CN118396506B - Method, device and storage medium for detecting driving behavior of vehicle based on driving track - Google Patents
Method, device and storage medium for detecting driving behavior of vehicle based on driving track Download PDFInfo
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Abstract
The application relates to the technical field of vehicle safety detection, and provides a method, a device and a storage medium for detecting vehicle driving behaviors based on a driving track. The method comprises the following steps: selecting one non-ship invoice from a plurality of non-ship invoices corresponding to the vehicles to be detected as a to-be-processed invoice; selecting N track points to be analyzed from a plurality of track points included in a transportation track of the invoice to be processed; dividing N track points to be analyzed into a plurality of track clues when the value of N is larger than or equal to a preset value; determining the processing sequence of all track cue groups according to the track points to be analyzed in each track cue group; arranging the processing sequence in a first track cue group as a current cue group; determining a first attribute characteristic of the current cue group according to first track data of track points to be analyzed in the current cue group; and determining whether the driving behavior of the vehicle to be detected is compliant according to the first track data or the first attribute characteristics, so that the judgment of the compliance of the driving behavior of the vehicle is more accurate.
Description
Technical Field
The application relates to the technical field of vehicle safety detection, in particular to a method, a device and a storage medium for detecting vehicle driving behaviors based on a driving track.
Background
Drivers drive vehicles to transport goods to destinations, and many drivers often have problems such as fatigue driving, speeding, night driving, and parking in a place without any reason in order to rapidly complete goods transportation tasks due to lack of an effective supervision method, thereby causing delays in goods transportation.
In the prior art, in order to ensure safe transportation of goods and timely delivery to a destination, driving behavior of a vehicle is generally monitored in real time by installing a monitoring device. However, by monitoring the driving behavior of the vehicle in this way, the monitoring device needs to be installed before the transportation, the monitoring device needs to be removed and returned after the vehicle arrives at the destination, the required cost is high, if the monitoring device is lost or damaged during the transportation, the follow-up judgment of compliance for the driving of the vehicle is not accurate enough, and the driver is difficult to prompt in time to transport the goods according to the preset time and place, so that the goods transportation is delayed.
Disclosure of Invention
The embodiment of the application aims to provide a method, a device and a storage medium for detecting vehicle driving behaviors based on a driving track, which are used for solving the problem of inaccurate compliance judgment for vehicle driving in the prior art.
In order to achieve the above object, a first aspect of the present application provides a method for detecting driving behavior of a vehicle based on a track, including:
selecting one non-ship invoice from a plurality of non-ship invoices corresponding to the vehicles to be detected as a to-be-processed invoice;
Acquiring a transport track of an invoice to be processed, wherein the transport track comprises a plurality of track points which are passed by a vehicle to be detected from the starting transport moment to the current transport moment;
selecting N track points to be analyzed from a plurality of track points, wherein N is a natural number;
dividing N track points to be analyzed into a plurality of track cue groups under the condition that the value of N is larger than or equal to a preset value, wherein each track cue group consists of track points to be analyzed of any two adjacent time points;
sequencing the processing sequence of all track cue groups according to the track points to be analyzed with the earliest transportation time or the latest transportation time in each track cue group, wherein the processing sequence of the track cue group where the track points to be analyzed with the earliest transportation time are positioned is positioned at the front;
arranging the processing sequence in a first track cue group as a current cue group;
determining a first attribute characteristic of the current cue group according to first track data of track points to be analyzed in the current cue group;
Under the condition that the generation condition of any one of the first types of driving events is met according to the first track data or the first attribute characteristics, determining the state of the first type of driving event as a generated state, and determining the first type of driving event of the generated state as a first event to be triggered;
Determining a track point to be analyzed corresponding to the earliest time in the current clue group as a first evidence track point of a first event to be triggered;
Determining a track point to be analyzed corresponding to the latest time in the current clue group as a second evidence track point of the first event to be triggered;
And determining whether the driving behavior of the vehicle to be detected is compliant according to the first evidence track point and the second evidence track point.
A second aspect of the present application provides an apparatus for detecting driving behavior of a vehicle based on a track, including:
a memory configured to store instructions; and
And the processor is configured to call the instruction from the memory and can realize the method for detecting the driving behavior of the vehicle based on the driving track when executing the instruction.
A third aspect of the application provides a machine-readable storage medium having stored thereon instructions that, when executed by a processor, cause the processor to be configured to perform the above-described method of detecting vehicle driving behaviour based on a track of a vehicle.
According to the technical scheme, the track points to be analyzed are selected from the transportation track of the invoice to be processed, whether the driving event is generated or not is judged based on the selected track point pairs to be analyzed, and whether the driving behavior of the vehicle is in compliance or not is detected based on the evidence track points of the generated driving event, so that the judgment of compliance of the driving behavior of the vehicle is more accurate.
Additional features and advantages of embodiments of the application will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain, without limitation, the embodiments of the application. In the drawings:
FIG. 1 schematically illustrates a flow chart of a method for detecting driving behavior of a vehicle based on a trajectory in accordance with an embodiment of the present application;
FIG. 2 schematically illustrates a flow chart of a method for detecting driving behavior of a vehicle based on a trajectory in accordance with another embodiment of the application;
fig. 3 schematically shows an internal structural view of a computer device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it should be understood that the detailed description described herein is merely for illustrating and explaining the embodiments of the present application, and is not intended to limit the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that, if there is a description of "first", "second", etc. in the embodiments of the present application, the description of "first", "second", etc. is only for descriptive purposes, and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present application.
Fig. 1 schematically shows a flow chart of a method for detecting driving behavior of a vehicle based on a trajectory in accordance with an embodiment of the present application. As shown in fig. 1, in an embodiment of the present application, a method for detecting driving behavior of a vehicle based on a driving track is provided, including the following steps:
Step 101: and selecting one non-ship invoice from a plurality of non-ship invoices corresponding to the vehicles to be detected as a to-be-processed invoice.
For the goods transported by the vehicle to be detected, when the goods are not transported to the corresponding destination by the vehicle to be detected, the non-transported invoice can be corresponding. Each non-ship invoice includes a transport track of a vehicle to be detected. The transportation trajectory may include a plurality of trajectory points through which the vehicle to be detected passes from the delivery time to the current time. When the driving behavior of the vehicle to be detected is detected, a plurality of non-shipment orders corresponding to the vehicle to be detected may be acquired, and one non-shipment order from the plurality of non-shipment orders may be optionally selected as the non-shipment order to be processed.
In one embodiment, before obtaining the plurality of non-transferred invoices corresponding to the vehicle to be detected, it may be further determined whether the analysis period for the driving behavior of the vehicle to be detected reaches a preset timing period. If the analysis period of the driving behavior of the vehicle to be detected reaches a preset timing period, a plurality of non-transferred invoices corresponding to the vehicle to be detected can be obtained, and the analysis period of the driving behavior of the vehicle to be detected is set to be zero. If the analysis period for the driving behavior of the vehicle to be detected does not reach the preset timing period, the driving behavior of the vehicle to be detected may not be analyzed until the analysis period for the driving behavior of the vehicle to be detected reaches the preset timing period. The analysis period for the driving behavior of the vehicle to be detected can be acquired through a timer. The preset timing period can be customized according to actual conditions. For example, the preset timing period may be set to 5min, and at this time, the driving behavior of the vehicle to be detected may be confirmed or judged at 5min intervals, so as to ensure the driving safety of the vehicle to be detected.
Step 102: and acquiring a transportation track of the invoice to be processed, wherein the transportation track comprises a plurality of track points which the vehicle to be detected passes from the starting transportation moment to the current transportation moment.
Step 103: n track points to be analyzed are selected from the plurality of track points, wherein N is a natural number.
After selecting the pending invoice, the processor may obtain a transportation track for the pending invoice. The transportation track comprises a plurality of track points which are passed by the vehicle to be detected from the starting transportation moment to the current transportation moment. The track data included in the track points can be obtained by a GPS positioning device on the vehicle to be detected. The track data may include information such as time, longitude, latitude, etc. corresponding to the vehicle to be detected when passing through the corresponding track point. The processor may then select N trajectory points to be analyzed from the plurality of trajectory points. Wherein N is a natural number. The locus points to be analyzed refer to locus points for analyzing driving behavior of the vehicle to be detected.
In the embodiment of the present application, selecting N track points to be analyzed from a plurality of track points includes: detecting whether the transportation track is acquired for the first time; under the condition that the transportation track is acquired for the first time, taking a plurality of track points from the starting transportation time to the current transportation time as track points to be analyzed, and storing the current track points corresponding to the current transportation time into a record table corresponding to the invoice to be processed; judging whether the current track point corresponding to the current transportation time is consistent with the track point recorded in the record table corresponding to the invoice to be processed under the condition that the transportation track is not acquired for the first time; returning to the step of selecting one non-ship invoice from the plurality of non-ship invoices as an invoice to be processed in the case where the current track point coincides with the track point recorded in the record table; and under the condition that the current track point is inconsistent with the track points recorded in the record table, taking all track points from the track points recorded in the record table to the current track point as track points to be analyzed, and updating the track points recorded in the record table to the current track point.
When N track points to be analyzed are selected from the plurality of track points, the processor can detect whether the transportation track is acquired for the first time. Specifically, for any one of the non-shipment invoices, when the non-shipment invoice is taken as a to-be-processed invoice and the transport track of the to-be-processed invoice is acquired for the first time, a record table may be newly created for the to-be-processed invoice. Thus, when detecting whether the transportation track of the invoice to be processed is acquired for the first time, it can be determined whether or not there is a corresponding record table of the invoice to be processed. If there is a corresponding record table for the pending invoice, it may be determined that the shipping track for the pending invoice was not first acquired. If the record table corresponding to the invoice id of the to-be-processed invoice does not exist, determining that the transportation track of the to-be-processed invoice is acquired for the first time.
When the transportation track is acquired for the first time, the processor may use a plurality of track points passing from the start of transportation to the current transportation as track points to be analyzed, and store the current track point corresponding to the current transportation to a record table corresponding to the invoice to be processed. And under the condition that the transportation track is not acquired for the first time, the processor can judge whether the current track point corresponding to the current transportation moment is consistent with the track point recorded in the record table corresponding to the invoice to be processed.
If the current track point is consistent with the track point recorded in the record table, it can be stated that the current track point of the vehicle to be detected is consistent with the latest track point in the last acquired transportation track, and the transportation track of the vehicle to be detected is unchanged from the last acquired transportation track, and at this time, the vehicle to be detected may not be analyzed again. At this point, the processor may return to the step of selecting an undelivered invoice from the plurality of undelivered invoices as a pending invoice.
If the current track point is inconsistent with the track point recorded in the record table, it can be stated that the current track point of the vehicle to be detected is inconsistent with the latest track point in the last acquired transportation track, the transportation track of the vehicle to be detected changes compared with the last acquired transportation track, at this time, the processor can take all track points from the track point recorded in the record table to the current track point as track points to be analyzed, and can update the track points recorded in the record table to be current track points. It can be seen that the track points recorded in the record table of the invoice are updated in real time with the transportation track of the invoice to the actual latest track points of the vehicle to be detected.
According to the scheme for selecting the N track points to be analyzed from the plurality of track points, when the transportation track is acquired for the first time, the plurality of track points from the starting transportation time to the current transportation time are used as the track points to be analyzed, when the transportation track is acquired for the non-first time and the current track points are inconsistent with the track points recorded in the record table, the driving behavior of the vehicle to be detected can be analyzed through the newly added track points, different track points to be analyzed are selected based on the acquisition times of the transportation track of the same invoice and the result of whether the current track points are changed compared with the track points recorded in the record table, repeated analysis of the track points is avoided, and the efficiency of subsequently determining the driving behavior of the vehicle to be detected is improved.
Step 104: and under the condition that the value of N is larger than or equal to a preset value, dividing N track points to be analyzed into a plurality of track cue groups, wherein each track cue group consists of track points to be analyzed of any two adjacent time points.
Under the condition that N track points to be analyzed are determined, the processor can judge whether the value of N is larger than or equal to a preset numerical value. The preset value may be set according to the requirement, for example, the preset value may be set to 2. When the value of N is greater than or equal to the preset value, the processor may divide the N track points to be analyzed into a plurality of track cue groups, where each track cue group is composed of track points to be analyzed at any two adjacent time points. For example, if there are 3 track points to be analyzed, a, b, and c are sequentially selected from the order of time from smaller to larger, the 3 track points to be analyzed may be divided into two track cue groups, and the two track cue groups are ab and bc, respectively.
In the embodiment of the present application, if the value of N is smaller than the preset value, the step of selecting one non-transferred invoice from the plurality of non-transferred invoices as the to-be-processed invoice may be returned until the number of to-be-analyzed track points determined from the new to-be-processed invoice is greater than or equal to the preset value.
Step 105: and sequencing the processing sequence of all the track cue groups according to the track points to be analyzed with the earliest transportation time or the latest transportation time in each track cue group, wherein the processing sequence of the track cue group where the track points to be analyzed with the earliest transportation time are positioned is positioned at the front.
The processor may sort the processing sequence of all the track cue groups according to the track points to be analyzed with the earliest or latest transportation time in each track cue group, and the processing sequence of the track cue group where the track point to be analyzed with the earliest transportation time is located is the front. For example, the two track thread groups are ab and bc, where the transport time of the track point a is 9:00 and the transport time of the track point b is 9:30, and the processing sequence of the track thread group including the ab track points may be determined before the track thread group including the bc track points.
Step 106: the processing order is arranged in the first track thread group as the current thread group.
Step 107: and determining a first attribute characteristic of the current cue group according to the first track data of the track points to be analyzed in the current cue group.
The processor may arrange the processing order in a first track cue group as a current cue group, and may determine a first attribute characteristic of the current cue group according to first track data of the track points to be analyzed in the current cue group. The first track data of each track point to be analyzed can include the transportation time, the transportation position and the transportation speed of the vehicle to be detected and city information of the vehicle to be detected. The first attribute feature may include a vehicle travel to be detected and a vehicle park to be detected, wherein the attribute feature of the vehicle travel to be detected may include an overspeed of the vehicle to be detected.
In the embodiment of the application, for the current cue group, according to the time difference between the transportation time of two track points to be analyzed in the current cue group, under the condition that the time difference is smaller than the preset duration, the average speed of the vehicle to be detected for the two track points to be analyzed can be determined according to the transportation speed of the vehicle to be detected in the current cue group. The preset duration may be customized according to requirements, for example, the preset duration may be 3min. And under the condition that the average speed per hour is smaller than the first preset speed per hour, determining that the first attribute characteristic of the current clue group is that the vehicle to be detected is parked. And under the condition that the average speed per hour is greater than or equal to a first preset speed per hour, determining that the first attribute characteristic of the current clue group is the running of the vehicle to be detected.
In the case that the average speed of time is greater than or equal to the first preset speed of time, it may be determined whether the average speed of time is greater than the second preset speed of time. If the average speed per hour is greater than the second preset speed per hour, determining that the first attribute characteristic of the current clue group is overspeed of the vehicle to be detected. If the average speed per hour is greater than or equal to the first preset speed per hour and less than the second preset speed per hour, the first attribute feature of the current clue group can be determined to be the running of the vehicle to be detected. The first preset time speed is smaller than the second preset time speed, and the first preset time speed and the second preset time speed can be customized according to requirements. For example, the first preset speed of time may be 1.5m/s and the second preset speed of time 120m/s.
Under the condition that the time difference between the transportation time of the two track points to be analyzed in the current clue group is greater than or equal to the preset duration, the distance of the vehicle to be detected to the two track points to be analyzed can be determined according to the positions of the vehicle to be detected in the current clue group. And under the condition that the distance is smaller than the preset distance, determining that the first attribute characteristic of the current clue group is that the vehicle to be detected is parked. And under the condition that the distance is greater than or equal to the preset distance, determining that the first attribute characteristic of the current clue group is the running of the vehicle to be detected. The preset distance may be customized according to the requirement, for example, the preset distance may be 300m.
Step 108: and determining the state of the driving event of the first type as a generated state and determining the driving event of the first type of the generated state as a first to-be-triggered event under the condition that the generation condition of any driving event of the first type is met according to the first track data or the first attribute characteristics.
Step 109: and determining the track point to be analyzed corresponding to the earliest time in the current clue group as a first evidence track point of the first event to be triggered.
Step 110: and determining the track point to be analyzed corresponding to the latest time in the current clue group as a second evidence track point of the first trigger event.
Step 111: and determining whether the driving behavior of the vehicle to be detected is compliant according to the first evidence track point and the second evidence track point.
In the case that the generation condition of any one of the first types of driving events is determined to be satisfied according to the first trajectory data or the first attribute feature, the processor may determine that the state of the first type of driving event is a generated state, and determine the first type of driving event of the generated state as a first to-be-triggered event. The driving event refers to a basic event that a vehicle to be detected may occur in the driving process. In an embodiment of the present application, the first type of driving event includes a stay-on event, an overdrive event, a night driving event, a city stay event, and a non-city stay event.
The processor may determine a trajectory point to be analyzed corresponding to an earliest time in the current cue set as a first evidence trajectory point of the first to-be-triggered event. The processor may determine a trace point to be analyzed corresponding to a latest time in the current cue group as a second evidence trace point of the first to-be-triggered event. The first evidence track point and the second evidence track point can be used for judging whether the first trigger event is triggered or not.
In an embodiment of the present application, determining whether the driving behavior of the vehicle to be detected is compliant according to the first evidence track point and the second evidence track point includes: determining the state of a first event to be triggered according to the first evidence track point and the second evidence track point; under the condition that the state of the first to-be-triggered event is an un-triggered state, determining a second attribute characteristic of the next track clue group according to second track data of the to-be-analyzed track points in the next track clue group; under the condition that the evidence collection condition of the first to-be-triggered event is met according to the second track data or the second attribute characteristics, updating the second evidence track point according to the to-be-analyzed track point corresponding to the latest time in the next track clue group; re-determining the state of the first event to be triggered according to the first evidence track point and the updated second evidence track point; under the condition that the state of the first to-be-triggered event is re-determined to be the triggered state, updating the first to-be-triggered event to be the first triggered event; and determining that the driving behavior of the vehicle to be detected from the starting transportation moment is not compliant when the first triggered event is an abnormal event.
The processor may determine a state of the first to-be-triggered event from the first evidence track point and the second evidence track point. Wherein the states of the first to-be-triggered event include an untriggered state and a triggered state. In the case that the state of the first to-be-triggered event is the non-triggered state, that is, the triggering condition of the first to-be-triggered event is not satisfied yet, the processor may determine the second attribute feature of the next track cue group according to the second track data of the to-be-analyzed track point in the next track cue group, so as to continuously collect the evidence track point that may trigger the first to-be-triggered event. That is, in the case where it is determined that the evidence collection condition of the first to-be-triggered event is satisfied according to the second trajectory data or the second attribute feature, the processor may update the second evidence trajectory point according to the to-be-analyzed trajectory point corresponding to the latest time in the next trajectory cue group. The processor may then redetermine the state of the first to-be-triggered event based on the first evidence track point and the updated second evidence track point. In the event that the state of the first to-be-triggered event is re-determined to be the triggered state, the processor may update the first to-be-triggered event to the first triggered event. And determining that the driving behavior of the vehicle to be detected from the starting transportation moment is not compliant when the first triggered event is an abnormal event. The abnormal events comprise a fatigue driving event, a stay overtime event, an overdrive event, a night driving event, a city stay event, a overtime goods-taking event and a transportation abnormal event.
According to the scheme, whether a certain driving event is generated or not is judged based on the track clue group, and after the certain driving event is generated and not triggered, the evidence track point of the generated and not triggered driving event is updated based on the subsequent track clue group, so that whether the generated and not triggered driving event is triggered or not is further judged, wherein the evidence track point can be used as evidence possibly triggering the certain driving event. Therefore, the scheme provides a progressive triggering event management mechanism (clue-evidence-event mechanism), and by separating the generation of the event from the triggering, the persistence and the sectional proof of the event triggering judgment are realized, and the timeliness is ensured to the greatest extent.
For example, for the current thread group A1, it includes a track point to be analyzed a and a track point to be analyzed b, where the transport time of the track point to be analyzed a is earlier than the transport time of the track point to be analyzed b. If the first attribute feature of the current thread group A1 is determined to be that the vehicle to be detected is stopped, the generation condition of the continuous retention event is determined to be satisfied, at this time, the continuous retention event generation may be determined, the track point a to be analyzed may be determined to be a retention start track point of the continuous retention event, and the track point b to be analyzed may be determined to be a retention end track point of the continuous retention event.
Then, the time difference and the distance between the track point a to be analyzed and the track point b to be analyzed can be determined, if the time difference is smaller than 15min and the distance is larger than or equal to the preset distance, the trigger condition of the continuous retention event is not met, and the state of the generated continuous retention event is an un-triggered state. At this time, the next set of track cues A2 may be analyzed. The track cue group A2 comprises a track point b to be analyzed and a track point c to be analyzed, wherein the transportation time of the track point b to be analyzed is earlier than that of the track point c to be analyzed.
If it is determined that the second attribute of the current thread group A2 is still the parking of the vehicle to be detected, that is, the second attribute meets the evidence collection condition of the continuous retention event, at this time, the retention ending track point of the continuous retention event may be updated to be the track point c to be analyzed. Thereafter, the time difference and distance between the locus point a to be analyzed and the locus point c to be analyzed can be determined. If the time difference is greater than or equal to 15min and the distance is smaller than the preset distance, the trigger condition of the continuous retention event can be determined to be met, and the continuous retention event can be determined to be triggered. Since the triggered sustained retention event is not an abnormal event, it is possible to determine the driving behavior compliance of the vehicle to be detected from the start of the transportation.
For another example, for the current thread group A1, it includes a track point to be analyzed a and a track point to be analyzed b, where the transport time of the track point to be analyzed a is earlier than the transport time of the track point to be analyzed b. If the first attribute feature of the current clue group A1 is determined to be that the vehicle to be detected is running, the generation condition of the continuous driving event is determined to be satisfied, at this time, the continuous driving event generation may be determined, the track point a to be analyzed may be determined to be a running start track point of the continuous driving event, and the track point b to be analyzed may be determined to be a running end track point of the continuous driving event.
Then, a time difference between the track point a to be analyzed and the track point b to be analyzed can be determined, if the time difference is smaller than 15min, the trigger condition of the continuous driving event is not met, and the generated state of the continuous driving event is an un-triggered state. At this time, the next set of track cues A2 may be analyzed. The track cue group A2 comprises a track point b to be analyzed and a track point c to be analyzed, wherein the transportation time of the track point b to be analyzed is earlier than that of the track point c to be analyzed.
If it is determined that the second attribute feature of the current thread group A2 is still the vehicle to be detected for driving, that is, the second attribute feature satisfies the evidence collection condition of the continuous driving event, at this time, the driving end track point of the continuous driving event may be updated to the track point c to be analyzed. Thereafter, a time difference between the locus point a to be analyzed and the locus point c to be analyzed can be determined. If the time difference is greater than or equal to 15 minutes, it may be determined that the trigger condition of the continuous driving event is satisfied, and it may be determined that the continuous driving event has been triggered. Since the triggered continuous driving event is not an abnormal event, it is possible to determine the driving behavior compliance of the vehicle to be detected from the start of the transportation.
For another example, for the current thread group A1, it includes a track point to be analyzed a and a track point to be analyzed b, where the transport time of the track point to be analyzed a is earlier than the transport time of the track point to be analyzed b. If the first attribute feature of the current clue group A1 is determined to be that the vehicle is overspeed, determining that the generation condition of the driving event, which is an overdrive event, is satisfied, at this time, determining that the overdrive event is generated, determining that the track point a to be analyzed is an overdrive start track point of the overdrive event, and determining that the track point b to be analyzed is an overdrive end track point of the overdrive event.
Then, the time difference and the average speed of the trajectory point a to be analyzed and the trajectory point b to be analyzed can be determined, if the average speed of the time does not exceed 120m/s and the time difference is less than or equal to 3min, the triggering condition of the overdrive event is not satisfied, and the state of the overdrive event is not triggered. At this time, the next set of track cues A2 may be analyzed. The track cue group A2 comprises a track point b to be analyzed and a track point c to be analyzed, wherein the transportation time of the track point b to be analyzed is earlier than that of the track point c to be analyzed.
If it is determined that the second attribute feature of the current thread group A2 is that the vehicle to be detected is running, that is, the second attribute feature satisfies the evidence collection condition of the overdrive event, at this time, the overspeed ending track point of the overdrive event may be updated to be the track point c to be analyzed. And then, determining the time difference and the average speed per hour between the track point to be analyzed a and the track point to be analyzed c, and if the average speed per hour exceeds 120m/s and the time difference is more than or equal to 3min, determining that the triggering condition of the overdrive event is met, and determining that the overdrive event is triggered. Since the triggered overdrive event is an abnormal event, it can be determined that the driving behavior of the vehicle to be detected from the start of the transportation is not compliant.
For example, for the current thread group A3, it includes a track point d to be analyzed and a track point e to be analyzed, where the transport time of the track point d to be analyzed is earlier than the transport time of the track point e to be analyzed. If it is determined that the transportation time of the track point d to be analyzed and the transportation time of the track point e to be analyzed in the current thread group A3 are both in the night driving time period (for example, may be from the early morning zero point to the five points), at this time, it may be determined that the generation condition of the night driving event is satisfied, it may be determined that the night driving event is generated, it may be determined that the track point d to be analyzed is a night driving start track point of the night driving event, and it may be determined that the track point e to be analyzed is a night driving end track point of the night driving event.
Then, the distance between the track point d to be analyzed and the track point e to be analyzed can be determined, if the distance at the moment does not exceed 500m, the trigger condition of the night driving event is not met, and the state of the generated night driving event is an un-triggered state. At this time, the next set of track cues set A4 may be analyzed. The track cue group A4 comprises a track point e to be analyzed and a track point f to be analyzed, wherein the transportation time of the track point e to be analyzed is earlier than that of the track point f to be analyzed.
If it is determined that the transportation time of the track point e to be analyzed and the transportation time of the track point f to be analyzed in the current cue group A4 are both in the night driving time period, and the second attribute feature of the current cue group A2 is that the vehicle to be detected is driving, that is, the second attribute feature satisfies the evidence collection condition of the night driving event, at this time, the night driving end track point of the night driving event may be updated to the track point f to be analyzed. Thereafter, the distance between the trajectory point d to be analyzed and the trajectory point f to be analyzed may be determined, and if the distance at this time exceeds 500m, it may be determined that the trigger condition of the night driving event is satisfied, and it may be determined that the night driving event has been triggered. Since the triggered night driving event is an abnormal event, it can be determined that the driving behavior of the vehicle to be detected from the start of the transportation is not compliant.
For example, for the current thread group A3, it includes a track point d to be analyzed and a track point e to be analyzed. If it is determined that the city information of the vehicle to be detected corresponding to the track point d to be analyzed and the city information of the vehicle to be detected corresponding to the track point e to be analyzed in the current cue group A3 are the same city, at this time, it may be determined that the generation condition of the urban resident event is satisfied, it may be determined that the urban resident event is generated, the track point d to be analyzed may be determined as the urban resident start track point of the urban resident event, and the track point e to be analyzed may be determined as the urban resident end track point of the urban resident event.
Then, the time difference between the track point d to be analyzed and the track point e to be analyzed can be determined, if the time difference is smaller than 4h, the trigger condition of the urban resident event is not met, and the generated state of the urban resident event is an un-triggered state. At this time, the next set of track cues set A4 may be analyzed. The track cue group A4 includes a track point to be analyzed e and a track point to be analyzed f.
If it is determined that the city information of the vehicle to be detected corresponding to the track point e to be analyzed and the track point f to be analyzed in the current cue group A4 are both the city information of the vehicle to be detected corresponding to the track point d to be analyzed, that is, the second track data meets the evidence collection condition of the urban resident event, at this time, the urban resident ending track point of the urban resident event can be updated to be the track point f to be analyzed. And then, determining the time difference between the track point d to be analyzed and the track point f to be analyzed, and if the time difference is greater than or equal to 4h, determining that the trigger condition of the urban resident event is met, and determining that the urban resident event is triggered. Since the triggered urban holding event is an abnormal event, it can be determined that the driving behavior of the vehicle to be detected from the start of the transportation is not compliant.
For example, for the current thread group A3, it includes a track point d to be analyzed and a track point e to be analyzed. If it is determined that the city information of the vehicle to be detected corresponding to the track point d to be analyzed and the city information of the vehicle to be detected corresponding to the track point e to be analyzed in the current cue group A3 are non-cities, at this time, it may be determined that the generating condition of the non-urban resident event is satisfied, it may be determined that the non-urban resident event is generated, the track point d to be analyzed may be determined as a non-urban space start track point of the non-urban resident event, and the track point e to be analyzed may be determined as a non-urban space end track point of the non-urban resident event.
Then, the time difference between the track point d to be analyzed and the track point e to be analyzed can be determined, if the time difference is smaller than 10min, the trigger condition of the non-urban resident event is not met, and the generated state of the non-urban resident event is an un-triggered state. At this time, the next set of track cues set A4 may be analyzed. The track cue group A4 includes a track point to be analyzed e and a track point to be analyzed f.
If it is determined that the city information of the vehicle to be detected corresponding to the track point e to be analyzed and the track point f to be analyzed in the current cue group A4 are non-cities, that is, the second track data meets the evidence collection condition of the non-city resident event, at this time, the non-city space ending track point of the non-city resident event can be updated to the track point f to be analyzed. And then, determining the time difference between the track point d to be analyzed and the track point f to be analyzed, if the time difference is greater than or equal to 10min, determining that the triggering condition of the non-urban resident event is met, and determining that the non-urban resident event is triggered. Since the triggered non-urban holding event is not an abnormal event, driving behavior compliance of the vehicle to be detected from the start of transportation can be determined.
In the embodiment of the application, the method further comprises the following steps: under the condition that the first trigger event is released is met is determined according to the second track data or the second attribute characteristics, updating the state of the first trigger event to be released, and clearing the first trigger event; and taking the track cue group which is sequentially arranged behind the next track cue group as a new current cue group, and returning to the step of determining the first attribute characteristics of the current cue group according to the first track data of the track points to be analyzed in the current cue group so as to analyze the newly determined current cue group until a plurality of track cue groups are analyzed.
In the case that it is determined that the release condition of the first trigger event is satisfied according to the second trajectory data or the second attribute feature, the processor may update the state of the first trigger event to the release state and clear the first trigger event. That is, the generated event to be triggered will not trigger any more, the processor may return the track thread group after the next track thread group in the processing order as a new current thread group to the step of determining the first attribute feature of the current thread group according to the first track data of the track point to be analyzed in the current thread group, so as to analyze the newly determined current thread group until the analysis of the plurality of track thread groups is completed.
For example, when the current thread group A1 (including the track point to be analyzed a and the track point to be analyzed b) is analyzed and it is determined that the sustained retention event is generated but not triggered, and then the next track thread group A2 (including the track point to be analyzed b and the track point to be analyzed c) is analyzed, if it is determined that the second attribute feature of the next track thread group A2 is that the vehicle to be detected is running, that is, the second attribute feature satisfies the release condition of the sustained retention event, at this time, it may be determined that the sustained retention event is released.
For another example, when the current thread group A1 (including the track point to be analyzed a and the track point to be analyzed b) is analyzed and then the continuous driving event is determined to be generated but not triggered, and then the next track thread group A2 (including the track point to be analyzed b and the track point to be analyzed c) is analyzed, if it is determined that the second attribute feature of the next track thread group A2 is that the vehicle to be detected is stopped, that is, the second attribute feature satisfies the release condition of the continuous driving event, at this time, the continuous driving event can be determined to be released.
For another example, when the current thread group A1 (including the track point to be analyzed a and the track point to be analyzed b) is analyzed and it is determined that the overdrive event is generated but not triggered, and then the next track thread group A2 (including the track point to be analyzed b and the track point to be analyzed c) is analyzed, if it is determined that the average speed between the track point to be analyzed b and the track point to be analyzed c in the next track thread group A2 is not more than 120m/s, that is, the second track data satisfies the condition of canceling the overdrive event, at this time, it may be determined that the overdrive event is cancelled.
For example, when it is determined that the night driving event is generated but not triggered after the current thread group A3 (including the track point to be analyzed d and the track point to be analyzed e) is analyzed, and then the next track thread group A4 (including the track point to be analyzed e and the track point to be analyzed f) is analyzed, if it is determined that the transportation time of the track point to be analyzed e or the track point to be analyzed f in the next track thread group A4 is not in the night driving period, that is, the second track data satisfies the release condition of the night driving event, at this time, it may be determined that the night driving event is released.
For example, when the current cue group A3 (including the track point to be analyzed d and the track point to be analyzed e) is analyzed and then the urban parking event is determined to be generated but not triggered, and then the next track cue group A4 (including the track point to be analyzed e and the track point to be analyzed f) is analyzed, if it is determined that the urban information of the vehicle to be detected corresponding to the track point to be analyzed e and the track point to be analyzed f in the next track cue group A4 is non-urban, that is, the second track data satisfies the condition of releasing the urban parking event, at this time, it may be determined that the urban parking event is released.
When the current cue group A3 (comprising the track point d to be analyzed and the track point e to be analyzed) is analyzed and then the non-urban resident event is determined to be generated but not triggered, and then the next track cue group A4 (comprising the track point e to be analyzed and the track point f to be analyzed) is analyzed, if the urban information of the vehicles to be detected corresponding to the track point e to be analyzed and the track point f to be analyzed in the next track cue group A4 is determined to be the same city, namely, the second track data meets the release condition of the non-urban resident event, at this time, the non-urban resident event can be determined to be released.
For example, as shown in Table 1 below, a rule table of a first type of driving event is provided.
TABLE 1 rule List of first type of driving event
| Event type | Generating conditions and accompanying evidence | Evidence trace points | Evidence collection conditions | Releasing condition | Trigger condition |
| Sustained retention event | Generating a track clue when the attribute of the track clue analyzed currently is parking; recording the track point with the previous time in the current track clue as the retention start track point during generation | Stay start track point and stay end track point | The attribute of the current analysis track clue is "stop", and the current retention ending track point is updated to a track point with later time in the current track clue | The attribute of the current analysis track clue is 'driving' | Calculating a time difference between the retention start track point and the retention end track point to be greater than or equal to 15 minutes; and, the distance between the retention start track point and the retention end track point is calculated to be smaller than the error distance. |
| Sustained driving event | Generating when the attribute of the track clue analyzed currently is 'driving'; recording the track point with the previous time in the current track clue as the track point of the running start during the generation | Travel start trajectory point and travel end trajectory point | The attribute of the current analysis track clue is 'running', and the current running ending track point is updated to be the track point with later time in the current track clue | The attribute of the current analysis track clue is parking " | Calculating a time difference between the travel start locus point and the travel end locus point to be 15 minutes or more |
| Overdrive event (abnormal event) | Generating when the attribute of the track clue analyzed currently is overspeed; recording the track point with the previous time in the current track clue as the track point of the running start during the generation | Overspeed start trace point and overspeed end trace point | The attribute of the current analysis track clue is 'driving', and the current overspeed ending track point is updated to be the track point with later time in the current track clue | Calculating the speed per hour between the overspeed starting track point and the overspeed ending track point to be not more than 120m/s | The speed per hour between the overspeed starting trajectory point and the overspeed ending trajectory point is calculated to be more than 120m/s, and the time difference between the overspeed starting trajectory point and the overspeed ending trajectory point is calculated to be more than 3 minutes. |
| Night driving event (abnormal event) | The time of two track points of the track clue which is analyzed currently is generated when the two track points are at night (0:00-5:00) at the same time; when the track point is generated, the track point with the front time in the current track clue is recorded as a night driving start track point, and the track point with the rear time is recorded as a night driving end track point | Night driving start track point and night driving end track point | The attribute of the current analysis track clue is 'driving', and two track points in the current analysis track clue are at night at the same time, and the current overspeed ending track point is updated to be the track point with the later time in the current track clue | The time of at least one track point in the track clue being analyzed is not at night | The distance between the night driving start track point and the night driving end track point exceeds 500m |
| In non-urban spaces (non-urban resident events) | The two track points of the track clue which is analyzed currently are marked as non-urban space, and the track point which is positioned in front of the current track clue and is positioned in time is recorded as a non-urban space starting track point when the track clue is generated | Non-urban space start trajectory point and non-urban space end trajectory point | Two track points in the track clue analyzed at present are marked as non-urban space at the same time, and the end track point of the non-urban space is updated to be the track point with later time in the track clue | When the urban resident event is triggered | Calculating the time difference between the non-urban space start track point and the non-urban space end track point to be more than or equal to 10 minutes |
| Urban resident event (abnormal event) | The two track points of the track clue which is analyzed at present are marked as the same city information, and the track point with the front time in the track clue is recorded as the city residence start track point when being generated | Urban parking start track point and urban parking end track point | The two track points in the track clue analyzed at present are marked as the same city information marked by the city residence start track points at the same time, and the city residence end track points are updated to track points with later time in the track clue at present | Event triggering in non-urban space | Calculating the time difference between the urban parking start track point and the urban parking end track point to be more than or equal to 4 hours |
In the embodiment of the application, the method further comprises the following steps: under the condition that the generation condition of any other driving event except the driving event is met according to the second track data or the second attribute characteristics, the state of the other driving event is determined to be the generated state, and the other driving event in the generated state is determined to be a second event to be triggered; determining evidence track points of a second to-be-triggered event according to the track points to be analyzed in the next track clue group; determining the state of the second event to be triggered according to the evidence track point of the second event to be triggered; under the condition that the state of the second to-be-triggered event is the triggered state, updating the second to-be-triggered event into a second triggered event; and determining that the driving behavior of the vehicle to be detected from the starting transportation moment is not compliant when the second triggered event is an abnormal event.
After a certain driving event is generated, there may be other driving event generation in addition to the driving event. In the case where it is determined that the generation condition of any other driving event than the driving event is satisfied according to the second trajectory data or the second attribute feature, the processor may determine that the state of the other driving event is the generated state, and determine the other driving event of the generated state as the second event to be triggered. For example, after the persistent stay event is generated, any driving event other than the persistent stay may be generated, for example, after the persistent stay event is generated, a persistent travel event is generated. The processor may determine an evidence trace point of the second to-be-triggered event based on the to-be-analyzed trace points in the next trace-cue set. Specifically, the processor may determine the trace point to be analyzed corresponding to the earliest time in the next trace-thread group as the third evidence trace point of the second event to be triggered, and may determine the trace point to be analyzed corresponding to the latest time in the next trace-thread group as the fourth evidence trace point of the second event to be triggered.
The processor may determine a state of the second to-be-triggered event based on the evidence trace point of the second to-be-triggered event. Wherein the state of the second to-be-triggered event comprises a triggered state and an untriggered state. And under the condition that the state of the second to-be-triggered event is determined to be the triggered state according to the evidence track point of the second to-be-triggered event, updating the second to-be-triggered event to be the second triggered event. In the event that the second triggered event is an abnormal event, the processor may determine that the driving behavior of the vehicle to be detected from the start of the transportation is not compliant.
In the embodiment of the application, under the condition that the state of the second to-be-triggered event is determined to be the non-triggered state according to the evidence track point of the second to-be-triggered event, returning to the step of determining the second attribute characteristic of the next track cue group according to the second track data of the to-be-analyzed track point in the next track cue group, so as to analyze the track cue groups which are sequentially arranged behind the next track cue group until a plurality of track cue groups are analyzed.
In the case that the state of the second to-be-triggered event is determined to be the non-triggered state according to the evidence track point of the second to-be-triggered event, the processor may return to the step of determining the second attribute feature of the next track cue group according to the second track data of the to-be-analyzed track point in the next track cue group, so as to analyze the track cue groups which are sequentially arranged behind the next track cue group until the plurality of track cue groups are analyzed.
In the embodiment of the application, the method further comprises the following steps: judging whether the generation condition of the associated event corresponding to the triggered event is met or not according to any one triggered event of the first triggered event and the second triggered event; under the condition that the generation condition of the related event is met, determining that the related event is generated by the triggered event, and determining the related event in the generated state as a third event to be triggered; determining the state of a third event to be triggered according to the evidence track points of the triggered event corresponding to the third event to be triggered; under the condition that the state of the third to-be-triggered event is the triggered state, updating the third to-be-triggered event into a third triggered event; and determining that the driving behavior of the vehicle to be detected from the starting transportation moment is not compliant when the third triggered event is an abnormal event.
For any one of the first triggered event and the second triggered event, the processor may determine whether a generation condition of an associated event corresponding to the triggered event is satisfied. When the triggered event is a continuous driving event or a night driving event, the corresponding associated event may be a fatigue driving event. When the triggered event is a sustained retention event, the corresponding associated event may be a retention timeout event. In the case that the generation condition of the associated event is satisfied, the processor may determine that the triggered event triggers generation of the associated event, and determine the associated event of the generated state as a third to-be-triggered event.
The processor may determine a state of the third to-be-triggered event according to the evidence trace point of the triggered event corresponding to the third to-be-triggered event. Specifically, the processor may use the trace point to be analyzed corresponding to the earliest time corresponding to the triggered event as the associated evidence trace point corresponding to the third to-be-triggered event, and use the trace point to be analyzed corresponding to the latest time in the next trace cue group as the evidence collection trace point corresponding to the third to-be-triggered event. In the case that the state of the third to-be-triggered event is the triggered state, the processor may update the third to-be-triggered event to the third triggered event. In the case where the third triggered event is an abnormal event, the processor may determine that the driving behavior of the vehicle to be detected from the start of the transportation is not compliant.
In one embodiment, when the state of the third to-be-triggered event is the non-triggered state, the track cue group whose processing sequence is arranged after the next track cue group may be analyzed, and if the track cue group analysis determines that the triggering condition of the corresponding association event is satisfied, the state of the third to-be-triggered event may be determined to be the triggered state, and further, the driving behavior of the vehicle to be detected may be determined. If the trace line cable group analysis determines that the release condition of the corresponding associated event is satisfied, the corresponding associated event may be deleted.
According to the scheme, aiming at any one triggered event of the first triggered event and the second triggered event, the triggered event can trigger the corresponding associated event to generate, so that the associated event of the generated state can be triggered, and the triggered associated event can be relieved. It can be seen that the above scheme provides an event linkage mechanism, which refers to a mechanism that an event is generated, released or triggered due to a certain event trigger.
For example, as shown in Table 2 below, a rule table of fatigue driving events is provided.
If the triggered event is a night driving event, generating a corresponding related event as a fatigue driving event, determining a night driving start track point of the night driving event as a fatigue driving start track point of the fatigue driving event, and determining a track point to be analyzed corresponding to the latest time in the next track clue group as a fatigue driving end track point of the fatigue driving event. If the triggered event is a continuous driving event, generating a corresponding associated event as a fatigue driving event, determining a driving start track point of the continuous driving event as a fatigue driving start track point of the fatigue driving event, and determining a track point to be analyzed corresponding to the latest time in the next track clue group as a fatigue driving end track point of the fatigue driving event.
And then, determining a time difference between the transportation time of the fatigue driving start track point and the transportation time of the fatigue driving end track point, and if the time difference is greater than or equal to 4 hours, determining that the fatigue driving event is triggered. If the time difference is smaller than 4 hours, the track clues after the next track clue are analyzed, and the release condition of the fatigue driving event is determined to be met under the condition that the trigger condition of the continuous retention event is met and the trigger condition of the night driving time is not met. At this time, the fatigue driving event release may be determined and deleted.
TABLE 2 rule List of fatigue Driving events
For example, as shown in Table 3 below, a rule table is provided that hosts timeout events.
If the triggered event is a continuous retention event, a corresponding association event is generated as a retention timeout event, wherein the attribute of the next track clue group is characterized in that the vehicle to be detected is parked, two track points to be analyzed in the next track clue group are parking track points, the retention start track point of the continuous retention event can be determined as the retention start track point of the retention timeout event, and the parking track point at the latest time can be determined as the retention end track point of the retention timeout event. When the error distance between the parking start track point and the parking end track point is larger than the preset error, the parking track point which is farthest from the parking end track point but not exceeding the error distance in the parking track points can be updated to be the parking start track point of the parking timeout event, and all parking track points before the updated parking start track point are deleted.
Thereafter, a time difference between the transit time of the dwell start trajectory point and the transit time of the dwell end trajectory point, and a distance between the transit location of the dwell start trajectory point and the transit location of the dwell end trajectory point, may be determined. If the time difference is greater than or equal to 2h and the distance is less than the error distance, it may be determined that a trigger condition of the stay timeout event is satisfied and the stay timeout event is triggered. If the trigger condition of the parking timeout event is not met, the track clue group after the next track clue group can be analyzed, and when the attribute characteristics of the track clue group after the next track clue group is obtained through analysis and is the running of the vehicle to be detected, the condition that the parking timeout event is relieved is determined to be met. At this point, the dwell timeout event may be determined to be resolved and deleted.
Table 3 rule table for resident timeout event
| Event type | Generating conditions and accompanying evidence | Evidence trace points | Evidence collection conditions | Releasing condition | Trigger condition |
| Residence time-out (abnormal event) | The generation of the continuous retention event is triggered; recording a dwell start track point in a continuous dwell event as a dwell start track point at the time of generation | Parking start and end track points (track points in track cues with all attributes "park" during parking start and end track points) | The attribute of the current analysis track clue is parking, two track points in the track clue are recorded as parking track points, and meanwhile, the resident ending track points are updated to track points with the latest time in all parking track points. In addition, when the distance between the parking start track point and the parking end track point is greater than the error distance, the track point which is farthest from the parking end track point but not exceeding the error distance in all the parking track points is updated to be the latest parking start track point, and then all the parking track points before the new parking start track point are deleted. | The attribute of the current analysis track clue is 'driving' | Calculating the time difference between the residence start track point and the residence end track point to be more than or equal to 2 hours; and, the distance between the residence start track point and the residence end track point is calculated to be smaller than the error distance. |
In the embodiment of the application, the method further comprises the following steps: after arranging the processing order in the first track cue group as the current cue group, acquiring the state of the invoice to be processed; determining the state of the driving event of the second type as a generated state and determining the driving event of the second type of the generated state as a fourth to-be-triggered event under the condition that the state of the invoice to be processed meets the generation condition of any driving event of the second type; determining an evidence track point of a fourth to-be-triggered event according to the track points to be analyzed in the current clue group; and determining whether the driving behavior of the vehicle to be detected is compliant or not according to the evidence track point of the fourth event to be triggered.
After ranking the processing order in the first track thread group as the current thread group, the processor may obtain the status of the to-be-processed invoice. In the case where the status of the invoice to be processed satisfies the generation condition of any one of the driving events of the second type, the processor may determine that the status of the driving event of the second type is the generated status, and determine that the driving event of the second type of the generated status is the fourth to-be-triggered event. In an embodiment of the present application, the second type of driving event includes a overtime pick event and a ship out exception event. The processor may determine an evidence track point of the fourth to-be-triggered event according to the track points to be analyzed in the current cue group, and may determine whether the driving behavior of the vehicle to be detected is compliant according to the evidence track point of the fourth to-be-triggered event.
Specifically, the processor may determine the state of the fourth to-be-triggered event according to the evidence trace point of the fourth to-be-triggered event. And under the condition that the state of the fourth to-be-triggered event is the triggered state, updating the fourth to-be-triggered event to the fourth triggered event, and determining that the driving behavior of the vehicle to be detected from the starting transportation moment is not compliant. And under the condition that the state of the fourth to-be-triggered event is the non-triggered state, updating the evidence track point of the fourth to-be-triggered event until the state of the fourth to-be-triggered event is determined to be the triggered state according to the evidence track point of the fourth to-be-triggered event.
For example, as shown in Table 4 below, a rule table of a second type of driving event is provided.
For a second type of driving event, namely a overtime pick-up event, if the state of the to-be-processed invoice is 'non-pick-up', determining that the generation condition of the overtime pick-up event is met, determining that the overtime pick-up event is generated, determining that the to-be-analyzed track point corresponding to the earliest time in the current track group is the current track point, then determining that the distance between the position of the current track point and the pick-up position indicated in the to-be-processed invoice is smaller than or equal to the preset distance, or determining that the trigger condition of the overtime pick-up event is not met if the transportation time of the current track point does not exceed the pick-up time indicated in the to-be-processed invoice, at this time, updating the current track point to the to-be-analyzed track point corresponding to the latest time in the next track group, and judging whether the trigger condition of the overtime pick-up event is met or not again.
If the distance between the updated position of the current track point and the pick-up position indicated in the invoice to be processed is greater than the preset distance and the transportation time of the updated current track point exceeds the pick-up time indicated in the invoice to be processed, determining that the trigger condition of the overtime pick-up event is met, and determining that the overtime pick-up event is triggered. If the distance between the updated current track point position and the pick-up position indicated in the to-be-processed invoice is smaller than the preset distance and the transportation time of the updated current track point is not longer than the pick-up time indicated in the to-be-processed invoice, determining that the release condition of the overtime pick-up event is met, and updating the state of the to-be-processed invoice to be 'picked-up'.
For a driving event of the second type, namely, a shipping exception event, if the state of the invoice to be processed is 'non-shipping', determining that the generation condition of the shipping exception event is met, determining that the shipping exception event is generated, determining that the track point to be analyzed corresponding to the earliest time in the current thread group is the current track point, then determining that the distance between the position of the current track point and the shipping position indicated in the invoice to be processed is smaller than or equal to a preset distance, or determining that the triggering condition of the shipping exception event is not met if the shipping time of the current track point does not exceed the shipping time indicated in the invoice to be processed, at this time, updating the current track point to the track point to be analyzed corresponding to the latest time in the next track thread group, and judging whether the triggering condition of the shipping exception event is met again. If the distance between the updated current track point position and the transportation position indicated in the invoice to be processed is greater than the preset distance and the transportation time of the updated current track point exceeds the transportation time indicated in the invoice to be processed, determining that the triggering condition of the transportation abnormal event is met, and determining that the transportation abnormal event is triggered.
If the distance between the updated position of the current track point and the indicated transportation position in the invoice to be processed is greater than the preset distance and the transportation time of the updated current track point exceeds the transportation time indicated in the invoice to be processed, determining that the trigger condition of the overtime transportation event is met, and determining that the overtime transportation event is triggered. If the distance between the updated current track point position and the shipping position indicated in the invoice to be processed is smaller than the preset distance and the shipping time of the updated current track point is not longer than the shipping time indicated in the invoice to be processed, determining that the release condition of the overtime shipping event is met, and updating the state of the invoice to be processed to be "shipped".
Table 4 rule table of second type of driving event
| Event type | Generating conditions and accompanying evidence | Evidence trace points | Evidence collection conditions | Releasing condition | Trigger condition |
| Overtime goods extraction (abnormal event) | The state of the shipping bill is 'not picked up', and the track point with the front time in the current track clue is recorded as the current track point when the shipping bill is generated | Current track point | Unconditionally, the current track point is directly updated to the track point with later time in the current track clue | The time of the current track point does not exceed the goods picking time specified in the delivery bill, and when the distance between the position of the current track point and the goods picking position indicated in the delivery bill is smaller than the preset distance, the release is carried out, and when the release is carried out, the state of the delivery bill is triggered to be changed into 'picked up' | The distance between the position of the current track point and the pick-up position indicated in the shipping bill is greater than the preset distance, and the time of the current track point exceeds the pick-up time specified in the shipping bill |
| Abnormal fortune (abnormal event) | The state of the shipping bill is 'not in charge', and the track point with the front time in the current track clue is recorded as the current track point when the shipping bill is generated | Current track point | Unconditionally, the current track point is directly updated to the track point with later time in the current track clue | The time of the current track point does not exceed the specified carrying time in the shipping bill, and when the distance between the position of the current track point and the carrying position indicated in the shipping bill is smaller than the preset distance, the release is carried out, and when the release is carried out, the state of the shipping bill is triggered to be changed into the carried state " | The distance between the position of the current track point and the indicated abutting position in the shipping bill is greater than the preset distance, and the time of the current track point exceeds the specified abutting time in the shipping bill |
In the embodiment of the application, the method further comprises the following steps: for any one triggered event of the first triggered event, the second triggered event and the third triggered event, judging whether the triggered event is the first trigger or not under the condition that the triggered event is an abnormal event; executing a preset driving intervention operation under the condition that the triggered event is the first trigger or the triggered event is the non-first trigger and the triggering duration of the triggered event exceeds the preset duration; and under the condition that the triggered event is not the first trigger and the triggering duration time does not exceed the preset duration time, the preset driving intervention operation is not executed.
For any one of the first triggered event, the second triggered event and the third triggered event, the processor may determine whether the triggered event is a first trigger if the triggered event is an abnormal event. The processor may perform a preset driving intervention operation in case the triggered event is a first trigger, or the triggered event is a non-first trigger and the trigger duration of the triggered event exceeds a preset duration. In the case where the triggered event is a non-first trigger and the trigger duration does not exceed the preset duration, the processor may not perform the preset driving intervention operation. The preset driving intervention operation may be writing a triggered event of a preset type into an exception list for recording, and sending the triggered event and the corresponding evidence track point to a transportation track diagram for displaying, and may also generate a notification corresponding to the triggered event according to a preset format and send the notification to a driver of the vehicle to be detected.
After the driving event is triggered, judging whether the triggered event is the first trigger or not, and judging whether the triggering duration of the triggered event exceeds the preset duration or not when the triggered event is not the first trigger, so that whether the preset driving intervention operation is executed or not is judged according to a judging result, repeated triggering of the same driving event can be avoided, and resources are saved.
As shown in fig. 2, a flow chart of another method for detecting driving behavior of a vehicle based on a track is provided.
And executing the track analysis task aiming at the vehicle to be detected according to the timing period, resetting the timer under the condition that the timing period is reached, and acquiring all undelivered shipping orders. The departure track points to all the latest track points are recorded in the departure track, and the information of each track point (including the information of time, longitude, latitude and the like when the vehicle to be detected reaches each track point) can be detected by a GPS positioning device arranged on the vehicle to be detected. And then, analyzing any undelivered shipping bill. Specifically, the trajectory data of the next shipping bill, i.e., the selected shipping bill, may be acquired. The track data is a series of track points which are continuous in time, all track points from a departure track point to a latest track point are recorded in the shipping bill, and each track point can comprise the corresponding transportation time, position, running speed and city information of the vehicle to be detected. Then, whether the latest track point is recorded or not can be detected, namely whether a record table corresponding to the shipping bill exists or not is detected, and whether the track data is acquired for the first time or not is judged.
If it is detected that the latest track point is not recorded, it can be determined that the track data of the shipping bill is acquired for the first time. At this time, all the track points from the departure track point to the current latest track point can be acquired. If the latest track point is detected to be recorded, determining that the track data of the shipping bill is not acquired for the first time. At this time, it may be further determined whether or not the latest track point in the track data coincides with the latest track point recorded previously. If the latest track point in the track data is consistent with the latest track point recorded before, the track data which is acquired newly is not changed compared with the track data which is acquired last time, and the analysis of the track data of the shipping slip can be stopped. If the latest track point in the track data is inconsistent with the latest track point recorded before, all track points between the latest track point and the last track point recorded in the last track data are acquired, and the latest track point recorded before is updated at the same time. The latest track point recorded previously refers to a track point recorded in a record table corresponding to the shipping bill.
After the track points are selected, it may be determined whether the number of selected track points is less than two track points. If the number of selected track points is less than two, the analysis of the track data of the shipping bill can be exited. If the number of the selected track points is greater than or equal to two, the selected track points can be organized into a plurality of track clues according to the time sequence. Wherein each track cue comprises two selected track points that are temporally adjacent. For example, if the selected track point is abc, it may be divided into two track cues (ab) and (bc), and when analyzing the track cues, the track cues (ab) are analyzed first and the track cues (bc) are analyzed sequentially in time occurrence order.
After being organized into a plurality of track cues, one track cue can be firstly selected according to the time occurrence sequence for analysis, namely, the next track cue is acquired, and the selected track cue is subjected to self attribute analysis. Specifically, the time difference, the distance, the speed of time and the city and other basic data between two track points in the selected track clue can be calculated, and then the attribute of the selected track clue is judged according to the calculated basic data. The attributes of the track clues may include driving and stopping, wherein driving also includes a special attribute of overspeed.
In calculating the distance between two track points in the selected track cues, the position (including longitude and latitude) of each track point can be based onA distance between two track points in the selected track cue is determined. Wherein, Refers to the longitude of any one of the track points in the selected track cue,Refers to the longitude of another track point in the selected track cue,Refers to the latitude of any one of the selected track points in the track cues,Refers to the latitude of another track point in the selected track cue.
When calculating the city information between two track points in the selected track clues, the geographical coordinates of the track points can be compared with the preconfigured electronic fences of all cities, if the electronic fences fall into the corresponding cities, the electronic fences are marked as the information of the corresponding cities, and if the electronic fences do not fall into any cities, the electronic fences are marked as non-city spaces.
For the selected track clues, if the time difference between two track points in the selected track clues is less than 3min, the average speed per hour between the two track points can be determined. If the average speed per hour is less than 1.5m/s, the selected track cue may be determined to be stationary in nature. If the average speed per hour is greater than or equal to 1.5m/s, the attribute of the selected track cue may be determined to be driving. If the average speed per hour is greater than or equal to 120m/s, then the selected track cue may be determined to have an attribute of speeding.
If the time difference between two track points in the selected track clue exceeds 3min, the distance between the two track points can be determined. If the distance is less than the error distance, the selected track cue may be determined to be park. If the distance is greater than or equal to the error distance, the attribute of the selected track cue may be determined to be travel. Wherein the error distance may be 300m.
After self attribute analysis of the selected track cues, an event evidence collection phase triggered by the track cues can be entered. Specifically, the evidence collection conditions of all the existing events can be traversed, and in the case that the selected track clues meet the evidence collection conditions of a certain event, the evidence track points of the hit event are updated to track points meeting the conditions in the selected track clues. Thereafter, a trace-thread triggered event generation phase may be entered. Specifically, the generation condition of the event which is not generated temporarily can be traversed, a corresponding new event is generated under the condition that the current track clue meets the generation condition, and the evidence track point of the new event is updated to the track point which meets the condition in the current track clue.
The settlement process may be performed separately for each event. For a generated event, the process includes determining whether a current evidence trace point satisfies a trigger condition resulting in triggering of the event, and whether a current trace or current situation satisfies a release condition resulting in release of the event. For non-generated events, the process includes determining whether the current event condition satisfies a generation condition, thereby resulting in event generation, which may inherit evidence trace points of the triggering event. If settlement is completed for all events based on the current trajectory line, the process may return to the step of obtaining the next trajectory line. If settlement is not completed in any event of all events obtained based on the current track line, settlement is continued.
If it is determined that an event is generated based on the current track cue but not triggered, then the trigger logic may not be executed. If the trigger is generated after a certain event is judged based on the current track clue, the trigger logic corresponding to the trigger event can be called. To avoid repeated triggering of the same event in a short time, each event is given a unique ID after generation and recorded in an event status table. If the same event is the first trigger, then trigger logic may be executed. If the same event is not the first trigger, whether the distance from the last trigger exceeds the preset duration can be judged. If the distance from the last trigger exceeds the preset time, the trigger logic can be executed. If the distance from the last trigger does not exceed the preset time length, the trigger logic may not be executed.
Under the condition that GPS positioning is only utilized, the influence caused by instability of the GPS positioning is fully considered, and the reality that the uploading time interval of the track point is long and irregular is considered, so that timeliness and effectiveness of judging abnormal driving events are ensured as far as possible in such a limiting environment, and a progressive triggering event management mechanism, namely a clue-evidence-event mechanism, is provided. By separating the generation and triggering of the event, the sustainability and the sectional type proof of the event triggering judgment are realized, and the timeliness is ensured to the maximum extent.
The above scheme is established on the basis of considering the discontinuities of the GPS error and the track points for all the events, and the high-efficiency demonstration in the low-efficiency evidence environment can be realized by carrying out high-standard adjustment on the triggering conditions of the events.
Because the clue-evidence-event mechanism is an event management mechanism based on evidence continuous collection and sectional type evidence, all track data do not need to be read when real-time analysis is carried out, the data read each time is less, the task amount of analysis is less, and each event can multiplex the analysis conclusion of unified track clues so as to prevent a plurality of events from being respectively and repeatedly analyzed, and the analysis efficiency is high. Meanwhile, the event linkage mechanism further prevents the repeated analysis of the event, and further improves the multiplexing rate of the analysis. Furthermore, the screening mechanism based on the key evidence ensures that each event is aimed at a plurality of key evidence track points which are screened in advance when triggering verification is carried out, and integral analysis verification is not required to be carried out on all cue data, so that the calculated amount can be contracted as much as possible, and the verification efficiency is accelerated.
According to the technical scheme, the track points to be analyzed are selected from the transportation track of the invoice to be processed, whether the driving event is generated or not is judged based on the selected track point pairs to be analyzed, and whether the driving behavior of the vehicle is in compliance or not is detected based on the evidence track points of the generated driving event, so that the judgment of compliance of the driving behavior of the vehicle is more accurate.
Fig. 1 and 2 are flow diagrams of a method for detecting driving behavior of a vehicle based on a track of a vehicle in one embodiment. It should be understood that, although the steps in the flowcharts of fig. 1 and 2 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 and 2 may include multiple sub-steps or phases that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or phases are performed necessarily occur sequentially, but may be performed alternately or alternately with at least a portion of other steps or other steps.
In one embodiment, there is provided an apparatus for detecting driving behavior of a vehicle based on a track of a vehicle, including:
a memory configured to store instructions; and
And the processor is configured to call the instruction from the memory and can realize the method for detecting the driving behavior of the vehicle based on the driving track when executing the instruction.
In one embodiment, a storage medium is provided having a program stored thereon, which when executed by a processor, implements the above-described method of detecting vehicle driving behavior based on a lane.
In one embodiment, a processor is provided for running a program, where the program runs to perform the above method for detecting driving behavior of a vehicle based on a vehicle track.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 3. The computer device includes a processor a01, a network interface a02, a memory (not shown) and a database (not shown) connected by a system bus. Wherein the processor a01 of the computer device is adapted to provide computing and control capabilities. The memory of the computer device includes internal memory a03 and nonvolatile storage medium a04. The nonvolatile storage medium a04 stores an operating system B01, a computer program B02, and a database (not shown in the figure). The internal memory a03 provides an environment for the operation of the operating system B01 and the computer program B02 in the nonvolatile storage medium a04. The database of the computer equipment is used for storing data such as judging results of whether the driving behaviors of the vehicle to be detected are in compliance or not. The network interface a02 of the computer device is used for communication with an external terminal through a network connection. The computer program B02, when executed by the processor a01, implements a method of detecting a driving behavior of a vehicle based on a lane departure.
It will be appreciated by those skilled in the art that the structure shown in FIG. 3 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
The embodiment of the application provides equipment, which comprises a processor, a memory and a program stored in the memory and capable of running on the processor, wherein the processor realizes the step of detecting the driving behavior of a vehicle based on the driving track when executing the program.
The application also provides a computer program product adapted to perform a program initialized with method steps for detecting a driving behaviour of a vehicle based on a path of a vehicle when executed on a data processing device.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (11)
1. A method for detecting driving behavior of a vehicle based on a track of a vehicle, the method comprising:
selecting one non-ship invoice from a plurality of non-ship invoices corresponding to the vehicles to be detected as a to-be-processed invoice;
Acquiring a transportation track of the invoice to be processed, wherein the transportation track comprises a plurality of track points which the vehicle to be detected passes from the starting transportation moment to the current transportation moment;
Selecting N track points to be analyzed from the plurality of track points, wherein N is a natural number;
dividing N track points to be analyzed into a plurality of track cue groups under the condition that the value of N is larger than or equal to a preset value, wherein each track cue group consists of track points to be analyzed of any two adjacent time points;
sequencing the processing sequence of all track cue groups according to the track points to be analyzed with the earliest transportation time or the latest transportation time in each track cue group, wherein the processing sequence of the track cue group where the track points to be analyzed with the earliest transportation time are positioned is positioned at the front;
the processing sequence is arranged in a first track cue group to be used as a current cue group;
Determining a first attribute characteristic of the current clue group according to first track data of track points to be analyzed in the current clue group;
determining that the state of the driving event of the first type is a generated state under the condition that the generation condition of any driving event of the first type is met according to the first track data or the first attribute characteristics, and determining the driving event of the first type of the generated state as a first to-be-triggered event, wherein the driving event of the first type comprises a continuous detention event, a continuous driving event, an overdrive driving event, a night driving event, a city detention event and a non-city detention event;
determining a track point to be analyzed corresponding to the earliest time in the current clue group as a first evidence track point of the first event to be triggered;
determining a track point to be analyzed corresponding to the latest time in the current clue group as a second evidence track point of the first event to be triggered;
Determining whether the driving behavior of the vehicle to be detected is compliant or not according to the first evidence track point and the second evidence track point;
Wherein the determining whether the driving behavior of the vehicle to be detected is compliant according to the first evidence track point and the second evidence track point includes:
determining the state of the first event to be triggered according to the first evidence track point and the second evidence track point;
determining a second attribute characteristic of a next track cue group according to second track data of track points to be analyzed in the next track cue group under the condition that the state of the first trigger event is an un-triggered state;
Under the condition that the evidence collection condition of the first to-be-triggered event is met according to the second track data and/or the second attribute characteristics, updating the second evidence track point according to the to-be-analyzed track point corresponding to the latest time in the next track clue group;
re-determining the state of the first event to be triggered according to the first evidence track point and the updated second evidence track point;
Updating the first to-be-triggered event to a first triggered event under the condition that the state of the first to-be-triggered event is re-determined to be the triggered state;
And determining that the driving behavior of the vehicle to be detected from the starting transportation moment is not compliant when the first triggered event is an abnormal event.
2. The method for detecting driving behavior of a vehicle based on a driving track according to claim 1, wherein selecting N track points to be analyzed from the plurality of track points includes:
Detecting whether the transportation track is acquired for the first time;
Under the condition that the transportation track is acquired for the first time, taking a plurality of track points from the starting transportation time to the current transportation time as track points to be analyzed, and storing the current track points corresponding to the current transportation time into a record table corresponding to the invoice to be processed;
judging whether the current track point corresponding to the current transportation moment is consistent with the track point recorded in the record table corresponding to the invoice to be processed under the condition that the transportation track is not acquired for the first time;
returning to the step of selecting, as an invoice to be processed, an invoice not to be transferred from among a plurality of invoices not to be transferred corresponding to the vehicle to be detected, in the case where the current track point coincides with the track point recorded in the recording table;
And under the condition that the current track point is inconsistent with the track points recorded in the recording table, taking all track points from the track points recorded in the recording table to the current track point as track points to be analyzed, and updating the track points recorded in the recording table to the current track point.
3. The method of detecting vehicle driving behavior based on a trajectory of a vehicle according to claim 1, further comprising:
Updating the state of the first to-be-triggered event to a released state and clearing the first to-be-triggered event under the condition that the first to-be-triggered event is released is determined to be met according to the second track data or the second attribute characteristics;
and taking the track thread group which is sequentially arranged behind the next track thread group as a new current thread group, and returning to the step of determining the first attribute characteristics of the current thread group according to the first track data of the track points to be analyzed in the current thread group so as to analyze the newly determined current thread group until the plurality of track thread groups are analyzed.
4. The method of detecting vehicle driving behavior based on a trajectory of a vehicle according to claim 1, further comprising:
Determining that the state of any other driving event except the driving event is a generated state and determining that the other driving event in the generated state is a second event to be triggered under the condition that the generation condition of any other driving event except the driving event is met according to the second track data or the second attribute characteristics;
Determining evidence track points of the second to-be-triggered event according to the track points to be analyzed in the next track cue group;
Determining the state of the second event to be triggered according to the evidence track point of the second event to be triggered;
updating the second to-be-triggered event to a second triggered event under the condition that the state of the second to-be-triggered event is the triggered state;
And if the second triggered event is an abnormal event, determining that the driving behavior of the vehicle to be detected from the starting transportation moment is not compliant.
5. The method for detecting vehicle driving behavior based on a trajectory of a vehicle according to claim 4, further comprising:
and returning to the step of determining the second attribute characteristics of the next track cue group according to the second track data of the track points to be analyzed in the next track cue group under the condition that the state of the first trigger event is re-determined to be the non-trigger state or the state of the second trigger event is determined to be the non-trigger state according to the evidence track points of the second trigger event, so as to analyze the track cue groups which are sequentially arranged behind the next track cue group until the plurality of track cue groups are analyzed.
6. The method for detecting vehicle driving behavior based on a trajectory of a vehicle according to claim 4, further comprising:
Judging whether the generation condition of the associated event corresponding to the triggered event is met or not according to any one of the first triggered event and the second triggered event;
Under the condition that the generation condition of the association event is met, determining that the triggered event triggers the generation of the association event, and determining the association event with the generated state as a third event to be triggered;
determining the state of the third event to be triggered according to the evidence track points of the triggered event corresponding to the third event to be triggered;
Updating the third to-be-triggered event into a third triggered event under the condition that the state of the third to-be-triggered event is the triggered state;
And if the third triggered event is an abnormal event, determining that the driving behavior of the vehicle to be detected from the starting transportation moment is not compliant.
7. The method of detecting vehicle driving behavior based on a trajectory of a vehicle of claim 6, further comprising:
For any one triggered event of the first triggered event, the second triggered event and the third triggered event, judging whether the triggered event is first trigger or not under the condition that the triggered event is an abnormal event;
Executing a preset driving intervention operation under the condition that the triggered event is the first trigger or the triggered event is the non-first trigger and the triggering duration of the triggered event exceeds the preset duration;
And under the condition that the triggered event is not triggered for the first time and the triggering duration of the triggered event does not exceed the preset duration, the preset driving intervention operation is not executed.
8. The method of detecting vehicle driving behavior based on a trajectory of a vehicle according to claim 1, further comprising:
after the processing sequence is arranged in the first track cue group as a current cue group, acquiring the state of the invoice to be processed;
Determining the state of the driving event of the second type as a generated state and determining the driving event of the second type of the generated state as a fourth to-be-triggered event under the condition that the state of the to-be-processed invoice meets the generation condition of any driving event of the second type;
Determining the evidence track point of the fourth to-be-triggered event according to the track points to be analyzed in the current clue group;
and determining whether the driving behavior of the vehicle to be detected is compliant or not according to the evidence track point of the fourth event to be triggered.
9. The method of detecting vehicle driving behavior based on a trajectory of a vehicle of claim 8, wherein the second type of driving event includes a overtime pick-up event and a tamper anomaly event.
10. An apparatus for detecting driving behavior of a vehicle based on a track of a vehicle, the apparatus comprising:
a memory configured to store instructions; and
A processor configured to recall the instructions from the memory and when executing the instructions enable the method of detecting vehicle driving behaviour based on a track as claimed in any one of claims 1 to 9.
11. A machine-readable storage medium having stored thereon instructions for causing a machine to perform the method of detecting vehicle driving behaviour based on a track as claimed in any one of claims 1 to 9.
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