Illegal accident-based intervention effectiveness analysis method, device and equipment

Abstract

The present application relates to a kind of intervention effect analysis method, device and equipment based on illegal accident, and it is related to the field of intelligent transportation.The intervention effect analysis method based on illegal accident provided by the present application not only pays attention to the change rate of illegal accident data, but also emphasizes the role of two key factors, intervention cost and intervention efficiency.In particular, this method calculates the cost-benefit ratio of each intervention measure by dynamically monitoring the illegal and accident data of a certain section of a road within a certain period of time, combined with the changes before and after the implementation of specific intervention measures, thereby achieving a more comprehensive and in-depth evaluation of the effectiveness of intervention measures.In this case, it can be revealed which types of intervention measures are most likely to bring significant safety improvements, and it can also help identify strategies that may consume excessive resources but have little effect, providing strong data support for policymakers.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent transportation, and in particular to an intervention effectiveness analysis method, device and equipment based on illegal accidents. BACKGROUND

[0002] In traffic management, the frequent occurrence of accidents and illegal behaviors has always been a problem to be solved. In order to effectively curb this trend, relevant departments usually take various traffic intervention measures to improve the public's safety awareness and legal awareness, reduce the number of illegal behaviors, and thus reduce the incidence of traffic accidents. These measures include but are not limited to strengthening traffic safety education, increasing law enforcement efforts, improving road infrastructure, and promoting the use of advanced vehicle safety technology.

[0003] However, traditional analysis methods often rely on simple data statistics and comparisons, such as changes in the number of accidents, the number of injured persons, or economic losses. Although this method can provide some reference information, it lacks specific consideration of the cost-effectiveness of intervention measures. More importantly, traditional methods fail to delve into the mechanisms behind intervention measures and their long-term impacts, making it difficult to accurately assess their actual effectiveness.

[0004] In addition, due to differences in social and economic backgrounds in different regions and different periods, the actual effectiveness of the same intervention measures will also vary in different places. This means that even if a measure has achieved good results in a certain place in the past, it cannot guarantee that it will be equally effective in other environments in the future. Therefore, simply relying on historical data for simple comparison is not enough to support decision-makers to make scientific and reasonable judgments. In this case, there is an urgent need for a more systematic and refined way to evaluate the effectiveness of traffic intervention measures. SUMMARY

[0005] The purpose of the present application is to provide an intervention effectiveness analysis method, device and equipment based on illegal accidents to solve the problems existing in the prior art.

[0006] To achieve the above purpose, the technical solution adopted by the present application is:

[0007] In a first aspect, the present application provides an intervention effectiveness analysis method based on illegal accidents, which comprises:

[0008] obtaining historical traffic intervention measure implementation information, wherein the historical traffic intervention measure implementation information at least includes intervention time, intervention method, intervention road section, and intervention vehicle;

[0009] obtain historical accident and illegal data, the historical accident and illegal data at least including road segment vehicle driving trajectory, road segment illegal data, road segment accident data, intervention vehicle driving trajectory, intervention vehicle illegal data, and intervention vehicle accident data;

[0010] determine total personnel consumption and total equipment consumption of the intervention mode, and determine intervention cost based on the total personnel consumption and the total equipment consumption of the intervention mode;

[0011] determine intervention efficiency according to the intervention road segment, the intervention time, the intervention vehicle, the road segment vehicle driving trajectory, and the intervention vehicle driving trajectory;

[0012] fit time trends of the road segment illegal data and the road segment accident data before intervention by using a time series analysis model to determine a prediction result set;

[0013] calculate deviation between the prediction result set and actual results after intervention to determine an overall deviation value;

[0014] take an area or group that does not receive warning education as a control group, take an area or group that receives warning education as an experimental group, and combine the road segment vehicle driving trajectory, the road segment illegal data, the road segment accident data, the intervention vehicle driving trajectory, the intervention vehicle illegal data, and the intervention vehicle accident data to determine illegal accident comparison change rates of the control group and the experimental group before and after warning education;

[0015] determine intervention effectiveness value according to the intervention cost, the intervention efficiency, the overall deviation value, and the illegal accident comparison change rate.

[0016] In a possible implementation, the determination of the total personnel consumption of the intervention mode includes:

[0017]

[0018] wherein Z is the total personnel consumption, z is single personnel consumption, s is personnel work efficiency, x is the xth personnel, and n is the total number of personnel.

[0019] In a possible implementation, the determination of the total equipment consumption of the intervention mode includes:

[0020]

[0021] wherein V is the total equipment consumption, v is single equipment consumption, s is equipment work efficiency, x is the xth equipment, and n is the total number of equipment.

[0022] In a possible implementation, the intervention cost is determined based on the total personnel consumption and the total equipment consumption of the intervention mode, and the intervention cost determination comprises:

[0023] C=(Z+V)D;

[0024] wherein C is the intervention cost, Z is the total personnel consumption, V is the total equipment consumption, and D is the number of days.

[0025] In a possible implementation, the intervention efficiency is determined according to the intervention section, the intervention time, the intervention vehicle, the section vehicle driving track, and the intervention vehicle driving track, and the intervention efficiency determination comprises:

[0026]

[0027] wherein E is the intervention efficiency, T is the intervention time, S 干预 is the intervention vehicle track, and S 轨迹 is the section vehicle driving track.

[0028] In a possible implementation, the overall deviation value is determined by performing deviation calculation on the prediction result set and the actual result after intervention, and the deviation calculation comprises:

[0029]

[0030] wherein Q is the overall deviation value, a is the actual result after intervention, l is the prediction result set, n is the number of time units, and x is the xth time unit.

[0031] In a possible implementation, the intervention effectiveness value is determined according to the intervention cost, the intervention efficiency, the overall deviation value, and the comparison change rate, and the intervention effectiveness value determination comprises:

[0032]

[0033] wherein R is the intervention effectiveness value, P x is the illegal accident comparison change rate, Q is the overall deviation value, E is the intervention efficiency, and C is the intervention cost.

[0034] In a possible implementation, the illegal accident comparison change rate is the difference between the experimental group change rate and the control group change rate.

[0035] In a second aspect, the present application provides an intervention effectiveness analysis device based on illegal accidents, which is applied to the intervention effectiveness analysis method based on illegal accidents as described above, and the device comprises:

[0036] an acquisition module configured to acquire historical traffic intervention implementation information, the historical traffic intervention implementation information including at least intervention time, intervention mode, intervention road section, and intervention vehicle;

[0037] The acquisition module is further configured to acquire historical accident and illegal data, the historical accident and illegal data including at least road section vehicle trajectory, road section illegal data, road section accident data, intervention vehicle trajectory, intervention vehicle illegal data, and intervention vehicle accident data.

[0038] A determination module configured to determine personnel total consumption and equipment total consumption of the intervention mode, and determine intervention cost based on the personnel total consumption and the equipment total consumption of the intervention mode.

[0039] The determination module is further configured to determine intervention efficiency according to the intervention road section, the intervention time, the intervention vehicle, the road section vehicle trajectory, and the intervention vehicle trajectory.

[0040] The determination module is further configured to determine a prediction result set by fitting time trends of the road section illegal data and the road section accident data before intervention using a time series analysis model.

[0041] The determination module is further configured to determine an overall deviation value by performing deviation calculation on the prediction result set and actual results after intervention.

[0042] The determination module is further configured to take an area or group that has not received warning education as a control group, take an area or group that has received warning education as an experimental group, and determine illegal accident ratio change rates of the control group and the experimental group before and after warning education in combination with the road section vehicle trajectory, the road section illegal data, the road section accident data, the intervention vehicle trajectory, the intervention vehicle illegal data, and the intervention vehicle accident data.

[0043] The determination module is further configured to determine intervention effectiveness value according to the intervention cost, the intervention efficiency, the overall deviation value, and the illegal accident ratio change rates.

[0044] In a third aspect, the present application provides a computer device, which comprises a processor and a memory, the memory storing at least one instruction, at least one program, a code set or an instruction set, and the processor being capable of loading and executing the at least one instruction, the at least one program, the code set or the instruction set to realize the intervention effectiveness analysis method based on illegal accidents as provided above.

[0045] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores at least one instruction, at least one program, a code set or an instruction set, and a processor can load and execute the at least one instruction, the at least one program, the code set or the instruction set to implement the intervention effectiveness analysis method based on illegal accidents as provided above.

[0046] In a fifth aspect, the present application provides a computer program product or a computer program, which comprises computer program instructions stored in a computer readable storage medium. A processor reads the computer instructions from the computer readable storage medium and executes the computer instructions, so that the computer device executes the intervention effectiveness analysis method based on illegal accidents as provided above.

[0047] The technical scheme provided by the present application has at least the following beneficial effects:

[0048] The intervention effectiveness analysis method based on illegal accidents provided by the present application not only focuses on the change rate of illegal accident data, but also emphasizes the role of two key factors, intervention cost and intervention efficiency. Specifically, this method calculates the cost-benefit ratio of each intervention measure by dynamically monitoring the illegal and accident data of a road section within a period of time, and combining the situation changes before and after the implementation of specific intervention measures, so as to realize more comprehensive and in-depth effect evaluation of intervention measures. In this case, it can be revealed which types of intervention measures are most likely to bring significant safety improvement, and it can also help to identify those strategies that may consume too many resources but have little effect, providing strong data support for policy makers. By introducing scientific data analysis means, the present application aims to make up for the shortcomings in the existing evaluation system, and provide new ideas and technical tools for traffic management departments to optimize resource allocation and improve work efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0049] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, illustrate the present application together with the embodiments, and explain the present application, but do not constitute a limitation on the present application.

[0050] Figure 1 A flow chart of an intervention effectiveness analysis method based on illegal accidents provided by an exemplary embodiment of the present application is shown.

[0051] Figure 2 A structural block diagram of an intervention effectiveness analysis device based on illegal accidents provided by an exemplary embodiment of the present application is shown.

[0052] Figure 3 A structural schematic diagram of a computer device for executing an intervention effectiveness analysis method based on illegal accidents provided by an exemplary embodiment of the present application is shown. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0054] The present application will be further described below with reference to the drawings and embodiments.

[0055] Figure 1 A flowchart of a method for analyzing intervention effectiveness based on illegal accidents is shown, which includes the following steps:

[0056] In step 101, historical traffic intervention measure implementation information is obtained, and the historical traffic intervention measure implementation information at least includes intervention time, intervention method, intervention road section, and intervention vehicle.

[0057] In the embodiments of the present application, this step aims to collect relevant data of past traffic intervention activities. These information at least should include the specific time of intervention, the method taken, the road section affected, and the type of vehicle involved. Through the arrangement of these basic information, a solid foundation can be provided for subsequent analysis. For example, it is understood whether additional law enforcement actions were taken on a certain road section within a certain time period, and which types of vehicles were affected. This step is crucial for understanding the actual implementation of intervention measures, and it helps to ensure the accuracy and reliability of subsequent evaluation.

[0058] In the embodiments of the present application, the intervention time refers to the start and end time of the intervention action; the intervention method refers to the specific method of the intervention action; the intervention road section refers to the location road section of the intervention action; and the intervention vehicle refers to the passing vehicle affected by the intervention action.

[0059] In the embodiments of the present application, the historical traffic intervention measure implementation information is obtained through a traffic management platform.

[0060] In step 102, historical accident and illegal data is obtained, and the historical accident and illegal data at least includes road section vehicle driving track, road section illegal data, road section accident data, intervention vehicle driving track, intervention vehicle illegal data, and intervention vehicle accident data.

[0061] In the embodiments of the present application, detailed traffic accident and illegal behavior records need to be collected from multiple perspectives, covering vehicle driving trajectories on ordinary road sections, specific illegal behavior details, accident cases that occur, and also the behavior patterns of vehicles directly involved in the intervention process and related data. This means that not only the general situation on the road needs to be considered, but also the objects directly affected by the intervention measures need to be paid special attention. The data set obtained in this way will be more comprehensive and can better reflect the real changes before and after the intervention, laying a good foundation for further analysis.

[0062] In the embodiments of the present application, the vehicle driving trajectory on the road section refers to the trajectory data of all vehicles in the intervention action road section; the illegal data on the road section refers to the traffic illegal data occurring on the road section where the intervention action is located; the accident data on the road section refers to the traffic accident data occurring on the road section where the intervention action is located; the driving trajectory of the intervention vehicle refers to the trajectory data of the vehicle affected by the intervention action; the illegal data of the intervention vehicle refers to the traffic illegal data of the vehicle affected by the intervention action; and the accident data of the intervention vehicle refers to the traffic accident data of the vehicle affected by the intervention action.

[0063] In the embodiments of the present application, the historical accident and illegal data are obtained through a traffic management platform.

[0064] In step 103, the total personnel consumption and total equipment consumption of the intervention mode are determined, and the intervention cost is determined based on the total personnel consumption and total equipment consumption of the intervention mode.

[0065] In the embodiments of the present application, in order to quantify the cost of each intervention, it is necessary to first determine the total amount of human resource consumption (such as the working time of police or staff) and the total amount of material resource consumption (for example, what kind of equipment and technical support is used) involved in each intervention. Based on the input of these two aspects, the total intervention cost can be calculated. This process not only involves direct visible cost factors such as personnel salary and equipment procurement cost, but also may include indirect costs such as economic losses caused by the decline of road traffic efficiency due to intervention. Accurate measurement of these costs is an important prerequisite for evaluating the economic benefits of intervention measures.

[0066] Specifically, the total personnel consumption of the intervention mode includes:

[0067]

[0068] Wherein, Z is the total personnel consumption, specifically refers to the total number of personnel participating in the intervention action, the unit is (person); z is the single personnel consumption, specifically refers to the number of single personnel participating in the intervention action, the unit is (person); s is the personnel working efficiency, specifically refers to the participation rate of single personnel participating in the intervention action; x is the xth personnel; n is the total number of personnel, specifically refers to the total number of personnel participating in the intervention action.

[0069] In one example, the total personnel consumption Z is shown in Table 1 as follows:

[0070] Personnel Consumption Principal personnel 1 Secondary personnel 0.5-1 Auxiliary personnel 0.1-0.5

[0071] In one example, the personnel work efficiency s is shown in Table 2 as follows:

[0072] Explanation Work rate Full participation 1 Partial participation 0.1-0.9 Maintenance support 0.1-0.5 Subsequent processing 0.1-0.2

[0073] The total device consumption of the intervention method is determined, including:

[0074]

[0075] Wherein, V is the total device consumption, specifically refers to: the total number of devices participating in the intervention action, units are (pieces); v is the single device consumption, specifically refers to: the number of single devices participating in the intervention action, units are (pieces); s is the device work efficiency, specifically refers to: the participation rate of single device participating in the intervention action; x is the xth device; n is the total number of devices.

[0076] In one example, the device work efficiency s is shown in Table 3 as follows:

[0077] Explanation Work rate Full task exclusive 1 Threaded processing 0.1-0.9

[0078] Based on the total personnel consumption and the total device consumption of the intervention method, the intervention cost is determined, including:

[0079] C = (Z + V)D;

[0080] Wherein, C is the intervention cost, specifically refers to: the total number of personnel and devices of the intervention action, units are (pieces per day); Z is the total personnel consumption; V is the total device consumption; D is the number of days, specifically refers to: the number of days of the intervention action, units are (days).

[0081] Step 104, determining the intervention efficiency according to the intervention section, the intervention time, the intervention vehicle, the vehicle driving track of the section, and the driving track of the intervention vehicle.

[0082] In the embodiments of the present application, this step requires evaluating the effectiveness of the intervention according to the time, place, and vehicle involved in the intervention, as well as the corresponding driving path. Specifically, it is to analyze the flow of vehicles on the specified section before and after the intervention, including changes in average speed, flow density, etc., to determine whether the intervention has achieved the expected purpose, i.e., to improve traffic safety or reduce the incidence of illegal behavior. In addition, it can further explore the differences in the impact of different types of intervention methods on the same area, so as to draw more detailed conclusions.

[0083] In detail, the intervention effect analysis method based on illegal accidents is characterized in that the intervention efficiency is determined according to the intervention section, the intervention time, the intervention vehicle, the vehicle trajectory of the section, and the trajectory of the intervention vehicle, and the intervention efficiency comprises:

[0084]

[0085] Wherein, E is the intervention efficiency, specifically refers to the proportion of the vehicle trajectory affected by the intervention action in the total trajectory of the section; T is the intervention time, the unit is (h); S 干预 is the trajectory of the intervention vehicle; S 轨迹 is the vehicle trajectory of the section.

[0086] Step 105, fitting the time trend of the illegal data and the section accident data before intervention by using a time series analysis model to determine a prediction result set.

[0087] In the embodiment of the present application, the method of time series analysis is used to predict the development trend of the number of illegal events and traffic accidents in the future period of time on the section if no intervention is made. This method can help us establish a "hypothetical" baseline to compare with the actual situation. By fitting the past data points and predicting the future trend, we can get a set of prediction result set, which will become one of the key references for measuring the intervention effect.

[0088] In an example, the time series analysis model is an ARIMA model. ARIMA model, full name Autoregressive Integrated Moving Average Model, is an important tool in time series analysis, widely used in prediction and modeling. It combines three core components: autoregression (AR), difference (I) and moving average (MA). The basic idea of ARIMA model is that the value at a time point is affected by the values in the past period of time and the random events or error terms in the past period of time.

[0089] Step 106, calculating the deviation between the prediction result set and the actual result after intervention to determine the overall deviation value.

[0090] In the embodiment of the present application, once the prediction result set is obtained, it can be compared with the real situation after intervention to calculate the gap between them, that is, the so-called "overall deviation value". This value reflects the degree of influence of the intervention measures on the original trend - if the deviation is large, it means that the intervention has played a significant role; otherwise, it means that the effect of intervention is not obvious or almost no effect. Such comparison can directly show the changes brought by intervention and provide basis for further optimization strategy.

[0091] Further, the deviation between the prediction result set and the actual result after intervention is calculated to determine the overall deviation value, including:

[0092]

[0093] Wherein Q is the overall deviation value, specifically refers to: the change ratio of the actual number of illegal accidents and the prediction value; a is the actual result after intervention, specifically refers to: the actual number of illegal accidents, the unit is (piece); l is the value of the prediction result set after time alignment, specifically refers to: the predicted number of illegal accidents, the unit is (piece); n is the number of time dimension units; x is the xth time unit.

[0094] Step 107, taking the region or group that has not received warning education as the control group, and taking the region or group that has received warning education as the experimental group, combining the vehicle driving trajectory of the road section, the illegal data of the road section, the accident data of the road section, the intervention vehicle driving trajectory, the illegal data of the intervention vehicle, and the accident data of the intervention vehicle, to determine the illegal accident rate of change of the control group and the experimental group before and after the warning education.

[0095] In the embodiments of the present application, in order to more accurately evaluate the effect of warning education intervention measures, it is recommended here to set up two different groups as research objects: one is the control group that has not received such education, and the other is the experimental group that has received warning education. Then, by comparing the change of illegal and accident frequency between the two groups under the same conditions (i.e. the same road section, similar time period, etc.), it can be more clearly seen whether the education activities really played a preventive role. This design is similar to the random controlled trial (RCT) in medical trials, which can effectively exclude other variable interference and improve the reliability of the conclusion.

[0096] To be specific, this step takes the region or group that has not received warning education as the control group, and takes the region or group that has received warning education as the experimental group, calculates the accident and illegal probability P according to the group, before and after intervention, with or without accidents, and with or without illegal, and the probability conditions are shown in the following Table Four:

[0097] Value X Y Z W 1 Experimental group Before intervention Accidents Violations 0 Control group After intervention No accidents No violations

[0098] (1) Calculate the illegal accident rate of the experimental group and the control group, as shown in the following Table Five:

[0099] Probability Experimental group Control group Pre-intervention violation rate P(W = 1 | Y = 1, X = 1) P(W = 1 | Y = 1, X = 0) Post-intervention violation rate P(W = 1 | Y = 0, X = 1) P(W = 1 | Y = 0, X = 0) Pre-intervention accident rate P(Z = 1 | Y = 1, X = 1) P(Z = 1 | Y = 1, X = 0) Post-intervention accident rate P(Z = 1 | Y = 0, X = 1) P(Z = 1 | Y = 0, X = 0)

[0100] (2) Calculate the overall change rate of the experimental group and the control group:

[0101] The illegal and accident influence degree is respectively m and n, m and n are estimated according to the traffic illegal and accident data of the last year.

[0102] The change rate of the experimental group:

[0103]

[0104] In the formula, X1 is the change rate of the experimental group, specifically refers to: the change proportion of accidents and illegal behaviors of the experimental group before and after the intervention action; P is the conditional probability, specifically refers to: the accident rate or illegal rate meeting a specific condition; m is the illegal influence rate, specifically refers to: the traffic illegal behavior influence factor; n is the accident influence rate, specifically refers to: the traffic accident influence factor.

[0105] The change rate of the control group:

[0106]

[0107] In the formula, X2 is the change rate of the control group, specifically refers to: the change proportion of accidents and illegal behaviors of the control group before and after the intervention action; P is the conditional probability, specifically refers to: the accident rate or illegal rate meeting a specific condition; m is the illegal influence rate, specifically refers to: the traffic illegal behavior influence factor; n is the accident influence rate, specifically refers to: the traffic accident influence factor.

[0108] (3) Calculate the final illegal accident ratio change rate:

[0109] P x =X1-X2;

[0110] Step 108, according to the intervention cost, intervention efficiency, overall deviation value, and illegal accident ratio change rate, determine the intervention effect value.

[0111] In the embodiments of the present application, the intervention cost, intervention efficiency, overall deviation value and illegal accident ratio change rate and other factors are comprehensively considered to calculate a comprehensive intervention effect value. This value not only summarizes whether a single intervention measure is successful or not, but also provides valuable lessons for future similar project planning. In this way, it not only helps decision makers make more intelligent choices, but also promotes the development of scientific management methods in the field of traffic safety.

[0112] Specifically, according to the intervention cost, intervention efficiency, overall deviation value, and ratio change rate, the intervention effect value is determined, including:

[0113]

[0114] Wherein, R is the intervention effect value, P x is the illegal accident ratio change rate, Q is the overall deviation value, E is the intervention efficiency, and C is the intervention cost.

[0115] Figure 2 A structural block diagram of an intervention effectiveness analysis device based on illegal accidents is shown, which is provided by an example embodiment of the present application. The intervention effectiveness analysis device based on illegal accidents is applied to the intervention effectiveness analysis method based on illegal accidents. The device comprises:

[0116] The acquisition module 201 is configured to acquire historical traffic intervention measure implementation information, and the historical traffic intervention measure implementation information at least includes intervention time, intervention mode, intervention road section, and intervention vehicle;

[0117] The acquisition module 201 is further configured to acquire historical accident and illegal data, and the historical accident and illegal data at least includes road section vehicle driving track, road section illegal data, road section accident data, intervention vehicle driving track, intervention vehicle illegal data, and intervention vehicle accident data;

[0118] The determination module 202 is configured to determine personnel total consumption and equipment total consumption of the intervention mode, and determine intervention cost based on the personnel total consumption and the equipment total consumption of the intervention mode;

[0119] The determination module 202 is further configured to determine intervention efficiency according to the intervention road section, the intervention time, the intervention vehicle, the road section vehicle driving track, and the intervention vehicle driving track;

[0120] The determination module 202 is further configured to determine a prediction result set by fitting time trends of the road section illegal data and the road section accident data before the intervention by using a time series analysis model;

[0121] The determination module 202 is further configured to perform deviation calculation on the prediction result set and actual results after the intervention to determine an overall deviation value;

[0122] The determination module 202 is further configured to take an area or group that does not receive warning education as a control group, take an area or group that receives warning education as an experimental group, and determine illegal accident comparison change rates of the control group and the experimental group before and after the warning education in combination with the road section vehicle driving track, the road section illegal data, the road section accident data, the intervention vehicle driving track, the intervention vehicle illegal data, and the intervention vehicle accident data;

[0123] The determination module 202 is further configured to determine intervention effectiveness value according to the intervention cost, the intervention efficiency, the overall deviation value, and the illegal accident comparison change rate.

[0124] In some embodiments, the determination of the personnel total consumption of the intervention mode comprises:

[0125]

[0126] Wherein, Z is total personnel consumption, z is single personnel consumption, s is personnel work efficiency, x is the xth personnel, and n is total number of personnel.

[0127] In some embodiments, the determining the total device consumption of the intervention mode comprises:

[0128]

[0129] Wherein, V is total device consumption, v is single device consumption, s is device work efficiency, x is the xth device, and n is total number of devices.

[0130] In some embodiments, the determining the intervention cost based on the total personnel consumption and the total device consumption of the intervention mode comprises:

[0131] C = (Z + V)D;

[0132] Wherein, C is intervention cost, Z is total personnel consumption, V is total device consumption, and D is days.

[0133] In some embodiments, the determining the intervention efficiency according to the intervention route, the intervention time, the intervention vehicle, the route vehicle driving track, and the intervention vehicle driving track comprises:

[0134]

[0135] Wherein, E is intervention efficiency, T is intervention time, S 干预 is intervention vehicle track, S 轨迹 is route vehicle driving track.

[0136] In some embodiments, the determining the overall deviation value by calculating deviation between the prediction result set and actual result after intervention comprises:

[0137]

[0138] Wherein, Q is overall deviation value, a is actual result after intervention, l is prediction result set, n is number of time dimension units, and x is the xth time unit.

[0139] In some embodiments, the determining the intervention effectiveness value according to the intervention cost, the intervention efficiency, the overall deviation value, and the comparison change rate comprises:

[0140]

[0141] Wherein, R is intervention effectiveness value, P x is illegal accident comparison change rate, Q is overall deviation value, E is intervention efficiency, and C is intervention cost.

[0142] In some embodiments, the illegal accident comparison change rate is a difference between the experimental group change rate and the control group change rate.

[0143] It should be noted that the illegal accident-based intervention effectiveness analysis device provided in the above embodiments is only exemplified by the division of the above functional modules, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above-described functions.

[0144] Figure 3 A structural schematic diagram of a computer device for executing an illegal accident-based intervention effectiveness analysis method is shown, and the computer device comprises:

[0145] The processor 301 comprises one or more processing cores, and the processor 301 executes various functional applications and data processing by running software programs and modules.

[0146] The receiver 302 and the transmitter 303 can be implemented as a communication component, which can be a communication chip. Alternatively, the communication component can implement a signal transmission function. That is, the transmitter 303 can be used to transmit control signals to an image acquisition device and a scanning device, and the receiver 302 can be used to receive corresponding feedback instructions.

[0147] The memory 304 is connected to the processor 301 through the bus 305.

[0148] The memory 304 can be used to store at least one instruction, and the processor 301 is used to execute the at least one instruction to realize each step in the above method embodiments.

[0149] The embodiment of the present application also provides a computer readable storage medium, and the readable storage medium stores at least one instruction, at least one program, a code set or an instruction set to be loaded and executed by a processor to realize the above illegal accident-based intervention effectiveness analysis method.

[0150] The present application also provides a computer program product or a computer program, which comprises computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to make the computer device execute the illegal accident-based intervention effectiveness analysis method described in any of the above embodiments.

[0151] Optionally, the computer readable storage medium can include a Read Only Memory (ROM), a Random Access Memory (RAM), a Solid State Disk (SSD), an optical disk, etc. The Random Access Memory can include a Resistance Random Access Memory (ReRAM) and a Dynamic Random Access Memory (DRAM). The above-mentioned sequence numbers of the embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0152] It can be understood that the specific examples herein are only to help those skilled in the art better understand the present disclosure, and not to limit the scope of the present application.

[0153] It can be understood that in various embodiments in the present specification, the size of the sequence number of each process does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the present disclosure.

[0154] It can be understood that the various embodiments described in the present specification can be implemented alone or in combination, and the present disclosure does not limit this.

[0155] Unless otherwise specified, all technical and scientific terms used in the present disclosure have the same meaning as understood by those skilled in the art of the present specification. The terms used in the present specification are only for the purpose of describing the specific embodiments, and are not intended to limit the scope of the present specification. The term "and / or" used in the present specification includes any and all combinations of one or more related listed items. The singular forms "a", "an" and "the" used in the present disclosure and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0156] It can be understood that the processor of the present disclosure can be an integrated circuit chip with processing capability of signals. In the implementation process, each step of the method embodiments described above can be completed by integrated logic circuits in hardware or instructions in software form in the processor. The processor described above can be a general processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. Each method, step and logic block diagram disclosed in the present disclosure can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the present disclosure can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register or other mature storage medium in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and combines the hardware to complete the steps of the above method.

[0157] It can be understood that the memory in the present disclosure can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read only memory (ROM), a programmable read only memory (PROM), an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM). It should be noted that the memory of the system and method described herein is intended to include but not limited to these and any other suitable type of memory.

[0158] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware, or a combination of computer software and electronic hardware. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present specification.

[0159] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0160] In several embodiments provided in the specification, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, and the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be omitted or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0161] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0162] In addition, each functional unit in each embodiment of the specification can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit.

[0163] If the functions are realized in the form of software functional units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the specification or the essential part of the prior art or the part of the technical solutions can be embodied in the form of a software product, and the computer software product stored in a storage medium includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the specification. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0164] The above is only a specific embodiment of the specification, but the protection scope of the application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the specification, which should be covered within the protection scope of the specification. Therefore, the protection scope of the application should be subject to the protection scope of the claims.

Claims

1. A method for analyzing the effectiveness of intervention based on illegal accidents, characterized in that: The method comprises: Acquiring historical traffic intervention implementation information, wherein the historical traffic intervention implementation information at least includes intervention time, intervention method, intervention road section, and intervention vehicle; Obtaining historical accident and violation data, wherein the historical accident and violation data at least includes road segment vehicle driving trajectories, road segment violation data, road segment accident data, intervening vehicle driving trajectories, intervening vehicle violation data, and intervening vehicle accident data; Determining the total personnel consumption and the total equipment consumption of the intervention method, and determining the intervention cost based on the total personnel consumption and the total equipment consumption of the intervention method; determining an intervention efficiency based on the intervention road section, the intervention time, the intervention vehicle, the vehicle driving trajectory on the road section, and the intervention vehicle driving trajectory; Using a time series analysis model to fit the time trends of the road section violation data and the road section accident data before the intervention, to determine a set of prediction results; Calculate the deviation between the predicted result set and the actual result after intervention to determine the overall deviation value; The regions or groups that did not receive warning education are used as a control group, and the regions or groups that received warning education are used as an experimental group. Based on the vehicle driving trajectories of the road section, the violation data of the road section, the accident data of the road section, the driving trajectories of the intervention vehicles, the violation data of the intervention vehicles, and the accident data of the intervention vehicles, the change rate of the violation and accident data of the control group and the experimental group before and after the warning education is determined. An intervention effectiveness value is determined based on the intervention cost, the intervention efficiency, the overall deviation value, and the illegal accident comparison change rate.

2. The intervention effectiveness analysis method based on illegal accidents according to claim 1 is characterized in that: The total personnel consumption for determining the intervention method includes: Among them, Z is the total personnel consumption, z is the consumption of a single person, s is the work efficiency of the person, x is the xth person, and n is the total number of people.

3. The intervention effectiveness analysis method based on illegal accidents according to claim 1 is characterized in that: The total equipment consumption of the intervention method is determined, including: Among them, V is the total equipment consumption, v is the consumption of a single device, s is the equipment working efficiency, x is the x-th device, and n is the total number of devices.

4. The intervention effectiveness analysis method based on illegal accidents according to claim 1 is characterized in that: The total personnel consumption and equipment consumption based on the intervention method are used to determine the intervention cost, including: C=(Z+V)D; Among them, C is the intervention cost, Z is the total personnel consumption, V is the total equipment consumption, and D is the number of days.

5. The method for analyzing the effectiveness of intervention based on illegal incidents according to claim 1, characterized in that: The determining of the intervention efficiency according to the intervention road section, the intervention time, the intervention vehicle, the driving trajectory of the vehicle on the road section, and the driving trajectory of the intervention vehicle includes: Among them, E is the intervention efficiency, T is the intervention time, S 干预 To intervene in the vehicle trajectory, S 轨迹 is the vehicle trajectory on the road section.

6. The method for analyzing the effectiveness of intervention based on illegal incidents according to claim 1, characterized in that: Calculating the deviation between the set of predicted results and the actual results after intervention to determine the overall deviation value includes: Among them, Q is the overall deviation value, a is the actual result after the intervention, l is the set of predicted results, n is the number of time dimension units, and x is the xth time unit.

7. The intervention effectiveness analysis method based on illegal accidents according to claim 1 is characterized in that: Determining the intervention effectiveness value according to the intervention cost, the intervention efficiency, the overall deviation value, and the comparison change rate includes: Among them, R is the intervention effectiveness value, P x is the comparison change rate of illegal accidents, Q is the overall deviation value, E is the intervention efficiency, and C is the intervention cost.

8. The method for analyzing the effectiveness of intervention based on illegal incidents according to claim 6, characterized in that: The comparative change rate of illegal accidents is the difference between the change rate of the experimental group and the change rate of the control group.

9. An intervention effectiveness analysis device based on illegal accidents, characterized in that: The device is applied to the intervention effectiveness analysis method based on illegal accidents according to any one of claims 1 to 8, and the device includes: An acquisition module is used to acquire historical traffic intervention implementation information, wherein the historical traffic intervention implementation information at least includes intervention time, intervention method, intervention road section, and intervention vehicle; The acquisition module is further configured to acquire historical accident and violation data, wherein the historical accident and violation data includes at least road segment vehicle driving trajectories, road segment violation data, road segment accident data, intervention vehicle driving trajectories, intervention vehicle violation data, and intervention vehicle accident data; a determination module, configured to determine the total personnel consumption and the total equipment consumption of the intervention method, and determine the intervention cost based on the total personnel consumption and the total equipment consumption of the intervention method; The determination module is further configured to determine an intervention efficiency based on the intervention road section, the intervention time, the intervention vehicle, the vehicle driving trajectory on the road section, and the intervention vehicle driving trajectory; The determination module is further configured to use a time series analysis model to fit the time trends of the road section violation data and the road section accident data before the intervention to determine a set of prediction results; The determination module is further configured to calculate a deviation between the set of predicted results and the actual results after the intervention to determine an overall deviation value; The determination module is further configured to use regions or groups that did not receive warning education as a control group and regions or groups that received warning education as an experimental group, and to determine a comparison rate of changes in the violation and accident data of the control group and the experimental group before and after the warning education based on the vehicle driving trajectories of the road section, the violation data of the road section, the accident data of the road section, the driving trajectories of the intervention vehicles, the violation data of the intervention vehicles, and the accident data of the intervention vehicles; The determination module is further configured to determine an intervention effectiveness value based on the intervention cost, the intervention efficiency, the overall deviation value, and the illegal accident comparison change rate.

10. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to implement the intervention effectiveness analysis method based on illegal accidents as described in any one of claims 1 to 8.

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