CN116824863B - Intelligent road network monitoring system - Google Patents
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 27
- 238000012545 processing Methods 0.000 claims abstract description 42
- 238000012423 maintenance Methods 0.000 claims abstract description 28
- 238000007781 pre-processing Methods 0.000 claims abstract description 19
- 238000000605 extraction Methods 0.000 claims abstract description 9
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- 238000001514 detection method Methods 0.000 description 7
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Abstract
The invention discloses an intelligent road network monitoring system which comprises a data acquisition module, a preprocessing module, an extraction module, a data processing module, a database module and a data output module, wherein the data acquisition module is used for acquiring data from a road network; the data acquisition module is used for acquiring real-time data on the road; the extraction module is used for receiving the real-time data of the preprocessing module and extracting effective real-time data information of the real-time data; the data processing module is used for analyzing, judging and obtaining the traffic capacity of the road; finally, making a security maintenance decision according to the traffic capacity information of the road; the intelligent road network monitoring system analyzes, judges and obtains the traffic capacity of the road through real-time data, can make a safety maintenance decision according to the traffic capacity information of the road, and timely provides auxiliary information such as maintenance, construction inspection and the like of the road, so that maintenance personnel can scientifically and reasonably improve road conditions and effectively improve the traffic capacity of the road.
Description
Technical Field
The invention relates to the field of road network monitoring, in particular to an intelligent road network monitoring system.
Background
Vehicles are becoming an indispensable necessity in people's life as a common transportation means, and the increasing popularity of vehicles also causes a series of traffic problems; the increasing congestion of urban traffic brings a plurality of problems to urban construction and citizen life, and particularly the problem of traffic congestion caused by faster promotion of individual automobile consumption in recent years has become an important factor for preventing urban development; the infrastructure of the road and the structural design of the road also influence the use traffic capacity of the road, so that the congestion problem is caused; in this case, if the traffic flow of the road is large, the road layout is unreasonable or the road is old, so that the traffic capacity of the road is greatly reduced; meanwhile, the old and damaged road facilities deform to bring certain potential safety hazards, so that the traffic capacity of roads is affected, but the existing road network system is huge, the detection difficulty is high, and the problems can not be found and treated in time.
In order to solve the problems that the existing road network system is huge, the detection difficulty is high and the road use state cannot be optimized in time, an intelligent road network monitoring system is provided.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: how to solve the problems that the existing road network system is huge, the detection difficulty is high, and the road use state cannot be optimized in time, and an intelligent road network monitoring system is provided.
The invention solves the technical problems through the following technical scheme, and comprises a data acquisition module, a preprocessing module, an extraction module, a data processing module, a database module and a data output module;
the data acquisition module is used for acquiring real-time data on the road, wherein the real-time data comprises vehicle running information and road state information;
the preprocessing module is used for classifying the real-time data and controlling the transmission direction of the real-time data according to the type of the real-time data;
the extraction module is used for receiving the real-time data of the preprocessing module and extracting effective real-time data information of the real-time data;
the database module is used for storing historical data;
the data processing module is used for receiving the real-time data from the data acquisition module, calling the historical data in the database module, and then analyzing and judging the real-time data by referring to the historical data to obtain the traffic capacity of the road; finally, making a security maintenance decision according to the traffic capacity information of the road;
the data output module is used for receiving the security maintenance decision made by the data processing module and outputting the security maintenance decision.
Preferably, the history data includes vehicle driving type data and road state type data, and when the real-time data enters the preprocessing module, the specific processing procedure of the preprocessing module is as follows:
and finally, the vehicle running information is sent to a data processing module, and the road state information is sent to a detection module.
Preferably, the database module includes historical road facility state information, the road state information includes real-time road facility state information, the real-time road facility state information includes picture information and video information, and a specific processing procedure of the data processing module for the road state information is as follows:
firstly, establishing a plurality of acquisition points a1, a2 and a3..
When the acquired data information is picture information;
shooting objects of monitoring points on a plurality of acquisition points respectively, correspondingly establishing first picture information groups b1, b2 and b3..
When the acquired data information is video information;
respectively carrying out 360-degree video recording on an object at a plurality of positions of a monitoring point, after the recording is completed, respectively intercepting a plurality of picture information on the plurality of acquisition points, and correspondingly establishing a second picture information group c1, c2 and c3.;
and carrying out picture enhancement on the first picture information group and the second picture information group, wherein a picture enhancement technology comprises a frequency domain method and a spatial domain method, so that a group of clear picture groups d1, d2 and d3..
Preferably, the processing procedure of the data processing module further includes:
modeling the state of the object of the monitoring point by utilizing accurate picture data according to the original data in the object of the monitoring point to obtain a modeling body F, wherein the original data comprises the length, the width and the height of the object of the monitoring point;
at least two concentric circles are established by taking the center of the modeling body F as an origin;
at least two straight lines which are perpendicular to each other and pass through the center of a circle are established;
two groups of marking points m1, m2, m3, m4, n1, n2, n3, n4 are respectively and independently established by the intersection points of the two straight lines and the two concentric circles;
the linear factor K between every two marking points is calculated by the level difference X and the height difference Y between any two marking points in each group, and the specific process is as follows:
Y=K*X+C
c is the difference between the measured height in the object with the marked point and the original data;
calculating linear factors of the two straight lines to be Km and Kn respectively;
finally, calculating the inclination angle alpha of the two straight lines according to a trigonometric function method and a collude law method, wherein alpha is an included angle between the two straight lines and the vertical direction;
setting the threshold value of the maximum inclination angle of the marked object as W;
when alpha is smaller than W, the danger coefficient is smaller, the road traffic capacity is good, and maintenance is not needed;
when alpha is larger than W, the risk coefficient is larger, the road traffic capacity is poor, overhauling is needed, and an opinion decision of the road facility inspection and repair is made.
Preferably, the data processor further performs the following processing procedure:
calling a historical inclination angle in a database module;
establishing a change curve of the inclination angle and time;
according to the safety range of the inclination angle, estimating a time interval range in which the inclination angle exceeds the safety range;
and making a maintenance concrete decision of the road facilities according to the time interval range.
Preferably, the history data includes lane position information and the data processor further performs the following processing procedure:
calling lane position information and historical road facility state information;
the method comprises the steps of calling real-time data, and comparing historical data with the real-time data to obtain a height difference Hx1 of the road facility;
the coverage rate of the road facilities to the lanes is calculated as follows:
Pi=（Hx1/tanα）/Hx2
wherein Hx2 is the lane width; alpha is more than 0 and less than 90;
when Pi is more than or equal to a preset threshold Z, the occupied area of the road facility is large, and a road facility maintenance warning decision is made.
Preferably, the database module has road live information, the historical data includes historical traffic flow data, the vehicle driving information includes vehicle quantity information and traffic light information, and the processing procedure of the data processing module for the vehicle driving information is as follows:
the method comprises the steps of calling road live information, taking a midpoint of a road intersection as an origin, and taking a preset radius R as a radius to establish a circular area G;
counting the number information Q1 of vehicles in the round area G and the number information Q2 of vehicles passing through the traffic lights in the green light period T1;
judging the road dredging capacity P, wherein the specific judging process is as follows:
P=Q2/Q1
when P is more than or equal to a preset threshold M, judging that the traffic is smooth in the period;
when P is less than a preset threshold M, judging that the traffic jam occurs in the period;
the time period of traffic jam is counted, and the specific counting process is as follows:
counting duration t=x (t1+t) of P < preset threshold M, wherein T is the interval time of adjacent green lights, X is the number of green lights, and is recorded as a blocking time period Tt;
the time period of congestion occurring in one day is denoted as Tt1, tt2, tt3,..ttn;
the blocking weight E is calculated, and the specific calculation process is as follows:
E=（Tt1+Tt2+Tt3+...+Ttn）/24
calculating the average value of the blockage weights E in a preset time periodThe preset time period is at least one week;
when (when)When the road traffic saturation degree is greater than or equal to a preset threshold value N, the road traffic capacity is poor;
when (when)When the preset threshold value N is less than the preset threshold value N, then the trackThe road traffic saturation degree is small, and the road traffic capacity is good;
when (when)And when the threshold value N is not less than the preset threshold value N, making a road renovation opinion decision.
Preferably, the history data includes lane position information, the vehicle running information further includes running speed information of the vehicle and running track information of the vehicle, and the data processing module is further used for counting the timeThe running speed information of the vehicle and the running track information of the vehicle of the road section which is not less than the preset threshold value N are processed as follows:
randomly extracting a plurality of automobiles as sample vehicles in a circular area G;
respectively calling the running speed information and the running track information of a plurality of sample automobiles;
counting the times S of the speed of the sample automobile passing through the road pilot lamp being 0;
counting the average number of times the speed of the automobile with a plurality of samples is 0;
When the average timesWhen the preset threshold value T is more than the preset threshold value T, the road accommodation quantity is insufficient, and a road capacity increasing concrete decision is made;
counting the number V1 of track changes in a plurality of sample vehicles and the number V2 of track changes and track changes in the track changing process of the plurality of sample vehicles, wherein the number V2 is 0, and the specific process is as follows:
firstly, lane position information is acquired, and then the number H of lanes occupied by the vehicle is judged according to the vehicle running track information;
if the number H of the lanes is more than or equal to 2, counting the number V1;
when the vehicle covers the lane line, the vehicle speed is in a state of 0, and the number V2 is counted;
calculating a vehicle plug rate J=V2/V1;
when the vehicle jam rate J is more than or equal to a preset threshold U, the lane distribution is unreasonable, and a road correction concrete decision is made.
Preferably, when P is less than the preset threshold M and traffic jam is determined in this period, the data processing module determines the following procedure:
when P is more than or equal to a preset threshold M, extracting the number of vehicles passing through the traffic lights when the traffic lights are any green lights, and calculating an average value Q3;
when P is smaller than a preset threshold M, extracting a plurality of traffic lights as any green light, and calculating an average value Q4 through the number of vehicles passing through the traffic lights;
calculating the ratio of Q4/Q3, and when the ratio of Q4/Q3 is smaller than a preset threshold I, artificially obstructing the overlong driving time at the intersection to make a concrete decision of road security management.
Preferably, the system further comprises a pre-storage module, wherein the pre-storage module is used for temporarily storing real-time data, and after the preset time, the real-time data are transferred to the database module.
Compared with the prior art, the invention has the following advantages: the intelligent road network monitoring system can collect real-time data of roads, call historical data in the database module, analyze and judge road facilities and traffic jam conditions in the real-time data by referring to the historical data, obtain traffic capacity of the roads, monitor road conditions in real time, reduce manual participation, greatly improve the problem of high detection difficulty caused by large road network systems, make safety maintenance decisions according to traffic capacity information of the roads, and timely provide auxiliary information such as maintenance, construction inspection and the like of the roads, so that maintenance personnel can scientifically and reasonably improve the road conditions and effectively improve the traffic capacity of the roads.
Drawings
Fig. 1 is an overall construction diagram of the present invention.
Detailed Description
The following describes in detail the examples of the present invention, which are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of protection of the present invention is not limited to the following examples.
As shown in fig. 1, this embodiment provides a technical solution: an intelligent road network monitoring system comprises a data acquisition module, a preprocessing module, an extraction module, a data processing module, a database module and a data output module;
the data acquisition module is used for acquiring real-time data on the road, wherein the real-time data comprises vehicle running information and road state information;
the preprocessing module is used for classifying the real-time data and controlling the transmission direction of the real-time data according to the type of the real-time data;
the extraction module is used for receiving the real-time data of the preprocessing module and extracting effective real-time data information of the real-time data;
the database module is used for storing historical data;
the data processing module is used for receiving the real-time data from the data acquisition module, calling the historical data in the database module, and then analyzing and judging the real-time data by referring to the historical data to obtain the traffic capacity of the road; finally, making a security maintenance decision according to the traffic capacity information of the road;
the data output module is used for receiving the security maintenance decision made by the data processing module and outputting the security maintenance decision.
The intelligent road network monitoring system can collect real-time data of roads, call historical data in the database module, analyze and judge road facilities and traffic jam conditions in the real-time data by referring to the historical data, obtain traffic capacity of the roads, monitor road conditions in real time, reduce manual participation, greatly improve the problem of high detection difficulty caused by large road network systems, make safety maintenance decisions according to traffic capacity information of the roads, and timely provide auxiliary information such as maintenance, construction inspection and the like of the roads, so that maintenance personnel can scientifically and reasonably improve the road conditions and effectively improve the traffic capacity of the roads.
It should be noted that, the history data includes vehicle driving type data and road state type data, and when the real-time data enters the preprocessing module, the specific processing procedure of the preprocessing module is as follows:
and finally, the vehicle running information is sent to a data processing module, and the road state information is sent to a detection module.
After the classification of the preprocessing module, the real-time data can be classified according to the type of the real-time data, so that the real-time data can be detected and processed conveniently, and the accuracy of the real-time data can be effectively improved.
In one embodiment, the database module includes historical road facility status information, the road status information includes real-time road facility status information, the real-time road facility status information includes picture information and video information, and the specific processing procedure of the data processing module for the road status information is as follows:
firstly, establishing a plurality of acquisition points a1, a2 and a3..
When the acquired data information is picture information;
shooting objects of monitoring points on a plurality of acquisition points respectively, correspondingly establishing first picture information groups b1, b2 and b3..
When the acquired data information is video information;
respectively carrying out 360-degree video recording on an object at a plurality of positions of a monitoring point, after the recording is completed, respectively intercepting a plurality of picture information on the plurality of acquisition points, and correspondingly establishing a second picture information group c1, c2 and c3.;
and carrying out picture enhancement on the first picture information group and the second picture information group, wherein a picture enhancement technology comprises a frequency domain method and a spatial domain method, so that a group of clear picture groups d1, d2 and d3..
And adopting a plurality of acquisition points to acquire pictures of the same object, simultaneously requiring the repeatability of pictures of adjacent acquisition points to be more than 70%, extracting pictures of the plurality of acquisition points according to video, screening out clearer pictures, and establishing a model of the object.
Further, the processing procedure of the data processing module further comprises:
modeling the state of the object of the monitoring point by utilizing accurate picture data according to the original data in the object of the monitoring point to obtain a modeling body F, wherein the original data comprises the length, the width and the height of the object of the monitoring point;
at least two concentric circles are established by taking the center of the modeling body F as an origin;
at least two straight lines which are perpendicular to each other and pass through the center of a circle are established;
two groups of marking points m1, m2, m3, m4, n1, n2, n3, n4 are respectively and independently established by the intersection points of the two straight lines and the two concentric circles;
the linear factor K between every two marking points is calculated by the level difference X and the height difference Y between any two marking points in each group, and the specific process is as follows:
Y=K*X+C
c is the difference between the measured height in the object with the marked point and the original data;
calculating linear factors of the two straight lines to be Km and Kn respectively;
finally, calculating the inclination angle alpha of the two straight lines according to a trigonometric function method and a collude law method, wherein alpha is an included angle between the two straight lines and the vertical direction;
it should be noted that, firstly, linear factor K is obtained by using a primary function, and then, the linear factor K is converted into a corresponding angle by using a trigonometric function;
setting the threshold value of the maximum inclination angle of the marked object as W;
when alpha is smaller than W, the danger coefficient is smaller, the road traffic capacity is good, and maintenance is not needed;
when alpha is larger than W, the risk coefficient is larger, the road traffic capacity is poor, overhauling is needed, and an opinion decision of the road facility inspection and repair is made.
When the inclination angle alpha is larger than the preset threshold value W, the road facilities are inclined greatly due to damage, the road facilities are dangerous, inspection and maintenance of the safety state of the road facilities are recommended, and the traffic capacity of the road is improved.
Still further, the data processor performs the following processing procedure:
calling a historical inclination angle in a database module;
establishing a change curve of the inclination angle and time;
according to the safety range of the inclination angle, estimating a time interval range in which the inclination angle exceeds the safety range;
and making a maintenance concrete decision of the road facilities according to the time interval range.
The damage degree of the road facilities can be reasonably and scientifically predicted, so that maintenance personnel can maintain the road facilities, and dangerous accidents are avoided.
Further, the history data includes lane position information and the data processor performs the following processing:
calling lane position information and historical road facility state information;
the method comprises the steps of calling real-time data, and comparing historical data with the real-time data to obtain a height difference Hx1 of the road facility;
the coverage rate of the road facilities to the lanes is calculated as follows:
Pi=（Hx1/tanα）/Hx2
wherein Hx2 is the lane width; alpha is more than 0 and less than 90;
when Pi is more than or equal to a preset threshold Z, the occupied area of the road facility is large, and a road facility maintenance warning decision is made.
The ratio of occupied roads after the road facilities are inclined is further calculated, so that influence of damaged road facilities is predicted, and a warning is sent to remind maintenance.
The road facilities include facilities on the road side or road of construction such as overpasses, street lamps, and bus stops.
In the second embodiment, the database module has road live information, the history data includes history traffic flow data, the vehicle running information includes vehicle number information and traffic light information, and the processing procedure of the data processing module for the vehicle running information is as follows:
the method comprises the steps of calling road live information, taking a midpoint of a road intersection as an origin, and taking a preset radius R as a radius to establish a circular area G;
counting the number information Q1 of vehicles in the round area G and the number information Q2 of vehicles passing through the traffic lights in the green light period T1;
judging the road dredging capacity P, wherein the specific judging process is as follows:
P=Q2/Q1
when P is more than or equal to a preset threshold M, judging that the traffic is smooth in the period;
when P is less than a preset threshold M, judging that the traffic jam occurs in the period;
the time period of traffic jam is counted, and the specific counting process is as follows:
counting duration t=x (t1+t) of P < preset threshold M, wherein T is the interval time of adjacent green lights, X is the number of green lights, and is recorded as a blocking time period Tt;
the time period of congestion occurring in one day is denoted as Tt1, tt2, tt3,..ttn;
the blocking weight E is calculated, and the specific calculation process is as follows:
E=（Tt1+Tt2+Tt3+...+Ttn）/24
calculating the average value of the blockage weights E in a preset time periodThe preset time period is at least one week;
when (when)When the road traffic saturation degree is greater than or equal to a preset threshold value N, the road traffic capacity is poor;
when (when)When the threshold value is less than the preset threshold value N, the road traffic saturation degree is small, and the road traffic capacity is good;
when (when)And when the threshold value N is not less than the preset threshold value N, making a road renovation opinion decision.
The road jam degree is judged through the road dredging capability P, the jam period of the road is further judged, the road jam is determined through the jam period, the road jam is occasional or universal, the road traffic saturation degree is determined, when the road saturation degree is large, the condition that the traffic pressure of the road is large is indicated, normal traffic and transportation cannot be met is not achieved, and therefore the opinion decision of road repair is made.
Further, the history data includes lane position information, the vehicle driving information further includes driving speed information of the vehicle and driving track information of the vehicle, and the data processing module is further used for counting the time of arrivalThe running speed information of the vehicle and the running track information of the vehicle of the road section which is not less than the preset threshold value N are processed as follows:
randomly extracting a plurality of automobiles as sample vehicles in a circular area G;
respectively calling the running speed information and the running track information of a plurality of sample automobiles;
counting the times S of the speed of the sample automobile passing through the road pilot lamp being 0;
counting the average number of times the speed of the automobile with a plurality of samples is 0;
When the average timesWhen the preset threshold value T is more than the preset threshold value T, the road accommodation quantity is insufficient, and a road capacity increasing concrete decision is made;
determining the congestion condition of the road through the starting and stopping frequency of the vehicle, and then suggesting to build auxiliary roads, viaducts or increase road width to increase the capacity of the road for accommodating the vehicle so as to reduce the use pressure of the road;
counting the number V1 of track changes in a plurality of sample vehicles and the number V2 of track changes and track changes in the track changing process of the plurality of sample vehicles, wherein the number V2 is 0, and the specific process is as follows:
firstly, lane position information is acquired, and then the number H of lanes occupied by the vehicle is judged according to the vehicle running track information;
it should be noted that, the determination of the number of lanes H occupied by the vehicle may be performed by the image acquisition device, and when the vehicle covers the lane lines, it is determined that the vehicle changes lanes, that is, the number of lanes H is more than or equal to 2 is satisfied;
if the number H of the lanes is more than or equal to 2, counting the number V1;
when the vehicle covers the lane line, the vehicle speed is in a state of 0, and the number V2 is counted;
calculating a vehicle plug rate J=V2/V1;
when the vehicle jam rate J is more than or equal to a preset threshold U, the lane distribution is unreasonable, and a road correction concrete decision is made.
According to the road modification specificity decision, it may be recommended to build a variable lane, or to re-plan a lane, while adjusting the distance of the road sign to the road intersection.
Still further, when P is less than the preset threshold M, and traffic jam is determined in this period, the determining process of the data processing module is as follows:
when P is more than or equal to a preset threshold M, extracting the number of vehicles passing through the traffic lights when the traffic lights are any green lights, and calculating an average value Q3;
when P is smaller than a preset threshold M, extracting a plurality of traffic lights as any green light, and calculating an average value Q4 through the number of vehicles passing through the traffic lights;
calculating the ratio of Q4/Q3, and when the ratio of Q4/Q3 is smaller than a preset threshold I, artificially obstructing the overlong driving time at the intersection to make a concrete decision of road security management.
When making the concrete decision of road security management, the lack of management at the road intersection and the lack of traffic consciousness of pedestrians are indicated, so that the situation can be improved through behaviors such as security management, science popularization and the like due to the blockage of human factors.
Preferably, the system further comprises a pre-storage module, wherein the pre-storage module is used for temporarily storing real-time data, and after the preset time, the real-time data are transferred to the database module.
When the road running state is required to be queried by using the data, the information can be timely extracted, the use is convenient, the complicated searching process is avoided, and the use efficiency is improved.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (4)
1. The intelligent road network monitoring system is characterized by comprising a data acquisition module, a preprocessing module, an extraction module, a data processing module, a database module and a data output module;
the data acquisition module is used for acquiring real-time data on the road, wherein the real-time data comprises vehicle running information and road state information;
the preprocessing module is used for classifying the real-time data and controlling the transmission direction of the real-time data according to the type of the real-time data;
the extraction module is used for receiving the real-time data of the preprocessing module and extracting effective real-time data information of the real-time data;
the database module is used for storing historical data;
the data processing module is used for receiving the real-time data from the preprocessing module, calling the historical data in the database module, analyzing and judging the real-time data by referring to the historical data to obtain the traffic capacity of the road, and finally making a security maintenance decision according to the traffic capacity information of the road;
the data output module is used for receiving the security maintenance decision made by the data processing module and outputting the security maintenance decision;
the history data comprise vehicle driving type data and road state type data, and when the real-time data enter the preprocessing module, the specific processing procedure of the preprocessing module is as follows:
leading historical data in a database module, comparing the real-time data with the historical data, dividing the real-time data into vehicle running information and road state information, and finally transmitting the road state information to a data processing module and transmitting the vehicle running information to an extraction module;
the database module comprises historical road facility state information, the road state information comprises real-time road facility state information, the real-time road facility state information comprises picture information and video information, and the specific processing process of the data processing module to the road state information is as follows:
firstly, establishing a plurality of acquisition points a1, a2 and a3..
When the acquired data information is picture information;
shooting objects of monitoring points on a plurality of acquisition points respectively, correspondingly establishing first picture information groups b1, b2 and b3..
When the acquired data information is video information;
respectively carrying out 360-degree video recording on an object at a plurality of positions of a monitoring point, after the recording is completed, respectively intercepting a plurality of picture information on the plurality of acquisition points, and correspondingly establishing a second picture information group c1, c2 and c3.;
carrying out picture enhancement on the first picture information group and the second picture information group, wherein a picture enhancement technology comprises a frequency domain method and a spatial domain method, so as to form a group of clear picture groups d1, d2 and d3..
The database module is provided with road live information, the historical data comprise historical traffic flow data, the vehicle running information comprises vehicle quantity information and traffic light information, and the data processing module processes the vehicle running information as follows:
the method comprises the steps of calling road live information, taking a midpoint of a road intersection as an origin, and taking a preset radius R as a radius to establish a circular area G;
counting the number information Q1 of vehicles in the round area G and the number information Q2 of vehicles passing through the traffic lights in the green light period T1;
judging the road dredging capacity P, wherein the specific judging process is as follows:
P=Q2/Q1
when P is more than or equal to a preset threshold M, judging that the traffic is smooth in the period;
when P is less than a preset threshold M, judging that the traffic jam occurs in the period;
the time period of traffic jam is counted, and the specific counting process is as follows:
counting duration t=x (t1+t) of P < preset threshold M, wherein T is the interval time of adjacent green lights, X is the number of green lights, and is recorded as a blocking time period Tt;
the time period of congestion occurring in one day is denoted as Tt1, tt2, tt3,..ttn;
the blocking weight E is calculated, and the specific calculation process is as follows:
E=（Tt1+Tt2+Tt3+...+Ttn）/24
calculating the average value of the blockage weights E in a preset time periodThe preset time period is at least one week;
when (when)When the road traffic saturation degree is greater than or equal to a preset threshold value N, the road traffic capacity is poor;
when (when)When the threshold value is less than the preset threshold value N, the road traffic saturation degree is small, and the road traffic capacity is good;
when (when)And when the threshold value N is not less than the preset threshold value N, making a road renovation opinion decision.
2. An intelligent road network monitoring system according to claim 1, wherein: the history data comprises lane position information, vehicle running information further comprises running speed information of the vehicle and running track information of the vehicle, and the data processing module is further used for counting the current timeThe running speed information of the vehicle and the running track information of the vehicle of the road section which is not less than the preset threshold value N are processed as follows:
randomly extracting a plurality of automobiles as sample vehicles in a circular area G;
respectively calling the running speed information and the running track information of a plurality of sample vehicles;
counting the times S of the speed of the sample vehicle passing through the road pilot lamp being 0;
counting the average number of times the vehicle speed of a plurality of samples is 0；
When the average timesWhen the preset threshold value beta is larger than the preset threshold value beta, the road accommodation quantity is insufficient, and a road capacity increasing concrete decision is made;
counting the number V1 of track changes in a plurality of sample vehicles and the number V2 of track changes and track changes in the track changing process of the plurality of sample vehicles, wherein the number V2 is 0, and the specific process is as follows:
firstly, lane position information is acquired, and then the number H of lanes occupied by the vehicle is judged according to the vehicle running track information;
if the number H of the lanes is more than or equal to 2, counting the number V1;
when the vehicle covers the lane line, the vehicle speed is in a state of 0, and the number V2 is counted;
calculating a vehicle plug rate J=V2/V1;
when the vehicle jam rate J is more than or equal to a preset threshold U, the lane distribution is unreasonable, and a road correction concrete decision is made.
3. An intelligent road network monitoring system according to claim 2, wherein: when P is smaller than the preset threshold M and traffic jam is judged in the period, the judging process of the data processing module is as follows:
when P is more than or equal to a preset threshold M, extracting the number of vehicles passing through the traffic lights when the traffic lights are any green lights, and calculating an average value Q3;
when P is smaller than a preset threshold M, extracting a plurality of traffic lights as any green light, and calculating an average value Q4 through the number of vehicles passing through the traffic lights;
calculating the ratio of Q4/Q3, and when the ratio of Q4/Q3 is smaller than a preset threshold I, artificially obstructing the overlong driving time at the intersection to make a concrete decision of road security management.
4. An intelligent road network monitoring system according to claim 1, wherein: the system also comprises a pre-storage module, wherein the pre-storage module is used for temporarily storing the real-time data, and after the preset time, the real-time data are transferred to the database module.
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