Vehicle driving information generation method and system based on vehicle positioning

Abstract

The embodiment of the invention discloses a vehicle driving information generation method and system based on vehicle positioning. The method comprises the steps that a vehicle using starting point, a vehicle using terminal point, a vehicle using unit, a vehicle using reason, vehicle real-time positioning information and vehicle running time of a vehicle are obtained in real time; a first driving track is generated according to the vehicle real-time positioning information, a second driving track is generated according to the vehicle starting point and the vehicle ending point, and track offset is determined according to a first offset monitoring point on the first driving track and a second offset monitoring point on the second driving track; obtaining building information of a final position of the first driving track, and determining a first risk value according to the vehicle use reason and the building information; the second risk value is determined according to the vehicle running time and the working time of the vehicle using unit, and the vehicle running information is generated according to the track offset, the first risk value, the second risk value and the first running track so as to be used for vehicle purpose judgment, so that the accuracy of the vehicle running information and the accuracy of vehicle purpose judgment are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data processing technology, and in particular to a method and system for generating vehicle driving information based on vehicle positioning. Background Art

[0002] With the continuous development of intelligent transportation systems and the continuous growth in the number of vehicles, vehicle usage management has become an important part of it. Vehicle usage management involves the monitoring and analysis of information such as vehicle flow, driving routes, parking conditions, and generating corresponding vehicle driving information based on the monitoring and analysis results to optimize the allocation of transportation resources.

[0003] In the related art, when generating vehicle driving data information, the vehicle driving trajectory is usually generated based on real-time positioning data, the pre-planned driving trajectory is matched with the real-time generated vehicle driving trajectory, and the risk of abnormal vehicle use is determined based on the matching result, thereby generating vehicle driving information based on the risk of abnormal vehicle use. However, there may be situations where the vehicle deviates from the preset driving trajectory due to temporary changes in vehicle use or due to special circumstances such as traffic accidents and traffic control, which may lead to inaccurate judgment of the vehicle abnormal risk value, affecting the accuracy of vehicle driving information and the accuracy of vehicle use judgment. Summary of the invention

[0004] The embodiment of the present application provides a method and system for generating vehicle driving information based on vehicle positioning, which solves the problem that the inaccurate judgment of the abnormal risk value of the vehicle affects the accuracy of the vehicle driving information and the accuracy of the judgment of the vehicle use. The risk of abnormal vehicle use can be comprehensively judged in terms of track offset, whether the vehicle use reason matches, and whether the vehicle use time matches, based on the vehicle operation information and the vehicle application information, thereby improving the accuracy of the vehicle driving information and the accuracy of the vehicle use judgment.

[0005] In a first aspect, an embodiment of the present application provides a method for generating vehicle driving information based on vehicle positioning, comprising: Real-time acquisition of vehicle operation information and vehicle application information of the vehicle, wherein the vehicle application information includes the vehicle starting point, vehicle end point, vehicle using unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time; Generate a first driving trajectory according to the real-time positioning information of the vehicle, generate a second driving trajectory according to the vehicle starting point and the vehicle end point, and identify multiple first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information; Determine a corresponding second offset monitoring point on the second driving trajectory according to the distance from each first offset monitoring point to the starting point of the vehicle, and determine the trajectory offset between the first offset monitoring point and the second offset monitoring point; Determine the end position of the first driving trajectory, obtain the building information of the end position, match the vehicle use reason with the building purpose in the building information, and determine the first risk value according to the matching result; The vehicle operation time is matched with the working time corresponding to the vehicle-using unit, a second risk value is determined according to the matching result, and vehicle driving information is generated according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory for determining the purpose of the vehicle.

[0006] Optionally, the identifying a plurality of first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information includes: Determine a first target detection range according to a preset detection distance and the first driving trajectory, and calibrate the first target detection range according to terrain information within the first target detection range and the first driving trajectory to obtain a second target detection range; According to the preset building information, a target position within the second target detection range is identified, a nearest monitoring point from the target position to the first driving trajectory is determined, and the nearest monitoring point is determined as a first offset monitoring point.

[0007] Optionally, calibrating the first target detection range according to the terrain information within the first target detection range and the first driving trajectory includes: A non-target area is determined according to terrain information within the first target detection range, size information of the non-target area is determined according to preset area map data and the first driving trajectory, and the first target detection range is calibrated according to the size information.

[0008] Optionally, determining the size information of the non-target area according to the preset area map data and the first driving trajectory, and calibrating the first target detection range according to the size information includes: Determine the shortest distance from the first driving track to the non-target area according to preset map data, and determine a first adjustment point on the non-target area according to the shortest distance; Generate a position reference line of the non-target area according to the first adjustment point, traverse reference points on the boundary of the non-target area, determine a reference point on one side of the position reference line as a first reference point, and determine a reference point on the other side of the position reference line as a second reference point; Calculate the distance between each first reference point and each second reference point respectively, and determine the first reference point with the longest distance as the second adjustment point, and determine the second reference point with the longest distance as the third adjustment point; A target adjustment range is determined according to the first adjustment point, the second adjustment point, and the third adjustment point, and the first target detection range is calibrated according to the target adjustment range.

[0009] Optionally, the acquiring of the building information of the destination location, matching the vehicle use reason with the building purpose in the building information, and determining the first risk value according to the matching result includes: Determine a risk assessment range according to the coordinates of the end point position and a preset assessment distance, and obtain building information within the risk assessment range; The multiple building uses in the building information are matched with the vehicle use reasons respectively, and a first risk value is determined according to the number of matches.

[0010] Optionally, the determining the trajectory offset between the first offset monitoring point and the second offset monitoring point includes: The offset distance between the first offset monitoring point and the second offset monitoring point is calculated, and the offset distance is compared with a preset distance threshold. When the offset distance is greater than the preset distance threshold, the offset angle between the first offset monitoring point and the second offset monitoring point is determined.

[0011] Optionally, generating vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory includes: Displaying the first driving track on a preset electronic map, and marking the first driving track on the preset electronic map according to the offset distance, the offset angle, and the first offset monitoring point to generate a vehicle offset marking map; The first risk value and the second risk value are weightedly calculated to obtain a vehicle abnormality risk value, and vehicle driving information is generated according to the vehicle offset mark map and the vehicle abnormality risk value.

[0012] In a second aspect, an embodiment of the present application provides a vehicle driving information generation system based on vehicle positioning, comprising: An information acquisition module is used to acquire vehicle operation information and vehicle application information of the vehicle in real time, wherein the vehicle application information includes the vehicle starting point, vehicle end point, vehicle using unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time; A driving trajectory generating module, used to generate a first driving trajectory according to the real-time positioning information of the vehicle, and to generate a second driving trajectory according to the starting point and the end point of the vehicle; an offset monitoring point identification module, used to identify a plurality of first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information, and determine a corresponding second offset monitoring point on the second driving trajectory according to a distance from each first offset monitoring point to the vehicle starting point; A trajectory deviation determination module, used to determine the trajectory deviation between the first deviation monitoring point and the second deviation monitoring point; a first risk value determination module, configured to determine the terminal position of the first driving trajectory, obtain building information at the terminal position, match the vehicle use reason with the building purpose in the building information, and determine a first risk value according to the matching result; A second risk value determination module is used to match the vehicle operation time with the working time corresponding to the vehicle-using unit, and determine a second risk value according to the matching result; The vehicle driving information generating module is used to generate vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory, so as to be used for determining the purpose of the vehicle.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors; a storage device configured to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method for generating vehicle driving information based on vehicle positioning as described in the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the method for generating vehicle driving information based on vehicle positioning as described in the first aspect.

[0015] The embodiment of the present application obtains vehicle operation information and vehicle application information of the vehicle in real time, wherein the vehicle application information includes the vehicle use starting point, vehicle use end point, vehicle use unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time; generates a first driving trajectory according to the vehicle real-time positioning information, generates a second driving trajectory according to the vehicle use starting point and vehicle use end point, and identifies multiple first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information; determines the corresponding second offset monitoring point on the second driving trajectory according to the distance from each first offset monitoring point to the vehicle use starting point, and determines the trajectory offset between the first offset monitoring point and the second offset monitoring point; determines the terminal position of the first driving trajectory, obtains the building information at the terminal position, matches the building use in the vehicle use reason and the building information, and determines the first risk value according to the matching result; matches the vehicle operation time with the working time corresponding to the vehicle use unit, determines the second risk value according to the matching result, and generates the vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory for judging the vehicle use. The first offset monitoring point can be identified through a preset detection distance and preset building information, thereby improving the accuracy of the first offset monitoring point and the accuracy of determining the trajectory offset. By respectively determining the trajectory offset, the first risk value, the second risk value and the first driving trajectory, and generating vehicle driving information including the trajectory offset, the first risk value, the second risk value and the first driving trajectory, the accuracy of the vehicle driving information and the accuracy of judging the purpose of the vehicle are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of a method for generating vehicle driving information based on vehicle positioning provided in an embodiment of the present application; Figure 2 is a schematic diagram of a vehicle offset mark provided in an embodiment of the present application; Figure 3 is a flow chart of a method for identifying a first offset monitoring point provided in an embodiment of the present application; Figure 4 is a schematic diagram of a first target detection range provided in an embodiment of the present application; Figure 5 is a flow chart of a method for determining size information of a non-target area provided in an embodiment of the present application; Figure 6 is a schematic diagram of a target detection range provided in an embodiment of the present application; Figure 7 It is a structural schematic diagram of a vehicle driving information generation system based on vehicle positioning provided in an embodiment of the present application; Figure 8 It is a structural schematic diagram of a vehicle driving information generating device based on vehicle positioning provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only part of the present application is shown in the accompanying drawings, but not all of the content. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0018] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0019] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0020] The following, in conjunction with the accompanying drawings, describes in detail the method and system for generating vehicle driving information based on vehicle positioning provided by the embodiments of the present application through specific embodiments and their application scenarios.

[0021] The vehicle driving information generation method based on vehicle positioning provided in the embodiment of the present application is used in the scenario of vehicle use management, such as real-time monitoring of the vehicle positioning data of the vehicle through Beidou positioning technology, and determining the risk value of the vehicle use and other detection conditions by processing the vehicle positioning data, so as to judge the vehicle use. Based on the above application scenarios, it can be understood that the execution subject of the present application can be a server.

[0022] Figure 1 is a flow chart of a method for generating vehicle driving information based on vehicle positioning provided in an embodiment of the present application, such as Figure 1 As shown, including: Step S101, real-time acquisition of vehicle operation information and vehicle use application information of the vehicle, wherein the vehicle use application information includes the vehicle use starting point, vehicle use end point, vehicle use unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time.

[0023] Among them, vehicle operation information refers to data and information generated during the operation of the vehicle, reflecting the vehicle's operating status, performance, location, environment and other aspects. Optionally, the vehicle operation information may also include vehicle real-time positioning information and vehicle operation information, wherein the vehicle real-time positioning information can be obtained by real-time monitoring and positioning of the vehicle's location, driving status and other information through the Beidou positioning system. Vehicle application information refers to detailed information on vehicle use needs and related circumstances submitted by the applicant to the vehicle management system before using the vehicle, which may include vehicle use time, number of passengers, etc. Optionally, the vehicle application information may also include the vehicle use starting point, vehicle use end point, vehicle use unit and vehicle use reason, etc. In one embodiment, the vehicle use starting point, vehicle use end point, vehicle use unit, vehicle use reason, vehicle real-time positioning information and vehicle operation time and other information are obtained in real time.

[0024] Step S102: Generate a first driving trajectory according to the real-time positioning information of the vehicle, generate a second driving trajectory according to the vehicle starting point and the vehicle end point, and identify multiple first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information.

[0025] The first driving trajectory is used to represent the actual driving trajectory of the vehicle, and the second driving trajectory is used to represent the pre-planned driving trajectory of the vehicle. The preset detection distance is used to represent the building detection distance from the first driving trajectory. The preset building information can be used to represent the location of the building, the building identification, and the building type. The first offset monitoring point is a point collected on the first driving trajectory for determining whether the driving trajectory is offset. In one embodiment, the actual driving trajectory of the vehicle, i.e., the first driving trajectory, is generated according to the real-time positioning information of the vehicle, and a reasonable driving route, i.e., the second driving trajectory, is pre-planned according to the starting point and the end point of the vehicle in the vehicle application information. The recognition range of the first offset monitoring point is determined according to the preset detection distance and the position of the first driving trajectory, and the target building matching the preset building information is identified within the recognition range, and the monitoring area is determined with the target building as the center and the preset detection distance as the radius, and the point where the monitoring area intersects with the first driving trajectory is determined as the first offset monitoring point. In order to improve the accuracy of the driving trajectory offset judgment, multiple first offset monitoring points can be identified.

[0026] Step S103: determining corresponding second offset monitoring points on the second driving trajectory according to the distances from each first offset monitoring point to the vehicle starting point, and determining the trajectory offset between the first offset monitoring point and the second offset monitoring point.

[0027] Among them, the points collected on the second driving trajectory of the second offset monitoring point are used to determine whether the driving trajectory is offset. The trajectory offset is used to indicate the degree of offset of the second driving trajectory compared to the first driving trajectory. The larger the offset, the higher the degree of offset between the first driving trajectory and the second driving trajectory. Correspondingly, the larger the trajectory offset, the higher the risk of abnormal vehicle use. In one embodiment, the distance between each first offset monitoring point and the starting point of the vehicle is calculated. If it is 100 meters, the point 100 meters away from the starting point of the vehicle is determined on the second driving trajectory as the second offset monitoring point, and it is determined whether the position coordinates of the first offset monitoring point and the second offset monitoring point are the same, that is, whether the trajectory offset is 0. If different, the relative position relationship between the first offset monitoring point and the second offset monitoring point is determined.

[0028] Optionally, the determining the trajectory offset between the first offset monitoring point and the second offset monitoring point includes: The offset distance between the first offset monitoring point and the second offset monitoring point is calculated, and the offset distance is compared with a preset distance threshold. When the offset distance is greater than the preset distance threshold, the offset angle between the first offset monitoring point and the second offset monitoring point is determined.

[0029] Among them, the offset distance is used to represent the distance between two monitoring points, and the offset angle is used to represent the relative position relationship between the two monitoring points. In one embodiment, the offset distance between the first offset monitoring point and the second offset monitoring point is first calculated, and the offset distance is compared with the preset distance threshold. If the offset distance is greater than the preset distance threshold, it is considered that the offset distance between the first offset monitoring point and the second offset monitoring point exceeds the normal offset distance, and there is a greater risk of abnormal vehicle use. At this time, the offset angle between the first offset detection point and the second offset monitoring point can be determined accordingly, and the position of the first offset monitoring point relative to the second offset monitoring point can be determined by the offset angle, so as to facilitate the subsequent determination of the offset direction based on the offset angle, and to determine whether the offset direction contains a pre-set scenic spot or entertainment venues such as KTV. If the offset distance is less than the preset distance threshold, it is considered that the vehicle may have adjusted the road conditions within a reasonable range according to the actual road conditions, and there is a small risk of abnormal vehicle use. At this time, there is no need to judge the relative position relationship between the first offset monitoring point and the second offset monitoring point.

[0030] The embodiment of the present application calculates the offset distance between the first offset monitoring point and the second offset monitoring point, and compares the offset distance with a preset distance threshold, and when the offset distance is greater than the preset distance threshold, determines the offset angle between the first offset monitoring point and the second offset monitoring point. In the above scheme, the judgment condition for judging abnormal vehicle use can be accurately generated based on the actual offset situation.

[0031] Step S104: determine the end point of the first driving trajectory, obtain the building information of the end point, match the vehicle use reason with the building purpose in the building information, and determine the first risk value according to the matching result.

[0032] Among them, the terminal position of the first driving trajectory is used to indicate the destination actually reached by the vehicle, the building use is used to indicate the actual use of the building, and the first risk value is used to indicate the risk that the actual use of the vehicle is inconsistent with the purpose of the vehicle use. If the first risk value is 0, it indicates that there is no risk of abnormal vehicle use. If the first risk value is 1, it indicates that there is a risk of abnormal vehicle use. In one embodiment, the stop time of the vehicle is determined according to the first driving trajectory, the final stop position is determined as the terminal position of the first driving trajectory, and the use of the building closest to the terminal position is determined, and the purpose of the vehicle use is matched with the purpose of the building. For example, if the purpose of the vehicle use is factory inspection, the building is a factory, and the purpose of the building is industrial production, then the purpose of the vehicle use is matched with the purpose of the building, and the first risk value is determined to be 0. If the purpose of the vehicle use is factory inspection, the building is an office building, and the purpose of the building is office space or business activities, then the purpose of the vehicle use does not match the purpose of the building, and the first risk value is determined to be 1.

[0033] Optionally, the acquiring of the building information of the destination location, matching the vehicle use reason with the building purpose in the building information, and determining the first risk value according to the matching result includes: Determine a risk assessment range according to the coordinates of the end point position and a preset assessment distance, and obtain building information within the risk assessment range; The multiple building uses in the building information are matched with the vehicle use reasons respectively, and a first risk value is determined according to the number of matches. Among them, the risk assessment range can be used to represent the identification range of building information. In one embodiment, the risk assessment range is determined according to the coordinates of the end point position and the preset assessment distance. Exemplarily, the risk assessment range is determined with the end point position as the center and the preset assessment distance as the radius, and the building uses of all buildings within the risk assessment range are obtained. Each building use is matched with the vehicle use reason, and the number of buildings that can be successfully matched with the vehicle use reason is determined. The first risk value is determined according to the mapping relationship between the preset matching number and the risk value.

[0034] In the embodiment of the present application, the risk assessment range is determined according to the coordinates of the end point and the preset assessment distance, and the building information within the risk assessment range is obtained; the multiple building uses in the building information are matched with the vehicle use reasons respectively, and the first risk value is determined according to the number of matches. In the above scheme, the accuracy of the first risk value is improved by correspondingly expanding the risk assessment range and matching the building uses corresponding to the multiple buildings within the risk range with the vehicle use reasons.

[0035] Step S105: Match the vehicle operation time with the working time corresponding to the vehicle-using unit, determine the second risk value according to the matching result, and generate vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory for judging the purpose of the vehicle.

[0036] Among them, the vehicle running time is used to indicate the time when the vehicle is in working state or in driving state, and can also be used to indicate the time when the vehicle is in non-target parking area. The second risk value is used to indicate the risk level of vehicle use during non-working hours. If the second risk value is 0, it indicates that there is no abnormal risk of vehicle use, and if the second risk value is 1, it indicates that there is an abnormal risk of vehicle use. The vehicle driving information is used to indicate the risk level of abnormal vehicle use, as well as the actual driving trajectory, offset position and offset degree of the vehicle, which can provide parameter data for the judgment of vehicle use. In one embodiment, the vehicle running time is matched with the working time corresponding to the vehicle user unit to determine whether the vehicle running time is within the working time range. If it is, it matches, and if it is not, it does not match. Exemplarily, if the vehicle running time is 10:00 and the working time corresponding to the vehicle user unit is 9:00-18:00, the vehicle running time matches the working time corresponding to the vehicle user unit, and the second risk value is 0 at this time. If the vehicle running time is 20:00 and the working time corresponding to the vehicle user unit is 9:00-18:00, the second risk value is 1 at this time. The track offset, the first risk value, the second risk value, the first driving track and other information are combined to generate vehicle driving information, so as to determine the purpose of the vehicle based on the vehicle driving information.

[0037] The embodiment of the present application obtains vehicle operation information and vehicle application information of the vehicle in real time, wherein the vehicle application information includes the vehicle use starting point, vehicle use end point, vehicle use unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time; generates a first driving trajectory according to the vehicle real-time positioning information, generates a second driving trajectory according to the vehicle use starting point and vehicle use end point, and identifies multiple first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information; determines the corresponding second offset monitoring point on the second driving trajectory according to the distance from each first offset monitoring point to the vehicle use starting point, and determines the trajectory offset between the first offset monitoring point and the second offset monitoring point; determines the terminal position of the first driving trajectory, obtains the building information at the terminal position, matches the building use in the vehicle use reason and the building information, and determines the first risk value according to the matching result; matches the vehicle operation time with the working time corresponding to the vehicle use unit, determines the second risk value according to the matching result, and generates the vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory for judging the vehicle use. In the above scheme, the first offset monitoring point can be identified through the preset detection distance and the preset building information, thereby improving the accuracy of the first offset monitoring point and the accuracy of determining the trajectory offset. By respectively determining the trajectory offset, the first risk value, the second risk value and the first driving trajectory, and generating vehicle driving information including the trajectory offset, the first risk value, the second risk value and the first driving trajectory, the accuracy of the vehicle driving information and the accuracy of the vehicle purpose judgment are improved.

[0038] Optionally, generating vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory includes: Displaying the first driving track on a preset electronic map, and marking the first driving track on the preset electronic map according to the offset distance, the offset angle, and the first offset monitoring point to generate a vehicle offset marking map; The first risk value and the second risk value are weightedly calculated to obtain a vehicle abnormality risk value, and vehicle driving information is generated according to the vehicle offset mark map and the vehicle abnormality risk value.

[0039] Figure 2 is a schematic diagram of a vehicle offset mark provided in an embodiment of the present application, such as Figure 2As shown, a first driving trajectory is displayed on an electronic area of ​​a preset area, and a first offset monitoring point corresponding to the offset is marked on the first driving trajectory. The second offset monitoring point corresponding to the first offset detection point is determined according to the offset distance and the offset angle, and the first driving trajectory, the offset distance, the offset angle, the first offset monitoring point and the second offset monitoring point are marked on the preset electronic map to generate a vehicle offset marking map. In one embodiment, the abnormal risk of the vehicle use reason is calculated according to the first risk value and the preset first risk weight coefficient, and the abnormal risk of the vehicle use time is calculated according to the second risk value and the preset second risk weight coefficient. The abnormal risk of the vehicle use reason and the abnormal risk of the vehicle use time are summed and calculated to obtain the abnormal risk value of the vehicle, and the abnormal risk value of the vehicle is combined with the vehicle offset marking map to generate vehicle driving information. Among them, the preset first risk weight coefficient is used to indicate the degree of influence of the abnormal vehicle use reason on the judgment of the vehicle use, and the preset second risk weight coefficient is used to indicate the degree of influence of the abnormal vehicle use time on the judgment of the vehicle use.

[0040] The embodiment of the present application displays the first driving track on a preset electronic map, and marks the first driving track on the electronic map according to the offset distance, offset angle and first offset monitoring point, generating a vehicle offset mark map; performs weighted calculation on the first risk value and the second risk value to obtain the vehicle abnormal risk value, and displays the vehicle abnormal risk value in the vehicle offset mark map. In the above scheme, the accuracy of vehicle driving information is improved, and the display effect of vehicle driving information is improved by displaying the actual driving route of the vehicle, whether there is an offset and the specific offset situation.

[0041] Figure 3 is a flow chart of a method for identifying a first offset monitoring point provided in an embodiment of the present application. Figure 3 As shown, including: Step S1021, determining a first target detection range according to a preset detection distance and the first driving trajectory, calibrating the first target detection range according to terrain information within the first target detection range and the first driving trajectory, to obtain a second target detection range.

[0042] The first target detection range refers to an area around the first driving track, and the size of the area can be determined based on a preset detection distance. Figure 4 is a schematic diagram of a first target detection range provided in an embodiment of the present application, such as Figure 4As shown, if the preset detection distance is 100 meters, the upper and lower boundaries of the first target detection range are determined to be 100 meters on both sides of the first driving track. The left and right boundaries of the first target detection range can be determined according to the starting point of the vehicle and the end point of the first driving track. The boundary containing the starting point of the vehicle and the boundary containing the end point of the first driving track are determined as the left and right boundaries of the first target detection range, and the shape of the first target detection range composed of the left and right boundaries and the upper and lower boundaries can be a rectangle or an irregular shape. Terrain information refers to various data describing the morphological characteristics of the earth's surface and its related attributes, such as mountains, plateaus, plains, hills, lakes and basins. The second target detection range refers to a smaller detection range obtained after calibrating the first target detection range, and the second target detection range is smaller than the first target detection range. In one embodiment, after determining the first target detection range, the terrain information within the first target detection range is identified to determine the target terrain within the first target detection range. The target terrain may be a preset terrain that is inaccessible to the vehicle, such as a river, a lake, etc. According to the range of the target terrain, the first target detection range is calibrated according to the range of the target terrain to obtain the range within the first target detection range excluding the range of the target terrain, that is, the second target detection range.

[0043] Step S1022: identifying a target position within the second target detection range according to preset building information, determining a nearest monitoring point from the target position to the first driving trajectory, and determining the nearest monitoring point as a first offset monitoring point.

[0044] The preset building information can be used to indicate the building identification information of each entertainment venue, such as XX scenic spot, KTV, etc., and the target location is used to indicate the location of the building of each entertainment venue. In one embodiment, the location of the entertainment venue such as the scenic spot or KTV within the second target detection range is determined according to the preset building identification information, and the shortest distance from the target location to the first driving trajectory is calculated, and the point on the first driving trajectory corresponding to the shortest distance is determined as the nearest monitoring point, and the nearest monitoring point is determined as the first offset monitoring point.

[0045] The embodiment of the present application determines the first target detection range according to the preset detection distance and the first driving trajectory, calibrates the first target detection range according to the terrain information within the first target detection range and the first driving trajectory, and obtains the second target detection range; identifies the target position within the second target detection range according to the preset building information, determines the nearest monitoring point from the target position to the first driving trajectory, and determines the nearest monitoring point as the first offset monitoring point. In the above scheme, by calibrating the first target detection range to obtain the second target detection range, the recognition efficiency of subsequent target positions can be improved, and by determining the nearest monitoring point from the target position to the first driving trajectory as the first offset monitoring point, the first offset detection point can be made more accurate, thereby improving the accuracy of subsequent calculations of trajectory offsets.

[0046] In one embodiment, calibrating the first target detection range according to the terrain information within the first target detection range and the first driving trajectory includes: A non-target area is determined according to terrain information within the first target detection range, size information of the non-target area is determined according to preset area map data and the first driving trajectory, and the first target detection range is calibrated according to the size information.

[0047] Among them, the non-target area is an area where the terrain is inaccessible to the vehicle, such as an area where a river is located. The size information of the non-target area can be used to represent the area, boundary length, and boundary position of the non-target area. In one embodiment, the non-target area that is inaccessible to the vehicle is determined based on the terrain information of the first target detection range, and the boundary value of the non-target area is determined based on the first driving trajectory. Exemplarily, the distance between each boundary point of the non-target area and the first driving trajectory is determined, and the boundary point closest to the first driving trajectory is determined. A target boundary line parallel to the first driving trajectory is made through the boundary point, and the position of the target boundary line is determined according to the preset area map data, and the first detection range boundary line closest to the target boundary line in the first target detection range is determined, and the first detection range boundary line is adjusted to a position that coincides with the target boundary line.

[0048] The embodiment of the present application determines the non-target area according to the terrain information within the first target detection range, determines the size information of the non-target area according to the preset area map data and the first driving trajectory, and calibrates the first target detection range according to the size information. In the above scheme, the non-target area is determined by terrain information, and the first target detection range is calibrated based on the size information of the non-target area, which can exclude the area within the first target detection range that the vehicle cannot reach, improve the division accuracy of the target detection range, and improve the recognition efficiency of the subsequent target position.

[0049] Figure 5is a flow chart of a method for determining size information of a non-target area provided in an embodiment of the present application. Figure 5 As shown, including: Step S201: determining a first target detection range according to a preset detection distance and the first driving trajectory, and determining a non-target area according to terrain information within the first target detection range.

[0050] Step S202: determining the shortest distance from the first driving track to the non-target area according to preset map data, and determining a first adjustment point on the non-target area according to the shortest distance.

[0051] The preset map data is used to represent a map of a pre-selected area, and data on the map. The data on the map can be used to represent the distance between two coordinate points and the relative position relationship between the two coordinate points. The first adjustment point is a boundary point on the boundary of the non-target area, which can be used to determine the adjustment range. The number of the first adjustment point is one. In one embodiment, the distance from each boundary point on the boundary of the non-target area to the first driving trajectory is calculated according to the preset map data, and the shortest distance is determined. The boundary point corresponding to the shortest distance is determined as the first adjustment point on the non-target area.

[0052] Step S203: generate a position reference line of the non-target area according to the first adjustment point, traverse the reference points on the boundary of the non-target area, determine the reference point on one side of the position reference line as the first reference point, and determine the reference point on the other side of the position reference line as the second reference point.

[0053] The position reference line is a boundary line that divides the non-target area into two sub-areas, the first reference point is a boundary point of the non-target area on one side of the boundary line, and the second reference point is a boundary point of the non-target area on the other side of the boundary line. Figure 6 is a schematic diagram of a target detection range provided in an embodiment of the present application, such as Figure 6 As shown, a position reference line of the non-target area is generated through the first adjustment point, and the non-target area is divided into two left and right sub-areas, the reference points on the boundary of the left sub-area, that is, the boundary points, are traversed, and the reference points of the left area are determined as the first reference points, the reference points on the boundary of the right area are traversed, and the reference points of the right area are determined as the second reference points.

[0054] Step S204: Calculate the distances between each first reference point and each second reference point respectively, and determine the first reference point with the farthest distance as the second adjustment point, and determine the second reference point with the farthest distance as the third adjustment point.

[0055] The distances between each first reference point and each second reference point are determined respectively according to the preset map data, and the first reference point and the second reference point with the farthest distance are determined, the first reference point with the farthest distance is determined as the second adjustment point, and the second reference point with the farthest distance is determined as the third adjustment point.

[0056] Step S205: determine a target adjustment range according to the first adjustment point, the second adjustment point and the third adjustment point, and calibrate the first target detection range according to the target adjustment range to obtain a second target detection range.

[0057] The target adjustment range is used to represent the range to be reduced in the first target detection range, and the shape of the target adjustment range can be a rectangle or an irregular shape. In one embodiment, the upper boundary or the lower boundary of the adjustment range is determined according to the first adjustment point, the left boundary of the adjustment range is determined according to the second adjustment point, the right boundary of the adjustment range is determined according to the third adjustment point, the target adjustment range is determined according to the upper boundary or the lower boundary and the left boundary and the right boundary, and the first target detection range is adjusted according to the target adjustment range to obtain the first target detection range that does not include the target adjustment range, that is, the second target detection range.

[0058] Step S206: Identify the target position within the second target detection range according to the preset building information, determine the nearest monitoring point from the target position to the first driving trajectory, and determine the nearest monitoring point as the first offset monitoring point.

[0059] The embodiment of the present application determines the shortest distance from the first driving track to the non-target area according to the preset map data, determines the first adjustment point on the non-target area according to the shortest distance, generates a position reference line of the non-target area according to the first adjustment point, traverses the reference points on the boundary of the non-target area, determines the reference point on one side of the position reference line as the first reference point, and determines the reference point on the other side of the position reference line as the second reference point; The distance between each first reference point and each second reference point is calculated respectively, and the first reference point with the longest distance is determined as the second adjustment point, and the second reference point with the longest distance is determined as the third adjustment point; the target adjustment range is determined according to the first adjustment point, the second adjustment point and the third adjustment point, and the first target detection range is calibrated according to the target adjustment range. In the above scheme, by respectively determining the first adjustment point, the second adjustment point and the third adjustment point, and generating the target adjustment range, the calibration accuracy of the first target detection range can be improved, the accuracy of the second target detection range is improved, and the efficiency of target position recognition for the second target detection range is improved.

[0060] Figure 7 is a structural diagram of a vehicle driving information generation system based on vehicle positioning provided in an embodiment of the present application, such as Figure 7 As shown, including: The information acquisition module 31 is used to acquire the vehicle operation information and vehicle application information of the vehicle in real time, wherein the vehicle application information includes the vehicle starting point, the vehicle end point, the vehicle using unit and the vehicle using reason, and the vehicle operation information includes the vehicle real-time positioning information and the vehicle operation time; A driving trajectory generating module 32, configured to generate a first driving trajectory according to the real-time positioning information of the vehicle, and to generate a second driving trajectory according to the vehicle starting point and the vehicle end point; The offset monitoring point identification module 33 is used to identify a plurality of first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information, and determine a corresponding second offset monitoring point on the second driving trajectory according to the distance from each first offset monitoring point to the vehicle starting point; A trajectory deviation determination module 34, configured to determine a trajectory deviation between the first deviation monitoring point and the second deviation monitoring point; A first risk value determination module 35 is used to determine the end position of the first driving trajectory, obtain the building information of the end position, match the vehicle use reason with the building purpose in the building information, and determine the first risk value according to the matching result; A second risk value determination module 36 is used to match the vehicle operation time with the working time corresponding to the vehicle-using unit, and determine a second risk value according to the matching result; The vehicle driving information generating module 37 is used to generate vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory for determining the purpose of the vehicle.

[0061] The embodiment of the present application obtains vehicle operation information and vehicle application information of the vehicle in real time, wherein the vehicle application information includes the vehicle use starting point, vehicle use end point, vehicle use unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time; generates a first driving trajectory according to the vehicle real-time positioning information, generates a second driving trajectory according to the vehicle use starting point and vehicle use end point, and identifies multiple first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information; determines the corresponding second offset monitoring point on the second driving trajectory according to the distance from each first offset monitoring point to the vehicle use starting point, and determines the trajectory offset between the first offset monitoring point and the second offset monitoring point; determines the terminal position of the first driving trajectory, obtains the building information at the terminal position, matches the building use in the vehicle use reason and the building information, and determines the first risk value according to the matching result; matches the vehicle operation time with the working time corresponding to the vehicle use unit, determines the second risk value according to the matching result, and generates the vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory for judging the vehicle use. The first offset monitoring point can be identified through a preset detection distance and preset building information, thereby improving the accuracy of the first offset monitoring point and the accuracy of determining the trajectory offset. By respectively determining the trajectory offset, the first risk value, the second risk value and the first driving trajectory, and generating vehicle driving information including the trajectory offset, the first risk value, the second risk value and the first driving trajectory, the accuracy of the vehicle driving information and the accuracy of judging the purpose of the vehicle are improved.

[0062] In a possible embodiment, the deviation monitoring point identification module 33 is specifically used for: Determine a first target detection range according to a preset detection distance and the first driving trajectory, and calibrate the first target detection range according to terrain information within the first target detection range and the first driving trajectory to obtain a second target detection range; According to the preset building information, a target position within the second target detection range is identified, a nearest monitoring point from the target position to the first driving trajectory is determined, and the nearest monitoring point is determined as a first offset monitoring point.

[0063] In a possible embodiment, the deviation monitoring point identification module 33 is specifically used for: A non-target area is determined according to terrain information within the first target detection range, size information of the non-target area is determined according to preset area map data and the first driving trajectory, and the first target detection range is calibrated according to the size information.

[0064] In a possible embodiment, the deviation monitoring point identification module 33 is specifically used for: Determine the shortest distance from the first driving track to the non-target area according to preset map data, and determine a first adjustment point on the non-target area according to the shortest distance; Generate a position reference line of the non-target area according to the first adjustment point, traverse reference points on the boundary of the non-target area, determine a reference point on one side of the position reference line as a first reference point, and determine a reference point on the other side of the position reference line as a second reference point; Calculate the distance between each first reference point and each second reference point respectively, and determine the first reference point with the longest distance as the second adjustment point, and determine the second reference point with the longest distance as the third adjustment point; A target adjustment range is determined according to the first adjustment point, the second adjustment point, and the third adjustment point, and the first target detection range is calibrated according to the target adjustment range.

[0065] In a possible embodiment, the first risk value determination module 35 is used to: Determine a risk assessment range according to the coordinates of the end point position and a preset assessment distance, and obtain building information within the risk assessment range; The multiple building uses in the building information are matched with the vehicle use reasons respectively, and a first risk value is determined according to the number of matches. In a possible embodiment, the trajectory deviation determination module 34 is used to: The offset distance between the first offset monitoring point and the second offset monitoring point is calculated, and the offset distance is compared with a preset distance threshold. When the offset distance is greater than the preset distance threshold, the offset angle between the first offset monitoring point and the second offset monitoring point is determined.

[0066] In a possible embodiment, the vehicle driving information generating module 37 is specifically used for: Displaying the first driving track on a preset electronic map, and marking the first driving track on the electronic map according to the offset distance, the offset angle, and the first offset monitoring point to generate a vehicle offset marking map; The first risk value and the second risk value are weightedly calculated to obtain a vehicle abnormality risk value, and vehicle driving information is generated according to the vehicle offset mark map and the vehicle abnormality risk value.

[0067] The embodiment of the present application also provides a vehicle driving information generating device based on vehicle positioning, and the vehicle driving information generating device based on vehicle positioning can be integrated with a vehicle driving information generating system based on vehicle positioning provided in the embodiment of the present application. Figure 8is a schematic diagram of a vehicle driving information generating device based on vehicle positioning provided in an embodiment of the present application, with reference to Figure 8 The vehicle driving information generating device based on vehicle positioning includes: an input device 43, an output device 44, a memory 42 and one or more processors 41; the memory 42 is used to store one or more programs; when one or more programs are executed by one or more processors 41, the one or more processors 41 implement the vehicle driving information generating method based on vehicle positioning as provided in the above embodiment. The input device 43, the output device 44, the memory 42 and the processor 41 can be connected via a bus or other means. Figure 8 The example of connecting through bus is taken in the following.

[0068] The memory 42, as a computing device readable storage medium, can be used to store software programs, computer executable programs and modules, such as the program instructions / modules corresponding to the vehicle driving information generation method based on vehicle positioning provided in any embodiment of the present application. The memory 42 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the device, etc. In addition, the memory 42 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 42 may further include a memory remotely arranged relative to the processor 41, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0069] The input device 43 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 44 may include a display device such as a display screen.

[0070] The processor 41 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 42, that is, realizes the above-mentioned method for generating vehicle driving information based on vehicle positioning.

[0071] The vehicle driving information generation system, device and computer based on vehicle positioning provided above can be used to execute the vehicle driving information generation method based on vehicle positioning provided in any of the above embodiments, and have corresponding functions and beneficial effects.

[0072] The embodiment of the present application further provides a storage medium storing computer executable instructions. When the computer executable instructions are executed by a computer processor, they are used to execute the vehicle driving information generation method based on vehicle positioning as provided in the above embodiment. The vehicle driving information generation method based on vehicle positioning includes: Real-time acquisition of vehicle operation information and vehicle application information of the vehicle, wherein the vehicle application information includes the vehicle starting point, vehicle end point, vehicle using unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time; Generate a first driving trajectory according to the real-time positioning information of the vehicle, generate a second driving trajectory according to the vehicle starting point and the vehicle end point, and identify multiple first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information; Determine a corresponding second offset monitoring point on the second driving trajectory according to the distance from each first offset monitoring point to the starting point of the vehicle, and determine the trajectory offset between the first offset monitoring point and the second offset monitoring point; Determine the end position of the first driving trajectory, obtain the building information of the end position, match the vehicle use reason with the building purpose in the building information, and determine the first risk value according to the matching result; The vehicle operation time is matched with the working time corresponding to the vehicle-using unit, a second risk value is determined according to the matching result, and vehicle driving information is generated according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory for determining the purpose of the vehicle.

[0073] Storage medium - any of various types of memory devices or storage devices. The term "storage medium" is intended to include: installation media, such as CD-ROM, floppy disk or tape device; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (such as hard disk or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the first computer system in which the program is executed, or may be located in a different second computer system, which is connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations (for example, in different computer systems connected by a network). The storage medium may store program instructions (for example, embodied as a computer program) that can be executed by one or more processors.

[0074] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present application, whose computer executable instructions are not limited to the vehicle driving information generation method based on vehicle positioning as described above, can also execute related operations in the vehicle driving information generation method based on vehicle positioning provided in any embodiment of the present application.

[0075] The vehicle driving information generation system, device and storage medium based on vehicle positioning provided in the above embodiments can execute the vehicle driving information generation method based on vehicle positioning provided in any embodiment of the present application. For technical details not described in detail in the above embodiments, please refer to the vehicle driving information generation method based on vehicle positioning provided in any embodiment of the present application.

[0076] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A method for generating vehicle driving information based on vehicle positioning, characterized in that: include: Acquire the vehicle operation information and vehicle application information of the vehicle in real time, wherein the vehicle application information includes the vehicle starting point, vehicle end point, vehicle using unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time; Generate a first driving trajectory according to the real-time positioning information of the vehicle, generate a second driving trajectory according to the vehicle starting point and the vehicle end point, and identify multiple first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information; Determine a corresponding second offset monitoring point on the second driving trajectory according to the distance from each first offset monitoring point to the starting point of the vehicle, and determine the trajectory offset between the first offset monitoring point and the second offset monitoring point; Determine the end position of the first driving trajectory, obtain the building information of the end position, match the vehicle use reason with the building purpose in the building information, and determine the first risk value according to the matching result; The vehicle operation time is matched with the working time corresponding to the vehicle-using unit, a second risk value is determined according to the matching result, and vehicle driving information is generated according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory for determining the purpose of the vehicle.

2. The method for generating vehicle driving information based on vehicle positioning according to claim 1, characterized in that: The step of identifying a plurality of first offset monitoring points on the first driving track according to a preset detection distance and preset building information includes: Determine a first target detection range according to a preset detection distance and the first driving trajectory, and calibrate the first target detection range according to terrain information within the first target detection range and the first driving trajectory to obtain a second target detection range; According to the preset building information, a target position within the second target detection range is identified, a nearest monitoring point from the target position to the first driving trajectory is determined, and the nearest monitoring point is determined as a first offset monitoring point.

3. The method for generating vehicle driving information based on vehicle positioning according to claim 2, characterized in that: The calibrating the first target detection range according to the terrain information within the first target detection range and the first driving trajectory includes: A non-target area is determined according to terrain information within the first target detection range, size information of the non-target area is determined according to preset area map data and the first driving trajectory, and the first target detection range is calibrated according to the size information.

4. The method for generating vehicle driving information based on vehicle positioning according to claim 3, characterized in that: The determining the size information of the non-target area according to the preset area map data and the first driving trajectory, and calibrating the first target detection range according to the size information, includes: Determine the shortest distance from the first driving track to the non-target area according to preset map data, and determine a first adjustment point on the non-target area according to the shortest distance; Generate a position reference line of the non-target area according to the first adjustment point, traverse reference points on the boundary of the non-target area, determine a reference point on one side of the position reference line as a first reference point, and determine a reference point on the other side of the position reference line as a second reference point; Calculate the distance between each first reference point and each second reference point respectively, and determine the first reference point with the longest distance as the second adjustment point, and determine the second reference point with the longest distance as the third adjustment point; A target adjustment range is determined according to the first adjustment point, the second adjustment point, and the third adjustment point, and the first target detection range is calibrated according to the target adjustment range.

5. The method for generating vehicle driving information based on vehicle positioning according to claim 1, characterized in that: The acquiring of the building information of the destination location, matching the vehicle use reason with the building purpose in the building information, and determining the first risk value according to the matching result includes: Determine a risk assessment range according to the coordinates of the end point position and a preset assessment distance, and obtain building information within the risk assessment range; The multiple building uses in the building information are matched with the vehicle use reasons respectively, and a first risk value is determined according to the number of matches.

6. The method for generating vehicle driving information based on vehicle positioning according to claim 1, characterized in that: The determining of the trajectory offset between the first offset monitoring point and the second offset monitoring point includes: The offset distance between the first offset monitoring point and the second offset monitoring point is calculated, and the offset distance is compared with a preset distance threshold. When the offset distance is greater than the preset distance threshold, the offset angle between the first offset monitoring point and the second offset monitoring point is determined.

7. The method for generating vehicle driving information based on vehicle positioning according to claim 6, characterized in that: The generating the vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory includes: Displaying the first driving track on a preset electronic map, and marking the first driving track on the preset electronic map according to the offset distance, the offset angle, and the first offset monitoring point to generate a vehicle offset marking map; The first risk value and the second risk value are weightedly calculated to obtain a vehicle abnormality risk value, and vehicle driving information is generated according to the vehicle offset mark map and the vehicle abnormality risk value.

8. A vehicle driving information generation system based on vehicle positioning, characterized in that: include: An information acquisition module is used to acquire vehicle operation information and vehicle application information of the vehicle in real time, wherein the vehicle application information includes the vehicle starting point, vehicle end point, vehicle using unit and vehicle use reason, and the vehicle operation information includes the vehicle real-time positioning information and vehicle operation time; A driving trajectory generating module, used to generate a first driving trajectory according to the real-time positioning information of the vehicle, and to generate a second driving trajectory according to the starting point and the end point of the vehicle; an offset monitoring point identification module, used to identify a plurality of first offset monitoring points on the first driving trajectory according to a preset detection distance and preset building information, and determine a corresponding second offset monitoring point on the second driving trajectory according to the distance from each first offset monitoring point to the starting point of the vehicle; A trajectory deviation determination module, used to determine the trajectory deviation between the first deviation monitoring point and the second deviation monitoring point; a first risk value determination module, configured to determine the terminal position of the first driving trajectory, obtain building information at the terminal position, match the vehicle use reason with the building purpose in the building information, and determine a first risk value according to the matching result; A second risk value determination module is used to match the vehicle operation time with the working time corresponding to the vehicle-using unit, and determine a second risk value according to the matching result; The vehicle driving information generating module is used to generate vehicle driving information according to the trajectory offset, the first risk value, the second risk value and the first driving trajectory, so as to be used for determining the purpose of the vehicle.

9. An electronic device, comprising: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle driving information generation method based on vehicle positioning as described in any one of claims 1-7.

10. A storage medium storing computer executable instructions, wherein the computer executable instructions are used to execute the vehicle driving information generation method based on vehicle positioning according to any one of claims 1 to 7 when executed by a computer processor.

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