Screening and shunting processing method and system for potential traffic safety hazard behaviors of electric bicycles

Abstract

The invention relates to the technical field of intelligent traffic management, and particularly discloses a screening and shunting processing method and system for potential traffic safety hazard behaviors of electric bicycles, and the processing method comprises the steps: obtaining all to-be-checked potential traffic safety hazard behavior records on the current day and corresponding electric bicycles; calculating the total number of times of historical traffic potential safety hazard behavior records of each corresponding electric bicycle within a certain historical time period, and screening out target electric bicycles with the total number of times of historical records greater than or equal to a preset number of times threshold value from all the corresponding electric bicycles; calculating a traffic potential safety hazard behavior score of each target electric bicycle on the current day; reminding the electric bicycle driver of which the total historical record number of times is not greater than a preset number of times threshold value; the target electric bicycle driver with the behavior score not larger than a preset score threshold value on the current day is educated; and punishing the target electric bicycle driver of which the behavior score on that day is greater than a preset score threshold. The social benefit of traffic potential safety hazard behavior management can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent traffic management, and more specifically, to a method and system for screening and diverting electric bicycle traffic safety hazard behaviors. Background Art

[0002] At present, the number of electric bicycles has far exceeded that of cars, which has caused a series of traffic safety problems. Traffic safety hazards such as running red lights, driving against traffic, occupying motor vehicle lanes, and not wearing helmets are frequent. Relevant management departments have begun to explore the use of intelligent traffic monitoring equipment to monitor and record different traffic safety hazard behaviors. The relevant methods are more focused on exploring the use of artificial intelligence technology to identify traffic safety hazard behaviors or improve the accuracy of capturing certain hazard behaviors.

[0003] Currently, all the image evidence of automobile traffic safety hazards captured by intelligent traffic monitoring equipment must be manually reviewed before they can be processed at the window. However, the number of electric bicycle traffic safety hazards is huge, which has exceeded the processing capacity of existing staff of the traffic management department by dozens of times. If all the captured traffic safety hazards are pushed to the staff without scientific screening and filtering by the information system, it will cause a huge processing burden for the staff at the image review and hazard behavior processing window. At the same time, there will be a lack of focus in the work, low utilization rate of management resources of government departments, and any improper handling will cause social public opinion. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the present invention provides a method and system for screening and diverting electric bicycle traffic safety hazard behaviors to solve the problem of insufficient human resources in the current management departments in handling electric bicycle traffic safety hazard behaviors.

[0005] As a first aspect of the present invention, a method for screening and diverting electric bicycle traffic safety hazard behaviors is provided, comprising:

[0006] Step S1: Obtain all traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycles;

[0007] Step S2: Retrieve all historical traffic safety hazard behavior records of each corresponding electric bicycle within a certain historical time period, and calculate the total number of historical traffic safety hazard behavior records of each corresponding electric bicycle within the certain historical time period, and then select target electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to a preset number threshold k1 from all corresponding electric bicycles;

[0008] Step S3: reviewing the pending traffic safety hazard behavior records of each target electric bicycle on that day, and calculating the traffic safety hazard behavior score of each target electric bicycle on that day based on all the reviewed traffic safety hazard behavior records of each target electric bicycle on that day;

[0009] Step S4: Send SMS reminders to electric bicycle drivers whose total number of historical traffic safety hazard behavior records is not greater than the preset number threshold k1; send SMS reminders to electric bicycle drivers whose traffic safety hazard behavior score on the day is greater than the preset score threshold F cap The target electric bicycle driver shall be punished; the traffic safety hazard behavior score on that day is not greater than the preset score threshold F cap The goal is to educate electric bicycle drivers.

[0010] Furthermore, the steps S1 and S2 further include:

[0011] All the traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycle license plate numbers are formed into a first list Tab1;

[0012] Form a second list Tab2 with each electric bicycle license plate number in the first list Tab1 and all corresponding historical traffic safety hazard behavior records within a certain historical period;

[0013] The total number of times P of historical traffic safety hazard behavior records for each electric bicycle license plate number in the second table Tab2 within a certain historical period of time is calculated, and the calculation formula is as follows:

[0014]

[0015] Among them, p i is the number of times the i-th historical traffic safety hazard behavior record appears for the same electric bicycle license plate number within a certain historical period of time, and n is the total number of types of historical traffic safety hazard behavior records;

[0016] Sort the total number of times P corresponding to each electric bicycle license plate number in the second list Tab2 from large to small to form the first column of the third list Tab3;

[0017] The total number m of the electric bicycle license plate numbers corresponding to each total number of times P in the first column of the third table Tab3 is formed into the second column of the third table Tab3;

[0018] The total number of traffic safety hazard behavior records to be reviewed on the same day for all electric bicycle license plate numbers corresponding to each total number of times P in the first column of the third list Tab3 is formed into the third column of the third list Tab3; wherein, the total number of traffic safety hazard behavior records to be reviewed on the same day for a certain electric bicycle license plate number corresponding to each total number of times P in the first column of the third list Tab3 is retrieved in association Among them, l i is the number of i-th type of traffic safety hazard behavior records to be reviewed for a certain electric bicycle license plate number on that day, j is the number of types of traffic safety hazard behavior records to be reviewed for a certain electric bicycle license plate number on that day; then each total number P in the first column of the third table Tab3 corresponds to the total number of traffic safety hazard behavior records to be reviewed for all electric bicycle license plate numbers on that day

[0019] The data in the third column of the third table Tab3 are accumulated from top to bottom to obtain the total number of accumulated value Sum1 of traffic safety hazard behavior records to be reviewed on that day; when the calculated total number of accumulated value Sum1 is greater than the preset daily review total number threshold Cap1, the accumulation calculation is stopped, and the corresponding total number P at this time is used as the preset number threshold k1;

[0020] Target electric bicycle license plate numbers whose total times P are greater than or equal to the preset times threshold k1 are screened out from the third list Tab3, and the pending traffic safety hazard behavior records of each target electric bicycle license plate number on that day are reviewed.

[0021] Furthermore, the traffic safety hazard behavior score of each target electric bicycle on that day is calculated based on all the verified traffic safety hazard behavior records of each target electric bicycle on that day, and further includes:

[0022] Construct the traffic safety hazard behavior score model F for each target electric bicycle on that day, and the formula is as follows:

[0023] F=f x +γf y +δf z

[0024] Among them, γ and δ are coefficient values, f x It represents the sum of the traffic safety impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day; f y represents the adjusted score of each target electric bicycle based on its historical penalty record on that day; f z Represents the adjusted score of each target electric bicycle on that day based on its historical education record.

[0025] Furthermore, the sum of the traffic safety impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day is f x The calculation formula is as follows:

[0026] According to all the verified traffic safety hazard behavior records of each target electric bicycle on that day, the multiple traffic safety hazard behaviors that occurred on each target electric bicycle on that day were divided into traffic safety hazard behaviors with serious impact, traffic safety hazard behaviors with general impact, and traffic safety hazard behaviors with slight impact, so as to form a traffic safety hazard behavior count matrix Q with different impact levels. i ;

[0027]

[0028] Among them, the matrix Q i The qi in the first column yanj The number of traffic safety hazards with the jth serious impact level is indicated; the qi in the second column yij The number of traffic safety hazards of the jth general impact level is represented by the qi in the third column. qingj Indicates the number of traffic safety hazard behaviors of the jth type with a minor impact;

[0029] Different weight values ​​are assigned to traffic safety hazard behaviors with serious impact, traffic safety hazard behaviors with general impact, and traffic safety hazard behaviors with slight impact, so as to form a weight value matrix. Among them, w yan The weight value of the traffic safety hazard behavior that indicates the degree of serious impact, w yi The weight value of the traffic safety hazard behavior with a general impact degree, w qing Indicates the weight value of traffic safety hazard behaviors with a minor impact;

[0030] The sum of the impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day is f x is the sum of the elements in the Qi*Wei matrix.

[0031] Furthermore, the adjustment score f of each target electric bicycle on that day based on its historical penalty record y The calculation formula is as follows:

[0032] f y =(S yan -1)*w yan +(S yi -1)*w yi +(S qing -1)*w qing

[0033] Among them, S yan The number of traffic safety hazards that seriously affect each target electric bicycle on that day is the matrix Q i The sum of the number of elements in the first column; S yi The number of traffic safety hazards with a general impact on each target electric bicycle on that day, that is, the matrix Q i The sum of the number of elements in the second column; S qing The matrix Q is the number of minor traffic safety hazards that occurred on each target electric bicycle on that day. i The sum of the number of elements in the third column;

[0034] If a target electric bicycle has multiple serious traffic safety hazards on the same day, it is determined whether the driver of the target electric bicycle has a historical penalty record for such serious traffic safety hazards within a certain historical period of time. If so, Otherwise, γ=-1; that is

[0035]

[0036] Calculate the daily average number of serious traffic safety hazards that occurred on the target electric bicycle within a certain historical period.

[0037] If the target electric bicycle has serious traffic safety hazards on that day, the number of behaviors S yan The daily average number of traffic safety hazards that are greater than the target and have a serious impact on electric bicycles within a certain historical period but

[0038] If the target electric bicycle has serious traffic safety hazards on that day, the number of behaviors S yan The daily average number of traffic safety hazards that are no greater than the target electric bicycle within a certain historical period and have a serious impact Then, the time series of the number of traffic safety hazard behaviors with serious impact on the target electric bicycle within a period of time after the last penalty record is used to perform a linear fit of a univariate linear function y = at + b to fit the

[0039] Wherein, t represents the tth day, the tth week or the tth quarter, and y represents the number of traffic safety hazards with serious impact occurring on the tth day, the tth week or the tth quarter.

[0040] Furthermore, the calculation formula of a is as follows:

[0041]

[0042] Among them, t i Indicates the tth time period after the most recent penalty record. i Day, t i Week or t i quarter;y i It represents the number of serious traffic safety hazards that occurred on the same day, week or quarter; n is the total number of days, weeks or quarters between the date of the most recent penalty record and the review date.

[0043] Furthermore, the adjusted score f of each target electric bicycle on that day based on its historical education record z The calculation formula is as follows:

[0044]

[0045] f(r,x)=r*x / 2

[0046] Among them, r is the number of traffic safety hazard behaviors of a certain type that occurred on a certain target electric bicycle on that day; j is the number of types of traffic safety hazard behaviors that occurred on the target electric bicycle on that day; x is the number of times the driver of the target electric bicycle has been educated for this type of traffic safety hazard behavior within a certain historical period of time. When x is not equal to 0, δ=1; when x is equal to 0, δ=-1.

[0047] Furthermore, the step S4 further includes:

[0048] The traffic safety hazard behavior score F of each target electric bicycle on that day is sorted from large to small to form the first column of the fourth list Tab4, the target electric bicycle license plate number corresponding to each traffic safety hazard behavior score in the first column of the fourth list Tab4 forms the second column of the fourth list Tab4, and the number of traffic safety hazard behaviors on that day corresponding to each target electric bicycle license plate number in the second column of the fourth list Tab4 forms the third column of the fourth list Tab4;

[0049] The data in the third column of the fourth table Tab4 are accumulated from top to bottom to obtain the total number of traffic safety hazard behavior records that have been reviewed on that day. The accumulated value Sum2; when the calculated total number of accumulated value Sum2 is greater than the preset daily total number of penalty threshold Cap2, the accumulation calculation is stopped, and the corresponding traffic safety hazard behavior score F at this time is used as the preset score threshold F cap ;

[0050] For traffic safety hazard behaviors with a score greater than the preset score threshold F capThe target electric bicycle driver is punished; the traffic safety hazard behavior score is not greater than the preset score threshold F cap The goal is to provide traffic safety education to electric bicycle drivers.

[0051] As a second aspect of the present invention, a screening and diversion processing system for electric bicycle traffic safety hazard behaviors is provided, comprising:

[0052] The acquisition module is used to obtain all the traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycles;

[0053] A screening module is used to retrieve all historical traffic safety hazard behavior records of each corresponding electric bicycle within a certain historical time period, and calculate the total number of historical traffic safety hazard behavior records of each corresponding electric bicycle within the certain historical time period, and then screen out target electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to a preset number threshold k1 from all corresponding electric bicycles;

[0054] A calculation module is used to review the pending traffic safety hazard behavior records of each target electric bicycle on that day, and calculate the traffic safety hazard behavior score of each target electric bicycle on that day based on all the reviewed traffic safety hazard behavior records of each target electric bicycle on that day;

[0055] The processing module is used to send SMS reminders to electric bicycle drivers whose total number of historical traffic safety hazard behavior records is not greater than the preset number threshold k1; and to send SMS reminders to electric bicycle drivers whose traffic safety hazard behavior score on the day is greater than the preset score threshold F cap The target electric bicycle driver shall be punished; the traffic safety hazard behavior score on that day is not greater than the preset score threshold F cap The goal is to provide traffic safety education to electric bicycle drivers.

[0056] The screening, diversion and processing method and system for electric bicycle traffic safety hazard behaviors provided by the present invention have the following advantages: with the help of electric bicycle traffic safety hazard behavior data captured by the existing intelligent monitoring equipment of the traffic management department, the historical continuous behavior characteristics of the parties involved in the traffic safety hazard behaviors are analyzed, not only considering the severity of the impact of different traffic safety hazard behaviors to be reviewed, but also considering the impact of historical safety education, punishment and other treatment measures on the driver's future driving behavior. At the same time, combined with the punishment window processing capacity, a comprehensive score is formed, and diversion is performed based on the comprehensive score calculation, and different treatment measures such as publicity and education and punishment are adopted respectively. Through this method, it is possible to punish as much as possible the stubborn elements whose traffic hazard behaviors have a bad impact and who have been dealt with but have not actively corrected themselves, thereby improving the efficiency of resource utilization for traffic hazard management. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present invention, but do not constitute a limitation of the present invention.

[0058] Figure 1 A flow chart of the screening and diversion processing method for electric bicycle traffic safety hazard behaviors provided by the present invention. DETAILED DESCRIPTION

[0059] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation method, structure, characteristics and effects of the screening and diversion processing method and system for electric bicycle traffic safety hazard behaviors proposed by the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] In this embodiment, a method for screening and diverting electric bicycle traffic safety hazard behaviors is provided, such as Figure 1 As shown, the screening and diversion processing method for electric bicycle traffic safety hazard behaviors includes:

[0061] Step S1: Obtain all traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycles;

[0062] It should be noted that the system can select the review date of the traffic safety hazard behavior records to be reviewed. For example, the review date is selected as July 11, 2024, that is, the current day is July 11, 2024, and all the traffic safety hazard behavior records to be reviewed on that day are extracted, and the electric bicycle license plate number (ID) corresponding to all the traffic safety hazard behavior records to be reviewed are obtained. Among them, the license plate number of the electric bicycle is automatically associated with all the traffic safety hazard behavior records to be reviewed corresponding to this vehicle.

[0063] In the embodiment of the present invention, as shown in Table 1, a total of 153,482 traffic safety hazard behavior records to be reviewed were extracted on July 11, involving 94,300 electric bicycles.

[0064] Table 1

[0065]

[0066] Step S2: Retrieve all historical traffic safety hazard behavior records of 94,300 electric bicycles within a certain historical time period, and calculate the total number of historical traffic safety hazard behavior records for each corresponding electric bicycle within the certain historical time period, and then select target electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to a preset number threshold k1 from all corresponding electric bicycles;

[0067] Preferably, in order to give full play to the limited review capabilities of traffic safety hazard behavior image reviewers, target electric bicycles with a high number of historical hazard times are screened. The steps S1 and S2 also include:

[0068] All the traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycle license plate numbers are formed into a first list Tab1;

[0069] Form a second list Tab2 with all the historical traffic safety hazard behavior records of each electric bicycle license plate number in the first list Tab1 and its corresponding certain historical time period (such as 30 days or 180 days before the review date);

[0070] It should be noted that if an electric bicycle license plate number has no historical traffic safety hazard record within a certain historical period of time (that is, 0), that is, the electric bicycle commits a traffic safety hazard for the first time on that day, the driver of the electric bicycle will be notified by text message to remind him to correct the problem.

[0071] The total number of times P of historical traffic safety hazard behavior records for each electric bicycle license plate number in the second table Tab2 within a certain historical period of time is calculated, and the calculation formula is as follows:

[0072]

[0073] Among them, p i is the number of times the same electric bicycle license plate number has the i-th historical traffic safety hazard behavior record in a certain historical period, and n is the total number of types of historical traffic safety hazard behavior records; for example, if an electric bicycle ran a red light twice and drove against the flow once in a certain historical period, then P = 3;

[0074] Sort the total number of historical traffic safety hazard behavior records P corresponding to each electric bicycle license plate number in the second list Tab2 from large to small to form the first column of the third list Tab3 (30-day historical hazard number);

[0075] The total number m of the electric bicycle license plate numbers corresponding to each total number of times P in the first column of the third table Tab3 forms the second column (corresponding to the number of vehicles) of the third table Tab3;

[0076] In the embodiment of the present invention, as shown in Table 1, within the past 30 days, among 94,300 electric bicycles, 1 electric bicycle had 16 records of potential traffic safety hazards, 3 electric bicycles had 15 records of potential traffic safety hazards, 9 electric bicycles had 14 records of potential traffic safety hazards...

[0077] For each total number P in the first column of the third list Tab3, form the third column (number of potential hazards awaiting review) of the third list Tab3 with the total number of records of potential traffic safety hazards awaiting review that occurred for all electric bicycle license plate numbers on the same day.

[0078] Specifically, perform an associated search for the total number of records of potential traffic safety hazards awaiting review that occurred for a certain electric bicycle license plate number corresponding to each total number P in the first column of the third list Tab3 on the same day where l i is the number of records of the i-th type of potential traffic safety hazard awaiting review that occurred for a certain electric bicycle license plate number on the same day, and j is the number of types of potential traffic safety hazards awaiting review that occurred for a certain electric bicycle license plate number on the same day;

[0079] Then, for each total number P in the first column of the third list Tab3, the total number of records of potential traffic safety hazards awaiting review that occurred for all electric bicycle license plate numbers on the same day

[0080] In the embodiment of the present invention, as shown in Table 1, within the past 30 days, 1 electric bicycle had 16 records of potential traffic safety hazards, and this electric bicycle had a total of 13 records of potential traffic safety hazards awaiting review on the same day; within the past 30 days, 3 electric bicycles had 15 records of potential traffic safety hazards, and these 3 electric bicycles had a total of 32 records of potential traffic safety hazards awaiting review on the same day; within the past 30 days, 9 electric bicycles had 14 records of potential traffic safety hazards, and these 9 electric bicycles had a total of 81 records of potential traffic safety hazards awaiting review on the same day; then, calculate in this way successively.

[0081] Cumulatively calculate the data in the third column of the third list Tab3 from top to bottom to obtain the cumulative value Sum1 of the total number of records of potential traffic safety hazards awaiting review on the same day; when Sum1 < Cap1, continue to accumulate; when the calculated cumulative value Sum1 of the total number of times is greater than or equal to the preset daily review total number threshold Cap1, stop the cumulative calculation, and at this time, the corresponding total number P is used as the preset number threshold k1;

[0082] It should be noted that based on the daily historical review data of the traffic safety hazard behavior image review staff, the preset daily review total number threshold Cap1 is evaluated.

[0083] In the embodiment of the present invention, it is assumed that the preset daily review total number threshold Cap1 = 12000, until the total number of daily review total number threshold Cap1 is accumulated, as shown in Table 1, 13 is the total number of the first row; 45 is the total number of 13+32 of the first and second rows, 126 is the total number of 13+32+81 of the first, second and third rows; 377 is the total number of 13+32+81+251 of the first, second, third and fourth rows...; when 12989≥12000, stop the accumulation calculation, and the preset number threshold k1 = 6. Note that 12989 is slightly larger than the review capacity and can be ignored, because in actual work, some waste images of traffic hazard behaviors will be generated, which can be ignored if slightly exceeded the review capacity.

[0084] Filter out target electric bicycle license plate numbers whose total number of times P is greater than or equal to the preset number threshold k1 from the third list Tab3, and review the pending traffic safety hazard behavior records of each target electric bicycle license plate number on that day, and then carry out traffic hazard persuasion and rectification measures.

[0085] It should be noted that, as shown in Table 1, the target electric bicycle license plate numbers are determined for 6 times or more to form a list of vehicles that will be punished for hidden dangers. Note: Whether to take k1 or k1+1 depends on the actual situation, because there will be many waste images that do not meet the requirements during the image review process. Therefore, the k1 value is slightly higher than the manual review ability, which can be ignored. If it is too much higher than the manual review ability, k1+1 can be taken.

[0086] Step S3: reviewing the pending traffic safety hazard behavior records of each target electric bicycle on that day, and calculating the traffic safety hazard behavior score of each target electric bicycle on that day based on all the reviewed traffic safety hazard behavior records of each target electric bicycle on that day;

[0087] In order to carry out more precise handling measures for the group of electric bicycles with a record of traffic safety hazard behaviors, the traffic safety hazard behavior records of this group are analyzed and judged. The present invention not only considers the severity of the impact of different traffic safety hazard behaviors to be reviewed, but also considers the impact of whether the driver has received safety education, punishment and other handling measures in the past on the driver's future driving behavior. At the same time, combined with the processing capabilities of the punishment window, a comprehensive score is formed, and diversion is carried out according to the calculation of the comprehensive score. Different handling measures such as publicity and education and punishment are taken respectively. Through this method, it is possible to punish the stubborn elements whose traffic hazard behaviors have a bad impact and who have been dealt with but have not actively corrected themselves, thereby improving the efficiency of resource utilization for traffic hazard management.

[0088] Preferably, the step of calculating the traffic safety hazard behavior score of each target electric bicycle on that day based on all the verified traffic safety hazard behavior records of each target electric bicycle on that day also includes:

[0089] Construct the traffic safety hazard behavior score model F for each target electric bicycle on that day, and the formula is as follows:

[0090] F=f x +γf y +δf z

[0091] Among them, γ and δ are coefficient values, f x It represents the sum of the traffic safety impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day; f y represents the adjusted score of each target electric bicycle based on its historical penalty record on that day; f z Represents the adjusted score of each target electric bicycle on that day based on its historical education record.

[0092] Specifically, the sum of the traffic safety impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day is f x The calculation formula is as follows:

[0093] According to all the verified traffic safety hazard behavior records of each target electric bicycle on that day, the multiple traffic safety hazard behaviors that occurred on each target electric bicycle on that day were divided into traffic safety hazard behaviors with serious impact (such as running red lights, driving in the wrong direction, etc.), traffic safety hazard behaviors with general impact (such as not wearing a helmet, etc.) and traffic safety hazard behaviors with slight impact (such as random parking, etc.), so as to form a traffic safety hazard behavior count matrix Q with different impact levels i ;

[0094]

[0095] Among them, the matrix Q i The qi in the first column yanj The number of traffic safety hazards with the jth serious impact level is indicated; the qi in the second column yij The number of traffic safety hazards of the jth general impact level is represented by the qi in the third column. qingj Indicates the number of traffic safety hazard behaviors of the jth type with a minor impact;

[0096] Different weight values ​​are assigned to traffic safety hazard behaviors with serious impact, traffic safety hazard behaviors with general impact, and traffic safety hazard behaviors with slight impact, so as to form a weight value matrix. Among them, wyan The weight value of the traffic safety hazard behavior that indicates the degree of serious impact, w yi The weight value of the traffic safety hazard behavior with a general impact degree, w qing The weight value of traffic safety hazard behavior with a minor impact; for example, the weight value w of traffic safety hazard behavior with a serious impact yan =4, the weight value w of the traffic safety hazard behavior with general impact yi =3, the weight value w of traffic safety hazard behavior with slight impact qing is 1, forming a weight value matrix

[0097] The sum of the impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day is f x is the sum of the elements in the Qi*Wei matrix.

[0098] For example, f x =11+8+8=27.

[0099] Specifically, the adjustment score f of each target electric bicycle based on its historical penalty record on that day is y The calculation formula is as follows:

[0100] f y =(S yan -1)*w yan +(S yi -1)*w yi +(S qing -1)*w qing

[0101] Among them, S yan The number of traffic safety hazards that seriously affect each target electric bicycle on that day is the matrix Q i The sum of the number of elements in the first column; S yi The number of traffic safety hazards with a general impact on each target electric bicycle on that day, that is, the matrix Q i The sum of the number of elements in the second column; S qing The matrix Q is the number of minor traffic safety hazards that occurred on each target electric bicycle on that day. i The sum of the number of elements in the third column;

[0102] For example, S yan =1+1+1=3, S yi =2+1+1=4; S qing =1+1+1=3, then f y=(3-1)*4+(4-1)*3+(3-1)*1=8+9+2=19.

[0103] If a target electric bicycle has multiple serious traffic safety hazards on the same day, it is determined whether the driver of the target electric bicycle has a historical penalty record for such serious traffic safety hazards within a certain historical period of time. If so, Otherwise, γ=-1; that is

[0104]

[0105] For example, a target electric bicycle has three serious traffic safety hazards on the same day. If the driver of the target electric bicycle has no historical punishment record for serious traffic safety hazards within a certain historical period, then γ = -1; at this time, γf y = -1*[(S yan -1)*w yan +(S yi -1)*w yi +(S qing -1)*w qing ]=-19.

[0106] Calculate the daily average number of serious traffic safety hazards that occurred on the target electric bicycle within a certain historical period.

[0107] If the target electric bicycle has serious traffic safety hazards on that day, the number of behaviors S yan The daily average number of traffic safety hazards that are greater than the target and have a serious impact on electric bicycles within a certain historical period but To increase the traffic safety hazard behavior score F; this means that the target electric bicycle driver did not properly correct his traffic safety hazard behavior after receiving the punishment, and more attention needs to be paid.

[0108] If the target electric bicycle has serious traffic safety hazards on that day, the number of behaviors S yan The daily average number of traffic safety hazards that are no greater than the target electric bicycle within a certain historical period and have a serious impact Then, the trend of traffic safety hazard behaviors with serious impact on the target electric bicycle in the period after the last penalty record is judged to be gradually increasing or decreasing. The time series of the number of traffic safety hazard behaviors in this period is linearly fitted with a univariate linear function y=at+b to fit the time series. Among them, t represents the tth day, tth week or tth quarter, and y represents the number of traffic safety hazard behaviors with serious impact on the tth day, tth week or tth quarter. Through univariate linear regression, the behavior pattern of traffic safety hazard behaviors of target electric bicycle drivers after being punished once is effectively determined with respect to the time series, that is, the behavioral constraints of the punishment on the driver are determined.

[0109] Specifically, the calculation formula of a is as follows:

[0110]

[0111] Among them, t i Indicates the tth time period after the most recent penalty record. i Day (week, season); yi It represents the number of traffic safety hazards with serious impact on the corresponding day (week, season); n is the total number of days (weeks, seasons) between the date of the most recent penalty record and the review date.

[0112] Specifically, the fitted predicted value using the trend coefficient a As the value of γ. If the fitting function is an increasing function, then a>0, indicating that after the last punishment, the traffic safety hazard behavior of this electric bicycle driver is still showing an increasing trend. If the trend function is a decreasing function, then a≤0, indicating that the traffic safety hazard behavior of the electric bicycle driver has shown a decreasing trend after the last punishment, and the behavior has been corrected to a certain extent. Then the traffic safety hazard behavior score F will decrease, and the level of attention can be appropriately reduced.

[0113] Specifically, the adjusted score f of each target electric bicycle based on its historical education record on that day z The calculation formula is as follows:

[0114]

[0115] f(r,x)=r*x / 2

[0116] Among them, r is the number of traffic safety hazard behaviors of a certain type that occurred on a certain target electric bicycle on that day; j is the number of types of traffic safety hazard behaviors that occurred on the target electric bicycle on that day; x is the number of times the driver of the target electric bicycle has been educated for this type of traffic safety hazard behavior within a certain historical period of time. When x is not equal to 0, δ=1; when x is equal to 0, δ=-1.

[0117] For example, if there have been three minor traffic safety hazards in the past and the person has been educated twice, then fz = 3 * 2 / 2 = 3.

[0118] Step S4: Send a text message reminder to the electric bicycle drivers whose total number of occurrences p of historical traffic safety hazard behavior records is not greater than the preset number threshold k1 to remind the vehicle drivers to correct their behaviors; impose penalties on the target electric bicycle drivers whose traffic safety hazard behavior scores on the current day are greater than the preset score threshold F cap ; conduct traffic safety education for the target electric bicycle drivers whose traffic safety hazard behavior scores on the current day are not greater than the preset score threshold F cap .

[0119] Preferably, in the step S4, it further includes:

[0120] Sort the traffic safety hazard behavior scores F of each target electric bicycle on the current day from largest to smallest to form the first column of the fourth list Tab4. Form the second column of the fourth list Tab4 with the license plate numbers of the target electric bicycles corresponding to each traffic safety hazard behavior score in the first column of the fourth list Tab4. Form the third column of the fourth list Tab4 with the number of occurrences of traffic safety hazard behaviors on the current day corresponding to each license plate number of the target electric bicycle in the second column of the fourth list Tab4;

[0121] Cumulatively calculate the data in the third column of the fourth list Tab4 from top to bottom to obtain the cumulative sum value Sum2 of the total number of audited traffic safety hazard behavior records on the current day; when Sum2 < Cap2, continue to accumulate; when the calculated cumulative sum value Sum2 is greater than or equal to the preset daily penalty total number threshold Cap2, stop the cumulative calculation, and use the corresponding traffic safety hazard behavior score F at this time as the preset score threshold F cap ;

[0122] Impose penalties on the target electric bicycle drivers whose traffic safety hazard behavior scores on the current day are greater than the preset score threshold F cap ; conduct traffic safety education for the target electric bicycle drivers whose traffic safety hazard behavior scores on the current day are not greater than the preset score threshold F cap .

[0123] Specifically, determine the preset daily penalty total number threshold Cap2 according to factors such as the processing capacity threshold of the traffic hazard handling window staff.

[0124] Further, select a certain percentage of target electric bicycle drivers for penalties from the target electric bicycle drivers whose traffic safety hazard behavior scores on the current day are greater than the preset score threshold F cap , for example, the penalty percentage is 25%.

[0125] As another embodiment of the present invention, a screening and diversion processing system for electric bicycle traffic safety hazard behaviors is provided, which includes:

[0126] The acquisition module is used to obtain all the traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycles;

[0127] A screening module is used to retrieve all historical traffic safety hazard behavior records of each corresponding electric bicycle within a certain historical time period, and calculate the total number of historical traffic safety hazard behavior records of each corresponding electric bicycle within the certain historical time period, and then screen out target electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to a preset number threshold k1 from all corresponding electric bicycles;

[0128] A calculation module is used to review the pending traffic safety hazard behavior records of each target electric bicycle on that day, and calculate the traffic safety hazard behavior score of each target electric bicycle on that day based on all the reviewed traffic safety hazard behavior records of each target electric bicycle on that day;

[0129] The processing module is used to send SMS reminders to electric bicycle drivers whose total number of historical traffic safety hazard behavior records is not greater than the preset number threshold k1; and to send SMS reminders to electric bicycle drivers whose traffic safety hazard behavior score on the day is greater than the preset score threshold F cap The target electric bicycle driver shall be punished; the traffic safety hazard behavior score on that day is not greater than the preset score threshold F cap The goal is to provide traffic safety education to electric bicycle drivers.

[0130] The screening and diversion processing method for electric bicycle traffic safety hazard behaviors provided by the present invention can effectively play the role of road intelligent traffic monitoring equipment, provide correction opportunities for electric bicycle drivers with traffic safety hazard behaviors in a wider coverage area, and improve the management department's processing effect on traffic safety hazard behaviors at a low cost. Since using this method, the same number of staff has tried this system for half a year, and the number of road traffic safety hazard behaviors has decreased by 40% year-on-year.

[0131] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technician familiar with this profession can make some changes or modifications to equivalent embodiments of equivalent changes using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the technical solution of the present invention.

Claims

1. A method for screening and diverting electric bicycle traffic safety hazard behaviors, characterized in that: include: Step S1: Obtain all traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycles; Step S2: Retrieve all historical traffic safety hazard behavior records of each corresponding electric bicycle within a certain historical time period, and calculate the total number of times that each corresponding electric bicycle has a historical traffic safety hazard behavior record within the certain historical time period, and then select target electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to a preset number threshold k1 from all corresponding electric bicycles; Step S3: reviewing the pending traffic safety hazard behavior records of each target electric bicycle on that day, and calculating the traffic safety hazard behavior score of each target electric bicycle on that day based on all the reviewed traffic safety hazard behavior records of each target electric bicycle on that day; Step S4: Sending SMS reminders to electric bicycle drivers whose total number of historical traffic safety hazard behavior records is not greater than the preset number threshold k1; For traffic safety hazard behaviors whose scores on that day are greater than the preset score threshold F cap The target electric bicycle driver shall be punished; the traffic safety hazard behavior score on that day is not greater than the preset score threshold F cap The goal is to provide traffic safety education to electric bicycle drivers.

2. The method for screening and diverting electric bicycle traffic safety hazard behaviors according to claim 1 is characterized in that: The steps S1 and S2 further include: All the traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycle license plate numbers are formed into a first list Tab1; Form a second list Tab2 with each electric bicycle license plate number in the first list Tab1 and all corresponding historical traffic safety hazard behavior records within a certain historical period; The total number of times P of historical traffic safety hazard behavior records for each electric bicycle license plate number in the second table Tab2 within a certain historical period of time is calculated, and the calculation formula is as follows: Among them, p i is the number of times the i-th historical traffic safety hazard behavior record appears for the same electric bicycle license plate number within a certain historical period of time, and n is the total number of types of historical traffic safety hazard behavior records; Sort the total number of times P corresponding to each electric bicycle license plate number in the second list Tab2 from large to small to form the first column of the third list Tab3; The total number m of the electric bicycle license plate numbers corresponding to each total number of times P in the first column of the third table Tab3 is formed into the second column of the third table Tab3; The total number of traffic safety hazard behavior records to be reviewed on the same day for all electric bicycle license plate numbers corresponding to each total number of times P in the first column of the third list Tab3 is formed into the third column of the third list Tab3; wherein, the total number of traffic safety hazard behavior records to be reviewed on the same day for a certain electric bicycle license plate number corresponding to each total number of times P in the first column of the third list Tab3 is retrieved in association Among them, l i is the number of i-th type of traffic safety hazard behavior records to be reviewed for a certain electric bicycle license plate number on that day, j is the number of types of traffic safety hazard behavior records to be reviewed for a certain electric bicycle license plate number on that day; then each total number P in the first column of the third table Tab3 corresponds to the total number of traffic safety hazard behavior records to be reviewed for all electric bicycle license plate numbers on that day The data in the third column of the third table Tab3 are accumulated from top to bottom to obtain the total number of accumulated value Sum1 of traffic safety hazard behavior records to be reviewed on that day; when the calculated total number of accumulated value Sum1 is greater than the preset daily review total number threshold Cap1, the accumulation calculation is stopped, and the corresponding total number P at this time is used as the preset number threshold k1; Target electric bicycle license plate numbers whose total times P are greater than or equal to the preset times threshold k1 are screened out from the third list Tab3, and the pending traffic safety hazard behavior records of each target electric bicycle license plate number on that day are reviewed.

3. The method for screening and diverting electric bicycle traffic safety hazard behaviors according to claim 1 is characterized in that: The traffic safety hazard behavior score of each target electric bicycle on that day is calculated based on all the reviewed traffic safety hazard behavior records of each target electric bicycle on that day, and also includes: Construct the traffic safety hazard behavior score model F for each target electric bicycle on that day, and the formula is as follows: F=f x +γf y +δf z Among them, γ and δ are coefficient values, f x It represents the sum of the traffic safety impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day; f y represents the adjusted score of each target electric bicycle based on its historical penalty record on that day; f z Represents the adjusted score of each target electric bicycle on that day based on its historical education record.

4. The method for screening and diverting electric bicycle traffic safety hazard behaviors according to claim 3 is characterized in that: The sum of the traffic safety impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day f x The calculation formula is as follows: According to all the verified traffic safety hazard behavior records of each target electric bicycle on that day, the multiple traffic safety hazard behaviors that occurred on each target electric bicycle on that day were divided into traffic safety hazard behaviors with serious impact, traffic safety hazard behaviors with general impact, and traffic safety hazard behaviors with slight impact, so as to form a traffic safety hazard behavior count matrix Q with different impact levels. i ; Among them, the matrix Q i The qi in the first column yanj The number of traffic safety hazards with the jth serious impact level is indicated; the qi in the second column yij The number of traffic safety hazards of the jth general impact level is represented by the qi in the third column. qingj Indicates the number of traffic safety hazard behaviors of the jth type with a minor impact; Different weight values ​​are assigned to traffic safety hazard behaviors with serious impact, traffic safety hazard behaviors with general impact, and traffic safety hazard behaviors with slight impact, so as to form a weight value matrix. Among them, w yan The weight value of the traffic safety hazard behavior that indicates the degree of serious impact, w yi The weight value of the traffic safety hazard behavior with a general impact degree, w qing Indicates the weight value of traffic safety hazard behaviors with a minor impact; The sum of the impact scores of all the traffic safety hazard behavior records that have been reviewed for each target electric bicycle on that day is f x is the sum of the elements in the Qi*Wei matrix.

5. The method for screening and diverting electric bicycle traffic safety hazard behaviors according to claim 4 is characterized in that: The adjusted score f of each target electric bicycle based on its historical penalty record on that day y The calculation formula is as follows: f y =(S yan -1)*w yan +(S yi -1)*w yi +(S qing -1)*w qing Among them, S yan The number of traffic safety hazards that seriously affect each target electric bicycle on that day is the matrix Q i The sum of the number of elements in the first column; S yi The number of traffic safety hazards with a general impact on each target electric bicycle on that day, that is, the matrix Q i The sum of the number of elements in the second column; S qing The matrix Q is the number of minor traffic safety hazards that occurred on each target electric bicycle on that day. i The sum of the number of elements in the third column; If a target electric bicycle has multiple serious traffic safety hazards on the same day, it is determined whether the driver of the target electric bicycle has a historical penalty record for such serious traffic safety hazards within a certain historical period of time. If so, Otherwise, γ=-1; that is Calculate the daily average number of serious traffic safety hazards that occurred on the target electric bicycle within a certain historical period. If the number of traffic safety hazards that seriously affect the target electric bicycle on that day is greater than the daily average number of traffic safety hazards that seriously affect the target electric bicycle in a certain historical period of time but If the target electric bicycle has a serious traffic safety hazard on that day, the number of Sya n The daily average number of traffic safety hazards that are no greater than the target electric bicycle within a certain historical period and have a serious impact Then, the time series of the number of traffic safety hazard behaviors with serious impact on the target electric bicycle within a period of time after the last penalty record is used to perform a linear fit of a univariate linear function y = at + b to fit the Wherein, t represents the tth day, the tth week or the tth quarter, and y represents the number of traffic safety hazards with serious impact occurring on the tth day, the tth week or the tth quarter.

6. The method for screening and diverting electric bicycle traffic safety hazard behaviors according to claim 5 is characterized in that: The calculation formula of a is as follows: Among them, t i Indicates the tth time period after the most recent penalty record. i Day, t i Week or t i quarter;y i It represents the number of serious traffic safety hazards that occurred on the same day, week or quarter; n is the total number of days, weeks or quarters between the date of the most recent penalty record and the review date.

7. The method for screening and diverting electric bicycle traffic safety hazard behaviors according to claim 5 is characterized in that: The adjusted score f of each target electric bicycle based on its historical education record on that day z The calculation formula is as follows: f(r,x)=r*x / 2 Among them, r is the number of traffic safety hazard behaviors of a certain type that occurred on a certain target electric bicycle on that day; j is the number of types of traffic safety hazard behaviors that occurred on the target electric bicycle on that day; x is the number of times the driver of the target electric bicycle has been educated for this type of traffic safety hazard behavior within a certain historical period of time. When x is not equal to 0, δ=1; when x is equal to 0, δ=-1.

8. The method for screening and diverting electric bicycle traffic safety hazard behaviors according to claim 1 is characterized in that: The step S4 further includes: The traffic safety hazard behavior score F of each target electric bicycle on that day is sorted from large to small to form the first column of the fourth list Tab4, the target electric bicycle license plate number corresponding to each traffic safety hazard behavior score in the first column of the fourth list Tab4 forms the second column of the fourth list Tab4, and the number of traffic safety hazard behaviors on that day corresponding to each target electric bicycle license plate number in the second column of the fourth list Tab4 forms the third column of the fourth list Tab4; The data in the third column of the fourth table Tab4 are accumulated from top to bottom to obtain the total number of traffic safety hazard behavior records that have been reviewed on that day. The accumulated value Sum2; when the calculated total number of accumulated value Sum2 is greater than the preset daily total number of penalty threshold Cap2, the accumulation calculation is stopped, and the corresponding traffic safety hazard behavior score F at this time is used as the preset score threshold F cap ; For traffic safety hazard behaviors with a score greater than the preset score threshold F cap The target electric bicycle driver is punished; the traffic safety hazard behavior score is not greater than the preset score threshold F cap The goal is to provide traffic safety education to electric bicycle drivers.

9. A screening and diversion processing system for electric bicycle traffic safety hazard behaviors, used to implement the screening and diversion processing method for electric bicycle traffic safety hazard behaviors as described in any one of claims 1 to 8, characterized in that: The screening and diversion processing system for electric bicycle traffic safety hazard behaviors includes: The acquisition module is used to obtain all the traffic safety hazard behavior records to be reviewed on that day and their corresponding electric bicycles; A screening module is used to retrieve all historical traffic safety hazard behavior records of each corresponding electric bicycle within a certain historical time period, and calculate the total number of historical traffic safety hazard behavior records of each corresponding electric bicycle within the certain historical time period, and then screen out target electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to a preset number threshold k1 from all corresponding electric bicycles; A calculation module is used to review the pending traffic safety hazard behavior records of each target electric bicycle on that day, and calculate the traffic safety hazard behavior score of each target electric bicycle on that day based on all the reviewed traffic safety hazard behavior records of each target electric bicycle on that day; The processing module is used to send SMS reminders to electric bicycle drivers whose total number of historical traffic safety hazard behavior records is not greater than the preset number threshold k1; and to send SMS reminders to electric bicycle drivers whose traffic safety hazard behavior score on the day is greater than the preset score threshold F cap The target electric bicycle driver shall be punished; the traffic safety hazard behavior score on that day is not greater than the preset score threshold F cap The goal is to provide traffic safety education to electric bicycle drivers.

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