160] In one example embodiment, the determining module 320 is specifically used for:

[0161] Based on the standard vehicle data, at least one motion data is determined. The motion data is the standard vehicle data in which the vehicle speed is not zero and / or the latitude and longitude changes in real time.

[0162] Motion data that are continuous in time and whose first time interval is less than a first time threshold are grouped into the same data set to determine at least one motion data set. The first time interval is the time interval between two adjacent motion data.

[0163] In one example embodiment, the determining module 320 is specifically used for:

[0164] Based on the standard vehicle data, at least one stationary data point is determined. The stationary data point is the standard vehicle data where the vehicle speed is zero and / or the latitude and longitude remain unchanged in real time.

[0165] Each static data point that is continuous in time and has a second time interval less than a second time threshold is grouped into the same data set to determine at least one static data set. The second time interval is the time interval between two adjacent static data points.

[0166] In the case where there is stationary data or a set of stationary data between two adjacent sets of motion data, the stationary data or set of stationary data with a third time interval less than a third time threshold is merged with the two adjacent sets of motion data to obtain at least one merged data set. The third time interval is the time interval between the stationary data or set of stationary data and the two adjacent sets of motion data.

[0167] Based on each merged data set, at least one motion data set is determined.

[0168] In one example embodiment, the target category includes data collection time, cumulative mileage, and vehicle speed, and the trip information includes trip duration, trip mileage, and trip speed;

[0169] The extraction module 330 is specifically used to extract the first data acquisition time value corresponding to the data acquisition time of the first motion data in the motion data set, the first cumulative mileage value corresponding to the cumulative mileage of the first motion data in the motion data set, the second data acquisition time value corresponding to the data acquisition time of the last motion data in the motion data set, the second cumulative mileage value corresponding to the cumulative mileage of the last motion data in the motion data set, and the first vehicle speed value corresponding to the vehicle speed of each motion data in the motion data set.

[0170] The determination module 320 is specifically used to determine the travel time of the target vehicle based on the first data acquisition time value and the second data acquisition time value, determine the travel mileage of the target vehicle based on the first cumulative mileage value and the second cumulative mileage value, and determine the travel speed of the target vehicle based on the first vehicle speed value corresponding to the speed of each motion data.

[0171] In one example embodiment, the target categories include data acquisition time, total current, and total voltage, and the travel information includes travel energy consumption;

[0172] The extraction module 330 is specifically used to extract the third data acquisition time value, the first total current value, and the first total voltage value corresponding to each motion data in the motion data set.

[0173] The determination module 320 is specifically used to determine the first travel duration value corresponding to the motion data set based on the time values ​​of each third data acquisition, and to determine the travel energy consumption of the target vehicle through formula (1):

[0174]

[0175] Where E represents the target vehicle's travel energy consumption, S i_I1 S represents the first total current value corresponding to the i-th motion data in the motion data set. i_V1Let t1 represent the first total voltage value corresponding to the i-th motion data in the motion data set, t1 represent the first travel duration value corresponding to the motion data set, and dt represent the integral over time.

[0176] In one example embodiment, the target categories include data acquisition time, total current, and total voltage, and the travel information includes travel-recovered energy.

[0177] The extraction module 330 is specifically used to extract the fourth data acquisition time value, the second total current value, and the second total voltage value corresponding to each motion data in the motion data set.

[0178] The determination module 320 is specifically used to determine the second travel duration value corresponding to the motion data set based on the values ​​of each fourth data acquisition time, and to determine the travel recovery energy of the target vehicle through formula (2):

[0179]

[0180] Where E_recovery represents the energy recovered during the target vehicle's journey, S i_I2 S represents the second total current value corresponding to the i-th motion data in the motion data set. i_V2 t2 represents the second total voltage value corresponding to the i-th motion data in the motion data set, t2 represents the second travel duration value corresponding to the motion data set, and dt represents the integral over time.

[0181] In one example embodiment, the target categories include data acquisition time, total current, and total voltage, and the travel information includes travel idling energy consumption;

[0182] The extraction module 330 is specifically used to extract the fifth data acquisition time value, the second vehicle speed value, the third total current value, and the third total voltage value corresponding to each motion data in the motion data set.

[0183] The determination module 320 is specifically used to determine the third travel duration value corresponding to the motion data set based on the fifth data acquisition time value, and to determine the travel idling energy consumption of the target vehicle through formula (3):

[0184]

[0185] Where E_idle represents the target vehicle's idle energy consumption, S i_I3 S represents the third total current value corresponding to the i-th motion data in the motion data set. i_V3 S represents the third total voltage value corresponding to the i-th motion data in the motion data set. i_speed2 t3 represents the second vehicle speed value corresponding to the i-th motion data in the motion dataset, t3 represents the third travel duration value corresponding to the motion dataset, and dt represents the integral over time.

[0186] In one example embodiment, the determining module 320 is specifically used for:

[0187] Based on the standard vehicle data, remove the standard vehicle data with missing data, and / or remove the standard vehicle data whose total voltage value is not within the preset voltage range, to obtain the cleaned standard vehicle data.

[0188] Based on the standard vehicle data after each cleaning, at least one set of motion data is determined.

[0189] The apparatus of this embodiment can be used to execute the method of any embodiment in the side embodiment of the vehicle trip information determination method. Its specific implementation process and technical effects are similar to those in the side embodiment of the vehicle trip information determination method. For details, please refer to the detailed description in the side embodiment of the vehicle trip information determination method, which will not be repeated here.

[0190] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present invention, such as... Figure 4 As shown, the electronic device may include a processor 410, a communications interface 420, a memory 430, and a communication bus 440, wherein the processor 410, communications interface 420, and memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute a vehicle trip information determination method. This method includes: acquiring at least two standard vehicle data sets of the target vehicle, wherein the standard vehicle data sets are the vehicle data uploaded by the target vehicle according to a data reporting standard protocol; determining at least one motion data set based on each standard vehicle data set, wherein the motion data set includes data corresponding to when the target vehicle is in a driving state; extracting at least one value corresponding to a target category from the motion data set, wherein the target category includes data categories related to trip information in the standard vehicle data; and determining the trip information of the target vehicle based on the at least one value corresponding to the target category.

[0191] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0192] On the other hand, embodiments of the present invention also provide a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements a method for determining vehicle travel information provided by the methods described above. The method includes: acquiring at least two standard vehicle data sets of a target vehicle, wherein the standard vehicle data sets are vehicle data uploaded by the target vehicle according to a data reporting standard protocol; determining at least one motion data set based on each standard vehicle data set, wherein the motion data set includes data corresponding to when the target vehicle is in a driving state; extracting at least one value corresponding to a target category from the motion data set, wherein the target category includes data categories related to travel information in the standard vehicle data sets; and determining the travel information of the target vehicle based on at least one value corresponding to the target category.

[0193] On the other hand, embodiments of the present invention also provide a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the vehicle trip information determination method provided by the above methods. The method includes: acquiring at least two standard vehicle data sets of a target vehicle, wherein the standard vehicle data sets are vehicle data uploaded by the target vehicle according to a data reporting standard protocol; determining at least one motion data set based on each standard vehicle data set, wherein the motion data set includes data corresponding to when the target vehicle is in a driving state; extracting at least one value corresponding to a target category from the motion data set, wherein the target category includes data categories related to trip information in the standard vehicle data; and determining the trip information of the target vehicle based on at least one value corresponding to the target category.

[0194] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0195] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0196] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining vehicle trip information, characterized in that, include: Obtain at least two standard vehicle data sets for the target vehicle, wherein the standard vehicle data sets are the vehicle data uploaded by the target vehicle in accordance with the data reporting standard protocol; Based on the standard vehicle data, at least one motion data set is determined, the motion data set including data corresponding to when the target vehicle is in a driving state; Extract at least one value corresponding to a target category from the motion data set, wherein the target category includes data categories related to trip information in the standard vehicle data; Based on at least one value corresponding to the target category, determine the trip information of the target vehicle; The determination of at least one set of motion data based on the standard vehicle data includes: Based on the aforementioned standard vehicle data, at least one motion data is determined, wherein the motion data is the standard vehicle data in which the vehicle speed is not zero and / or the latitude and longitude change in real time. Motion data that are continuous in time and whose first time interval is less than a first time threshold are grouped into the same data set to determine at least one motion data set, wherein the first time interval is the time interval between two adjacent motion data sets. Based on the standard vehicle data, at least one stationary data is determined, wherein the stationary data is the standard vehicle data in which the vehicle speed is zero and / or the latitude and longitude remain unchanged in real time. Each static data point that is continuous in time and has a second time interval less than a second time threshold is grouped into the same data set to determine at least one static data set, wherein the second time interval is the time interval between two adjacent static data points. In the case where there is stationary data or stationary data set between two adjacent motion data sets, the stationary data or stationary data set with a third time interval less than a third time threshold is merged with the two adjacent motion data sets to obtain at least one merged data set, wherein the third time interval is the time interval between the stationary data or stationary data set and the two adjacent motion data sets. Based on each of the merged data sets, at least one motion data set is determined.

2. The method for determining vehicle trip information according to claim 1, characterized in that, The target categories include data collection time, cumulative mileage, and vehicle speed; the trip information includes trip duration, trip mileage, and trip speed. Extracting at least one value corresponding to the target category from the motion data set includes: Extract the first data acquisition time value corresponding to the data acquisition time of the first motion data in the motion data set, the first cumulative mileage value corresponding to the cumulative mileage of the first motion data in the motion data set, the second data acquisition time value corresponding to the data acquisition time of the last motion data in the motion data set, the second cumulative mileage value corresponding to the cumulative mileage of the last motion data in the motion data set, and the first vehicle speed value corresponding to the vehicle speed of each motion data in the motion data set; Determining the trip information of the target vehicle based on at least one value corresponding to the target category includes: The travel time of the target vehicle is determined based on the first data acquisition time value and the second data acquisition time value; the travel mileage of the target vehicle is determined based on the first cumulative mileage value and the second cumulative mileage value; and the travel speed of the target vehicle is determined based on the first speed value corresponding to the speed of each of the motion data.

3. The method for determining vehicle trip information according to claim 1, characterized in that, The target category includes data acquisition time, total current, and total voltage; the travel information includes travel energy consumption. Extracting at least one value corresponding to the target category from the motion data set includes: Extract the third data acquisition time value, the first total current value, and the first total voltage value corresponding to each motion data in the motion data set; Determining the trip information of the target vehicle based on at least one value corresponding to the target category includes: Based on the third data acquisition time values, the first travel duration value corresponding to the motion data set is determined, and the travel energy consumption of the target vehicle is determined by formula (1): （1） in, This indicates the travel energy consumption of the target vehicle. This represents the first total current value corresponding to the i-th motion data in the motion data set. t1 represents the first total voltage value corresponding to the i-th motion data point in the motion data set, and t1 represents the first travel duration value corresponding to the motion data set. It represents the integral over time.

4. The method for determining vehicle trip information according to claim 1, characterized in that, The target category includes data acquisition time, total current, and total voltage; the travel information includes travel energy recovery. Extracting at least one value corresponding to the target category from the motion data set includes: Extract the fourth data acquisition time value, the second total current value, and the second total voltage value corresponding to each of the motion data in the motion data set; Determining the trip information of the target vehicle based on at least one value corresponding to the target category includes: Based on the fourth data acquisition time values, the second travel duration value corresponding to the motion data set is determined, and the travel recovery energy of the target vehicle is determined by formula (2): （2） in, This indicates the energy recovered during the trip of the target vehicle. This represents the second total current value corresponding to the i-th motion data in the motion data set. t1 represents the second total voltage value corresponding to the i-th motion data point in the motion data set, and t2 represents the second travel duration value corresponding to the motion data set. It represents the integral over time.

5. The method for determining vehicle trip information according to claim 1, characterized in that, The target categories include data acquisition time, vehicle speed, total current, and total voltage; the trip information includes trip idling energy consumption. Extracting at least one value corresponding to the target category from the motion data set includes: Extract the fifth data acquisition time value, the second vehicle speed value, the third total current value, and the third total voltage value corresponding to each of the motion data in the motion data set; Determining the trip information of the target vehicle based on at least one value corresponding to the target category includes: Based on the fifth data acquisition time values, the third travel duration value corresponding to the motion data set is determined, and the travel idling energy consumption of the target vehicle is determined by formula (3): （3） in, This indicates the target vehicle's idle energy consumption. This represents the third total current value corresponding to the i-th motion data in the motion data set. This represents the third total voltage value corresponding to the i-th motion data in the motion data set. t3 represents the second vehicle speed value corresponding to the i-th motion data point in the motion data set, and t3 represents the third travel duration value corresponding to the motion data set. It represents the integral over time.

6. The method for determining vehicle trip information according to any one of claims 1-5, characterized in that, The determination of at least one set of motion data based on the standard vehicle data includes: Based on the standard vehicle data, remove the standard vehicle data with missing data and / or remove the standard vehicle data whose total voltage value is not within the preset voltage range to obtain the cleaned standard vehicle data. Based on the standard vehicle data after each cleaning, at least one set of motion data is determined.

7. A vehicle trip information determination device, characterized in that, include: The acquisition module is used to acquire at least two standard vehicle data of the target vehicle, wherein the standard vehicle data is the vehicle data uploaded by the target vehicle in accordance with the data reporting standard protocol; The determination module is used to determine at least one set of motion data based on the standard vehicle data, wherein the set of motion data includes data corresponding to when the target vehicle is in a driving state; The extraction module is used to extract at least one value corresponding to a target category from the motion data set, wherein the target category includes data categories related to travel information in the standard vehicle data; The determining module is further configured to determine the travel information of the target vehicle based on at least one value corresponding to the target category; The determining module is specifically used for: Based on the aforementioned standard vehicle data, at least one motion data is determined, wherein the motion data is the standard vehicle data in which the vehicle speed is not zero and / or the latitude and longitude change in real time. Motion data that are continuous in time and have a first time interval less than a first time threshold are grouped into the same data set to determine at least one motion data set, wherein the first time interval is the time interval between two adjacent motion data sets; Based on the standard vehicle data, at least one stationary data is determined, wherein the stationary data is the standard vehicle data in which the vehicle speed is zero and / or the latitude and longitude remain unchanged in real time. Each piece of static data that is continuous in time and whose second time interval is less than the second time threshold is divided into the same data set to determine at least one static data set, wherein the second time interval is the time interval between two adjacent pieces of static data; In the case where there is stationary data or stationary data set between two adjacent motion data sets, the stationary data or stationary data set with a third time interval less than a third time threshold is merged with the two adjacent motion data sets to obtain at least one merged data set, wherein the third time interval is the time interval between the stationary data or stationary data set and the two adjacent motion data sets. Based on each of the merged data sets, at least one motion data set is determined.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the vehicle trip information determination method as described in any one of claims 1 to 6.

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