Vehicle driving behavior monitoring method and device

Abstract

The invention provides a vehicle driving behavior monitoring method and device, and relates to the technical field of intelligent monitoring, and the method comprises the steps: obtaining positioning points corresponding to a driving track of a target vehicle, collecting the vehicle sensor information of each positioning point, carrying out the track segmentation of the driving track, obtaining the track segmentation information, and carrying out the monitoring of the vehicle driving behavior. And on the basis of automatically segmenting the driving track of the target vehicle, further determining the vehicle driving behavior according to track segmentation information. According to the vehicle driving behavior monitoring method provided by the invention, the rationality and accuracy of track automatic segmentation are improved, and the vehicle driving behavior can be further determined according to track segmentation information.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to a vehicle driving behavior monitoring method and device. Background Art

[0002] The vehicle trajectory automatic segmentation method is a key technology for processing continuous trajectory data, and is mainly used in data analysis, behavior recognition, path planning, etc. In the prior art, trajectory segmentation methods mainly include: time interval segmentation method and time period segmentation method.

[0003] Time interval segmentation method: By setting a fixed time threshold, when the time difference between two adjacent trajectory points exceeds this threshold, the trajectory is cut between these two points. This method does not take into account abnormal vehicle conditions, such as using a backup power supply to upload positioning information when the vehicle is turned off, and the speed of the vehicle is 0 when it is parked; Time segmentation method: The trajectory is divided according to a specific time period (such as natural days, hours, etc.). If the trajectory crosses the boundary of the set time period, it is cut at the boundary. This method has fixed segmentation and does not take into account the driving scene. It often splits a complete driving trajectory into multiple segments.

[0004] The segmentation method in the prior art not only has low accuracy, but also does not involve analysis of vehicle driving behavior. Summary of the invention

[0005] The present invention provides a vehicle driving behavior monitoring method and device to solve the above problems existing in the prior art.

[0006] The present invention provides a vehicle driving behavior monitoring method, comprising the following steps.

[0007] Obtaining the positioning points corresponding to the driving trajectory of the target vehicle, and collecting vehicle sensor information at each positioning point; Segmenting the driving trajectory according to the vehicle sensor information and recording trajectory segmentation information; The vehicle driving behavior is determined based on all trajectory segment information.

[0008] According to a vehicle driving behavior monitoring method provided by the present invention, the vehicle sensor information includes vehicle speed and ACC state information.

[0009] According to a vehicle driving behavior monitoring method provided by the present invention, segmenting the driving trajectory according to the vehicle sensor information includes: According to the time interval between the positioning time of the current positioning point and the last speed time, determine whether the current positioning point is used as the starting point of a new trajectory segment; When the time interval is greater than a preset threshold, the current positioning point is determined as the starting point of a new trajectory segment, and the end point of the previous trajectory segment is determined as the positioning point corresponding to the last speed time.

[0010] According to a vehicle driving behavior monitoring method provided by the present invention, the recorded trajectory segment information includes: Record the mileage summary, effective speed summary, number of effective speed items, segment start time, and segment end time of the track segment.

[0011] According to a vehicle driving behavior monitoring method provided by the present invention, the recorded trajectory segment information includes: Calculate the distance between two adjacent positioning points in the trajectory segment; And the distances between all adjacent positioning are accumulated to obtain the mileage summary of the trajectory segment.

[0012] According to a vehicle driving behavior monitoring method provided by the present invention, the recorded trajectory segment information includes: Determine the positioning validity and speed validity of each positioning point in the trajectory segment; if the corresponding position data of the positioning point exists and the acc state information is in the ignition state, the positioning is valid, and if the speed corresponding to the positioning point is greater than zero, the speed is valid; The effective speed summary and the number of effective speed items are determined based on the speed corresponding to the effective positioning point and the number of effective positioning points.

[0013] The present invention also provides a vehicle driving behavior monitoring device, comprising the following modules: An acquisition module is used to acquire the positioning points corresponding to the driving trajectory of the target vehicle and collect vehicle sensor information at each positioning point; A segmentation module, used to segment the driving trajectory according to the vehicle sensor information and record trajectory segmentation information; The determination module is used to determine the vehicle driving behavior based on all trajectory segment information.

[0014] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the vehicle driving behavior monitoring method described in any one of the above methods is implemented.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the vehicle driving behavior monitoring method as described in any one of the above is implemented.

[0016] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the vehicle driving behavior monitoring method as described above is implemented.

[0017] The present invention provides a vehicle driving behavior monitoring method, which obtains positioning points corresponding to the driving trajectory of a target vehicle and collects vehicle sensor information at each positioning point, segments the driving trajectory, obtains trajectory segmentation information, and improves the rationality and accuracy of automatic trajectory segmentation; then, on the basis of accurately and reasonably segmenting the driving trajectory of the target vehicle, further determines the vehicle driving behavior according to the trajectory segmentation information, including whether the vehicle is parked for a long time in a time period; and how many times the driver has driven, the distance of each driving, and the driving time interval in other time periods. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flow chart of a vehicle driving behavior monitoring method provided by the present invention.

[0020] Figure 2 It is a schematic diagram of algorithm implementation relationship dependency steps in a vehicle driving behavior monitoring method provided by the present invention.

[0021] Figure 3 It is a structural schematic diagram of a vehicle driving behavior monitoring device provided by the present invention.

[0022] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0023] For long-term trajectory records, from the perspective of data management, if they are processed as a whole, the amount of data will often be too large to be effectively stored, retrieved, and analyzed. Segmentation can simplify data management and processing. Therefore, it is often necessary to segment the trajectory to simplify data management and processing.

[0024] In the prior art, the time interval segmentation method does not take into account abnormal vehicle conditions. For example, when the vehicle is turned off, the backup power supply is used to upload the positioning information, and when the vehicle is parked, the speed is 0. The time period segmentation method often has fixed segments and does not take into account the driving scene, which will split a complete driving trajectory into multiple segments.

[0025] In addition, the segmentation method in the prior art only considers the problems of low retrieval efficiency and poor rendering performance caused by excessive data volume, but does not involve the driver's behavior analysis.

[0026] The present invention provides a vehicle driving behavior monitoring method, which determines the vehicle condition based on the vehicle sensor information, and filters invalid positioning in scenarios such as engine shutdown (the vehicle's built-in battery uploads trajectory positioning data), long-term parking, etc. At the same time, it can also analyze the driver's behavior, such as how many times the driver has driven in a certain period of time, the distance of each driving, and the time interval, etc.

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] Combine the following Figures 1 to 4 The vehicle driving behavior monitoring method and device of the present invention are described.

[0029] The vehicle driving behavior monitoring method provided by the present invention includes obtaining vehicle trajectory data and vehicle sensor data. By obtaining sensor data to determine whether the vehicle is operating normally, filtering abnormal positioning information, and comprehensively judging whether the trajectory is segmented based on the vehicle driving conditions and positioning information, the rationality and accuracy of automatic trajectory segmentation are improved. At the same time, the driver's behavior can also be analyzed, such as how many times the driver has traveled in a certain period of time, the distance of each travel, and the time interval, etc.

[0030] Figure 1 is a flow chart of a vehicle driving behavior monitoring method provided by the present invention, such as Figure 1 As shown, the method includes the following: Step 101: Acquire the positioning points corresponding to the driving trajectory of the target vehicle, and collect vehicle sensor information at each positioning point.

[0031] In any driving trajectory of the target vehicle, multiple positioning points are set, and the location information of these positioning points is obtained through the Beidou navigation system.

[0032] Optionally, the vehicle sensor information includes vehicle speed and acc status information.

[0033] Specifically, the vehicle speed information and the ACC state of the vehicle (i.e., whether the vehicle is in the ignition state or the ignition off state) are collected through the vehicle sensor, and whether the vehicle is operating normally is determined based on the vehicle speed information and the ACC state of the vehicle. For example, if the vehicle speed is not 0 and is in the ignition state, the vehicle is determined to be operating normally; if the vehicle speed is 0 and / or is in the ignition off state, the vehicle is determined to be not operating.

[0034] Step 102: segment the driving trajectory according to the vehicle sensor information, and record trajectory segment information.

[0035] Optionally, segmenting the driving trajectory according to the vehicle sensor information includes: According to the time interval between the positioning time of the current positioning point and the last speed time, determine whether the current positioning point is used as the starting point of a new trajectory segment; When the time interval is greater than a preset threshold, the current positioning point is determined as the starting point of a new trajectory segment, and the end point of the previous trajectory segment is determined as the positioning point corresponding to the last speed time.

[0036] Specifically, in an embodiment of the present invention, the threshold of the time interval between the positioning time of the current positioning point and the last speed time is set to 10 minutes (in other scenarios or embodiments, the threshold can also be set to any other value such as 20 minutes or 40 minutes. In the embodiment of the present invention, the threshold is set to 10 minutes as an example for explanation).

[0037] Assuming that the positioning time of the current position of the target vehicle is 10:00, and the last time the target vehicle had speed (i.e., the speed was greater than zero) was 9:30, the time interval is 30 minutes, which is greater than the threshold (10 minutes). At this time, the current positioning point (i.e., the positioning point corresponding to 10:00) can be used as the starting point of a new driving trajectory segment, and the positioning point corresponding to 9:30 can be used as the positioning point corresponding to the last time there was speed (i.e., the speed was greater than zero).

[0038] Optionally, the recorded trajectory segmentation information includes: Record the mileage summary, effective speed summary, number of effective speed items, segment start time, and segment end time of the track segment.

[0039] Specifically, the track segment information includes mileage summary, effective speed summary, number of effective speed items, segment start time and segment end time.

[0040] Assume that the positioning time of the current positioning point of the target vehicle is 10:00, and the last time the target vehicle had speed (i.e., speed greater than zero) was 9:30, which is greater than the threshold (10 minutes). Then the positioning point corresponding to 10:00 is the starting point of a new trajectory segment, and the segment start time is 10:00. The positioning point corresponding to 9:30 is the positioning point corresponding to the last time with speed (i.e., speed greater than zero), and 9:30 is the segment end time of the previous segment.

[0041] Optionally, the recorded trajectory segmentation information includes: Determine the positioning validity and speed validity of each positioning point in the trajectory segment; if the corresponding position data of the positioning point exists and the acc state information is in the ignition state, the positioning is valid, and if the speed corresponding to the positioning point is greater than zero, the speed is valid; The effective speed summary and the number of effective speed items are determined based on the speed corresponding to the effective positioning point and the number of effective positioning points.

[0042] Specifically, if the current positioning speed is greater than zero, the effective speed summary is added to the current positioning speed, and the number of effective speeds is added by 1; the last speed (positioning speed is greater than zero) time is the positioning time corresponding to the last speed moment.

[0043] Assume that the positioning time of the current positioning point of the target vehicle is 10:00, the location data corresponding to the positioning point is A Square (the location data can also be other locations such as B Street or C Building, as long as the latitude and longitude coordinates are valid), and the speed is 20 kilometers per hour (the speed can also be other values ​​such as 10 kilometers per hour or 30 kilometers per hour, as long as it is greater than 0), then it means that the positioning of the target vehicle at 10:00 is valid and the speed is valid. At this time, the positioning point corresponding to 10:00 (ie, A Square) is recorded as a valid positioning point, and the total number of valid positioning points is increased by 1 to determine the effective speed summary; the speed corresponding to 10:00 is the effective speed (ie, 20 kilometers per hour), and the total number of effective speed items is increased by 1 to determine the number of effective speed items.

[0044] Optionally, the recorded trajectory segmentation information includes: Calculate the distance between two adjacent positioning points in the trajectory segment; And the distances between all adjacent positioning are accumulated to obtain the mileage summary of the trajectory segment.

[0045] Specifically, a track segment contains multiple sub-segments, and each sub-segment contains multiple vehicle positioning coordinates. For example, a sub-segment contains four vehicle positioning coordinates, namely positioning 1 (initial positioning), positioning 2, positioning 3, and positioning 4. When calculating the mileage of this sub-segment, first set positioning 1 as the primary coordinate, and then determine whether positioning 2 can be used as a secondary coordinate based on the time interval between the positioning time of positioning 2 and the positioning time of positioning 1 (i.e., the last time there was speed).

[0046] Assume that the threshold value of the time interval is 10 minutes.

[0047] When the time interval between the positioning time of positioning 2 and the positioning time of positioning 1 is less than or equal to 10 minutes: If positioning 2 is valid, positioning 2 is used as the secondary coordinate. At this time, the distance between positioning 1 and positioning 2 and other data information are calculated, and then positioning 2 is reset as the primary coordinate; Continue to use the above method to determine whether location 3 is set as the secondary coordinate. If so, calculate the distance between location 2 and location 3; If positioning 3 has speed, the speed is accumulated and the number of speed bars is accumulated.

[0048] When the time interval between the positioning time of positioning 2 and the positioning time of positioning 1 is greater than 10 minutes: If the location before and after positioning 1 is not involved in the calculation, it is an isolated point, the start and end time of the segment are both the positioning time of positioning 1, and the segment mileage is 0.

[0049] When the time interval between positioning 3 and positioning 2 is greater than 10 minutes: If positioning 3 is valid, the coordinates and positioning time of positioning 2 are the end coordinates and end time of the previous segment, and the coordinates of positioning 3 are the start coordinates of the next segment; If positioning 3 has speed, the positioning time of positioning 3 is the start time of the next segment.

[0050] Similarly, multiple mileage values ​​can be obtained by calculation, and the mileage summary of multiple sub-segments in the trajectory segment can be obtained by accumulating them.

[0051] The vehicle driving behavior monitoring method provided by the present invention determines the vehicle condition based on the vehicle sensor information, and filters out invalid positioning in scenarios such as engine shutdown (the vehicle's built-in battery uploads trajectory positioning data) or long-term parking during segmentation, so as to avoid multiple segmentation of the driving trajectory caused by invalid positioning. For example, the positioning data when the vehicle is turned off or parked is concentrated in one position, resulting in meaningless segmentation. By filtering out the meaningless segmentation, the accuracy of the vehicle driving trajectory segmentation is improved.

[0052] The vehicle driving behavior monitoring method provided by the present invention has flexible segmentation, judges the vehicle condition according to the vehicle sensor information (including vehicle speed and ACC status information, etc.), and performs segmentation in combination with specific driving scenarios. It will not split a complete driving trajectory into multiple segments, thereby improving the rationality of the driving trajectory segmentation of the target vehicle.

[0053] Based on any of the above embodiments, the actual calculation process involved in the trajectory segmentation process in the embodiment of the present invention is described below. Figure 2 Schematic diagram of algorithm implementation relationship dependency steps in a vehicle driving behavior monitoring method provided by the present invention. Figure 2 shown.

[0054] First, construct the initialization values.

[0055] Mileage summary: mileageSum is 0 (mileage of each segmented trajectory).

[0056] Effective speed summary: speedSum is 0 (the effective speed of each segmented trajectory is accumulated and summarized).

[0057] Number of valid speeds: speedCount is 0 (the number of valid speeds for each segmented trajectory is summarized).

[0058] First coordinates: (Lat1, Lng1) (the latitude and longitude coordinates where the segment positioning starts).

[0059] Secondary coordinates: (Lat2, Lng2) (the latitude and longitude coordinates of the segment’s end location).

[0060] Segment start time: beginTime.

[0061] Segment end time: splitSpeedTime.

[0062] Finally there is speed time: lastSpeedTime.

[0063] Secondly, a batch of trajectory positioning points are taken cyclically to record the trajectory segment information, mainly including the mileage and average speed of the segment.

[0064] The mileage between the first and second coordinates of a segment is calculated as follows: Given the positions of two points P1 (positioning start) and P2 (positioning end) on the surface of the earth, the latitude and longitude coordinates of P1 are (Lat1, Lng1), and the latitude and longitude coordinates of P2 are (Lat2, Lng2).

[0065] The great circle distance d (in meters) between these two points can be calculated by following these steps: (1) Convert latitude and longitude from degrees to radians, where The radian corresponding to the latitude coordinate lat1 of P1, The radian corresponding to the latitude coordinate lat2 of P2, It is the difference in radians between the longitude coordinate lng2 of P2 and the longitude coordinate lng1 of P1.

[0066] =lat1× , =lat2× , =(lng2−lng1)×

[0067] (2) Calculate the intermediate value a: a=sin( )⋅sin( )+cos( )⋅cos( )⋅cos( )

[0068] (3) Calculate the angular distance θ between points P1 and P2 (in radians): θ=arccos(min(a,1))

[0069] (4) Finally, calculate the distance d (in meters) between points P1 and P2 by multiplying the angular distance by the mean radius R of the Earth: d = θ⋅R

[0070] Where: R is the mean radius of the Earth (approximately 6371000 meters); arccos is the inverse cosine function; min(a, 1) ensures that the argument of the arccos function does not exceed 1, which is to avoid problems caused by rounding errors in numerical calculations.

[0071] The average speed avgSpeed ​​between the first and second coordinates of the segment is calculated as follows (retain two decimal places): avgSpeed=Math.round(AvgSpeed*100.0) / 100.0

[0072] Based on any of the above embodiments, before recording the track segment information, it is also necessary to determine whether the track segment information is a starting point.

[0073] For example, if the target vehicle has been stationary and starts for the first time at 10:00 (the speed at 10:00 is greater than 0), then the positioning point corresponding to 10:00 can be used as the starting point of a new trajectory segment. The valid positioning and valid speed corresponding to 10:00 are the first data, indicating that it is the first data of this batch of trajectory positioning. At this time, the mileage summary, valid speed summary, number of valid speeds, segment start time, and segment end time are initialized. The segment start time is 10:00, that is, starting from 10:00, the subsequent driving trajectory of the target vehicle is segmented and the trajectory segment information is recorded.

[0074] Step 103: Determine the vehicle driving behavior based on all the trajectory segment information.

[0075] Based on the accurate and reasonable segmentation of the target vehicle trajectory information, the embodiment of the present invention further determines the vehicle driving behavior based on the segmentation results of the trajectory information. For example, in a certain time period, the vehicle is parked for a long time; in other time periods, how many times the driver drove, the distance of each driving, and the time interval, etc.

[0076] The present invention provides a vehicle driving behavior monitoring method, which determines whether the vehicle is running normally by acquiring vehicle trajectory data and vehicle sensor data, and filters abnormal or invalid positioning information according to the vehicle driving conditions and positioning information, and comprehensively determines whether the driving trajectory needs to be segmented, thereby improving the rationality and accuracy of automatic trajectory segmentation; then, on the basis of accurately and reasonably segmenting the target vehicle trajectory information, based on the segmentation results of the trajectory information, the vehicle driving behavior is further determined, including whether the vehicle is parked for a long time in a time period; in other time periods, how many times the driver has driven, the distance of each driving, and the driving time interval, etc.

[0077] A vehicle driving behavior monitoring device provided by the present invention is described below. The vehicle driving behavior monitoring device described below and the vehicle driving behavior monitoring method described above can be referenced to each other.

[0078] Based on any of the above embodiments, Figure 3 is a structural schematic diagram of a vehicle driving behavior monitoring device provided by the present invention, such as Figure 3 As shown, an embodiment of the present invention provides a vehicle driving behavior monitoring device, including an acquisition module 301, a segmentation module 302 and a determination module 303, wherein: The acquisition module 301 is used to obtain the positioning points corresponding to the driving trajectory of the target vehicle and collect the vehicle sensor information of each positioning point; the segmentation module 302 is used to segment the driving trajectory according to the vehicle sensor information and record the trajectory segmentation information; the determination module 303 is used to determine the vehicle driving behavior based on all the trajectory segmentation information.

[0079] A vehicle driving behavior monitoring device provided by the present invention determines whether the vehicle is running normally by acquiring vehicle trajectory data and vehicle sensor data, and filters abnormal or invalid positioning information according to the vehicle driving conditions and positioning information, and comprehensively determines whether the driving trajectory needs to be segmented, thereby improving the rationality and accuracy of automatic trajectory segmentation; then, on the basis of accurately and reasonably segmenting the target vehicle trajectory information, based on the segmentation results of the trajectory information, the vehicle driving behavior is further determined, including whether the vehicle is parked for a long time in a time period; in other time periods, how many times the driver has driven, the distance of each driving, and the driving time interval, etc.

[0080] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communications interface 420 and the memory 430 communicate with each other via the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the vehicle driving behavior monitoring method, which includes: Obtaining the positioning points corresponding to the driving trajectory of the target vehicle, and collecting vehicle sensor information at each positioning point; Segmenting the driving trajectory according to the vehicle sensor information and recording trajectory segmentation information; The vehicle driving behavior is determined based on all trajectory segment information.

[0081] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0082] On the other hand, the present invention further provides a computer program product, the computer program product includes a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute the vehicle driving behavior monitoring method provided by the above methods, the method includes: Obtaining the positioning points corresponding to the driving trajectory of the target vehicle, and collecting vehicle sensor information at each positioning point; Segmenting the driving trajectory according to the vehicle sensor information and recording trajectory segmentation information; The vehicle driving behavior is determined based on all trajectory segment information.

[0083] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the vehicle driving behavior monitoring method provided by the above methods is implemented, and the method includes: Obtaining the positioning points corresponding to the driving trajectory of the target vehicle, and collecting vehicle sensor information at each positioning point; Segmenting the driving trajectory according to the vehicle sensor information and recording trajectory segmentation information; The vehicle driving behavior is determined based on all trajectory segment information.

[0084] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0085] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0086] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0087] It should also be noted that the terms "target", "first", "second", etc. in the present invention are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms 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 herein, and the objects distinguished by "first" and "second" are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more.

[0088] In the present invention, the term "plurality" refers to two or more than two, and other quantifiers are similar to them.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle driving behavior monitoring method, characterized in that: include: Obtaining the positioning points corresponding to the driving trajectory of the target vehicle, and collecting vehicle sensor information at each positioning point; Segmenting the driving trajectory according to the vehicle sensor information and recording trajectory segmentation information; The vehicle driving behavior is determined based on all trajectory segment information.

2. The vehicle driving behavior monitoring method according to claim 1, characterized in that: The vehicle sensor information includes vehicle speed and acc status information.

3. The vehicle driving behavior monitoring method according to claim 1, characterized in that: The segmenting the driving trajectory according to the vehicle sensor information includes: According to the time interval between the positioning time of the current positioning point and the last speed time, determine whether the current positioning point is used as the starting point of a new trajectory segment; When the time interval is greater than a preset threshold, the current positioning point is determined as the starting point of a new trajectory segment, and the end point of the previous trajectory segment is determined as the positioning point corresponding to the last speed time.

4. The vehicle driving behavior monitoring method according to claim 1, characterized in that: The recorded track segmentation information includes: Record the mileage summary, effective speed summary, number of effective speed items, segment start time, and segment end time of the track segment.

5. The vehicle driving behavior monitoring method according to claim 1, characterized in that: The recorded track segmentation information includes: Calculate the distance between two adjacent positioning points in the trajectory segment; And the distances between all adjacent positioning are accumulated to obtain the mileage summary of the trajectory segment.

6. The vehicle driving behavior monitoring method according to claim 1, characterized in that: The recorded track segmentation information includes: Determine the positioning validity and speed validity of each positioning point in the trajectory segment; if the corresponding position data of the positioning point exists and the acc state information is in the ignition state, the positioning is valid, and if the speed corresponding to the positioning point is greater than zero, the speed is valid; The effective speed summary and the number of effective speed items are determined based on the speed corresponding to the effective positioning point and the number of effective positioning points.

7. A vehicle driving behavior monitoring device, characterized in that: include: An acquisition module is used to acquire the positioning points corresponding to the driving trajectory of the target vehicle and collect vehicle sensor information at each positioning point; A segmentation module, used to segment the driving trajectory according to the vehicle sensor information and record trajectory segmentation information; The determination module is used to determine the vehicle driving behavior based on all trajectory segment information.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the vehicle driving behavior monitoring method as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle driving behavior monitoring method as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the vehicle driving behavior monitoring method as described in any one of claims 1 to 6 is implemented.

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