CN115966079B - Traffic road safety operation monitoring management platform based on data analysis - Google Patents
Traffic road safety operation monitoring management platform based on data analysis Download PDFInfo
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Abstract
The invention relates to the technical field of road safety operation monitoring, and particularly discloses a traffic road safety operation monitoring management platform based on data analysis, which comprises an intersection basic information acquisition module, an intersection accident screening module, an intersection accident serious condition analysis module, an intersection accident state analysis module, an intersection accident handling mode selection module, an intersection traffic police dispatch module and a traffic management database.
Description
Technical Field
The invention belongs to the technical field of road safety operation monitoring, and relates to a traffic road safety operation monitoring management platform based on data analysis.
Background
With the continuous development of urban economy and traffic, the occurrence frequency of traffic accidents is increased, and the traffic accidents comprise motor vehicle accidents and non-motor vehicle accidents, wherein the traffic accidents caused by the fact that non-motor vehicles run red light when passing through an intersection in the non-motor vehicle traffic accidents can be avoided through traffic police supervision or intersection prompt, so that the analysis of the non-motor vehicle traffic accidents caused by the fact that the non-motor vehicles run red light in the intersection is needed for reducing the traffic accidents of the non-motor vehicles in the intersection.
The non-motor vehicle traffic accident caused by red light running at the crossroad is not analyzed at present, and obviously, the analysis mode has the following problems: 1. the severity level of the non-motor vehicle traffic accident in the crossroad reflects the dangerous situation of the non-motor vehicle traffic accident, the dangerous situation of the non-motor vehicle traffic accident corresponding to the red light running in the crossroad cannot be effectively displayed at present only by monitoring the red light running situation of the non-motor vehicle traffic accident in the crossroad, and further the traffic safety and the traffic fluency of the crossroad cannot be effectively guaranteed.
2. Traffic police dispatch influences the stable condition of crossroad traffic, and current technique does not carry out analysis to the traffic police dispatch information of crossroad according to the non-motor vehicle accident state in the crossroad to can not effectually increase the consciousness that non-motor vehicle obeyed traffic rule and the standardability that non-motor vehicle was gone, also can not improve the smoothness of crossroad traffic simultaneously, also can not reasonable distribution traffic police's work content and work load to a certain extent, and then can not improve traffic police's work efficiency and work effect.
Disclosure of Invention
The invention aims to provide a traffic road safety operation monitoring and managing platform based on data analysis, which solves the problems in the background technology.
The aim of the invention can be achieved by the following technical scheme: a traffic road safety operation monitoring management platform based on data analysis, comprising: the intersection basic information acquisition module is used for acquiring basic information corresponding to each intersection in a designated area in a designated period, wherein the basic information comprises positions and each accident video, and then the intersections are numbered as 1,2.
The intersection accident screening module is used for screening out non-motor vehicle accidents corresponding to red light running of all the intersections in the specified area in the specified period according to all the accident videos corresponding to all the intersections in the specified area in the specified period, and obtaining accident information corresponding to the non-motor vehicle accidents corresponding to the red light running of all the intersections in the specified area in the specified period.
The intersection accident severity analysis module is used for analyzing accident severity coincidence coefficients of non-motor vehicle accidents corresponding to red light running in all intersections in a specified area in a specified period.
The intersection accident state analysis module is used for analyzing and obtaining the accident state dangerous coincidence coefficient of the non-motor vehicle corresponding to the red light running in each intersection in the specified period based on the accident serious coincidence coefficient of the non-motor vehicle corresponding to the red light running in each intersection in the specified period.
The intersection accident handling mode selection module is used for judging accident handling modes corresponding to non-motor vehicle accidents running red light in all intersections in a specified period, wherein the accident handling modes comprise a traffic police management mode, a voice safety prompt mode and a prompt-free mode, and then all intersections corresponding to the traffic police management mode, the voice safety prompt mode and the prompt-free mode are obtained.
The intersection traffic police dispatch module is used for analyzing traffic police dispatch information corresponding to each intersection in the traffic police management mode, obtaining traffic police dispatch information corresponding to each intersection in the traffic police management mode and carrying out traffic police dispatch.
The voice safety prompt module is used for carrying out voice safety prompt on each intersection in the voice safety prompt mode.
In the above, the screening process is as follows: dividing each accident video corresponding to each intersection in the designated area in the designated period into each video picture, further obtaining each accident vehicle type corresponding to each accident in each intersection in the designated area in the designated period, and judging that the accident corresponding to the accident in the intersection in the designated area in the designated period is a non-motor vehicle accident if the accident vehicle type corresponding to the accident in the intersection in the designated area in the designated period exists as a non-motor vehicle accident, thereby obtaining each non-motor vehicle accident corresponding to each intersection in the designated area in the designated period.
And extracting each video picture corresponding to each non-motor vehicle accident of each cross road opening in the designated area in the designated period, and further obtaining the color of the traffic indicator lamp corresponding to each non-motor vehicle accident of each cross road opening in the designated area in the designated period.
If the traffic indicator light corresponding to a certain crossroad in the specified area in the specified period is red, judging that the non-motor vehicle accident corresponding to the crossroad in the specified area in the specified period is a non-motor vehicle accident corresponding to the red light running, and screening to obtain the non-motor vehicle accidents corresponding to the crossroad in the specified area in the specified period.
In the above, the specific process of obtaining the color of the traffic indicator corresponding to each non-motor vehicle accident at each intersection in the specified area in the specified period is as follows: the color tone, brightness and saturation corresponding to the traffic indicator lamp at the moment of occurrence of each non-motor vehicle accident in each intersection are obtained from each video picture corresponding to each non-motor vehicle accident in each intersection in the appointed area in the appointed period and respectively marked as SD ij′ 、MD ij′ And BH ij′ Wherein i represents the corresponding number of each intersection, i=1, 2. Once again, n is, j 'represents a number corresponding to each non-motor vehicle accident, j' =1 ',2'.
The hue, brightness and saturation corresponding to the standard red traffic lights are obtained from the traffic management database and respectively marked as SD, MD and BH.
According to the calculation formulaObtaining the coincidence coefficient of red traffic indicator lamps corresponding to non-motor vehicle accidents at all crossroads>Wherein τ 1 、τ 2 、τ 3 The weight factors corresponding to the set hue, brightness and saturation are respectively set.
Comparing the red traffic indicator lamp coincidence coefficient corresponding to each non-motor vehicle accident in each intersection with the set standard red traffic indicator lamp coincidence coefficient, if the red traffic indicator lamp coincidence coefficient corresponding to a certain non-motor vehicle accident in a certain intersection is larger than or equal to the standard red traffic indicator lamp coincidence coefficient, judging that the traffic indicator lamp color corresponding to the certain non-motor vehicle accident in the intersection is red, otherwise, judging that the traffic indicator lamp color corresponding to the certain non-motor vehicle accident in the intersection is not red, and obtaining the traffic indicator lamp color corresponding to each non-motor vehicle accident in each intersection in this way.
The accident information comprises accident handling time, accident involved people, the surface area and damage area of each accident vehicle.
In the above, the analyzing the accident severity coefficient of each non-motor vehicle accident corresponding to the red light running in each intersection in the specified period comprises the following specific analysis process: substituting the accident handling time length, accident number and damage area of each accident vehicle of each non-motor vehicle accident corresponding to red light running of each crossroad in the designated area in the designated period into a calculation formulaObtaining accident severity coincidence coefficient of red light running corresponding to each non-motor vehicle accident in each crossroad in the designated period>Wherein T is ij 、R ij 、S iju 、S i ′ ju Respectively representing the accident handling time of the j non-motor vehicle accident corresponding to the red light running at the i-th intersection in the designated period, the accident number, the u-th accident vehicle breakage area and the surface area of the u-th accident vehicle, wherein m represents the number of non-motor vehicle accidents and epsilon 1 、ε 2 、ε 3 The set accident handling time, accident number, and weight factor corresponding to the damage area of the accident vehicle are respectively defined, j represents the number corresponding to each non-motor vehicle accident, j=1, 2.
In the above, the analysis obtains the accident state risk coincidence coefficient of the non-motor vehicle corresponding to the red light running in each intersection in the specified period, and the specific analysis process is as follows: based on the non-motor vehicle accidents of running red light corresponding to the cross road openings in the specified area in the specified period, the number of the non-motor vehicle accidents of running red light corresponding to the cross road openings in the specified area in the specified period is obtainedQuantity, thereby according to the calculation formulaObtaining a non-motor vehicle accident state risk coincidence coefficient beta corresponding to red light running in each intersection in a specified period i Wherein N is i Indicating the number of non-motor vehicle accidents corresponding to the red light running of the ith crossroad in the specified area in the specified period, wherein n indicates the number of crossroads and gamma 1 、γ 2 The set accident number of the non-motor vehicles and the accident severity of the non-motor vehicle accidents are respectively the weight factors corresponding to the coefficient.
In the foregoing, the analysis is performed on the traffic police dispatch information corresponding to each intersection in the traffic police management mode, and the specific analysis process is as follows: and obtaining the position corresponding to each intersection in the traffic police management mode and the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running based on each intersection in the traffic police management mode.
And comparing the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running of each intersection in the traffic police management mode with the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running of each traffic police demand quantity stored in the traffic management database to obtain the traffic police demand quantity corresponding to each intersection in the traffic police management mode.
And obtaining the numbers and the positions corresponding to the schedulable traffic police from the traffic management database, and further analyzing and obtaining the numbers corresponding to the schedulable traffic police at the intersections in the traffic police management mode according to the positions of the intersections and the positions of the schedulable traffic police in the traffic police management mode.
And marking the traffic police demand quantity and the schedulable traffic police number corresponding to each intersection in the traffic police management mode as traffic police scheduling information corresponding to each intersection in the traffic police management mode.
In the above, the analyzing obtains the numbers of the schedulable traffic police corresponding to each intersection in the traffic police management mode, and the specific analyzing process is as follows: acquiring each schedulable traffic police and the traffic police management mode according to the positions corresponding to each crossroad and each schedulable traffic police in the traffic police management modeThe shortest arrival route among the crossroads is obtained, the number and the route length of the crossroads corresponding to the shortest arrival route among the schedulable traffic police and the crossroads in the traffic police management mode are respectively recorded asAnd->Where g represents the number corresponding to each schedulable traffic police, g=1, 2. The number of the combination of the components of the formula, i ' represents a number corresponding to each intersection in the traffic police management mode, i ' =1 ', 2.
According to the calculation formulaObtaining the priority meeting coefficient of the arrival between each traffic police and each intersection in the traffic police management mode>Wherein n' represents the number of intersections, σ, in traffic police management mode 1 、σ 2 The weight factors corresponding to the set number of intersections and the route length are respectively adopted.
The on-duty priority coincidence coefficients between each schedulable traffic police and each intersection in the traffic police management mode are compared with each other, and meanwhile, each schedulable traffic police corresponding to each intersection in the traffic police management mode is obtained according to the traffic police demand quantity corresponding to each intersection in the traffic police management mode, so that the number of each schedulable traffic police corresponding to each intersection in the traffic police management mode is extracted.
The traffic management database is used for storing the reference red light running non-motor vehicle accident state risk coincidence coefficient interval, the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running quantity required by each traffic police, the number and the position corresponding to each schedulable traffic police and storing the tone, the brightness and the saturation corresponding to the standard red traffic indicator.
Compared with the prior art, the invention has the following beneficial effects: 1. according to the traffic road safety operation monitoring management platform based on data analysis, through analyzing the non-motor vehicle accident state and the solution corresponding to the red light running in each intersection, the problem of non-motor vehicle traffic accident analysis limitation in the prior art is solved, intelligent monitoring of the non-motor vehicle accident running in the intersection is realized, and the red light running phenomenon and the traffic accident of the non-motor vehicle in the intersection are effectively reduced.
2. According to the invention, the accident severity coefficient of each non-motor vehicle accident corresponding to the red light running in each crossroad is analyzed in the crossroad accident severity analysis module, so that the dangerous situation of each non-motor vehicle traffic accident corresponding to the red light running in each crossroad is truly displayed, and accurate data is provided for the non-motor vehicle accident state analysis corresponding to the red light running in the subsequent crossroad.
3. According to the invention, through judging the accident handling mode corresponding to the accident of the non-motor vehicle running the red light in each intersection in the intersection accident handling mode selection module, the targeted analysis and management of the intersections are realized, the management efficiency of traffic management departments on the intersections is greatly improved, and meanwhile, the awareness of the non-motor vehicle to observe the traffic rules and the standardization of the non-motor vehicle running are effectively increased.
4. According to the traffic police dispatching method and the traffic police dispatching system, the traffic police dispatching information corresponding to each intersection in the traffic police management mode is analyzed, so that the working content of the traffic police and the rationality of workload distribution are effectively guaranteed, and the working efficiency and the working effect of the traffic police are greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a system module connection structure according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a traffic road safety operation monitoring and management platform based on data analysis includes: the system comprises an intersection basic information acquisition module, an intersection accident screening module, an intersection accident serious condition analysis module, an intersection accident state analysis module, an intersection accident handling mode selection module, an intersection traffic police dispatch module and a traffic management database.
The traffic management database is respectively connected with an intersection accident screening module, an intersection accident handling mode selection module and an intersection traffic police dispatching module, the intersection accident screening module is also connected with an intersection basic information acquisition module and an intersection accident serious condition analysis module, the intersection accident state analysis module is also connected with the intersection accident serious condition analysis module and the intersection accident handling mode selection module, and the intersection accident handling mode selection module is also connected with the intersection traffic police dispatching module and the intersection traffic police dispatching module.
The intersection basic information acquisition module is used for acquiring basic information corresponding to each intersection in a designated area in a designated period, wherein the basic information comprises positions and each accident video, and then the intersections are numbered as 1,2.
In a specific embodiment, basic information corresponding to each intersection in a specified area in a specified period is acquired, and the specific acquisition process is as follows: according to the Beidou positioning system, positions corresponding to all the intersections are obtained, a plurality of cameras are installed in all the intersections, and then according to all the cameras in all the intersections, all the accident videos corresponding to all the intersections in a designated area in a designated period are obtained.
The specified period may be a certain period in the history time, and may specifically be in the previous month or in the previous two months.
The intersection accident screening module is used for screening out non-motor vehicle accidents corresponding to red light running of all the intersections in the specified area in the specified period according to all the accident videos corresponding to all the intersections in the specified area in the specified period, and obtaining accident information corresponding to the non-motor vehicle accidents corresponding to the red light running of all the intersections in the specified area in the specified period.
In a specific embodiment, the screening process is as follows: dividing each accident video corresponding to each intersection in a designated area in a designated period into each video picture, further obtaining each accident vehicle type corresponding to each accident in each intersection in the designated area in the designated period, and judging that the accident corresponding to each accident in each intersection in the designated area in the designated period is a non-motor vehicle accident if the accident vehicle type corresponding to each accident in each intersection in the designated area in the designated period exists as a non-motor vehicle accident, thereby obtaining each non-motor vehicle accident corresponding to each intersection in the designated area in the designated period;
and extracting each video picture corresponding to each non-motor vehicle accident of each cross road opening in the designated area in the designated period, and further obtaining the color of the traffic indicator lamp corresponding to each non-motor vehicle accident of each cross road opening in the designated area in the designated period.
If the traffic indicator light corresponding to a certain crossroad in the specified area in the specified period is red, judging that the non-motor vehicle accident corresponding to the crossroad in the specified area in the specified period is a non-motor vehicle accident corresponding to the red light running, and screening to obtain the non-motor vehicle accidents corresponding to the crossroad in the specified area in the specified period.
In a further specific embodiment, the acquiring the color of the traffic indicator corresponding to each non-motor vehicle accident at each intersection in the designated area in the designated period specifically acquiresThe process is as follows: the color tone, brightness and saturation corresponding to the traffic indicator lamp at the moment of occurrence of each non-motor vehicle accident in each intersection are obtained from each video picture corresponding to each non-motor vehicle accident in each intersection in the appointed area in the appointed period and respectively marked as SD ij′ 、MD ij′ And BH ij′ Wherein i represents the corresponding number of each intersection, i=1, 2. Once again, n is, j 'represents a number corresponding to each non-motor vehicle accident, j' =1 ',2'.
The hue, brightness and saturation corresponding to the standard red traffic lights are obtained from the traffic management database and respectively marked as SD, MD and BH.
According to the calculation formulaObtaining the coincidence coefficient of red traffic indicator lamps corresponding to non-motor vehicle accidents at all crossroads>Wherein τ 1 、τ 2 、τ 3 The weight factors corresponding to the set hue, brightness and saturation are respectively set.
Comparing the red traffic indicator lamp coincidence coefficient corresponding to each non-motor vehicle accident in each intersection with the set standard red traffic indicator lamp coincidence coefficient, if the red traffic indicator lamp coincidence coefficient corresponding to a certain non-motor vehicle accident in a certain intersection is larger than or equal to the standard red traffic indicator lamp coincidence coefficient, judging that the traffic indicator lamp color corresponding to the certain non-motor vehicle accident in the intersection is red, otherwise, judging that the traffic indicator lamp color corresponding to the certain non-motor vehicle accident in the intersection is not red, and obtaining the traffic indicator lamp color corresponding to each non-motor vehicle accident in each intersection in this way.
In another specific embodiment, the accident information includes accident handling duration, accident number, surface area of each accident vehicle and damage area.
In another specific embodiment, the acquiring the accident information of each non-motor vehicle accident corresponding to the red light running in each intersection in the specified area in the specified period specifically includes the following steps: and obtaining the accident handling time of each non-motor vehicle accident corresponding to red light running at each intersection based on the accident video of each non-motor vehicle accident corresponding to red light running at each intersection.
The accident involved person number in each video picture of each non-motor vehicle accident corresponding to red light running at each intersection is obtained from each video picture of each non-motor vehicle accident corresponding to red light running at each intersection, and the maximum involved person number is screened out from the video picture as the accident involved person number of each non-motor vehicle accident corresponding to red light running at each intersection.
The method comprises the steps of obtaining images of vehicles before and after the accident of each non-motor vehicle accident corresponding to red light running at each intersection from video images of each non-motor vehicle accident corresponding to red light running at each intersection, further obtaining corresponding surface areas of the vehicles, and comparing the images of the vehicles before and after the accident of each non-motor vehicle accident corresponding to red light running at each intersection to obtain damage areas of vehicles of each accident in each non-motor vehicle accident corresponding to red light running at each intersection.
The intersection accident severity analysis module is used for analyzing accident severity coincidence coefficients of non-motor vehicle accidents corresponding to red light running in all intersections in a specified area in a specified period.
In a specific embodiment, the analyzing the accident severity coefficient of each non-motor vehicle accident corresponding to the red light running at each intersection in the specified period includes the following steps: substituting the accident handling time length, accident number and damage area of each accident vehicle of each non-motor vehicle accident corresponding to red light running of each crossroad in the designated area in the designated period into a calculation formulaObtaining accident severity coincidence coefficient of red light running corresponding to each non-motor vehicle accident in each crossroad in the designated period>Wherein T is ij 、R ij 、S iju 、S i ′ ju Respectively representing the accident handling time of the j non-motor vehicle accident corresponding to the red light running at the i-th intersection in the designated period, the accident number, the u-th accident vehicle breakage area and the surface area of the u-th accident vehicle, wherein m represents the number of non-motor vehicle accidents and epsilon 1 、ε 2 、ε 3 The set accident handling time, accident number, and weight factor corresponding to the damage area of the accident vehicle are respectively defined, j represents the number corresponding to each non-motor vehicle accident, j=1, 2.
According to the method and the device, the accident serious coincidence coefficient of the non-motor vehicle accidents corresponding to the red light running in each crossroad is analyzed, the dangerous situation of the non-motor vehicle traffic accidents corresponding to the red light running in each crossroad is truly displayed, and accurate data are provided for the non-motor vehicle accident state analysis corresponding to the red light running in the subsequent crossroad.
The intersection accident state analysis module is used for analyzing and obtaining the accident state dangerous coincidence coefficient of the non-motor vehicle corresponding to the red light running in each intersection in the specified period based on the accident serious coincidence coefficient of the non-motor vehicle corresponding to the red light running in each intersection in the specified period.
In a specific embodiment, the analysis obtains the accident state risk coincidence coefficient of the non-motor vehicle corresponding to the red light running in each intersection in the specified period, and the specific analysis process is as follows: based on the non-motor vehicle accidents corresponding to red light running of each intersection in the specified area in the specified period, the number of the non-motor vehicle accidents corresponding to red light running of each intersection in the specified area in the specified period is obtained, and therefore a calculation formula is usedObtaining a non-motor vehicle accident state risk coincidence coefficient beta corresponding to red light running in each intersection in a specified period i Wherein N is i Indicating the number of non-motor vehicle accidents corresponding to the red light running of the ith crossroad in the specified area in the specified period, wherein n indicates the number of crossroads and gamma 1 、γ 2 The set accident number of the non-motor vehicles and the accident severity of the non-motor vehicle accidents are respectively the weight factors corresponding to the coefficient.
The intersection accident handling mode selection module is used for judging accident handling modes corresponding to non-motor vehicle accidents running red light in all intersections in a specified period, wherein the accident handling modes comprise a traffic police management mode, a voice safety prompt mode and a prompt-free mode, and then all intersections corresponding to the traffic police management mode, the voice safety prompt mode and the prompt-free mode are obtained.
In a specific embodiment, the specific determining process is as follows: and comparing the accident state risk coincidence coefficient of the non-motor vehicle corresponding to the red light running in each intersection in the specified period with the reference red light running accident state risk coincidence coefficient interval of the non-motor vehicle stored in the traffic management database.
If the accident state risk coincidence coefficient of the non-motor vehicle corresponding to the red light running in the intersection in the specified period is larger than the upper limit value of the accident state risk coincidence coefficient interval of the reference red light running non-motor vehicle, judging that the accident handling mode corresponding to the red light running non-motor vehicle accident in the intersection in the specified period is a traffic police management mode.
If the accident state risk coincidence coefficient of the non-motor vehicle corresponding to the red light running in the intersection in the specified period is within the accident state risk coincidence coefficient interval of the non-motor vehicle corresponding to the red light running in the reference intersection in the specified period, judging that the accident handling mode corresponding to the accident of the non-motor vehicle corresponding to the red light running in the intersection in the specified period is a voice safety prompt mode.
If the accident state risk coincidence coefficient of the non-motor vehicle corresponding to the red light running in the intersection in the specified period is smaller than the lower limit value of the accident state risk coincidence coefficient interval of the reference red light running non-motor vehicle, judging that the accident handling mode corresponding to the red light running non-motor vehicle accident in the intersection in the specified period is a prompt-free mode.
Corresponding crossroads in the traffic police management mode, the voice safety prompt mode and the unnecessary prompt mode are obtained through statistics in the mode.
According to the embodiment of the invention, through judging the accident handling mode corresponding to the non-motor vehicle accident running the red light in each intersection, the targeted analysis and management of the intersection are realized, the management efficiency of the traffic management department on the intersection is greatly improved, and meanwhile, the awareness of the non-motor vehicle to observe the traffic rules and the standardization of the non-motor vehicle running are effectively increased.
The intersection traffic police dispatch module is used for analyzing traffic police dispatch information corresponding to each intersection in the traffic police management mode, obtaining traffic police dispatch information corresponding to each intersection in the traffic police management mode and carrying out traffic police dispatch.
In a specific embodiment, the analysis is performed on traffic police dispatch information corresponding to each intersection in the traffic police management mode, and a specific analysis process is as follows: and obtaining the position corresponding to each intersection in the traffic police management mode and the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running based on each intersection in the traffic police management mode.
And comparing the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running of each intersection in the traffic police management mode with the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running of each traffic police demand quantity stored in the traffic management database to obtain the traffic police demand quantity corresponding to each intersection in the traffic police management mode.
And obtaining the numbers and the positions corresponding to the schedulable traffic police from the traffic management database, and further analyzing and obtaining the numbers corresponding to the schedulable traffic police at the intersections in the traffic police management mode according to the positions of the intersections and the positions of the schedulable traffic police in the traffic police management mode.
And marking the traffic police demand quantity and the schedulable traffic police number corresponding to each intersection in the traffic police management mode as traffic police scheduling information corresponding to each intersection in the traffic police management mode.
In another specific embodiment, the analyzing obtains numbers of each schedulable traffic police corresponding to each intersection in the traffic police management mode, and the specific analyzing process is as follows: acquiring shortest arrival routes between each schedulable traffic police and each intersection in the traffic police management mode according to the positions corresponding to each intersection in the traffic police management mode and the positions corresponding to each schedulable traffic police, acquiring the number of intersections and the route length of the shortest arrival routes corresponding to each intersection in each schedulable traffic police and each intersection in the traffic police management mode, and respectively marking asAnd->Where g represents the number corresponding to each schedulable traffic police, g=1, 2. The number of the combination of the components of the formula, i ' represents a number corresponding to each intersection in the traffic police management mode, i ' =1 ', 2.
According to the calculation formulaObtaining the priority meeting coefficient of the arrival between each traffic police and each intersection in the traffic police management mode>Wherein n' represents the number of intersections, σ, in traffic police management mode 1 、σ 2 The weight factors corresponding to the set number of intersections and the route length are respectively adopted.
The on-duty priority coincidence coefficients between each schedulable traffic police and each intersection in the traffic police management mode are compared with each other, and meanwhile, each schedulable traffic police corresponding to each intersection in the traffic police management mode is obtained according to the traffic police demand quantity corresponding to each intersection in the traffic police management mode, so that the number of each schedulable traffic police corresponding to each intersection in the traffic police management mode is extracted.
In the above, each schedulable traffic police corresponding to each cross road port in the traffic police management mode is obtained, and the specific analysis process is as follows: comparing the on-duty priority coincidence coefficients between each schedulable traffic police and each intersection in the traffic police management mode to obtain the corresponding sequence of each intersection in the traffic police management mode, and further obtaining each schedulable traffic police corresponding to each intersection in the traffic police management mode based on the traffic police demand quantity corresponding to each intersection in the traffic police management mode;
if each intersection in the traffic police management mode has a certain schedulable traffic police, comparing the on-duty priority coincidence coefficient between the schedulable traffic police and each intersection in the traffic police management mode, and selecting the intersection corresponding to the maximum on-duty priority coincidence coefficient as the schedulable traffic police of the intersection in the traffic police management mode corresponding to the schedulable traffic police.
According to the traffic police management method and device, the traffic police scheduling information corresponding to each intersection in the traffic police management mode is analyzed, so that the working content of the traffic police and the rationality of workload distribution are effectively guaranteed, and the working efficiency and the working effect of the traffic police are greatly improved.
The voice safety prompt module is used for carrying out voice safety prompt on each intersection in the voice safety prompt mode.
The traffic management database is used for storing reference red light running non-motor vehicle accident state danger meeting coefficient intervals, non-motor vehicle accident state danger meeting coefficients corresponding to the red light running quantity required by each traffic police, numbers and positions corresponding to each schedulable traffic police and storing tone, brightness and saturation corresponding to the standard red traffic indicator lights.
According to the embodiment of the invention, through analyzing the non-motor vehicle accident state and the solution corresponding to the red light running in each intersection, the problem of limitation of analysis of non-motor vehicle traffic accidents in the prior art is solved, intelligent monitoring of the non-motor vehicle accidents running the red light in the intersections is realized, and the red light running phenomenon and traffic accidents of the non-motor vehicles in the intersections are effectively reduced.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (6)
1. A traffic road safety operation monitoring and management platform based on data analysis, which is characterized by comprising:
the intersection basic information acquisition module is used for acquiring basic information corresponding to each intersection in the designated area in the designated period, wherein the basic information comprises positions and each accident video, and further, the intersections are numbered as follows in sequence according to a preset sequence；
The intersection accident screening module is used for screening out non-motor vehicle accidents corresponding to red light running of all the intersections in the specified area in the specified period according to all the accident videos corresponding to all the intersections in the specified area in the specified period, and obtaining accident information corresponding to the non-motor vehicle accidents corresponding to the red light running of all the intersections in the specified area in the specified period;
the intersection accident severity analysis module is used for analyzing accident severity coincidence coefficients of non-motor vehicle accidents corresponding to red light running in each intersection in a designated area in a designated period;
the intersection accident state analysis module is used for analyzing and obtaining accident state danger coincidence coefficients of the non-motor vehicle corresponding to the red light running in each intersection in the specified period based on the accident severity coincidence coefficients of the non-motor vehicle corresponding to the red light running in each intersection in the specified period;
the intersection accident handling mode selection module is used for judging accident handling modes corresponding to non-motor vehicle accidents running red light in all intersections in a specified period, wherein the accident handling modes comprise a traffic police management mode, a voice safety prompt mode and a no-prompt mode, and then all intersections corresponding to the traffic police management mode, the voice safety prompt mode and the no-prompt mode are obtained;
the intersection traffic police dispatch module is used for analyzing traffic police dispatch information corresponding to each intersection in the traffic police management mode, obtaining traffic police dispatch information corresponding to each intersection in the traffic police management mode and carrying out traffic police dispatch;
the voice safety prompting module is used for prompting voice safety for each crossroad in the voice safety prompting mode;
the accident information comprises accident handling time, accident personnel number, surface area and damage area of each accident vehicle;
the accident serious coincidence coefficient of each non-motor vehicle accident corresponding to the red light running in each intersection in the specified period is analyzed, and the specific analysis process is as follows:
substituting the accident handling time length, accident number and damage area of each accident vehicle of each non-motor vehicle accident corresponding to red light running of each crossroad in the designated area in the designated period into a calculation formulaObtaining accident severity coincidence coefficient of red light running corresponding to each non-motor vehicle accident in each crossroad in the designated period>Wherein->、/>、/>、/>Respectively represent the j non-maneuver of the corresponding red light running of the i-th crossroad in the designated area in the designated periodAccident handling duration of vehicle accidents, accident number, damaged area of the vehicle at the ith accident, surface area of the vehicle at the ith accident, m represents the number of non-motor vehicle accidents, and ∈>、/>、/>Respectively setting weight factors corresponding to accident handling time, accident number and accident vehicle damage area, wherein j represents numbers corresponding to non-motor vehicle accidents, < + >>U represents the number corresponding to each accident vehicle,；
the analysis is carried out to obtain non-motor vehicle accident state risk coincidence coefficients corresponding to red light running in each intersection in a specified period, and the specific analysis process is as follows:
based on the non-motor vehicle accidents corresponding to red light running of each intersection in the specified area in the specified period, the number of the non-motor vehicle accidents corresponding to red light running of each intersection in the specified area in the specified period is obtained, and therefore a calculation formula is usedObtaining non-motor vehicle accident state risk coincidence coefficient corresponding to red light running in each intersection in a specified period>Wherein->Indicating the ith ten in the specified area in the specified periodThe number of non-motor vehicle accidents corresponding to red light running at the crossroad, n represents the number of crossroads,/-the number of crossroads>、/>The set accident number of the non-motor vehicles and the accident severity of the non-motor vehicle accidents are respectively the weight factors corresponding to the coefficient.
2. The traffic road safety operation monitoring and management platform based on data analysis according to claim 1, wherein: the specific screening process is as follows:
dividing each accident video corresponding to each intersection in a designated area in a designated period into each video picture, further obtaining each accident vehicle type corresponding to each accident in each intersection in the designated area in the designated period, and judging that the accident corresponding to each accident in each intersection in the designated area in the designated period is a non-motor vehicle accident if the accident vehicle type corresponding to each accident in each intersection in the designated area in the designated period exists as a non-motor vehicle accident, thereby obtaining each non-motor vehicle accident corresponding to each intersection in the designated area in the designated period;
extracting each video picture of each cross road opening corresponding to each non-motor vehicle accident in the specified area in the specified period, and further obtaining the color of the traffic indicator lamp of each cross road opening corresponding to each non-motor vehicle accident in the specified area in the specified period;
if the traffic indicator light corresponding to a certain crossroad in the specified area in the specified period is red, judging that the non-motor vehicle accident corresponding to the crossroad in the specified area in the specified period is a non-motor vehicle accident corresponding to the red light running, and screening to obtain the non-motor vehicle accidents corresponding to the crossroad in the specified area in the specified period.
3. The traffic road safety operation monitoring and management platform based on data analysis according to claim 2, wherein: the specific acquisition process is as follows:
acquiring the color tone, brightness and saturation corresponding to the traffic indicator lamp at the moment of occurrence of each non-motor vehicle accident in each intersection from each video picture corresponding to each non-motor vehicle accident in each intersection in each specified area in a specified period, and respectively marking as、/>And->Wherein i represents the number corresponding to each intersection, < >>，/>Numbers corresponding to accidents of the non-motor vehicles, < >>；
Obtaining the corresponding hue, brightness and saturation of the standard red traffic indicator from the traffic management database and respectively marking as、/>And->；
According to the calculation formulaObtaining the coincidence coefficient of red traffic indicator lights corresponding to non-motor vehicle accidents at all crossroads>Wherein->、/>、/>Respectively setting weight factors corresponding to the tone, the brightness and the saturation;
comparing the red traffic indicator lamp coincidence coefficient corresponding to each non-motor vehicle accident in each intersection with the set standard red traffic indicator lamp coincidence coefficient, if the red traffic indicator lamp coincidence coefficient corresponding to a certain non-motor vehicle accident in a certain intersection is larger than or equal to the standard red traffic indicator lamp coincidence coefficient, judging that the traffic indicator lamp color corresponding to the certain non-motor vehicle accident in the intersection is red, otherwise, judging that the traffic indicator lamp color corresponding to the certain non-motor vehicle accident in the intersection is not red, and obtaining the traffic indicator lamp color corresponding to each non-motor vehicle accident in each intersection in this way.
4. The traffic road safety operation monitoring and management platform based on data analysis according to claim 1, wherein: the traffic police dispatch information corresponding to each intersection in the traffic police management mode is analyzed, and the specific analysis process is as follows:
based on each intersection in the traffic police management mode, obtaining the corresponding positions of each intersection in the traffic police management mode and the corresponding non-motor vehicle accident state risk coincidence coefficient of the red light running;
comparing the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running of each intersection in the traffic police management mode with the non-motor vehicle accident state risk coincidence coefficient corresponding to the red light running of each traffic police demand quantity stored in the traffic management database to obtain the traffic police demand quantity corresponding to each intersection in the traffic police management mode;
acquiring numbers and positions corresponding to the schedulable traffic police from a traffic management database, and analyzing and obtaining the numbers corresponding to the schedulable traffic police at each intersection in the traffic police management mode according to the positions of the intersections and the schedulable traffic police in the traffic police management mode;
and marking the traffic police demand quantity and the schedulable traffic police number corresponding to each intersection in the traffic police management mode as traffic police scheduling information corresponding to each intersection in the traffic police management mode.
5. The traffic road safety operation monitoring and management platform based on data analysis according to claim 4, wherein: the analysis obtains the serial numbers of the traffic police corresponding to each schedulable traffic police at each intersection in the traffic police management mode, and the specific analysis process is as follows:
acquiring shortest arrival routes between each schedulable traffic police and each intersection in the traffic police management mode according to the positions corresponding to each intersection in the traffic police management mode and the positions corresponding to each schedulable traffic police, acquiring the number of intersections and the route length of the shortest arrival routes corresponding to each intersection in each schedulable traffic police and each intersection in the traffic police management mode, and respectively marking asAnd->Wherein g represents the number corresponding to each schedulable traffic police,>，/>representing crossroads in traffic police management modeNumber corresponding to mouth,/->；
According to the calculation formulaObtaining the priority meeting coefficient of the arrival at the crossroads in each schedulable traffic police and each traffic police management mode +.>Wherein->Indicating the number of crossroads in traffic police management mode, < +.>、/>Respectively setting weight factors corresponding to the number of intersections and the length of the route;
the on-duty priority coincidence coefficients between each schedulable traffic police and each intersection in the traffic police management mode are compared with each other, and meanwhile, each schedulable traffic police corresponding to each intersection in the traffic police management mode is obtained according to the traffic police demand quantity corresponding to each intersection in the traffic police management mode, so that the number of each schedulable traffic police corresponding to each intersection in the traffic police management mode is extracted.
6. The traffic road safety operation monitoring and management platform based on data analysis according to claim 1, wherein: the traffic management database is used for storing reference red light running non-motor vehicle accident state danger meeting coefficient intervals, non-motor vehicle accident state danger meeting coefficients corresponding to the red light running quantity required by each traffic police, numbers and positions corresponding to each schedulable traffic police and storing tone, brightness and saturation corresponding to the standard red traffic indicator lights.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3193319A1 (en) * | 2016-01-13 | 2017-07-19 | Ekin, Akif | Smart recording, control and warning system for crossroad traffic |
| CN110942629A (en) * | 2019-11-29 | 2020-03-31 | 中核第四研究设计工程有限公司 | Road traffic accident management method and device and terminal equipment |
| CN114550445A (en) * | 2022-01-24 | 2022-05-27 | 广东省城乡规划设计研究院有限责任公司 | Urban area traffic safety state evaluation method and device |
| KR102453688B1 (en) * | 2021-04-28 | 2022-10-11 | 아주대학교산학협력단 | System for assessmenting potential risk of traffic accident and method thereof |
| CN115240422A (en) * | 2022-07-22 | 2022-10-25 | 合肥师范学院 | Real-time cyclist detection reminding system based on traffic video |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3193319A1 (en) * | 2016-01-13 | 2017-07-19 | Ekin, Akif | Smart recording, control and warning system for crossroad traffic |
| CN110942629A (en) * | 2019-11-29 | 2020-03-31 | 中核第四研究设计工程有限公司 | Road traffic accident management method and device and terminal equipment |
| KR102453688B1 (en) * | 2021-04-28 | 2022-10-11 | 아주대학교산학협력단 | System for assessmenting potential risk of traffic accident and method thereof |
| CN114550445A (en) * | 2022-01-24 | 2022-05-27 | 广东省城乡规划设计研究院有限责任公司 | Urban area traffic safety state evaluation method and device |
| CN115240422A (en) * | 2022-07-22 | 2022-10-25 | 合肥师范学院 | Real-time cyclist detection reminding system based on traffic video |
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