Vehicle operating condition analysis method and device, computer equipment, medium and product

Abstract

The application relates to a vehicle operation condition analysis method and device, computer equipment, a storage medium and a computer program product. According to preset vehicle load dimensions and road condition dimensions, a plurality of driving conditions are determined, and operation data corresponding to each driving condition is determined from a target operation data set. Data analysis is performed on at least one of baseline data corresponding to each driving condition and performance data of a single vehicle under each driving condition, and a vehicle operation condition analysis result is obtained. Each driving condition of the vehicle can be evaluated respectively, so that accurate vehicle operation condition analysis results can be obtained based on baseline indexes under each driving condition.

Description

Technical Field

[0001] This application relates to the field of vehicle analysis technology, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for analyzing vehicle operating conditions. Background Technology

[0002] Vehicle condition analysis based on Internet of Vehicles big data often follows a predetermined indicator analysis logic, statistically analyzing actual operating conditions. This requires selecting representative routes and obtaining road traffic data to analyze vehicle operating conditions and obtain parameters describing those conditions.

[0003] However, this method can only provide an overall assessment of vehicle operating conditions, and cannot break down the conditions into smaller segments. Consequently, it is impossible to determine the specific performance of each operating condition indicator, leading to errors in the analysis of vehicle operating conditions. Summary of the Invention

[0004] Therefore, it is necessary to provide a vehicle operating condition analysis method, device, computer equipment, computer-readable storage medium, and computer program product that can accurately analyze vehicle operating conditions in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for analyzing vehicle operating conditions, the method comprising:

[0006] Acquire a target operational data set of multiple specified vehicles from the vehicle network data;

[0007] Based on the preset vehicle load and road condition dimensions, multiple driving conditions are determined, and the corresponding driving data for each driving condition is determined from the target driving data set.

[0008] Based on the operating data corresponding to each driving condition, the baseline data corresponding to each driving condition is determined; the baseline data consists of sub-baseline data under various driving condition indicators.

[0009] Based on the operating data of a single vehicle under each driving condition, the performance data of the single vehicle under each driving condition is determined; the performance data consists of sub-performance data under multiple driving condition indicators.

[0010] Based on at least one of the baseline data corresponding to each driving condition, or the performance data of a single vehicle under each driving condition, data analysis is performed to obtain the vehicle operating condition analysis results.

[0011] In one embodiment, the step of acquiring a target operational data set of multiple designated vehicles from the vehicle network data includes:

[0012] Acquire vehicle network data;

[0013] Obtain target attribute information and target time period; target attribute information is used to identify the specified vehicle.

[0014] Based on the target attribute information and the target time period, filter out the set of operating data of a specified vehicle within the target time period from the vehicle network data;

[0015] Perform data cleaning operations on the running dataset to obtain the target running dataset.

[0016] In one embodiment, the step of determining multiple driving conditions based on preset vehicle load and road condition dimensions includes:

[0017] Determine the various load categories within the vehicle load dimension;

[0018] Identify various road types and slope types within the road condition dimension;

[0019] By arranging and combining load categories, road types, and gradient types, various driving conditions can be obtained.

[0020] In one embodiment, the step of performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain the vehicle operating condition analysis result includes:

[0021] Based on the operating data of a single vehicle under each driving condition, determine the proportion of each driving condition for a single vehicle.

[0022] Based on the proportion of each driving condition and the baseline data corresponding to each driving condition, the target baseline data of a single vehicle under the target driving condition is calculated; the target driving condition is the combination of driving conditions corresponding to a single vehicle within the target time period.

[0023] Data analysis is performed based on the target baseline data to obtain the vehicle operating condition analysis results.

[0024] In one embodiment, the vehicle operating condition analysis result includes aggregated comparative analysis results; the step of performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain the vehicle operating condition analysis result includes:

[0025] Acquire performance data of multiple vehicles under various driving conditions;

[0026] Based on the baseline data corresponding to each driving condition and the performance data of multiple vehicles under each driving condition, the data are aggregated and compared to obtain the aggregated comparison analysis results.

[0027] In one embodiment, the vehicle operating condition analysis results include classification and comparison analysis results; the step of performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain the vehicle operating condition analysis results includes:

[0028] Determine the first vehicle set and the second vehicle set;

[0029] Based on the performance data of a single vehicle under various driving conditions, determine the first performance data of each vehicle in the first vehicle set under various driving conditions, and determine the second performance data of each vehicle in the second vehicle set under various driving conditions.

[0030] The classification and comparison results are obtained by performing classification and comparison processing based on the first performance data and the second performance data.

[0031] Secondly, this application also provides a vehicle operating condition analysis device, the device comprising:

[0032] The data acquisition module is used to acquire a set of target operating data for multiple specified vehicles in the vehicle network data.

[0033] The operating condition determination module is used to determine various driving conditions based on preset vehicle load and road condition dimensions, and to determine the corresponding operating data for each driving condition from the target operating data set.

[0034] The baseline determination module is used to determine the baseline data corresponding to each driving condition based on the operating data corresponding to each driving condition; the baseline data consists of sub-baseline data under various driving condition indicators.

[0035] The performance determination module is used to determine the performance data of a single vehicle under each driving condition based on the operating data of the single vehicle under each driving condition; the performance data consists of sub-performance data under multiple driving condition indicators;

[0036] The operating condition analysis module is used to perform data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, and to obtain the vehicle operating condition analysis results.

[0037] Thirdly, this application also provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method steps of any one of the first aspects.

[0038] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method steps of any one of the first aspects.

[0039] Fifthly, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the method steps of any one of the first aspects.

[0040] The aforementioned vehicle operating condition analysis method, device, computer equipment, storage medium, and computer program product determine multiple driving conditions based on preset vehicle load and road condition dimensions, and determine the corresponding operating data for each driving condition from the target operating data set. By using at least one of the baseline data corresponding to each driving condition and the performance data of a single vehicle under each driving condition, data analysis is performed to obtain vehicle operating condition analysis results. It can evaluate each driving condition of the vehicle separately, thereby obtaining accurate vehicle operating condition analysis results based on the baseline indicators under each driving condition. Attached Figure Description

[0041] Figure 1 This is a flowchart illustrating a vehicle operating condition analysis method in one embodiment;

[0042] Figure 2 This is a flowchart illustrating the steps for determining multiple driving conditions in one embodiment;

[0043] Figure 3 This is a flowchart illustrating the steps for obtaining vehicle operating condition analysis results in one embodiment;

[0044] Figure 4 This is a flowchart illustrating a vehicle operating condition method in one embodiment;

[0045] Figure 5 This is a schematic diagram of the aggregated comparative analysis of vehicle speed distribution in one embodiment;

[0046] Figure 6 This is a structural block diagram of a vehicle operating condition analysis device in one embodiment;

[0047] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0049] The vehicle operating condition analysis method provided in this application can be applied to a terminal. The terminal determines multiple driving conditions based on preset vehicle load and road condition dimensions, and identifies the corresponding operating data for each driving condition from a target operating data set. Then, based on the operating data for each driving condition, it determines baseline data for each driving condition. Finally, based on the operating data for each individual vehicle under each driving condition, it determines the performance data of the individual vehicle under each driving condition. Based on at least one of the baseline data for each driving condition or the performance data of the individual vehicle under each driving condition, data analysis is performed to obtain the vehicle operating condition analysis results. The terminal can be, but is not limited to, various personal computers, laptops, etc.

[0050] In one embodiment, such as Figure 1 As shown, a method for analyzing vehicle operating conditions is provided. Taking the application of this method to the terminal in the above embodiment as an example, the method includes the following steps:

[0051] S102: Obtain the target operating data set of multiple specified vehicles from the vehicle network data.

[0052] The vehicle-to-everything (V2X) data refers to the V2X big data platform. This platform collects vehicle data, road condition information, and other data using devices, sensors, or data import methods, and stores it for processing. The terminal obtains a target operational data set of multiple designated vehicles from the V2X big data platform. These designated vehicles are those selected by the terminal based on their static attribute information, which represents attributes common to all vehicles. This static attribute information is obtained by fusing vehicle static information from the Manufacturing Execution System (MES) and the Manufacturing Execution System (MES). Specifically, the static attribute information includes: Vehicle Identifier (VIN), Terminal Identifier (TID), Vehicle Model, Engine Type, Transmission Type, and Drive Axle Type.

[0053] The target operational data set refers to the collection of operational data from multiple specified vehicles, including vehicle speed, fuel consumption, and engine speed. The terminal creates a vehicle static attribute database by integrating vehicle static information from the MES and ERP systems. Using this database, vehicles are filtered through cross-referencing to obtain the multiple specified vehicles. Cross-referencing refers to performing join queries using Structured Query Language (SQL).

[0054] S104: Based on the preset vehicle load dimension and road condition dimension, determine multiple driving conditions, and determine the corresponding driving data for each driving condition from the target driving data set.

[0055] The load dimension refers to the different load capacities of the vehicle. The terminal divides the vehicle load into multiple segments according to a preset load dimension, such as 5t intervals. Typically, the vehicle load can be divided into 10 segments. The road condition dimension includes road type and road gradient. The terminal merges road types, mainly dividing them into three categories: highway, urban, and suburban. Based on different road gradients, the terminal categorizes the corresponding gradient labels into five types: flat road, uphill, steep uphill, downhill, and steep downhill. Specifically, the terminal determines multiple driving conditions based on the preset vehicle load and road condition dimensions. Each driving condition includes vehicle load, road type, and road gradient. For a target operating data set of multiple specified vehicles, the terminal determines the corresponding operating data for each driving condition based on the operating data in the target operating data set.

[0056] S106: Based on the operating data corresponding to each driving condition, determine the baseline data corresponding to each driving condition; the baseline data consists of sub-baseline data under various operating condition indicators.

[0057] The terminal calculates baseline data for each driving condition based on the corresponding operating data. Baseline data refers to sub-baseline data under multiple operating condition indicators. Each driving condition includes multiple operating condition indicators, such as fuel consumption, vehicle speed, and engine speed; typically, 60 indicators are selected. For each operating condition indicator under each driving condition, the terminal calculates the average value of the operating data for the same type of vehicle to obtain sub-baseline data for each operating condition indicator, such as average fuel consumption and average vehicle speed, which serve as the sub-baseline data for the corresponding operating condition indicator.

[0058] S108: Based on the operating data of a single vehicle under each driving condition, determine the performance data of the single vehicle under each driving condition; the performance data consists of sub-performance data under multiple driving condition indicators.

[0059] The terminal determines the performance data of a single vehicle under each driving condition based on the corresponding operating data of the single vehicle under each driving condition. The performance data consists of sub-performance data under multiple driving condition indicators, and the sub-performance data represents the target operating data of a single vehicle under each driving condition indicator.

[0060] S110: Based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, perform data analysis to obtain the vehicle operating condition analysis results.

[0061] When analyzing the operating conditions of a single vehicle, the analysis typically focuses on the vehicle's driving conditions over a specific period. Within this timeframe, the vehicle may experience multiple different driving conditions. Therefore, it's necessary to calculate the combined baseline data for each vehicle's combined operating conditions during this period. Specifically, taking vehicle speed as an example, the terminal performs a weighted sum based on the proportion of each operating condition for the single vehicle and the baseline speed data for each operating condition to obtain the combined baseline data used to evaluate the single vehicle. For multiple vehicles, however, data analysis is required using the performance data of each vehicle under various driving conditions, along with the corresponding baseline data for each driving condition, to obtain the final vehicle operating condition analysis results.

[0062] In the above-mentioned vehicle operating condition analysis method, multiple driving conditions are determined based on preset vehicle load and road condition dimensions. The corresponding operating data for each driving condition is determined from the target operating data set. Data analysis is performed using the baseline data corresponding to each driving condition and at least one of the performance data of a single vehicle under each driving condition to obtain the vehicle operating condition analysis results. This method can evaluate each driving condition of the vehicle separately, thereby obtaining accurate vehicle operating condition analysis results based on the baseline indicators under each driving condition.

[0063] In one embodiment, the step of obtaining a target operational data set of multiple designated vehicles from vehicle network data includes: obtaining vehicle network data; obtaining target attribute information and target time period; using the target attribute information to determine the designated vehicles; filtering out the operational data set of the designated vehicles within the target time period from the vehicle network data based on the target attribute information and target time period; and performing data cleaning operations on the operational data set to obtain the target operational data set.

[0064] Among them, the target attribute information refers to the static attribute information of the vehicle. The target time period can be set according to the actual application requirements. Based on the target attribute information and the target time period, the terminal filters out the set of operating data of the specified vehicle in the target time period from the vehicle network data. The data obtained here first needs to be preprocessed. Specifically, the terminal groups the set of operating data according to the vehicle VIN code and time, removes duplicate data, and then the terminal cleans the grouped data to remove abnormal data in the set of operating data, thus obtaining the target set of operating data.

[0065] In this embodiment, based on the target attribute information and the target time period, the set of operating data of a specified vehicle within the target time period is selected from the vehicle network data. By performing data cleaning operations on the set of operating data, the target set of operating data is obtained, which can avoid the occurrence of abnormal data in the set of operating data, thereby ensuring the accuracy of the vehicle operating condition analysis results.

[0066] In one embodiment, such as Figure 2 As shown, based on preset vehicle load and road condition dimensions, various driving conditions are determined, including:

[0067] S202: Determine multiple load categories in the vehicle load dimension.

[0068] Among them, the vehicle load category refers to the vehicle's load capacity. Generally speaking, the vehicle load category is divided into 10 types, ranging from 5t to 50t.

[0069] S204: Determines various road types and gradient types in the road condition dimension.

[0070] The road types include three types: expressway, urban, and suburban. The slope types include five types: flat, uphill, steep uphill, downhill, and steep downhill.

[0071] S206: By arranging and combining load categories, road types, and gradient types, various driving conditions can be obtained.

[0072] The terminal processes load categories, road types, and slope types into 150 subdivided driving conditions, each including vehicle load, road type, and road slope.

[0073] In this embodiment, by determining multiple load categories in the vehicle load dimension and multiple road types and slope types in the road condition dimension, and by arranging and combining load categories, road types, and slope types, multiple driving conditions are obtained. This allows for the subdivision of vehicle driving conditions, enabling analysis of each subdivided driving condition and ensuring the accuracy of the vehicle operating condition analysis results.

[0074] In one embodiment, such as Figure 3 As shown, the steps for obtaining vehicle operating condition analysis results by performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition include:

[0075] S302: Determine the proportion of each driving condition for a single vehicle based on the operating data of the vehicle under each driving condition.

[0076] When analyzing the operating conditions of a single vehicle, the analysis is usually conducted over a period of time. During this period, the vehicle may have multiple different operating conditions. It is necessary to calculate the combined baseline data of the combined operating conditions of a single vehicle during this period. Therefore, the terminal determines the proportion of each operating condition for a single vehicle based on the operating data corresponding to each operating condition of the single vehicle.

[0077] S304: Based on the proportion of each driving condition and the baseline data corresponding to each driving condition, the target baseline data of a single vehicle under the target driving condition is calculated; the target driving condition is the combination of driving conditions corresponding to a single vehicle within the target time period.

[0078] Taking vehicle speed distribution as an example, assuming the proportion of each driving condition for a single vehicle is represented as [a1, a2, a3... an], and the baseline data corresponding to each driving condition is represented as [ax1, ax2, ax3... axn], then the target baseline data for a single vehicle under the target driving condition is represented as Y = a1*[ax1, ax2, ax3... axn] + a2*[ax1, ax2, ax3... axn] + a3*[ax1, ax2, ax3... axn] + ... + an*[ax1, ax2, ax3... axn]. The terminal calculates the target baseline data for a single vehicle under the target driving condition by performing a weighted sum based on the proportion of each driving condition and the baseline data corresponding to each driving condition.

[0079] S306: Based on the target baseline data, perform data analysis to obtain the vehicle operating condition analysis results.

[0080] The terminal performs data analysis based on the target baseline data, compares the target baseline data with the actual indicator data of a single vehicle, analyzes the operating conditions of a single vehicle, and obtains the vehicle operating condition analysis results.

[0081] In this embodiment, the target baseline data of a single vehicle under the target driving condition is calculated by using the proportion of each driving condition corresponding to a single vehicle and the baseline data corresponding to each driving condition. Based on the target baseline data, data analysis is performed to obtain the vehicle operating condition analysis results. This allows for the analysis of the vehicle's subdivided driving conditions, thereby enabling the analysis of a single vehicle based on the overall driving conditions and ensuring the accuracy of the vehicle operating condition analysis results.

[0082] In one embodiment, the vehicle operating condition analysis result includes an aggregated comparison analysis result. The step of performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain the vehicle operating condition analysis result includes: acquiring the performance data of multiple vehicles under each driving condition; and performing aggregated comparison processing based on the baseline data corresponding to each driving condition and the performance data of multiple vehicles under each driving condition to obtain the aggregated comparison analysis result.

[0083] The terminal aggregates performance data of multiple vehicles under various driving conditions and for each condition indicator to obtain target performance data representing the performance of multiple vehicles. The target performance data corresponding to each driving condition and each condition indicator is then compared with the corresponding baseline data to analyze the operating conditions of multiple vehicles and obtain aggregated comparative analysis results.

[0084] In this embodiment, by aggregating and comparing the baseline data corresponding to each driving condition and the performance data of multiple vehicles under each driving condition, the aggregated comparison analysis results are obtained, which can provide an overall analysis of the operating conditions of multiple vehicles.

[0085] In one embodiment, the vehicle operating condition analysis result includes a classification comparison analysis result. The step of performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain the vehicle operating condition analysis result includes: determining a first vehicle set and a second vehicle set; determining the first performance data of each vehicle in the first vehicle set under each driving condition based on the performance data of a single vehicle under each driving condition, and determining the second performance data of each vehicle in the second vehicle set under each driving condition; and performing classification comparison processing based on the first performance data and the second performance data to obtain the classification comparison analysis result.

[0086] The terminal, based on application requirements, determines a first set of vehicles and a second set of vehicles, and acquires the first and second performance data for each vehicle under various driving conditions. The terminal then compares and categorizes the first performance data for each driving condition and its corresponding second performance data with the second performance data, analyzing the operational conditions of the first and second vehicle sets to obtain the classification and comparison analysis results. The first and second performance data are aggregated data of the performance data of all vehicles in the first and second vehicle sets, respectively.

[0087] In this embodiment, by classifying and comparing the first performance data of each vehicle in the first vehicle set under various driving conditions with the second performance data of each vehicle in the second vehicle set under various driving conditions, a classification and comparison analysis result is obtained, which can analyze the comparison of driving conditions between multiple vehicle sets and between individual vehicle sets.

[0088] In one embodiment, such as Figure 4 As shown, a method for analyzing vehicle operating conditions based on big data from the Internet of Vehicles is provided. This method includes the following steps:

[0089] S10: Vehicle Screening: The terminal integrates vehicle static information from the MES and ERP systems to create a vehicle static information database. Through this database, multi-dimensional cross-queries are used to enable quick vehicle screening and searching. Available vehicle static attributes include: VIN, TID, vehicle model, engine type, transmission type, drive axle model, platform, product line, production date, odometer reading, and design serial number.

[0090] S20: Data preprocessing: The terminal partitions and groups data according to the vehicle's VIN and time, and performs cleaning operations such as deduplication, outlier removal, and data filling.

[0091] S30: Operating Condition Statistics: The terminal divides the vehicle's load signal into 10 load categories based on 5t, 10t, ..., 50t (5t intervals); merges road types into three types: highway, urban, and suburban; divides slope labels into five types: flat road, uphill, steep uphill, downhill, and steep downhill; and arranges and combines the load category, road type, and slope type to obtain various driving conditions.

[0092] The terminal is divided into 150 driving conditions based on load category, road type and slope type. It further calculates the operating conditions index for each driving condition. The operating conditions index includes more than 60 items such as average fuel consumption, average vehicle speed, vehicle speed distribution, engine speed distribution, gear fuel consumption distribution, vehicle speed fuel consumption distribution, engine speed torque analysis and braking frequency.

[0093] The terminal calculates the average value of the operating data corresponding to each operating condition index under each driving condition, which is defined as the baseline data of each operating condition index under each driving condition for this vehicle model.

[0094] S40: Result Analysis: For a single vehicle: The terminal calculates the target baseline data of a single vehicle under the target driving condition by using the proportion of each driving condition corresponding to the single vehicle and the baseline data corresponding to each driving condition, and performs data analysis based on the target baseline data.

[0095] For multiple vehicles: (1) Aggregated comparative analysis: The terminal aggregates the performance data of multiple vehicles under various driving conditions and under various operating conditions to obtain target performance data representing the performance of multiple vehicles. The target performance data corresponding to each driving condition and operating condition is compared with the corresponding baseline data to analyze the operating conditions of multiple vehicles. For example Figure 5 As shown, Figure 5 This is a schematic diagram illustrating the aggregated comparative analysis of vehicle speed distribution under a certain driving condition. Figure 5 Bar 1 represents the aggregated vehicle speed distribution data, and bar 2 represents the baseline data of the vehicle speed distribution. By comparing the aggregated vehicle speed distribution data with the baseline data, the operating conditions of multiple vehicles can be analyzed.

[0096] (2) Classification and comparison analysis: Based on application requirements, the terminal determines the first vehicle set and the second vehicle set, and obtains the first performance data and second performance data of each vehicle under each driving condition. The terminal classifies and compares the first performance data corresponding to each driving condition and each condition indicator with the corresponding second performance data, analyzes the comparison of the operating conditions of the first vehicle set and the second vehicle set, and analyzes the comparison of operating conditions between multiple vehicle sets and between individual vehicle sets.

[0097] In this embodiment, by arranging and combining load categories, road types, and slope types, multiple driving conditions are obtained. Based on the proportion of each driving condition and the baseline data of each condition index under each driving condition, weighted statistics are performed to evaluate each driving condition of the vehicle. Thus, based on the baseline index under each driving condition, accurate vehicle operating condition analysis results are obtained.

[0098] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0099] Based on the same inventive concept, this application also provides a vehicle operating condition analysis device for implementing the vehicle operating condition analysis method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more vehicle operating condition analysis device embodiments provided below can be found in the limitations of the vehicle operating condition analysis method described above, and will not be repeated here.

[0100] In one embodiment, such as Figure 6 As shown, a vehicle operating condition analysis device is provided, including: a data acquisition module 10, an operating condition determination module 20, a baseline determination module 30, a performance determination module 40, and an operating condition analysis module 50, wherein:

[0101] Data acquisition module 10 is used to acquire a target operating data set of multiple specified vehicles in the vehicle network data;

[0102] The working condition determination module 20 is used to determine multiple driving conditions based on preset vehicle load and road condition dimensions, and to determine the corresponding operating data for each driving condition from the target operating data set.

[0103] The baseline determination module 30 is used to determine the baseline data corresponding to each driving condition based on the operating data corresponding to each driving condition; the baseline data consists of sub-baseline data under multiple driving condition indicators.

[0104] The performance determination module 40 is used to determine the performance data of a single vehicle under each driving condition based on the operating data of the single vehicle under each driving condition; the performance data consists of sub-performance data under multiple driving condition indicators.

[0105] The operating condition analysis module 50 is used to perform data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, and to obtain the vehicle operating condition analysis results.

[0106] In one embodiment, the data acquisition module 10 includes: a vehicle network data acquisition unit, an attribute information acquisition unit, a data filtering unit, and a set acquisition unit, wherein:

[0107] The vehicle-to-everything (V2X) data acquisition unit is used to acquire V2X data.

[0108] The attribute information acquisition unit is used to acquire target attribute information and target time period; the target attribute information is used to determine the specified vehicle.

[0109] The data filtering unit is used to filter out the set of operating data of a specified vehicle within a target time period from the vehicle network data based on target attribute information and target time period.

[0110] The set acquisition unit is used to perform data cleaning operations on the running data set to obtain the target running data set.

[0111] In one embodiment, the operating condition determination module 20 includes: a category determination unit, a type determination unit, and an operating condition acquisition unit, wherein:

[0112] The category determination unit is used to determine multiple load categories in the vehicle load dimension.

[0113] The type determination unit is used to determine various road types and slope types in the road condition dimension.

[0114] The working condition acquisition unit is used to arrange and combine load category, road type and slope type to obtain various driving conditions.

[0115] In one embodiment, the working condition analysis module 50 includes: a proportion determination unit, a baseline calculation unit, and a data analysis unit, wherein:

[0116] The percentage determination unit is used to determine the percentage of each driving condition for a single vehicle based on the operating data of the vehicle under each driving condition.

[0117] The baseline calculation unit is used to calculate the target baseline data of a single vehicle under the target driving condition based on the proportion of each driving condition and the baseline data corresponding to each driving condition; the target driving condition is the combination of driving conditions corresponding to a single vehicle within the target time period.

[0118] The data analysis unit is used to perform data analysis based on the target baseline data to obtain the vehicle operating condition analysis results.

[0119] In one embodiment, the operating condition analysis module 50 includes: a performance acquisition unit and an aggregation comparison unit, wherein:

[0120] The performance acquisition unit is used to acquire performance data of multiple vehicles under various driving conditions.

[0121] The aggregation comparison unit is used to perform aggregation comparison processing based on the baseline data corresponding to each driving condition and the performance data of multiple vehicles under each driving condition, and to obtain the aggregation comparison analysis results.

[0122] In one embodiment, the operating condition analysis module 50 includes: a set determination unit, a performance determination unit, and a classification analysis unit, wherein:

[0123] The set determination unit is used to determine the first vehicle set and the second vehicle set.

[0124] The performance determination unit is used to determine the first performance data of each vehicle in the first vehicle set under each driving condition based on the performance data of a single vehicle under each driving condition, and to determine the second performance data of each vehicle in the second vehicle set under each driving condition.

[0125] The classification analysis unit is used to perform classification comparison processing based on the first performance data and the second performance data to obtain the classification comparison analysis results.

[0126] Each module in the aforementioned vehicle operating condition analysis device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0127] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for analyzing vehicle operating conditions. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0128] Those skilled in the art will understand that Figure 7The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0129] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: acquiring a target operating data set of multiple specified vehicles from vehicle network data; determining multiple driving conditions based on preset vehicle load and road condition dimensions, and determining operating data corresponding to each driving condition from the target operating data set; determining baseline data corresponding to each driving condition based on the operating data corresponding to each driving condition; the baseline data consists of sub-baseline data under multiple operating condition indicators; determining performance data of a single vehicle under each driving condition based on the operating data corresponding to each single vehicle under each driving condition; the performance data consists of sub-performance data under multiple operating condition indicators; and performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain vehicle operating condition analysis results.

[0130] In one embodiment, the process of a processor executing a computer program to acquire a target set of operational data for multiple designated vehicles in vehicle network data includes: acquiring vehicle network data; acquiring target attribute information and a target time period; using the target attribute information to determine the designated vehicles; filtering out the set of operational data for the designated vehicles within the target time period from the vehicle network data based on the target attribute information and the target time period; and performing data cleaning operations on the set of operational data to obtain the target set of operational data.

[0131] In one embodiment, when the processor executes a computer program, it determines multiple driving conditions based on preset vehicle load dimensions and road condition dimensions, including: determining multiple load categories in the vehicle load dimension; determining multiple road types and slope types in the road condition dimension; and arranging and combining the load categories, road types, and slope types to obtain multiple driving conditions.

[0132] In one embodiment, when the processor executes a computer program, it performs data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain vehicle operating condition analysis results. This includes: determining the proportion of each driving condition corresponding to a single vehicle based on the operating data corresponding to each driving condition; calculating the target baseline data of a single vehicle under a target driving condition based on the proportion of each driving condition and the baseline data corresponding to each driving condition; the target driving condition being a combination of driving conditions corresponding to a single vehicle within a target time period; and performing data analysis based on the target baseline data to obtain vehicle operating condition analysis results.

[0133] In one embodiment, the vehicle operating condition analysis results involved when the processor executes the computer program include aggregated comparison analysis results; based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, data analysis is performed to obtain vehicle operating condition analysis results, including: acquiring the performance data of multiple vehicles under each driving condition; and performing aggregated comparison processing based on the baseline data corresponding to each driving condition and the performance data of multiple vehicles under each driving condition to obtain aggregated comparison analysis results.

[0134] In one embodiment, the vehicle operating condition analysis results involved when the processor executes the computer program include classification and comparison analysis results; based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, data analysis is performed to obtain vehicle operating condition analysis results, including: determining a first vehicle set and a second vehicle set; based on the performance data of a single vehicle under each driving condition, determining the first performance data of each vehicle in the first vehicle set under each driving condition, and determining the second performance data of each vehicle in the second vehicle set under each driving condition; and performing classification and comparison processing based on the first performance data and the second performance data to obtain classification and comparison analysis results.

[0135] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program performs the following steps: acquiring a target operating data set of multiple specified vehicles from vehicle network data; determining multiple driving conditions based on preset vehicle load and road condition dimensions, and determining operating data corresponding to each driving condition from the target operating data set; determining baseline data corresponding to each driving condition based on the operating data corresponding to each driving condition; the baseline data consists of sub-baseline data under multiple operating condition indicators; determining performance data of a single vehicle under each driving condition based on the operating data corresponding to each single vehicle under each driving condition; the performance data consists of sub-performance data under multiple operating condition indicators; and performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain vehicle operating condition analysis results.

[0136] In one embodiment, when a computer program is executed by a processor, the acquisition of a target set of operational data for multiple designated vehicles in vehicle network data includes: acquiring vehicle network data; acquiring target attribute information and a target time period; using the target attribute information to determine the designated vehicles; filtering out the set of operational data for the designated vehicles within the target time period from the vehicle network data based on the target attribute information and the target time period; and performing data cleaning operations on the set of operational data to obtain the target set of operational data.

[0137] In one embodiment, when the computer program is executed by the processor, it involves determining multiple driving conditions based on preset vehicle load dimensions and road condition dimensions, including: determining multiple load categories in the vehicle load dimension; determining multiple road types and slope types in the road condition dimension; and arranging and combining the load categories, road types, and slope types to obtain multiple driving conditions.

[0138] In one embodiment, when a computer program is executed by a processor, it involves data analysis based on at least one of baseline data corresponding to each driving condition or performance data of a single vehicle under each driving condition to obtain vehicle operating condition analysis results. This includes: determining the proportion of each driving condition corresponding to a single vehicle based on the operating data of a single vehicle under each driving condition; calculating target baseline data of a single vehicle under a target driving condition based on the proportion of each driving condition and the baseline data corresponding to each driving condition; the target driving condition being a combination of driving conditions corresponding to a single vehicle within a target time period; and performing data analysis based on the target baseline data to obtain vehicle operating condition analysis results.

[0139] In one embodiment, the vehicle operating condition analysis results involved when the computer program is executed by the processor include aggregated comparison analysis results; based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, data analysis is performed to obtain vehicle operating condition analysis results, including: acquiring the performance data of multiple vehicles under each driving condition; and performing aggregated comparison processing based on the baseline data corresponding to each driving condition and the performance data of multiple vehicles under each driving condition to obtain aggregated comparison analysis results.

[0140] In one embodiment, the vehicle operating condition analysis results involved when the computer program is executed by the processor include classification and comparison analysis results; based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, data analysis is performed to obtain vehicle operating condition analysis results, including: determining a first vehicle set and a second vehicle set; based on the performance data of a single vehicle under each driving condition, determining the first performance data of each vehicle in the first vehicle set under each driving condition, and determining the second performance data of each vehicle in the second vehicle set under each driving condition; and performing classification and comparison processing based on the first performance data and the second performance data to obtain classification and comparison analysis results.

[0141] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: acquiring a target operating data set of multiple designated vehicles from vehicle network data; determining multiple driving conditions based on preset vehicle load and road condition dimensions, and determining operating data corresponding to each driving condition from the target operating data set; determining baseline data corresponding to each driving condition based on the operating data corresponding to each driving condition; the baseline data consists of sub-baseline data under multiple operating condition indicators; determining performance data of a single vehicle under each driving condition based on the operating data corresponding to each single vehicle under each driving condition; the performance data consists of sub-performance data under multiple operating condition indicators; and performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition to obtain vehicle operating condition analysis results.

[0142] In one embodiment, when a computer program is executed by a processor, the acquisition of a target set of operational data for multiple designated vehicles in vehicle network data includes: acquiring vehicle network data; acquiring target attribute information and a target time period; using the target attribute information to determine the designated vehicles; filtering out the set of operational data for the designated vehicles within the target time period from the vehicle network data based on the target attribute information and the target time period; and performing data cleaning operations on the set of operational data to obtain the target set of operational data.

[0143] In one embodiment, when the computer program is executed by the processor, it involves determining multiple driving conditions based on preset vehicle load dimensions and road condition dimensions, including: determining multiple load categories in the vehicle load dimension; determining multiple road types and slope types in the road condition dimension; and arranging and combining the load categories, road types, and slope types to obtain multiple driving conditions.

[0144] In one embodiment, when a computer program is executed by a processor, it involves data analysis based on at least one of baseline data corresponding to each driving condition or performance data of a single vehicle under each driving condition to obtain vehicle operating condition analysis results. This includes: determining the proportion of each driving condition corresponding to a single vehicle based on the operating data of a single vehicle under each driving condition; calculating target baseline data of a single vehicle under a target driving condition based on the proportion of each driving condition and the baseline data corresponding to each driving condition; the target driving condition being a combination of driving conditions corresponding to a single vehicle within a target time period; and performing data analysis based on the target baseline data to obtain vehicle operating condition analysis results.

[0145] In one embodiment, the vehicle operating condition analysis results involved when the computer program is executed by the processor include aggregated comparison analysis results; based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, data analysis is performed to obtain vehicle operating condition analysis results, including: acquiring the performance data of multiple vehicles under each driving condition; and performing aggregated comparison processing based on the baseline data corresponding to each driving condition and the performance data of multiple vehicles under each driving condition to obtain aggregated comparison analysis results.

[0146] In one embodiment, the vehicle operating condition analysis results involved when the computer program is executed by the processor include classification and comparison analysis results; based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition, data analysis is performed to obtain vehicle operating condition analysis results, including: determining a first vehicle set and a second vehicle set; based on the performance data of a single vehicle under each driving condition, determining the first performance data of each vehicle in the first vehicle set under each driving condition, and determining the second performance data of each vehicle in the second vehicle set under each driving condition; and performing classification and comparison processing based on the first performance data and the second performance data to obtain classification and comparison analysis results.

[0147] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0148] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0149] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for analyzing vehicle operating conditions, characterized in that, The method includes: Acquire a target operational data set of multiple designated vehicles from vehicle network data; the designated vehicles are target vehicles selected based on vehicle static attribute information. Determine the various load categories within the vehicle load dimension; Identify various road types and slope types within the road condition dimension; The load category, road type, and slope type are arranged and combined to obtain multiple driving conditions, and the corresponding driving data for each driving condition is determined from the target driving data set; the road condition dimension includes road type and road slope. Based on the operating data corresponding to each driving condition, baseline data corresponding to each driving condition is determined; the baseline data consists of sub-baseline data under multiple operating condition indicators. Based on the operating data of a single vehicle under each driving condition, the performance data of the single vehicle under each driving condition is determined; the performance data consists of sub-performance data under multiple driving condition indicators. Based on the operating data of a single vehicle under each driving condition, determine the proportion of each driving condition for that single vehicle. Based on the proportion of each driving condition and the baseline data corresponding to each driving condition, a weighted sum is performed to calculate the target baseline data of a single vehicle under the target driving condition; the target driving condition is the combination of driving conditions corresponding to a single vehicle within the target time period. Data analysis is performed based on the target baseline data to obtain vehicle operating condition analysis results; wherein, the vehicle operating condition analysis results include the analysis results of the driving conditions of a single vehicle over a period of time and the analysis results of the operating conditions of multiple vehicles.

2. The method according to claim 1, characterized in that, The acquisition of the target operational data set of multiple designated vehicles in the vehicle network data includes: Acquire vehicle network data; Obtain target attribute information and target time period; the target attribute information is used to determine the specified vehicle. Based on the target attribute information and the target time period, a set of operating data of a specified vehicle within the target time period is filtered from the vehicle network data; The running data set is cleaned to obtain the target running data set.

3. The method according to claim 1, characterized in that, The vehicle operating condition analysis results include aggregated comparative analysis results; the process of obtaining vehicle operating condition analysis results by performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition includes: Acquire performance data of multiple vehicles under various driving conditions; Based on the baseline data corresponding to each driving condition and the performance data of multiple vehicles under each driving condition, the data are aggregated and compared to obtain the aggregated comparison analysis results.

4. The method according to claim 1, characterized in that, The vehicle operating condition analysis results include classification and comparison analysis results; the process of obtaining vehicle operating condition analysis results by performing data analysis based on at least one of the baseline data corresponding to each driving condition or the performance data of a single vehicle under each driving condition includes: Determine the first vehicle set and the second vehicle set; Based on the performance data of a single vehicle under various driving conditions, determine the first performance data of each vehicle in the first vehicle set under various driving conditions, and determine the second performance data of each vehicle in the second vehicle set under various driving conditions. Based on the first performance data and the second performance data, a classification comparison process is performed to obtain the classification comparison analysis results.

5. A vehicle operating condition analysis device, characterized in that, The device includes: The data acquisition module is used to acquire a target operating data set of multiple designated vehicles from the vehicle network data; the designated vehicles are target vehicles selected based on vehicle static attribute information. The working condition determination module is used to determine multiple load categories in the vehicle load dimension; determine multiple road types and slope types in the road condition dimension; arrange and combine the load categories, road types, and slope types to obtain multiple driving conditions, and determine the operating data corresponding to each driving condition from the target operating data set; the road condition dimension includes road type and road slope. The baseline determination module is used to determine the baseline data corresponding to each driving condition based on the operating data corresponding to each driving condition; the baseline data consists of sub-baseline data under multiple driving condition indicators. The performance determination module is used to determine the performance data of a single vehicle under each driving condition based on the operating data of the single vehicle under each driving condition; the performance data consists of sub-performance data under multiple driving condition indicators. The operating condition analysis module is used to determine the proportion of each driving condition for a single vehicle based on the operating data corresponding to each driving condition; to calculate the target baseline data for a single vehicle under the target driving condition by performing a weighted sum based on the proportion of each driving condition and the baseline data corresponding to each driving condition; the target driving condition is a combination of driving conditions corresponding to a single vehicle within a target time period; and to perform data analysis based on the target baseline data to obtain vehicle operating condition analysis results; wherein, the vehicle operating condition analysis results include the analysis results of the driving conditions of a single vehicle within a certain period and the analysis results of the operating conditions of multiple vehicles.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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