CN111798678A - Urban traffic intelligent monitoring coordination management system based on big data - Google Patents
Urban traffic intelligent monitoring coordination management system based on big data Download PDFInfo
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Abstract
The invention discloses an urban traffic intelligent monitoring coordination management system based on big data, which comprises a traffic flow monitoring analysis module, an accident analysis processing module, a traffic database, a remote server and a traffic light display terminal, wherein the traffic flow monitoring analysis module is used for monitoring the traffic flow of a road intersection, dynamically adjusting the green light passing time of the intersection according to the real-time traffic flow, acquiring a monitoring image of a traffic accident occurring at the intersection by the accident analysis processing module, and switching the traffic light of the intersection to a specified red traffic light for display, thereby solving the unreasonable problem of the existing traffic management system, improving the traffic road management level, alleviating the urban road jam, further reducing the occurrence of primary and secondary traffic accidents, and enhancing the traffic experience of traffic users, meanwhile, the management efficiency of a traffic manager is improved.
Description
Technical Field
The invention relates to the technical field of traffic monitoring and management, in particular to an urban traffic intelligent monitoring and coordination management system based on big data.
Background
With the increasing mileage of urban roads and the rapid growth of vehicles, the congestion and the traffic accidents of urban roads are increased. In order to improve the safety level of traffic and reduce the incidence of accidents, traffic management is required.
However, in places with some defects in current traffic management, such as design of interval time of traffic lights at a road intersection, the interval time of the current traffic lights is basically unchanged within 24 hours a day, the traffic volume at the peak and the valley of the intersection is not considered, the traffic volume of one road at one intersection is constantly changed, the traffic volume of the road at one intersection is changed under normal conditions, the traffic volume of the road at the peak of going to work and the traffic volume of the road at the peak of going to school and learning are reversed, and if the traffic lights are not adjusted in time at the moment, road congestion is caused by the traffic lights.
For example, a traffic accident occurs at a road intersection, at present, when the traffic accident occurs at the intersection, traffic police personnel are informed to handle the traffic accident, but other vehicles at the intersection can normally run according to traffic indicating lamps, so that a secondary traffic accident can be caused, and meanwhile, the accident scene can be damaged, so that the traffic police personnel are difficult to obtain evidence. In order to make up for the defect places in the existing traffic management system, the invention designs an urban traffic intelligent monitoring and coordination management system based on big data.
Disclosure of Invention
The invention aims to provide an intelligent urban traffic monitoring and coordination management system based on big data, aiming at the problems of unreasonable traffic light interval time setting and traffic accident handling at a road intersection in the background technology, carrying out statistical analysis on the traffic flow of the intersection by time intervals, dynamically adjusting the green light passing time of the intersection according to the real-time traffic flow, simultaneously carrying out monitoring image acquisition on the traffic accident at the intersection, and switching the traffic light of the intersection to a specified red traffic light for displaying so as to avoid secondary accidents and solve the problems in the background technology.
The purpose of the invention can be realized by the following technical scheme:
an urban traffic intelligent monitoring coordination management system based on big data comprises a traffic flow monitoring analysis module, an accident analysis processing module, a traffic database, a remote server and a traffic light display terminal, wherein the traffic flow monitoring analysis module is used for monitoring the traffic flow of a road intersection and dynamically adjusting the green light passing time of the intersection according to the real-time traffic flow, and the accident analysis processing module is used for collecting monitoring images of traffic accidents occurring at the intersection and switching the traffic lights of the intersection to a specified red traffic light for display;
the remote server is respectively connected with the traffic flow monitoring and analyzing module and the accident analyzing and processing module, and the traffic light display terminal is respectively connected with the traffic flow monitoring and analyzing module and the accident analyzing and processing module;
traffic flow control analysis module includes traffic flow statistics module and actual traffic flow analysis module of passing, traffic flow statistics module includes the traffic flow detector, and it is installed at the intersection of urban road for the traffic flow parameter to this intersection vehicle is passed and is detected, and divides this intersection traffic flow parameter passed and passed according to predetermined detection time quantum that will detect, and each detection time quantum time interval is the same, constitutes detection time quantum traffic flow parameter set Cw(Cw1,Cw2,...,Cwt,...,Cwm)，Cwt is represented as w-th traffic flow parameter of t-th detection time period, w is represented as traffic flow parameter, and w is equal to wl,wv,wd，wl,wv,wdRespectively expressing the length, the speed and the distance between vehicles passing through the intersection, counting the traffic flow of each detection time period according to a traffic flow calculation formula, and sending the traffic flow to a remote server;
the actual traffic flow analysis module receives the traffic flow of each detection time period sent by the traffic flow statistics module, obtains the actual green light traffic time of the motor vehicle at the intersection, obtains the average number of passing vehicles in the actual green light traffic time through calculation, further obtains the actual traffic flow in a single detection time period, and sends the actual traffic flow in the single detection time period of the motor vehicle at the intersection to the remote server;
the traffic database is used for storing accident object characteristics corresponding to various traffic accidents, wherein the various traffic accidents comprise human-vehicle accidents and vehicle accidents, the accident object characteristics corresponding to the human-vehicle accidents are pedestrians and vehicles, the accident object characteristics corresponding to the vehicle accidents are vehicles and vehicles, accident detail characteristics corresponding to different levels of traffic accidents of the various traffic accidents are stored, shortened time corresponding to each time shortening coefficient and prolonged time corresponding to each time prolonging coefficient are stored, and influence coefficients of peak and low valley detection time periods are stored;
the accident analysis processing module comprises an accident image monitoring and collecting module and an accident characteristic analysis module;
the accident image monitoring and collecting module comprises a high-definition camera and is used for carrying out real-time video monitoring on the pedestrian flow and the vehicle condition passing through the intersection, collecting the intersection image at the moment when a traffic accident occurs, recording the time point of the accident, carrying out focusing amplification treatment on the collected intersection image, sending the intersection image to the accident characteristic analysis module, and sending the time point of the accident to the remote server;
the accident feature analysis module receives the processed intersection image sent by the accident image monitoring and collecting module, extracts accident object features in the image, wherein the accident object features refer to whether an accident object is a pedestrian or a vehicle, the accident object features are roughly compared one by one with accident object features corresponding to various traffic accidents stored in a traffic database, the extracted features and the accident object features corresponding to various traffic accidents are counted, the traffic accident category with the highest similarity is screened, when the screened highest similarity is larger than a set similarity threshold value, the traffic accident category with the highest similarity is output as the category of the intersection accident, after the category of the intersection accident is determined, the intersection image is subjected to image segmentation processing to obtain an accident area image, the obtained accident area image is locally amplified to capture accident detail features, if the traffic accident belongs to a human-vehicle accident, the accident detail characteristics comprise the condition of pedestrian injury, the number of casualties and the condition of vehicle collision, if the traffic accident belongs to a vehicle accident, the accident detail characteristics comprise the number of accident vehicles, the distance between the vehicles and the condition of vehicle collision, the captured accident detail characteristics are matched with the accident detail characteristics corresponding to different levels of traffic accidents stored in a traffic database, the accident levels corresponding to the accident detail characteristics captured by the type of traffic accidents are screened and sent to a remote server;
the remote server receives the traffic flow of each detection time period and the actual traffic flow of each intersection motor vehicle in each detection time period sent by the traffic flow monitoring and analyzing module, compares the received actual traffic flow of each intersection motor vehicle in each detection time period with the traffic flow of each detection time period, if the actual traffic flow is greater than the traffic flow in a certain detection time period, the received actual traffic flow of each intersection motor vehicle in each detection time period indicates that the traffic flow in the detection time period is less, counts the detection time periods with the traffic flow less than the actual traffic flow, the number of the detection time periods is 1,2, 1, i, g, which is marked as a valley detection time period, carries out operation of shortening the green light traffic time, counts time shortening coefficients, extracts the shortening time corresponding to each time shortening coefficient in a traffic database, screens the shortening time corresponding to each valley detection time period, and sends the counted number of the valley detection time periods and the corresponding shortening time of the motor vehicle green light to a traffic light display The terminal is used for counting the time periods when the traffic flow is greater than the actual traffic flow, wherein the number is 1,2, a.
The remote server receives the accident grade and the accident occurrence time point sent by the accident analysis processing module and the geographical position of the intersection where the accident occurs sent by the GPS positioning module, and obtains the traffic light signal of the crossroad at the moment, if the traffic light signal of the crossroad at the moment is the red light, continuously keeping the red light on, if the traffic light signal at the intersection is a green light or a yellow light at the moment, sending a control instruction of switching the signal light into the red light to the traffic light display terminal, meanwhile, the red light estimated delay time is obtained through calculation according to the optimal navigation path from the traffic control center to the accident scene, which is sent by the distance tracking navigation module, calculating according to the time point of the accident to obtain the red light delay time point, and sending to the traffic light display terminal, receiving a delay arrival point early warning signal fed back by a traffic light display terminal, and sending the delay arrival point early warning signal to a traffic control center;
meanwhile, the remote server sends the accident grade of the accident and the geographical position of the intersection where the accident occurs to a traffic control center, and the traffic control center dispatches related personnel for processing;
the traffic light display terminal receives the valley detection time period number and the corresponding motor vehicle green light shortening time length sent by the remote server, receives the peak detection time period number and the corresponding motor vehicle green light prolonging time length, and shortens or prolongs the green light passing time of the corresponding detection time period;
meanwhile, the traffic light display terminal receives the signal light transformation control command and the red light delay time point sent by the remote server, switches corresponding signal light operation, sends a delay arrival point early warning signal to the remote server when the red light delay time point reaches the calculated red light delay time point, and simultaneously receives the control command sent by the traffic control center, and continues to delay the red light or switches the red light to the green light operation.
According to an implementation manner of the invention, the traffic flow calculation formula
Where V is the speed of the vehicle, L is the body length of the vehicle, S is the inter-vehicle distance, and Δ T is the individual detection period duration.
According to one implementation mode of the invention, the calculation formula of the average number of vehicles capable of passing through the intersection in the actual passing time of the green light of the motor vehicle is
TFruit of Chinese wolfberryThe actual passing time of the green light of the motor vehicle at the intersection is represented, D is the intersection distance,
expressed as the average body length of the vehicle leading to the intersection,
the average speed of the vehicle passing through the intersection is shown, and K is the number of bidirectional lanes at the intersection.
According to one implementation mode of the invention, the calculation formula of the actual traffic flow in the single detection time period is
Δ T is expressed as a single detection period duration, TFruit of Chinese wolfberryThe actual passing time of the motor vehicle green light at the intersection is represented, and R is the average number of vehicles capable of passing through the actual passing time of the motor vehicle green light at the intersection.
According to one possible implementation of the present invention, the time reduction factor is calculated by the formula
ξi shrinkTime reduction coefficient, Q, expressed as the ith valley detection periodFruit of Chinese wolfberryExpressed as actual traffic flow, Q, for a single detection periodiTraffic flow, λ, expressed as the ith valley detection periodIs low inExpressed as a valley detection time period influence coefficient, the time delay coefficient is calculated by
ξYanExpressed as the time extension factor, Q, of the ith peak detection periodjTraffic flow, λ, expressed as the jth valley detection periodHeight ofExpressed as a peak detection time period impact coefficient.
According to an implementation mode of the invention, the system further comprises a GPS positioning module which is used for acquiring the geographical position information of the intersection and sending the geographical position information to the remote server.
According to an implementation mode of the invention, the system further comprises a traffic control center which is respectively connected with the remote server and the distance tracking navigation module, receives the accident grade sent by the remote server, the geographical position of the intersection where the accident occurs and the optimal navigation path sent by the distance tracking navigation module, takes different measures according to different accident grades, dispatches related personnel to process according to the optimal navigation path, and simultaneously receives the early warning signal of the delay arrival point sent by the remote server, if the related personnel does not arrive at the accident scene at the moment, sends a continuous delay instruction to the traffic light display terminal, and if the related personnel arrives at the accident scene at the moment, sends a green light switching control instruction to the traffic light display terminal.
According to an implementation mode of the invention, the system further comprises a distance tracking navigation module which is connected with the GPS positioning module and is used for acquiring position information of a traffic control center, comparing the geographical position of the intersection where the accident occurs, which is sent by the GPS positioning module, with the position information of the traffic control center, providing an optimal navigation path and sending the optimal navigation path to the traffic control center.
Has the advantages that:
(1) the traffic flow monitoring and analyzing module is combined to monitor the traffic flow of the road intersection, dynamically adjust the green light passing time of the intersection according to the real-time traffic flow, acquire the monitoring image of the traffic accident at the intersection and switch the traffic light of the intersection to the designated red traffic light for display, so that the problem of unreasonable existing traffic management systems is solved, the existing traffic systems are well coordinated, the traffic road management level is improved, the urban road jam is alleviated, the occurrence of primary and secondary traffic accidents is further reduced, the traffic experience of traffic users is enhanced, and the management efficiency of traffic managers is also improved.
(2) According to the invention, by arranging the GPS positioning module and the distance tracking navigation module, when a traffic accident occurs, the optimal navigation path is obtained by positioning the geographical position of the accident occurrence place and the geographical position information of the traffic control center according to the distance route planning, so that the related processing personnel can conveniently and quickly arrive, the red light delay time is reduced, and the occurrence of secondary traffic accidents caused by the fact that other vehicles at the accident occurrence place do not obey the traffic rules due to overlong waiting time is avoided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic block diagram of the present invention;
FIG. 2 is a schematic view of a traffic flow monitoring and analyzing module according to the present invention;
fig. 3 is a schematic diagram of an accident analysis processing module according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-3, an intelligent monitoring, coordinating and managing system for urban traffic based on big data comprises a traffic flow monitoring and analyzing module, an accident analyzing and processing module, a traffic database, a remote server, a GPS positioning module, a distance tracking and navigating module, a traffic control center and a traffic light display terminal, wherein the traffic flow monitoring and analyzing module is used for monitoring the traffic flow of a road intersection and dynamically adjusting the green light passing time of the intersection according to the real-time traffic flow, and the accident analyzing and processing module is used for collecting monitoring images of traffic accidents occurring at the intersection and switching the traffic lights of the intersection to a designated red traffic light for display.
The remote server is respectively connected with the traffic flow monitoring and analyzing module, the accident analyzing and processing module and the traffic control center, the traffic light display terminal is respectively connected with the remote server and the traffic control center, the GPS positioning module is respectively connected with the remote server and the distance tracking navigation module, the distance tracking navigation module is connected with the traffic control center, and the traffic database is respectively connected with the accident analyzing and processing module and the remote server.
The traffic flow monitoring and analyzing module comprises a traffic flow counting module and an actual traffic flow analyzing module, the traffic flow counting module comprises a traffic flow detector, the traffic flow detector is installed at the intersection of the urban road and used for detecting traffic flow parameters of passing vehicles at the intersection and dividing the detected traffic flow parameters at the intersection according to a preset detection time period, time intervals of all the detection time periods are the same, and a detection time period traffic flow parameter set C is formedw(Cw1,Cw2,...,Cwt,...,Cwm)，Cwt is represented as w-th traffic flow parameter of t-th detection time period, w is represented as traffic flow parameter, and w is equal to wl,wv,wd，wl,wv,wdRespectively representing the length, the speed and the distance between vehicles passing through the intersection, and counting the traffic flow of each detection time period according to a traffic flow calculation formula
In the formula, V represents the speed of the vehicle, L represents the body length of the vehicle, S represents the distance between the vehicles, and Delta T represents the time length of a single detection time period, and the traffic flow counting module sends the traffic flow of each detection time period to the remote server.
The preset detection time period in this embodiment may be 24:00-3:00, 3:00-,6:00, 6:00-9:00, 9:00-12:00, 12:00-15:00, 15:00-18:00, 18:00-21:00, 21:00-24:00, and the duration of a single detection time period is three hours, but is not limited to this detection time period division manner.
Actual traffic flow analysis moduleThe method is used for acquiring the actual passing time of the motor vehicle at the intersection under the green light, and obtaining the average number of vehicles capable of passing through the actual passing time under the green light through calculation
TFruit of Chinese wolfberryThe actual passing time of the green light of the motor vehicle at the intersection is represented, D is the intersection distance,
expressed as the average body length of the vehicle leading to the intersection,
the average speed of the vehicles passing through the intersection is represented, K is the number of bidirectional lanes of the intersection, and the actual traffic flow in a single detection time period is obtained
Δ T is expressed as a single detection period duration, TFruit of Chinese wolfberryThe traffic flow analysis module sends the actual traffic flow of the motor vehicle at the intersection in a single detection time period to the remote server.
In the preferred embodiment, the average vehicle length and the average vehicle speed in the average vehicle number calculation formula for calculating the passing time of the green light can be obtained by averaging the vehicle length and the vehicle speed in the vehicle flow parameters in each detection time period.
The traffic database is used for storing accident object characteristics corresponding to various traffic accidents, wherein the various traffic accidents comprise human-vehicle accidents and vehicle accidents, the accident object characteristics corresponding to the human-vehicle accidents are pedestrians and vehicles, the accident object characteristics corresponding to the vehicle accidents are vehicles and vehicles, accident detail characteristics corresponding to different levels of traffic accidents of the various traffic accidents are stored, shortening time corresponding to each time shortening coefficient and prolonging time corresponding to each time prolonging coefficient are stored, and influence coefficients of peak and low valley detection time periods are stored.
The accident analysis processing module comprises an accident image monitoring and collecting module and an accident characteristic analysis module;
the accident image monitoring and collecting module comprises a high-definition camera and is used for carrying out real-time video monitoring on the pedestrian flow and the vehicle condition passing through the intersection, collecting the intersection image at the moment when a traffic accident occurs, recording the time point of the accident, carrying out focusing amplification treatment on the collected intersection image, sending the intersection image to the accident characteristic analysis module, and sending the time point of the accident to the remote server;
the accident feature analysis module receives the processed intersection image sent by the accident image monitoring and collecting module, extracts accident object features in the image, wherein the accident object features refer to whether an accident object is a pedestrian or a vehicle, the accident object features are roughly compared one by one with accident object features corresponding to various traffic accidents stored in a traffic database, the extracted features and the accident object features corresponding to various traffic accidents are counted, the traffic accident category with the highest similarity is screened, when the screened highest similarity is larger than a set similarity threshold value, the traffic accident category with the highest similarity is output as the category of the intersection accident, after the category of the intersection accident is determined, the intersection image is subjected to image segmentation processing to obtain an accident area image, the obtained accident area image is locally amplified to capture accident detail features, if the traffic accident belongs to a human-vehicle accident, the accident detail characteristics comprise the condition of pedestrian injury, the number of casualties and the condition of vehicle collision, if the traffic accident belongs to a vehicle accident, the accident detail characteristics comprise the number of accident vehicles, the distance between the vehicles and the condition of vehicle collision, the captured accident detail characteristics are matched with the accident detail characteristics corresponding to different levels of traffic accidents stored in a traffic database, the accident levels corresponding to the accident detail characteristics captured by the traffic accidents are screened, and the accident levels are sent to a remote server.
The remote server receives the traffic flow monitoring and analyzing moduleComparing the received actual traffic flow of the single detection time period of the motor vehicle at the intersection with the actual traffic flow of the single detection time period of the motor vehicle at the intersection, if the actual traffic flow is larger than the traffic flow in a certain detection time period, indicating that the traffic flow in the detection time period is less, counting the detection time periods with the traffic flow smaller than the actual traffic flow, wherein the number of the detection time periods is 1,2, 1, i, g, is recorded as a valley detection time period, carrying out green light traffic time shortening operation, and counting the time shortening coefficient
ξi shrinkTime reduction coefficient, Q, expressed as the ith valley detection periodFruit of Chinese wolfberryExpressed as actual traffic flow, Q, for a single detection periodiTraffic flow, λ, expressed as the ith valley detection periodIs low inExpressing as a valley detection time period influence coefficient, extracting a shortened time corresponding to each time shortening coefficient in a traffic database, screening the shortened time corresponding to the time shortening coefficient of each valley detection time period, sending the counted valley detection time period number and the corresponding motor vehicle green light shortened time to a traffic light display terminal, if the actual traffic flow is less than the traffic flow in a certain detection time period, indicating that the traffic flow in the detection time period is more, counting the detection time period when the traffic flow is greater than the actual traffic flow, and recording the number as 1,2,
ξyanExpressed as the time extension factor, Q, of the ith peak detection periodjTraffic flow, λ, expressed as the jth valley detection periodHeight ofThe peak detection time period is expressed as a peak detection time period influence coefficient, the extension time corresponding to the time extension coefficient of each peak detection time period is screened, and the counted peak detection time period number and the corresponding motor vehicle green light extension time are sentTo the traffic light display terminal.
The preferred embodiment innovatively provides a time shortening coefficient and a time prolonging coefficient, and the green light passing time of each detection time period is reasonably adjusted according to the green light shortening time corresponding to the time shortening coefficient and the green light prolonging time corresponding to the time prolonging coefficient, so that traffic jam is avoided, and the intellectualization and humanization of the system are reflected.
And the GPS positioning module is used for acquiring the geographical position information of the intersection and sending the geographical position information to the remote server and the distance tracking navigation module.
The remote server receives the accident grade and the time point of the accident sent by the accident analysis processing module and the geographical position of the crossroad where the accident occurs sent by the GPS positioning module, acquires the traffic light signal of the crossroad at the moment, continuously keeps on lighting the red light if the traffic light signal of the crossroad at the moment is the red light, sends a control instruction of switching the signal light into the red light to the traffic light display terminal if the traffic light signal of the crossroad at the moment is the green light or the yellow light, simultaneously obtains the estimated delay time of the red light through calculation according to the optimal navigation path from the traffic control center to the accident site sent by the distance tracking navigation module, determines the estimated delay time of the red light according to the ratio of the distance of the optimal navigation path and the average speed of the police car, calculates according to the time point of the accident occurrence to obtain the delay time point of the red light, the red light delay time point is calculated by adding the time point of the accident and the estimated red light delay time length, and the red light delay time point is sent to the traffic light display terminal, receives the early warning signal of the delay arrival point fed back by the traffic light display terminal and sends the early warning signal to the traffic control center.
The red light delay time in the embodiment is set to reserve time for traffic management personnel to arrive at the accident site, and meanwhile, the red light delay is convenient for accident site protection.
Meanwhile, the remote server sends the accident grade of the accident and the geographical position of the intersection where the accident occurs to a traffic control center, and the traffic control center dispatches related personnel for processing;
and the distance tracking navigation module is used for acquiring the position information of the traffic control center, comparing the geographical position of the intersection where the accident occurs, which is sent by the GPS positioning module, with the position information of the traffic control center, providing the optimal navigation path, and sending the optimal navigation path to the traffic control center.
In the embodiment, the GPS positioning module and the distance tracking navigation module are arranged, when a traffic accident occurs, the optimal navigation path is obtained by positioning the geographical position of the accident occurrence place and the geographical position information of the traffic control center according to the distance route planning, so that the related processing personnel can conveniently and quickly arrive, the red light delay time is reduced, and the occurrence of secondary traffic accidents caused by the fact that other vehicles at the accident occurrence place do not comply with traffic rules due to overlong waiting time is avoided.
The traffic control center receives the accident grade sent by the remote server, the geographical position of the crossroad where the accident occurs and the optimal navigation path sent by the distance tracking navigation module, takes different measures according to different accident grades, dispatches related personnel to process according to the optimal navigation path, the different measures comprise adding hands, calling rescue vehicles and the like, simultaneously receives a delay arrival early warning signal sent by the remote server, and sends a continuous delay instruction to the traffic light display terminal if the related personnel do not arrive at the accident site, so that the secondary traffic accident and accident site damage caused by normal driving of a vehicle when the related personnel do not arrive at the accident site are avoided, and if the related personnel arrive at the accident site, the green light switching control instruction is sent to the traffic light display terminal.
The traffic light display terminal receives the valley detection time period number and the corresponding motor vehicle green light shortening time length sent by the remote server, receives the peak detection time period number and the corresponding motor vehicle green light prolonging time length, and shortens or prolongs the green light passing time of the corresponding detection time period;
meanwhile, the traffic light display terminal receives the signal light transformation control command and the red light delay time point sent by the remote server, switches corresponding signal light operation, sends a delay arrival point early warning signal to the remote server when the red light delay time point reaches the calculated red light delay time point, and simultaneously receives the control command sent by the traffic control center, and continues to delay the red light or switches the red light to the green light operation.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (8)
1. The utility model provides an urban traffic intelligent monitoring coordination management system based on big data which characterized in that: the traffic flow monitoring and analyzing module is used for monitoring the traffic flow of a road intersection and dynamically adjusting the green light passing time of the intersection according to the real-time traffic flow, and the accident analyzing and processing module is used for monitoring image acquisition of traffic accidents occurring at the intersection and switching the traffic lights of the intersection to a specified red traffic light for display;
the remote server is respectively connected with the traffic flow monitoring and analyzing module and the accident analyzing and processing module, and the traffic light display terminal is respectively connected with the traffic flow monitoring and analyzing module and the accident analyzing and processing module;
traffic flow control analysis module includes traffic flow statistics module and actual traffic flow analysis module of passing, traffic flow statistics module includes the traffic flow detector, and it is installed at the intersection of urban road for the traffic flow parameter to this intersection vehicle is passed and is detected, and divides this intersection traffic flow parameter passed and passed according to predetermined detection time quantum that will detect, and each detection time quantum time interval is the same, constitutes detection time quantum traffic flow parameter set Cw(Cw1,Cw2,...,Cwt,...,Cwm)，Cwt is represented as w-th traffic flow parameter of t-th detection time period, w is represented as traffic flow parameter, and w is equal to wl,wv,wd，wl,wv,wdRespectively expressing the length, the speed and the distance between vehicles passing through the intersection, counting the traffic flow of each detection time period according to a traffic flow calculation formula, and sending the traffic flow to a remote server;
the actual traffic flow analysis module is used for acquiring the actual traffic time of the motor vehicle at the intersection at the green light, obtaining the average number of passing vehicles in the actual traffic time of the green light through calculation, further acquiring the actual traffic flow in a single detection time period, and sending the actual traffic flow in the single detection time period of the motor vehicle at the intersection to the remote server by the actual traffic flow analysis module;
the traffic database is used for storing accident object characteristics corresponding to various traffic accidents, wherein the various traffic accidents comprise human-vehicle accidents and vehicle accidents, the accident object characteristics corresponding to the human-vehicle accidents are pedestrians and vehicles, the accident object characteristics corresponding to the vehicle accidents are vehicles and vehicles, accident detail characteristics corresponding to different levels of traffic accidents of the various traffic accidents are stored, shortened time corresponding to each time shortening coefficient and prolonged time corresponding to each time prolonging coefficient are stored, and influence coefficients of peak and low valley detection time periods are stored;
the accident analysis processing module comprises an accident image monitoring and collecting module and an accident characteristic analysis module;
the accident image monitoring and collecting module comprises a high-definition camera and is used for carrying out real-time video monitoring on the pedestrian flow and the vehicle condition passing through the intersection, collecting the intersection image at the moment when a traffic accident occurs, recording the time point of the accident, carrying out focusing amplification treatment on the collected intersection image, sending the intersection image to the accident characteristic analysis module, and sending the time point of the accident to the remote server;
the accident feature analysis module receives the processed intersection image sent by the accident image monitoring and collecting module, extracts accident object features in the image, wherein the accident object features refer to whether an accident object is a pedestrian or a vehicle, the accident object features are roughly compared one by one with accident object features corresponding to various traffic accidents stored in a traffic database, the extracted features and the accident object features corresponding to various traffic accidents are counted, the traffic accident category with the highest similarity is screened, when the screened highest similarity is larger than a set similarity threshold value, the traffic accident category with the highest similarity is output as the category of the intersection accident, after the category of the intersection accident is determined, the intersection image is subjected to image segmentation processing to obtain an accident area image, the obtained accident area image is locally amplified to capture accident detail features, if the traffic accident belongs to a human-vehicle accident, the accident detail characteristics comprise the condition of pedestrian injury, the number of casualties and the condition of vehicle collision, if the traffic accident belongs to a vehicle accident, the accident detail characteristics comprise the number of accident vehicles, the distance between the vehicles and the condition of vehicle collision, the captured accident detail characteristics are matched with the accident detail characteristics corresponding to different levels of traffic accidents stored in a traffic database, the accident levels corresponding to the accident detail characteristics captured by the type of traffic accidents are screened and sent to a remote server;
the remote server receives the traffic flow of each detection time period and the actual traffic flow of each intersection motor vehicle in each detection time period sent by the traffic flow monitoring and analyzing module, compares the received actual traffic flow of each intersection motor vehicle in each detection time period with the traffic flow of each detection time period, if the actual traffic flow is greater than the traffic flow in a certain detection time period, the received actual traffic flow of each intersection motor vehicle in each detection time period indicates that the traffic flow in the detection time period is less, counts the detection time periods with the traffic flow less than the actual traffic flow, the number of the detection time periods is 1,2, 1, i, g, which is marked as a valley detection time period, carries out operation of shortening the green light traffic time, counts time shortening coefficients, extracts the shortening time corresponding to each time shortening coefficient in a traffic database, screens the shortening time corresponding to each valley detection time period, and sends the counted number of the valley detection time periods and the corresponding shortening time of the motor vehicle green light to a traffic light display The terminal is used for counting the time periods when the traffic flow is greater than the actual traffic flow, wherein the number is 1,2, a.
The remote server receives the accident grade and the accident occurrence time point sent by the accident analysis processing module and the geographical position of the intersection where the accident occurs sent by the GPS positioning module, and obtains the traffic light signal of the crossroad at the moment, if the traffic light signal of the crossroad at the moment is the red light, continuously keeping the red light on, if the traffic light signal at the intersection is a green light or a yellow light at the moment, sending a control instruction of switching the signal light into the red light to the traffic light display terminal, meanwhile, the red light estimated delay time is obtained through calculation according to the optimal navigation path from the traffic control center to the accident scene, which is sent by the distance tracking navigation module, calculating according to the time point of the accident to obtain the red light delay time point, and sending to the traffic light display terminal, receiving a delay arrival point early warning signal fed back by a traffic light display terminal, and sending the delay arrival point early warning signal to a traffic control center;
meanwhile, the remote server sends the accident grade of the accident and the geographical position of the intersection where the accident occurs to a traffic control center, and the traffic control center dispatches related personnel for processing;
the traffic light display terminal receives the valley detection time period number and the corresponding motor vehicle green light shortening time length sent by the remote server, receives the peak detection time period number and the corresponding motor vehicle green light prolonging time length, and shortens or prolongs the green light passing time of the corresponding detection time period;
meanwhile, the traffic light display terminal receives the signal light transformation control command and the red light delay time point sent by the remote server, switches corresponding signal light operation, sends a delay arrival point early warning signal to the remote server when the red light delay time point reaches the calculated red light delay time point, and simultaneously receives the control command sent by the traffic control center, and continues to delay the red light or switches the red light to the green light operation.
2. The intelligent monitoring and coordination management system for urban traffic based on big data according to claim 1, characterized in that: the traffic flow calculation formula
Where V is the speed of the vehicle, L is the body length of the vehicle, S is the inter-vehicle distance, and Δ T is the individual detection period duration.
3. The intelligent monitoring and coordination management system for urban traffic based on big data according to claim 1, characterized in that: the calculation formula of the average number of vehicles capable of passing through in the actual passing time of the green light of the motor vehicle at the intersection is
TFruit of Chinese wolfberryThe actual passing time of the green light of the motor vehicle at the intersection is represented, D is the intersection distance,
expressed as the average body length of the vehicle leading to the intersection,
the average speed of the vehicle passing through the intersection is shown, and K is the number of bidirectional lanes at the intersection.
4. The intelligent monitoring and coordination management system for urban traffic based on big data according to claim 1, characterized in that: the calculation formula of the actual traffic flow in a single detection time period is
Δ T is expressed as a single detection period duration, TFruit of Chinese wolfberryThe actual passing time of the motor vehicle green light at the intersection is represented, and R is the average number of vehicles capable of passing through the actual passing time of the motor vehicle green light at the intersection.
5. The intelligent monitoring and coordination management system for urban traffic based on big data according to claim 1, characterized in that: the time shortening coefficient is calculated by the formula
ξi shrinkTime reduction coefficient, Q, expressed as the ith valley detection periodFruit of Chinese wolfberryExpressed as actual traffic flow, Q, for a single detection periodiTraffic flow, λ, expressed as the ith valley detection periodIs low inExpressed as a valley detection time period influence coefficient, the time delay coefficient is calculated by
ξYanExpressed as the time extension factor, Q, of the ith peak detection periodjTraffic flow, λ, expressed as the jth valley detection periodHeight ofExpressed as a peak detection time period impact coefficient.
6. The intelligent monitoring and coordination management system for urban traffic based on big data according to claim 1, characterized in that: the system also comprises a GPS positioning module which is used for acquiring the geographical position information of the intersection and sending the information to the remote server.
7. The intelligent monitoring and coordination management system for urban traffic based on big data according to claim 1, characterized in that: the system also comprises a traffic control center which is respectively connected with the remote server and the distance tracking navigation module, receives the accident grade sent by the remote server, the geographical position of the intersection where the accident occurs and the optimal navigation path sent by the distance tracking navigation module, takes different measures according to the accident grade, dispatches related personnel to process according to the optimal navigation path, receives the early warning signal of the delay arrival point sent by the remote server, sends a continuous delay instruction to the traffic light display terminal if the related personnel do not arrive at the accident site at the moment, and sends a green light switching control instruction to the traffic light display terminal if the related personnel arrive at the accident site at the moment.
8. The intelligent monitoring and coordination management system for urban traffic based on big data according to claim 1, characterized in that: the system also comprises a distance tracking navigation module which is connected with the GPS positioning module and used for acquiring the position information of the traffic control center, comparing the geographical position of the intersection where the accident occurs, which is sent by the GPS positioning module, with the position information of the traffic control center, providing the optimal navigation path and sending the optimal navigation path to the traffic control center.
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