Method and system for screening and diverting treatment of traffic safety hidden danger behaviors of electric bicycles

Abstract

This invention relates to the field of intelligent traffic management technology, specifically disclosing a method and system for screening and diverting traffic safety hazard behaviors of electric bicycles. The method includes: acquiring all pending traffic safety hazard behavior records and their corresponding electric bicycles for the current day; calculating the total number of historical traffic safety hazard behavior records for each corresponding electric bicycle within a certain historical time period; selecting target electric bicycles from all corresponding electric bicycles whose total historical record count is greater than or equal to a preset threshold; calculating the traffic safety hazard behavior score for each target electric bicycle for the current day; issuing a reminder to electric bicycle riders whose total historical record count is not greater than the preset threshold; educating target electric bicycle riders whose current day behavior score is not greater than a preset threshold; and penalizing target electric bicycle riders whose current day behavior score is greater than the preset threshold. This invention can improve the social benefits of managing traffic safety hazard behaviors.

Description

Technical Field

[0001] This invention relates to the field of intelligent traffic management technology, and more specifically, to a method and system for screening and diverting traffic safety hazards associated with electric bicycles. Background Technology

[0002] Currently, the number of electric bicycles far exceeds that of cars, leading to a series of traffic safety problems, such as running red lights, riding against traffic, occupying motor vehicle lanes, and not wearing helmets. Relevant management departments have begun exploring the use of intelligent traffic monitoring equipment to monitor and record various traffic safety hazards. These methods primarily focus on exploring the use of artificial intelligence technology to identify potential traffic safety hazards or improve the accuracy of capturing images of specific hazards.

[0003] Currently, all images of potential traffic safety hazards captured by intelligent traffic monitoring equipment require manual review before processing. However, the number of potential traffic safety hazards posed by electric bicycles is enormous, exceeding the processing capacity of existing traffic management staff by dozens of times. If all captured traffic safety hazards are pushed to staff without scientific filtering by an information system, it will place a huge burden on image review and hazard processing personnel. Furthermore, this will result in a lack of focus, low utilization of government resources, and any mishandling could lead to public criticism. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for screening and diverting potential traffic safety hazards associated with electric bicycles, thereby resolving the current problem of insufficient human resources in handling potential traffic safety hazards associated with electric bicycles by management departments.

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

[0006] Step S1: Obtain all pending traffic safety hazard records for the day and their corresponding electric bicycles;

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

[0008] Step S3: Review the pending traffic safety hazard behavior records for each target electric bicycle on the same day, and calculate the traffic safety hazard behavior score for each target electric bicycle on the same day based on all the reviewed traffic safety hazard behavior records for each target electric bicycle on the same day.

[0009] Step S4: Send SMS reminders to electric bicycle riders whose total number of historical traffic safety hazard behaviors does not exceed the preset threshold k1; send SMS reminders to riders whose traffic safety hazard behavior score for the day exceeds the preset threshold F. cap The target electric bicycle rider will be penalized; the score for the traffic safety hazard behavior on that day will not exceed the preset score threshold F. cap The goal is to educate electric bicycle riders.

[0010] Furthermore, steps S1 and S2 also include:

[0011] Create a first list (Tab1) containing all pending traffic safety hazard records for the day and their corresponding electric bicycle license plate numbers.

[0012] The first list Tab1 contains the license plate number of each electric bicycle and its corresponding record of all historical traffic safety hazards within a certain historical period, forming the second list Tab2.

[0013] The total number of times P, representing historical traffic safety hazard records for each electric bicycle license plate number in the second list Tab2, within a certain historical time period is calculated using the following formula:

[0014]

[0015] Where, p i The number of times the same electric bicycle license plate number has the i-th type of historical traffic safety hazard behavior record within a certain historical period, where 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 largest to smallest to form the first column of the third list Tab3;

[0017] Form the second column of the third list Tab3 with the total number of electric bicycle license plate numbers m corresponding to each total number P in the first column of the third list Tab3;

[0018] The third column of the third list Tab3 is formed by the total number of times each total count P in the first column of the third list Tab3 corresponds to any electric bicycle license plate number with pending traffic safety hazard records on that day. The third column is further defined by the associated retrieval of the total number of times each total count P in the first column of the third list Tab3 corresponds to any specific electric bicycle license plate number with pending traffic safety hazard records on that day. Among them, l i Let be the number of pending traffic safety hazard records for a given electric bicycle license plate number on a given day, and j be the number of different types of pending traffic safety hazard records for a given electric bicycle license plate number on a given day. Then, for each total count P in the first column of the third list (Tab3), there is the total number of pending traffic safety hazard records for all electric bicycle license plates on a given day.

[0019] The data in the third column of the third list Tab3 are accumulated from top to bottom to obtain the total number of traffic safety hazard behavior records pending review for the day, Sum1. When the calculated total number of accumulated values ​​Sum1 is greater than the preset daily review total number threshold Cap1, the accumulation calculation is stopped, and the corresponding total number P is used as the preset number threshold k1.

[0020] Select target electric bicycle license plate numbers from the third list Tab3 whose total number of occurrences P is greater than or equal to the preset number of occurrences threshold k1, and review the pending traffic safety hazard behavior records for each target electric bicycle license plate number on the same day.

[0021] Furthermore, the calculation of the traffic safety hazard score for each target electric bicycle on that day, based on all verified traffic safety hazard behavior records for that day, also includes:

[0022] Construct a traffic safety hazard behavior score model F for each target electric bicycle on the day, using the following formula:

[0023] F = f x +γf y +δf z

[0024] Where γ and δ are both coefficient values, f x This represents the sum of the traffic safety impact scores for all reviewed traffic safety hazard records for each target electric bicycle on that day; f y This indicates the adjusted score for each target electric bicycle on that day based on its historical penalty record; f z This indicates the adjusted score for each target electric bicycle on that day based on its historical educational record.

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

[0026] Based on all verified traffic safety hazard records for each target electric bicycle on that day, the multiple traffic safety hazard incidents occurring on each target electric bicycle that day are categorized into traffic safety hazard incidents with serious impact, traffic safety hazard incidents with moderate impact, and traffic safety hazard incidents with minor impact, thus forming a traffic safety hazard incident count matrix Q of different impact levels. i ;

[0027]

[0028] Where, matrix Q i qi in the first column yanj This indicates the number of traffic safety hazards of the jth severity level; qi in the second column yij This indicates the number of traffic safety hazards of the j-th type with general impact, and the qi in the third column represents the number of such hazards. qingj This indicates the number of traffic safety hazards of the jth minor impact level;

[0029] Different weight values ​​are assigned to traffic safety hazards with severe impact, moderate impact, and minor impact to form a weight value matrix. Among them, w yan The weight value w represents the severity of traffic safety hazards. yi The weight value w represents the level of impact of traffic safety hazards. qing Weight values ​​indicating the degree of minor impact of traffic safety hazards;

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

[0031] Furthermore, the adjusted score f for each target electric bicycle on that day is 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 serious traffic safety hazards occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total number of elements in the first column; S yi The number of traffic safety hazards of general impact level occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total number of elements in the second column; S qing The number of minor traffic safety hazards occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total number of elements in the third column;

[0034] If a target electric bicycle is involved in multiple serious traffic safety hazards on a given day, it will be determined whether the driver of that electric bicycle has a history of penalties for such serious traffic safety hazards within a certain historical period. If so, then... Otherwise, γ = -1; that is...

[0035]

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

[0037] If the target electric bicycle causes a serious traffic safety hazard on that day, S yan The daily average number of traffic safety hazards involving electric bicycles that have a significant impact over a certain historical period, exceeding the target number. but

[0038] If the target electric bicycle causes a serious traffic safety hazard on that day, S yan The number of traffic safety hazards involving electric bicycles that do not exceed the average daily number of incidents with a serious impact within a certain historical period. Then, using the time series of the number of serious traffic safety hazard incidents involving the target electric bicycle within a period of time following the most recent penalty record, a univariate linear function y = at + b is linearly fitted to obtain the result.

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

[0040] Furthermore, the formula for calculating 'a' is as follows:

[0041]

[0042] Among them, t i This indicates the t-th time interval following the most recent penalty record. i Heaven, the t i Week or t i Quarter; y i This indicates the number of traffic safety hazards that have a serious impact on the corresponding 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 date of review.

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

[0044]

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

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

[0047] Furthermore, step S4 also includes:

[0048] Sort the traffic safety hazard behavior scores F of each target electric bicycle in descending order to form the first column of the fourth list Tab4. Form the second column of the fourth list Tab4 with the license plate number of each target electric bicycle license plate number in the first column of the fourth list Tab4. Form the third column of the fourth list Tab4 with the number of traffic safety hazard behaviors that occurred on the same day for each target electric bicycle license plate number in the second column of the fourth list Tab4.

[0049] The data in the third column of the fourth list (Tab4) are summed sequentially from top to bottom to obtain the total number of traffic safety hazard records reviewed for the day, Sum2. When the calculated total number of sums (Sum2) exceeds the preset daily penalty threshold (Cap2), the summation calculation stops, and the corresponding traffic safety hazard score (F) is used as the preset score threshold (F). cap ;

[0050] For behaviors that pose a traffic safety hazard, the score is greater than the preset score threshold F. capThe target electric bicycle driver will be penalized; the score for traffic safety hazard behavior will not exceed the preset score threshold F. cap The goal is to provide traffic safety education to electric bicycle riders.

[0051] As a second aspect of the present invention, a screening and diversion system for potential traffic safety hazards associated with electric bicycles is provided, comprising:

[0052] The acquisition module is used to acquire all pending traffic safety hazard behavior records and their corresponding electric bicycles for the current day;

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

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

[0055] The processing module is used to send SMS reminders to electric bicycle riders whose total number of historical traffic safety hazard records does not exceed the preset threshold k1; and to send SMS reminders to riders whose traffic safety hazard score for the day exceeds the preset threshold F. cap The target electric bicycle rider will be penalized; the score for the traffic safety hazard behavior on that day will not exceed the preset score threshold F. cap The goal is to provide traffic safety education to electric bicycle riders.

[0056] The method and system for screening and diverting traffic safety hazards related to electric bicycles provided by this invention have the following advantages: By utilizing data on traffic safety hazards captured by existing intelligent monitoring equipment of traffic management departments, the historical continuous behavioral characteristics of the individuals involved in these hazards are analyzed. This analysis considers not only the severity of the impact of different traffic safety hazards to be reviewed, but also the impact of past safety education, penalties, and other disciplinary measures on the driver's future driving behavior. Furthermore, by combining the processing capacity of the penalty window, a comprehensive score is generated. Based on this comprehensive score, different disciplinary measures, such as publicity and education or penalties, are applied accordingly. This method can effectively punish those with serious traffic safety hazards who have been penalized but do not actively correct their behavior, thereby improving the efficiency of resource utilization in traffic hazard management. Attached Figure Description

[0057] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the following detailed description to explain the invention, but do not constitute a limitation thereof.

[0058] Figure 1 The flowchart illustrates the method for screening and diverting traffic safety hazards associated with electric bicycles provided by this invention. Detailed Implementation

[0059] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the method and system for screening and diverting traffic safety hazards of electric bicycles proposed according to the present invention. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0060] This embodiment provides a method for screening and diverting behaviors that pose a traffic safety hazard to electric bicycles, such as... Figure 1 As shown, the method for screening and diverting traffic safety hazards associated with electric bicycles includes:

[0061] Step S1: Obtain all pending traffic safety hazard records for the day and their corresponding electric bicycles;

[0062] It should be noted that the system allows users to select the review date for traffic safety hazard records pending review. For example, if the review date is selected as July 11, 2024, then the system will extract all pending traffic safety hazard records for that day and obtain the corresponding electric bicycle license plate numbers (IDs). The license plate number of the electric bicycle will be automatically associated with all pending traffic safety hazard records for that vehicle.

[0063] In this embodiment of the invention, as shown in Table 1, a total of 153,482 traffic safety hazard behavior records pending review 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 period, and calculate the total number of times each corresponding electric bicycle has a historical traffic safety hazard behavior record within a certain historical period. Then, select target electric bicycles from all corresponding electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to the preset number threshold k1.

[0067] Preferably, to fully utilize the limited review capabilities of personnel reviewing images of traffic safety hazards, target electric bicycles with a high number of historical hazard incidents are screened. Steps S1 and S2 further include:

[0068] Create a first list (Tab1) containing all pending traffic safety hazard records for the day and their corresponding electric bicycle license plate numbers.

[0069] The second list, Tab2, is formed by recording all historical traffic safety hazard behaviors of each electric bicycle license plate number in the first list Tab1 and its corresponding historical time period (such as 30 days or 180 days before the review date).

[0070] It should be noted that if a certain electric bicycle license plate number has no historical traffic safety hazard records within a certain historical period (i.e., 0), meaning that this is the first time that electric bicycle has had a traffic safety hazard on that day, the electric bicycle driver will be notified via SMS to remind him to correct the behavior.

[0071] The total number of times P, representing historical traffic safety hazard records for each electric bicycle license plate number in the second list Tab2, within a certain historical time period is calculated using the following formula:

[0072]

[0073] Where, p i P represents the number of times the same electric bicycle license plate number has the i-th type of historical traffic safety hazard behavior record within a certain historical period, where n is the total number of types of historical traffic safety hazard behavior records; for example, if an electric bicycle runs a red light twice and goes against traffic once within a certain historical period, then P = 3.

[0074] Sort the total number of historical traffic safety hazard records P corresponding to each electric bicycle license plate number in the second list Tab2 from largest to smallest to form the first column of the third list Tab3 (number of historical hazards in 30 days);

[0075] Form the total number of electric bicycle license plate numbers m corresponding to each total number P in the first column of the third list Tab3 into the second column of the third list Tab3 (corresponding to the number of vehicles);

[0076] In an 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 traffic safety hazard behaviors, 3 electric bicycles had 15 records of traffic safety hazard behaviors, 9 electric bicycles had 14 records of traffic safety hazard behaviors...

[0077] Form the third column (number of pending review hazards) of the third list Tab3 with the total number of records of pending review traffic safety hazard behaviors that occurred on the same day for all electric bicycle license plate numbers corresponding to each total number P in the first column of the third list Tab3;

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

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

[0080] In an embodiment of the present invention, as shown in Table 1, within the past 30 days, 1 electric bicycle had 16 records of traffic safety hazard behaviors, and this electric bicycle had a total of 13 records of pending review traffic safety hazard behaviors on the same day; within the past 30 days, 3 electric bicycles had 15 records of traffic safety hazard behaviors, and these 3 electric bicycles had a total of 32 records of pending review traffic safety hazard behaviors on the same day; within the past 30 days, 9 electric bicycles had 14 records of traffic safety hazard behaviors, and these 9 electric bicycles had a total of 81 records of pending review traffic safety hazard behaviors 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 pending review traffic safety hazard behaviors 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 the preset daily review total number threshold Cap1 is evaluated based on the daily historical review data of traffic safety hazard behavior image review staff.

[0083] In this embodiment of the invention, it is assumed that the preset daily total number of reviews threshold Cap1 = 12000, until it accumulates to the preset daily total number of reviews threshold Cap1, as shown in Table 1. 13 is the total number of reviews in the first row; 45 is the total number of reviews in the first and second rows (13 + 32); 126 is the total number of reviews in the first, second, and third rows (13 + 32 + 81); 377 is the total number of reviews in the first, second, third, and fourth rows (13 + 32 + 81 + 251)...; when 12989 ≥ 12000, the accumulation calculation stops, and at this time the preset number of reviews threshold k1 = 6. Note that 12989 is slightly larger than the review capacity and can be ignored because, in actual work, some traffic hazard behavior images will be discarded, slightly exceeding the review capacity and can be ignored.

[0084] Select target electric bicycle license plate numbers whose total number of occurrences P is greater than or equal to the preset number of occurrences 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 the same day, and then carry out traffic hazard persuasion and rectification measures.

[0085] It should be noted that, as shown in Table 1, the license plate numbers of target electric bicycles that have been flagged 6 times or more are identified to form a list of vehicles subject to hazard penalties. Note: Whether to use k1 or k1+1 depends on the actual situation, as many unacceptable images will be discarded during the image review process. Therefore, a value slightly higher than the manual review capacity can be ignored; if it is significantly higher than the manual review capacity, k1+1 can be used.

[0086] Step S3: Review the pending traffic safety hazard behavior records for each target electric bicycle on the same day, and calculate the traffic safety hazard behavior score for each target electric bicycle on the same day based on all the reviewed traffic safety hazard behavior records for each target electric bicycle on the same day.

[0087] To implement more precise measures for dealing with electric bicycle riders with records of traffic safety hazards, this invention analyzes and assesses these records. It considers not only the severity of the impact of different traffic safety hazards under review, but also the influence of past safety education and penalties on the rider's future driving behavior. Furthermore, it combines the processing capacity of penalty windows to generate a comprehensive score. Based on this score, riders are categorized and dealt with using different measures such as public education and penalties. This method can effectively punish those with serious traffic safety hazards who have been penalized but do not actively correct their behavior, thereby improving the efficiency of traffic hazard management resource utilization.

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

[0089] Construct a traffic safety hazard behavior score model F for each target electric bicycle on the day, using the following formula:

[0090] F = f x +γf y +δf z

[0091] Where γ and δ are both coefficient values, f x This represents the sum of the traffic safety impact scores for all reviewed traffic safety hazard records for each target electric bicycle on that day; f y This indicates the adjusted score for each target electric bicycle on that day based on its historical penalty record; f z This indicates the adjusted score for each target electric bicycle on that day based on its historical educational record.

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

[0093] Based on all verified traffic safety hazard records for each target electric bicycle on that day, the multiple traffic safety hazard behaviors occurring on each target electric bicycle that day are categorized into serious impact traffic safety hazard behaviors (such as running red lights, riding against traffic, etc.), moderate impact traffic safety hazard behaviors (such as not wearing a helmet, etc.), and minor impact traffic safety hazard behaviors (such as illegal parking, etc.) to form a traffic safety hazard behavior count matrix Q of different impact levels. i ;

[0094]

[0095] Where, matrix Q i qi in the first column yanj This indicates the number of traffic safety hazards of the jth severity level; qi in the second column yij This indicates the number of traffic safety hazards of the j-th type with general impact, and the qi in the third column represents the number of such hazards. qingj This indicates the number of traffic safety hazards of the jth minor impact level;

[0096] Different weight values ​​are assigned to traffic safety hazards with severe impact, moderate impact, and minor impact to form a weight value matrix. Among them, wyan The weight value w represents the severity of traffic safety hazards. yi The weight value w represents the level of impact of traffic safety hazards. qing The weight value indicates the degree of minor impact of traffic safety hazards; for example, the weight value w for serious traffic safety hazards. yan The weight value w is 4, representing the general impact of traffic safety hazard behaviors. yi The weight value w is 3, representing a minor impact on traffic safety. qing Set the weight to 1 to form a weight matrix.

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

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

[0099] Specifically, the adjusted score f for each target electric bicycle on that day is based on its historical penalty record. 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 serious traffic safety hazards occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total number of elements in the first column; S yi The number of traffic safety hazards of general impact level occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total number of elements in the second column; S qing The number of minor traffic safety hazards occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total 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 is involved in multiple serious traffic safety hazards on a given day, it will be determined whether the driver of that electric bicycle has a history of penalties for such serious traffic safety hazards within a certain historical period. If so, then... Otherwise, γ = -1; that is...

[0104]

[0105] For example, if a target electric bicycle is involved in three serious traffic safety hazards on a given day, and the driver of that electric bicycle has no prior record of penalties for serious traffic safety hazards within a certain historical period, then γ = -1; in this case, γf y =-1*[(S yan -1)*w yan +(S yi -1)*w yi +(S qing -1)*w qing = -19.

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

[0107] If the target electric bicycle causes a serious traffic safety hazard on that day, S yan The daily average number of traffic safety hazards involving electric bicycles that have a significant impact over a certain historical period, exceeding the target number. but The score F for traffic safety hazard behavior was increased, indicating that the electric bicycle driver failed to correct his traffic safety hazard behavior after being punished, and that greater attention is needed.

[0108] If the target electric bicycle causes a serious traffic safety hazard on that day, S yan The number of traffic safety hazards involving electric bicycles that do not exceed the average daily number of incidents with a serious impact within a certain historical period. Then, determine whether the trend of serious traffic safety hazards involving the target electric bicycle in the period following the most recent penalty record is gradually increasing or decreasing. Perform a univariate linear function y = at + b linear fitting on the time series of traffic safety hazard incidents during this period to obtain the result. Where t represents day t, week t, or quarter t, and y represents the number of traffic safety hazards with a serious impact on day t, week t, or quarter t. Through univariate linear regression, the behavioral patterns of traffic safety hazards committed by the target electric bicycle rider after being penalized are effectively determined over time, i.e., the binding force of the penalty on the rider's behavior is determined.

[0109] Specifically, the formula for calculating 'a' is as follows:

[0110]

[0111] Among them, t i This indicates the t-th time interval following the most recent penalty record. i Day (week, season); yi This indicates the number of traffic safety hazards that have a serious impact on the corresponding day (week, quarter); n is the total number of days (week, quarter) between the date of the most recent penalty record and the date of review.

[0112] Specifically, the fitted predicted value using the trend coefficient 'a' The value of γ is used as the parameter. If the fitted function is an increasing function, then a > 0, indicating that the electric bicycle rider's traffic safety hazards continued to increase after the previous penalty was issued. If the score F for the traffic safety hazard increases, more attention needs to be paid to it; if the trend function is a decreasing function, then a≤0, indicating that the traffic safety hazard behavior of this electric bicycle rider has shown a decreasing trend since the last penalty, and the behavior has been corrected and regulated to some extent. If the score F for traffic safety hazard behavior decreases, the level of attention can be appropriately reduced.

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

[0114]

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

[0116] Where r is the number of traffic safety hazards of a certain type that occur on a certain target electric bicycle on a given day; j is the number of types of traffic safety hazards that occur on a certain target electric bicycle on a given day; x is the number of times the driver of the target electric bicycle has been educated for this type of traffic safety hazard within a certain historical period. 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 individual 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 on 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 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 value Sum2 of the total number of times 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 on 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] Furthermore, select a certain penalty proportion of the target electric bicycle drivers 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 penalty. For example, the penalty proportion is 25%.

[0125] As another embodiment of the present invention, a screening and diversion system for potential traffic safety hazards of electric bicycles is provided, comprising:

[0126] The acquisition module is used to acquire all pending traffic safety hazard behavior records and their corresponding electric bicycles for the current day;

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

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

[0129] The processing module is used to send SMS reminders to electric bicycle riders whose total number of historical traffic safety hazard records does not exceed the preset threshold k1; and to send SMS reminders to riders whose traffic safety hazard score for the day exceeds the preset threshold F. cap The target electric bicycle rider will be penalized; the score for the traffic safety hazard behavior on that day will not exceed the preset score threshold F. cap The goal is to provide traffic safety education to electric bicycle riders.

[0130] The method for screening and diverting potential traffic safety hazards associated with electric bicycles provided by this invention can effectively leverage the capabilities of intelligent road traffic monitoring equipment. It offers a wider range of opportunities for electric bicycle riders exhibiting potential traffic safety hazards to correct their behavior, thereby improving the effectiveness of management departments in handling such hazards at a low cost. Since using this method, with the same number of staff, after a six-month trial of the system, potential traffic safety hazards on the road have decreased by 40% year-on-year.

[0131] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for screening and diverting traffic safety hazards associated with electric bicycles, characterized in that, include: Step S1: Obtain all pending traffic safety hazard records for the day and their corresponding electric bicycles; Step S2: Retrieve all historical traffic safety hazard behavior records for each corresponding electric bicycle within a certain historical time period, and calculate the total number of times each corresponding electric bicycle has historical traffic safety hazard behavior records within a certain historical time period. Then, select target electric bicycles from all corresponding electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to the preset number threshold k1. Step S3: Review the pending traffic safety hazard behavior records for each target electric bicycle on the same day, and calculate the traffic safety hazard behavior score for each target electric bicycle on the same day based on all the reviewed traffic safety hazard behavior records for each target electric bicycle on the same day. Step S4: Send SMS reminders to electric bicycle riders whose total number of historical traffic safety hazard records does not exceed the preset threshold k1; For traffic safety hazard behaviors that score higher than the preset threshold F on the day cap The target electric bicycle rider will be penalized; the score for the traffic safety hazard behavior on that day will not exceed the preset score threshold F. cap The goal is to provide traffic safety education to electric bicycle riders. The step of calculating the traffic safety hazard score for each target electric bicycle based on all verified traffic safety hazard records for that day also includes: Construct a traffic safety hazard behavior score model for each target electric bicycle on the day. The formula is as follows: ， in, and All are coefficient values. This represents the sum of the traffic safety impact scores for all reviewed traffic safety hazard records for each target electric bicycle on that day. This indicates the adjusted score for each target electric bicycle on that day based on its historical penalty record; This indicates the adjusted score for each target electric bicycle on that day based on its historical educational record.

2. The method for screening and diverting traffic safety hazard behaviors of electric bicycles according to claim 1, characterized in that, Steps S1 and S2 also include: Create a first list (Tab1) containing all pending traffic safety hazard records for the day and their corresponding electric bicycle license plate numbers. The first list Tab1 contains the license plate number of each electric bicycle and its corresponding record of all historical traffic safety hazards within a certain historical period, forming the second list Tab2. The total number of times P, representing historical traffic safety hazard records for each electric bicycle license plate number in the second list Tab2, within a certain historical time period is calculated using the following formula: ， in, The number of times the same electric bicycle license plate number has the i-th type of historical traffic safety hazard behavior record within a certain historical period, where 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 largest to smallest to form the first column of the third list Tab3; Form the second column of the third list Tab3 with the total number of electric bicycle license plate numbers m corresponding to each total number P in the first column of the third list Tab3; The third column of the third list Tab3 is formed by the total number of times each total count P in the first column of the third list Tab3 corresponds to any electric bicycle license plate number with pending traffic safety hazard records on that day. The third column is further defined by the associated retrieval of the total number of times each total count P in the first column of the third list Tab3 corresponds to any specific electric bicycle license plate number with pending traffic safety hazard records on that day. ;in, Let be the number of pending traffic safety hazard records for a given electric bicycle license plate number on a given day, and j be the number of different types of pending traffic safety hazard records for a given electric bicycle license plate number on a given day. Then, for each total count P in the first column of the third list (Tab3), there is the total number of pending traffic safety hazard records for all electric bicycle license plates on a given day. ; The data in the third column of the third list (Tab3) are summed sequentially from top to bottom to obtain the total sum of traffic safety hazard behavior records pending review for the day, Sum1. If the calculated total sum of Sum1 exceeds the preset daily review threshold... When the time is reached, the cumulative calculation stops, and the total number of times P at this time is taken as the preset number threshold k1; Select target electric bicycle license plate numbers from the third list Tab3 whose total number of occurrences P is greater than or equal to the preset number of occurrences threshold k1, and review the pending traffic safety hazard behavior records for each target electric bicycle license plate number on the same day.

3. The method for screening and diverting traffic safety hazard behaviors of electric bicycles according to claim 1, characterized in that, The sum of the traffic safety impact scores of all reviewed traffic safety hazard records for each target electric bicycle on that day. The calculation formula is as follows: Based on all verified traffic safety hazard records for each target electric bicycle on that day, the multiple traffic safety hazard incidents occurring on each target electric bicycle that day are categorized into traffic safety hazard incidents with serious impact, traffic safety hazard incidents with moderate impact, and traffic safety hazard incidents with minor impact, thus forming a traffic safety hazard incident count matrix Q of different impact levels. i ; Q i = ， Where, matrix Q i The first column The second column represents the number of traffic safety hazards of the jth severity level; The third column represents the number of traffic safety hazards of the j-th type with general impact. This indicates the number of traffic safety hazards of the jth minor impact level; Different weight values ​​are assigned to traffic safety hazards with severe impact, moderate impact, and minor impact to form a weight value matrix. ,in, The weight values ​​indicate the severity of traffic safety hazards. The weight values ​​represent the general impact level of traffic safety hazard behaviors. Weight values ​​indicating the degree of minor impact of traffic safety hazards; The sum of the impact scores of all reviewed traffic safety hazard records for each target electric bicycle on that day. for The sum of all elements in the matrix.

4. The method for screening and diverting traffic safety hazard behaviors of electric bicycles according to claim 3, characterized in that, The adjusted score for each target electric bicycle on that day is based on its historical penalty record. The calculation formula is as follows: + + ， in, The number of serious traffic safety hazards occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total number of elements in the first column; The number of traffic safety hazards of general impact level occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total number of elements in the second column; The number of minor traffic safety hazards occurring on each target electric bicycle on a given day, i.e., matrix Q. i The total number of elements in the third column; If a target electric bicycle is involved in multiple serious traffic safety hazards on a given day, it will be determined whether the driver of that electric bicycle has a history of penalties for such serious traffic safety hazards within a certain historical period. If so, then... ;otherwise, ;Right now ， Calculate the average daily number of serious traffic safety hazards involving the target electric bicycle within a certain historical period. ; If the target electric bicycle is involved in a number of traffic safety hazards with a serious impact on the day The daily average number of traffic safety hazards involving electric bicycles that have a significant impact over a certain historical period, exceeding the target number. ,but ; If the target electric bicycle is involved in a number of traffic safety hazards with a serious impact on the day The number of traffic safety hazards involving electric bicycles that do not exceed the average daily number of incidents with a serious impact within a certain historical period. Then, using the time series of the number of serious traffic safety hazard incidents involving the target electric bicycle within a period of time following the most recent penalty record, a univariate linear function y=at+b is linearly fitted to obtain the result. , Where t represents the tth day, the tth week, or the tth quarter, and y represents the number of traffic safety hazards with a serious impact that occurred on the tth day, the tth week, or the tth quarter.

5. The method for screening and diverting traffic safety hazard behaviors of electric bicycles according to claim 4, characterized in that, The calculation formula is as follows: ， in, This indicates the period following the most recent penalty record. Heaven, the First Zhou or the Quarter; This indicates the number of traffic safety hazards that occurred on the corresponding day, week, or quarter, and had a significant impact. This refers to the total number of days, weeks, or quarters between the date of the most recent penalty record and the date of review.

6. The method for screening and diverting traffic safety hazard behaviors of electric bicycles according to claim 4, characterized in that, The adjusted score for each target electric bicycle on that day is based on its historical educational record. The calculation formula is as follows: ， ， in, Let j be the number of traffic safety hazards of a certain type committed by a specific electric bicycle on a given day; j be the number of different types of traffic safety hazards committed by the specific electric bicycle on a given day; and x be the number of times the driver of the specific electric bicycle has been educated for this type of traffic safety hazard within a certain historical period. When x is not equal to 0, When x equals 0, .

7. The method for screening and diverting traffic safety hazard behaviors of electric bicycles according to claim 1, characterized in that, Step S4 further includes: The traffic safety hazard score for each target electric bicycle on that day. Sort the data from largest to smallest to form the first column of the fourth list (Tab4). Then, form the second column of the fourth list (Tab4) with the target electric bicycle license plate number corresponding to each traffic safety hazard behavior score in the first column of the fourth list (Tab4). Finally, form the third column of the fourth list (Tab4) with the number of traffic safety hazard behaviors that occurred on the same day corresponding to each target electric bicycle license plate number in the second column of the fourth list (Tab4). The data in the third column of the fourth list (Tab4) are summed sequentially from top to bottom to obtain the total number of traffic safety hazard records reviewed for the day, Sum2. If the calculated total number of sums (Sum2) exceeds the preset daily penalty threshold... When the time comes, stop the cumulative calculation and assign the corresponding traffic safety hazard score. As the preset score threshold F cap ; For behaviors that pose a traffic safety hazard, the score is greater than the preset score threshold F. cap The target electric bicycle driver will be penalized; the score for traffic safety hazard behavior will not exceed the preset score threshold F. cap The goal is to provide traffic safety education to electric bicycle riders.

8. A system for screening and diverting traffic safety hazard behaviors of electric bicycles, used to implement the method for screening and diverting traffic safety hazard behaviors of electric bicycles as described in any one of claims 1 to 7, characterized in that, The electric bicycle traffic safety hazard screening and triage system includes: The acquisition module is used to acquire all pending traffic safety hazard behavior records and their corresponding electric bicycles for the current day; The filtering module is used to retrieve all historical traffic safety hazard behavior records of each corresponding electric bicycle within a certain historical time period, calculate the total number of historical traffic safety hazard behavior records of each corresponding electric bicycle within a certain historical time period, and then filter out target electric bicycles from all corresponding electric bicycles whose total number of historical traffic safety hazard behavior records is greater than or equal to the preset number threshold k1. The calculation module is used to review the pending traffic safety hazard behavior records of each target electric bicycle on the same day, and calculate the traffic safety hazard behavior score of each target electric bicycle on the same day based on all the reviewed traffic safety hazard behavior records of each target electric bicycle on the same day. The processing module is used to send SMS reminders to electric bicycle riders whose total number of historical traffic safety hazard records does not exceed the preset threshold k1; and to send SMS reminders to riders whose traffic safety hazard score for the day exceeds the preset threshold F. cap The target electric bicycle rider will be penalized; the score for the traffic safety hazard behavior on that day will not exceed the preset score threshold F. cap The goal is to provide traffic safety education to electric bicycle riders.

Images