CN116721550A - Traffic management system based on grid computing - Google Patents
Traffic management system based on grid computing Download PDFInfo
- Publication number
- CN116721550A CN116721550A CN202311000753.8A CN202311000753A CN116721550A CN 116721550 A CN116721550 A CN 116721550A CN 202311000753 A CN202311000753 A CN 202311000753A CN 116721550 A CN116721550 A CN 116721550A
- Authority
- CN
- China
- Prior art keywords
- traffic
- traffic management
- area
- expressed
- monitoring
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000011156 evaluation Methods 0.000 claims abstract description 51
- 230000010365 information processing Effects 0.000 claims abstract description 15
- 238000007781 pre-processing Methods 0.000 claims abstract description 15
- 238000004458 analytical method Methods 0.000 claims abstract description 11
- 238000012544 monitoring process Methods 0.000 claims description 76
- 206010039203 Road traffic accident Diseases 0.000 claims description 36
- 238000004364 calculation method Methods 0.000 claims description 12
- 238000000034 method Methods 0.000 claims description 11
- 230000002159 abnormal effect Effects 0.000 claims description 9
- 238000012937 correction Methods 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 5
- 238000013461 design Methods 0.000 description 7
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/53—Recognition of crowd images, e.g. recognition of crowd congestion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- Chemical & Material Sciences (AREA)
- Multimedia (AREA)
- Analytical Chemistry (AREA)
- Tourism & Hospitality (AREA)
- Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Data Mining & Analysis (AREA)
- Educational Administration (AREA)
- General Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Primary Health Care (AREA)
- Marketing (AREA)
- Remote Sensing (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Quality & Reliability (AREA)
- Development Economics (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Human Computer Interaction (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a traffic management system based on grid computing, which particularly relates to the traffic field, and comprises a traffic management area dividing module, a traffic management information acquisition module, a traffic management information preprocessing module, a traffic management information processing module, a traffic control early warning module, a traffic information analysis module, a traffic information evaluation module and a traffic information database module.
Description
Technical Field
The invention relates to the technical field of traffic, in particular to a traffic management system based on grid computing.
Background
With the rapid development of traffic and modern information technology, the traffic management system of grid computing is widely supported, the traffic management of grid computing is a mode for intelligently managing traffic through distributed computing resources, traffic data of each grid area is monitored, analyzed and predicted in real time by dividing the traffic area into a series of grid areas, intelligent and modern development of the traffic management system is promoted, traffic pressure is relieved, and traffic efficiency is improved.
However, when the system is actually used, the system still has some defects, such as the traditional manual recording mode of acquiring data by the current traffic management system, the problems of large data collection amount, complex data processing and high data error rate exist in the mode, and meanwhile, due to the reasons of failure of acquisition equipment and the like, the real-time updating of the data is slow, so that the traffic management efficiency is low;
the existing traffic management system, especially the urban public transportation system, is often formed by combining single subsystems, the subsystems lack of effective integration after respectively analyzing data information in traffic operation, a unified assessment mechanism is not available, and the whole system lacks intellectualization, so that the capabilities of autonomous decision making and intelligent management are reduced, and accurate management and adjustment are difficult to make.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an embodiment of the present invention provides a traffic management system based on grid computing, which is used for solving the above-mentioned problems set forth in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
traffic management area dividing module: the method is used for dividing the target traffic management area into monitoring subareas according to an equal port division mode, and marking the monitoring subareas of the target traffic management area as 1 and 2 … … n in sequence.
Traffic management information acquisition module: the method is used for collecting state parameter values of all monitoring subareas of the target traffic management area.
The traffic management information acquisition module comprises a traffic road accident acquisition unit and a traffic road flow acquisition unit.
Traffic management information preprocessing module: the traffic accident rate is calculated by the number of traffic accident occurrences and the total number of similar accident occurrences of each monitoring subarea of the target traffic management area, the transit time weight is calculated by the transit time of each monitoring subarea of the target traffic management area, the population density is calculated by the traffic flow and the geographic area of the monitoring area, and the vehicle density is calculated by the traffic flow and the road length of the monitoring area.
Traffic management information processing module: the traffic management information preprocessing module is used for receiving the data information transmitted by the traffic management information preprocessing module, calculating to obtain a traffic road accident occurrence index according to the traffic accident occurrence rate and the traffic time weight, and calculating to obtain a traffic road safety traffic index according to population density and vehicle density.
Traffic control early warning module: and the system is used for extracting the traffic road safety traffic indexes of each monitoring subarea of the target traffic management area to obtain traffic road safety traffic early warning indexes, and carrying out corresponding treatment measures after comparison and analysis.
Traffic information analysis module: the traffic management information processing module is used for receiving the data information transmitted by the traffic management information processing module and calculating to obtain a traffic management safety evaluation coefficient through the traffic road accident occurrence index and the traffic road safety passage index.
Traffic information assessment module: the traffic management safety evaluation system is used for acquiring traffic management safety evaluation coefficients of all monitoring subareas of the target traffic management area, comparing the traffic management safety evaluation coefficients with preset traffic management safety evaluation coefficients, and carrying out corresponding treatment measures according to the results.
Traffic information database module: the method is used for storing the geographic area of each monitoring subarea of the target traffic management area, the road length of the traffic junction area and the historical traffic management safety evaluation coefficient.
Preferably, the specific division mode of the traffic management area division module is as follows:
the population distribution of the traffic management area is acquired, the traffic management area is determined to be a target area, the target area is divided into n monitoring subareas according to an equal mouth dividing mode, and all the monitoring subareas of the target traffic management area are marked as 1 and 2 … … n in sequence.
Preferably, the specific collection mode of the traffic management information collection module is as follows:
traffic road accident acquisition unit: collecting the traffic accident occurrence times, the total occurrence times of similar accidents and the passing time of each monitoring subarea of the target traffic management area, and respectively marking as、/>、/>Where i=1, 2 … … n, i denotes the i-th monitoring subregion number.
Traffic flow collection unit: the method comprises the steps of arranging a camera and a road sensor in a traffic junction area, collecting on-site images of the traffic junction area through the camera, carrying out face recognition to collect the traffic flow of each monitoring subarea of a target traffic management area, and collecting the traffic flow of each monitoring subarea of the target traffic management area through the sensor arranged on a road, wherein the traffic flow is respectively marked as、/>Where i=1, 2 … … n, i denotes the i-th monitoring subregion number.
Preferably, the traffic management information preprocessing module specifically includes:
substituting the number of traffic accidents and the total number of similar accidents into a formula:
wherein->Expressed as the occurrence rate of traffic accidents, gc as the occurrence number of traffic accidents, gz as the total occurrence number of similar accidents,/->A correction factor expressed as a traffic accident occurrence rate.
Substituting the transit time into the formula:
kt=where kt is denoted as transit time weight, +.>The calculation formula of k is as follows: />=/>*100%。
Substituting the traffic and the geographic area into the formula:
LP=wherein LP is expressed as population density, ">Expressed as flow of people, < >>Represented as a geographic area of the earth,expressed as a correction factor for population density.
Substituting the traffic flow and the road length into the formula:
LC=LC is denoted as vehicle density, LC is denoted as vehicle flow,/->Expressed as road length>A correction factor expressed as a vehicle density.
Preferably, the specific processing mode of the traffic management information processing module is as follows:
the calculation formula of the traffic road accident occurrence index is as follows:
+/>wherein->Expressed as traffic road accident occurrence index +.>Expressed as traffic accident occurrence->Denoted as preset traffic accident occurrence rate, kt denoted as transit time weight,/->Expressed as preset transit time weight, +.>、/>Other influencing factors respectively expressed as the occurrence rate of traffic accidents and the passing time weight.
The calculation formula of the traffic road safety passage index is as follows:
wherein->Represented as a traffic road safety traffic index,expressed as the density of the mouth->Expressed as a preset population density->Expressed as vehicle density>Expressed as preset vehicle density +.>、/>Expressed as other influencing factors of the person's mouth density, vehicle density, respectively.
Preferably, the traffic control early warning module specifically comprises:
extracting traffic road safety traffic indexes of all monitoring subareas of the target traffic management area to obtain a traffic road safety traffic early warning index formula:=/>and if the traffic road safety traffic early warning index of each monitoring subarea of the target traffic management area is larger than the preset traffic road safety traffic early warning index, indicating that each monitoring subarea of the target traffic management area needs to conduct traffic control, sending a traffic supervision instruction to a traffic management center.
Preferably, the calculation formula of the traffic management security evaluation coefficient is as follows:
wherein->Expressed as traffic management security assessment factor, +.>Expressed as traffic road accident occurrence index +.>Expressed as a traffic road safety traffic index.
The method comprises the following steps:。
preferably, the specific evaluation mode of the traffic information evaluation module is as follows:
acquiring traffic management safety evaluation coefficients of all monitoring subareas of the target traffic management area, comparing the traffic management safety evaluation coefficients with preset traffic management safety evaluation coefficients, if the traffic management safety evaluation coefficients are larger than the preset traffic management safety evaluation coefficients, indicating that abnormal states exist in traffic management of a certain monitoring subarea of the target traffic management area, immediately informing corresponding management personnel to perform early warning, and otherwise, indicating that abnormal conditions exist in traffic management of a certain monitoring subarea of the target traffic management area.
The invention has the technical effects and advantages that:
1. the invention provides a traffic management system based on grid computing, which is characterized in that a camera and a road sensor are arranged in a traffic junction area, the camera acquires on-site images of the traffic junction area, face recognition is carried out to acquire the traffic flow of each monitoring subarea of a target traffic management area, the sensor acquires the traffic flow, the number of times of traffic accidents, the total number of times of similar accidents and the traffic time of each monitoring subarea of the target traffic management area are acquired, the data are processed and analyzed to obtain a traffic road accident index and a traffic road safety traffic index, the traffic management safety evaluation coefficient is further analyzed and obtained, corresponding processing measures are carried out after the comparison and analysis, the autonomous decision and intelligent management capability of traffic are realized, a manager is helped to acquire the latest data by a real-time monitoring system, and the corresponding adjustment is carried out, so that the traffic management efficiency is improved.
Drawings
Fig. 1 is a schematic diagram of a system module connection according to the present invention.
Fig. 2 is a schematic diagram of a traffic management information collection module according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a traffic management system based on grid computing, which comprises a traffic management area dividing module, a traffic management information acquisition module, a traffic management information preprocessing module, a traffic management information processing module, a traffic control early warning module, a traffic information analysis module, a traffic information evaluation module and a traffic information database module.
The traffic management area dividing module is connected with the traffic management information acquisition module, the traffic management information acquisition module is connected with the traffic management information preprocessing module, the traffic management information preprocessing module is connected with the traffic management information processing module, the traffic management information processing module is connected with the traffic control early warning module and the traffic information analysis module, the traffic information analysis module is connected with the traffic information evaluation module, the traffic information evaluation module is connected with the traffic information database module, and the traffic control early warning module is connected with the traffic information database module.
The traffic management area dividing module is used for dividing the target traffic management area into monitoring subareas according to an equal-mouth dividing mode, and marking the monitoring subareas of the target traffic management area as 1 and 2 … … n in sequence.
In one possible design, the specific division manner of the traffic management area division module is as follows:
the population distribution of the traffic management area is acquired, the traffic management area is determined to be a target area, the target area is divided into n monitoring subareas according to an equal mouth dividing mode, and all the monitoring subareas of the target traffic management area are marked as 1 and 2 … … n in sequence.
The traffic management information acquisition module is used for acquiring state parameter values of all monitoring subareas of the target traffic management area.
Referring to fig. 2, the traffic management information collecting module includes a traffic road accident collecting unit and a traffic road flow collecting unit.
In one possible design, the specific collection mode of the traffic management information collection module is as follows:
the traffic road accident acquisition unit acquires the traffic accident occurrence times, the total occurrence times of similar accidents and the passing time of each monitoring subarea of the target traffic management area, and marks the traffic accident occurrence times, the total occurrence times of similar accidents and the passing time as、/>、/>Where i=1, 2 … … n,i is denoted as the i-th monitoring subregion number.
The traffic road flow acquisition unit is provided with a camera and a road sensor in the traffic junction area, acquires on-site images of the traffic junction area through the camera, acquires the traffic flow of each monitoring subarea of the target traffic management area through face recognition, acquires the traffic flow of each monitoring subarea of the target traffic management area through the sensor arranged on the road, and marks the traffic flow as follows respectively、/>Where i=1, 2 … … n, i denotes the i-th monitoring subregion number.
The traffic management information preprocessing module is used for receiving the data information transmitted by the traffic management information acquisition module, eliminating abnormal values in the data, calculating the traffic accident occurrence rate through the traffic accident occurrence times of all monitoring subareas of the target traffic management area and the total times of similar accident occurrences, calculating the traffic time weight through the traffic time of all monitoring subareas of the target traffic management area, calculating population density through the traffic flow of the monitoring area and the geographic area, and calculating the vehicle density through the traffic flow of the monitoring area and the road length.
In one possible design, the traffic management information preprocessing module specifically includes:
substituting the number of traffic accidents and the total number of similar accidents into a formula:
wherein->Expressed as the occurrence rate of traffic accidents, gc as the occurrence number of traffic accidents, gz as the total occurrence number of similar accidents,/->Repair expressed as incidence of traffic accidentPositive factors.
Substituting the transit time into the formula:
kt=where kt is denoted as transit time weight, +.>The calculation formula of k is as follows: />=/>*100%。
Substituting the traffic and the geographic area into the formula:
LP=wherein LP is expressed as population density, ">Expressed as flow of people, < >>Represented as a geographic area of the earth,expressed as a correction factor for population density.
Substituting the traffic flow and the road length into the formula:
LC=LC is denoted as vehicle density, LC is denoted as vehicle flow,/->Expressed as road length>A correction factor expressed as a vehicle density.
The traffic management information processing module is used for receiving the data information transmitted by the traffic management information preprocessing module, calculating to obtain a traffic road accident index according to the traffic accident rate and the passing time weight, and calculating to obtain a traffic road safety passing index according to the population density and the vehicle density.
In one possible design, the specific processing manner of the traffic management information processing module is as follows:
the calculation formula of the traffic road accident occurrence index is as follows:
+/>wherein->Expressed as traffic road accident occurrence index +.>Expressed as traffic accident occurrence->Denoted as preset traffic accident occurrence rate, kt denoted as transit time weight,/->Expressed as preset transit time weight, +.>、/>Other influencing factors respectively expressed as the occurrence rate of traffic accidents and the passing time weight.
The calculation formula of the traffic road safety passage index is as follows:
wherein->Represented as a traffic road safety traffic index,expressed as the density of the mouth->Expressed as a preset population density->Expressed as vehicle density>Expressed as preset vehicle density +.>、/>Expressed as other influencing factors of the person's mouth density, vehicle density, respectively.
The traffic control early warning module is used for extracting traffic road safety traffic indexes of all monitoring subareas of the target traffic management area to obtain traffic road safety traffic early warning indexes, and performing corresponding treatment measures after comparison and analysis.
In one possible design, the traffic control early warning module specifically includes:
extracting traffic road safety traffic indexes of all monitoring subareas of the target traffic management area to obtain a traffic road safety traffic early warning index formula:=/>if the traffic road safety traffic early warning index of each monitoring subarea of the target traffic management area is larger than the preset traffic road safety traffic early warning index, indicating that each monitoring subarea of the target traffic management area needs to conduct traffic control, sending out trafficAnd supervising the instruction to the traffic management center.
The traffic information analysis module is used for receiving the data information transmitted by the traffic management information processing module and calculating to obtain a traffic management safety evaluation coefficient through the traffic road accident index and the traffic road safety traffic index.
In one possible design, the calculation formula of the traffic management security assessment coefficient is:
wherein->Expressed as traffic management security assessment factor, +.>Expressed as traffic road accident occurrence index +.>Expressed as a traffic road safety traffic index.
The method comprises the following steps:。
the traffic information evaluation module is used for acquiring traffic management safety evaluation coefficients of all monitoring subareas of the target traffic management area, comparing the traffic management safety evaluation coefficients with preset traffic management safety evaluation coefficients, and carrying out corresponding treatment measures according to the results.
In one possible design, the specific evaluation manner of the traffic information evaluation module is as follows:
acquiring traffic management safety evaluation coefficients of all monitoring subareas of the target traffic management area, comparing the traffic management safety evaluation coefficients with preset traffic management safety evaluation coefficients, if the traffic management safety evaluation coefficients are larger than the preset traffic management safety evaluation coefficients, indicating that abnormal states exist in traffic management of a certain monitoring subarea of the target traffic management area, immediately informing corresponding management personnel to perform early warning, and otherwise, indicating that abnormal conditions exist in traffic management of a certain monitoring subarea of the target traffic management area.
The traffic information database module is used for storing the geographic area of each monitoring subarea of the target traffic management area, the road length of the traffic junction area and the historical traffic management safety evaluation coefficient.
In this embodiment, it needs to be specifically explained that, the camera collects the field image of the traffic junction area through the camera and the road sensor installed in the traffic junction area, and performs face recognition to collect the traffic flow of each monitoring subarea of the target traffic management area, and collects the traffic flow through the sensor installed on the road, collects the number of times of traffic accidents, the total number of times of similar accidents and the passing time of each monitoring subarea of the target traffic management area, processes the data, analyzes the data to obtain the traffic accident occurrence index and the traffic road safety pass index, further analyzes the data to obtain the traffic management safety evaluation coefficient, compares the traffic management safety evaluation coefficient with the preset traffic management safety evaluation coefficient, if the traffic management safety evaluation coefficient is greater than the preset traffic management safety evaluation coefficient, it indicates that the traffic management of a certain monitoring subarea of the target traffic management area has abnormal state, and immediately notifies corresponding management personnel to perform early warning, thereby realizing the capability of autonomous decision and intelligent management of traffic, helping the manager to obtain the latest data and make corresponding adjustment by the real-time monitoring system of the manager, and improving the traffic management efficiency.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. A traffic management system based on grid computing, comprising:
traffic management area dividing module: dividing the target traffic management area into monitoring subareas according to an equal-mouth dividing mode, and marking the monitoring subareas of the target traffic management area as 1 and 2 … … n in sequence;
traffic management information acquisition module: the system is used for collecting state parameter values of all monitoring subareas of the target traffic management area;
the traffic management information acquisition module comprises a traffic road accident acquisition unit and a traffic road flow acquisition unit;
traffic management information preprocessing module: the traffic management information acquisition module is used for receiving the data information transmitted by the traffic management information acquisition module, eliminating abnormal values in the data, calculating the traffic accident occurrence rate according to the traffic accident occurrence times of all monitoring subareas of the target traffic management area and the total number of similar accident occurrence times, calculating the passing time weight according to the passing time of all monitoring subareas of the target traffic management area, calculating population density according to the traffic flow of the monitoring area and the geographic area, and calculating the vehicle density according to the traffic flow of the monitoring area and the road length;
traffic management information processing module: the traffic management information preprocessing module is used for receiving the data information transmitted by the traffic management information preprocessing module, calculating to obtain a traffic road accident occurrence index according to the traffic accident occurrence rate and the traffic time weight, and calculating to obtain a traffic road safety traffic index according to population density and vehicle density;
traffic control early warning module: the method comprises the steps of extracting traffic road safety traffic indexes of all monitoring subareas of a target traffic management area, obtaining traffic road safety traffic early warning indexes, and carrying out corresponding treatment measures after comparison analysis;
traffic information analysis module: the traffic management information processing module is used for receiving the data information transmitted by the traffic management information processing module and calculating to obtain a traffic management safety evaluation coefficient through the traffic road accident occurrence index and the traffic road safety traffic index;
traffic information assessment module: the traffic management safety evaluation system is used for acquiring traffic management safety evaluation coefficients of all monitoring subareas of the target traffic management area, comparing the traffic management safety evaluation coefficients with preset traffic management safety evaluation coefficients and carrying out corresponding treatment measures according to the results;
traffic information database module: the method is used for storing the geographic area of each monitoring subarea of the target traffic management area, the road length of the traffic junction area and the historical traffic management safety evaluation coefficient.
2. The grid computing-based traffic management system of claim 1, wherein: the specific division mode of the traffic management area division module is as follows:
the population distribution of the traffic management area is acquired, the traffic management area is determined to be a target area, the target area is divided into n monitoring subareas according to an equal mouth dividing mode, and all the monitoring subareas of the target traffic management area are marked as 1 and 2 … … n in sequence.
3. The grid computing-based traffic management system of claim 1, wherein: the specific acquisition mode of the traffic management information acquisition module is as follows:
traffic road accident acquisition unit: collecting the traffic accident occurrence times, the total occurrence times of similar accidents and the passing time of each monitoring subarea of the target traffic management area, and respectively marking as、/>、/>Where i=1, 2 … … n, i is denoted as the i-th monitoring subregion number;
traffic flow collection unit: the method comprises the steps of arranging a camera and a road sensor in a traffic junction area, collecting on-site images of the traffic junction area through the camera, carrying out face recognition to collect the traffic flow of each monitoring subarea of a target traffic management area, and collecting the traffic flow of each monitoring subarea of the target traffic management area through the sensor arranged on a road, wherein the traffic flow is respectively marked as、/>Where i=1, 2 … … n, i denotes the i-th monitoring subregion number.
4. The grid computing-based traffic management system of claim 1, wherein: the traffic management information preprocessing module specifically comprises:
substituting the number of traffic accidents and the total number of similar accidents into a formula:
wherein->Expressed as the occurrence rate of traffic accidents, gc as the occurrence number of traffic accidents, gz as the total occurrence number of similar accidents,/->A correction factor expressed as a traffic accident occurrence rate;
substituting the transit time into the formula:
kt=where kt is denoted as transit time weight, +.>The calculation formula of k is as follows: />=/>*100%;
Substituting the traffic and the geographic area into the formula:
LP=wherein LP representsFor population density->Expressed as flow of people, < >>Expressed as geographical area>A correction factor expressed as a population density;
substituting the traffic flow and the road length into the formula:
LC=LC is denoted as vehicle density, LC is denoted as vehicle flow,/->Expressed as road length>A correction factor expressed as a vehicle density.
5. The grid computing-based traffic management system of claim 1, wherein: the specific processing mode of the traffic management information processing module is as follows:
the calculation formula of the traffic road accident occurrence index is as follows:
+/>wherein->Expressed as traffic road accident occurrence index +.>Expressed as traffic accident occurrence->Denoted as preset traffic accident occurrence rate, kt denoted as transit time weight,/->Expressed as preset transit time weight, +.>、/>Other influencing factors respectively expressed as traffic accident occurrence rate and transit time weight;
the calculation formula of the traffic road safety passage index is as follows:
wherein->Expressed as traffic road safety traffic index +.>Expressed as the density of the mouth->Expressed as a preset population density->Expressed as vehicle density>Expressed as preset vehicle density +.>、/>Expressed as other influencing factors of the person's mouth density, vehicle density, respectively.
6. The grid computing-based traffic management system of claim 1, wherein: the traffic control early warning module specifically comprises:
extracting traffic road safety traffic indexes of all monitoring subareas of the target traffic management area to obtain a traffic road safety traffic early warning index formula:=/>and if the traffic road safety traffic early warning index of each monitoring subarea of the target traffic management area is larger than the preset traffic road safety traffic early warning index, indicating that each monitoring subarea of the target traffic management area needs to conduct traffic control, sending a traffic supervision instruction to a traffic management center.
7. The grid computing-based traffic management system of claim 1, wherein: the calculation formula of the traffic management safety evaluation coefficient is as follows:
wherein->Expressed as traffic management security assessment factor, +.>Expressed as traffic road accident occurrence index +.>Expressed as a traffic road safety traffic index;
the method comprises the following steps:。
8. the grid computing-based traffic management system of claim 1, wherein: the specific evaluation mode of the traffic information evaluation module is as follows:
acquiring traffic management safety evaluation coefficients of all monitoring subareas of the target traffic management area, comparing the traffic management safety evaluation coefficients with preset traffic management safety evaluation coefficients, if the traffic management safety evaluation coefficients are larger than the preset traffic management safety evaluation coefficients, indicating that abnormal states exist in traffic management of a certain monitoring subarea of the target traffic management area, immediately informing corresponding management personnel to perform early warning, and otherwise, indicating that abnormal conditions exist in traffic management of a certain monitoring subarea of the target traffic management area.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311000753.8A CN116721550B (en) | 2023-08-10 | 2023-08-10 | Traffic management system based on grid computing |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311000753.8A CN116721550B (en) | 2023-08-10 | 2023-08-10 | Traffic management system based on grid computing |
Publications (2)
Publication Number | Publication Date |
---|---|
CN116721550A true CN116721550A (en) | 2023-09-08 |
CN116721550B CN116721550B (en) | 2023-10-24 |
Family
ID=87870144
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202311000753.8A Active CN116721550B (en) | 2023-08-10 | 2023-08-10 | Traffic management system based on grid computing |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN116721550B (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117475646A (en) * | 2023-10-06 | 2024-01-30 | 纬创软件(武汉)有限公司 | Pedestrian detection method based on artificial intelligence |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101714298A (en) * | 2009-10-30 | 2010-05-26 | 北京工业大学 | Method for calculating urban crossroad mixed traffic order degree |
WO2010058058A1 (en) * | 2008-11-18 | 2010-05-27 | 4Destia Oy | Arrangement and related method for analysing and controlling traffic conditions at borders |
CA3016825A1 (en) * | 2017-09-15 | 2019-03-15 | Sergio Machado Goncalves | Predictive, integrated and intelligent system for control of times in traffic lights |
CN110633558A (en) * | 2019-11-05 | 2019-12-31 | 贵州财经大学 | Urban traffic system modeling system |
CN113808399A (en) * | 2021-09-15 | 2021-12-17 | 谦亨信息化技术与***(苏州)有限公司 | Intelligent traffic management method and system based on big data |
CN114973661A (en) * | 2022-05-16 | 2022-08-30 | 深圳市中建恒峰电子有限公司 | Traffic signal lamp with intelligent control and traffic flow data storage functions |
CN115497301A (en) * | 2022-11-21 | 2022-12-20 | 深圳市城市交通规划设计研究中心股份有限公司 | Evaluation method of traffic organization optimization scheme, electronic device and storage medium |
WO2023098076A1 (en) * | 2021-12-03 | 2023-06-08 | 东南大学 | Multidimensional influence factor-based road safety evaluation method and system |
CN116560325A (en) * | 2023-06-08 | 2023-08-08 | 河南开扩智能科技有限公司 | Data acquisition management system and management method based on Internet intelligent gateway |
-
2023
- 2023-08-10 CN CN202311000753.8A patent/CN116721550B/en active Active
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2010058058A1 (en) * | 2008-11-18 | 2010-05-27 | 4Destia Oy | Arrangement and related method for analysing and controlling traffic conditions at borders |
CN101714298A (en) * | 2009-10-30 | 2010-05-26 | 北京工业大学 | Method for calculating urban crossroad mixed traffic order degree |
CA3016825A1 (en) * | 2017-09-15 | 2019-03-15 | Sergio Machado Goncalves | Predictive, integrated and intelligent system for control of times in traffic lights |
CN110633558A (en) * | 2019-11-05 | 2019-12-31 | 贵州财经大学 | Urban traffic system modeling system |
CN113808399A (en) * | 2021-09-15 | 2021-12-17 | 谦亨信息化技术与***(苏州)有限公司 | Intelligent traffic management method and system based on big data |
WO2023098076A1 (en) * | 2021-12-03 | 2023-06-08 | 东南大学 | Multidimensional influence factor-based road safety evaluation method and system |
CN114973661A (en) * | 2022-05-16 | 2022-08-30 | 深圳市中建恒峰电子有限公司 | Traffic signal lamp with intelligent control and traffic flow data storage functions |
CN115497301A (en) * | 2022-11-21 | 2022-12-20 | 深圳市城市交通规划设计研究中心股份有限公司 | Evaluation method of traffic organization optimization scheme, electronic device and storage medium |
CN116560325A (en) * | 2023-06-08 | 2023-08-08 | 河南开扩智能科技有限公司 | Data acquisition management system and management method based on Internet intelligent gateway |
Non-Patent Citations (6)
Title |
---|
ANURAG KANUNGO: "Smart traffic lights switching and traffic density calculation using video processing", 2014 RECENT ADVANCES IN ENGINEERING AND COMPUTATIONAL SCIENCES (RAECS), pages 1 - 6 * |
吴俊杰: "从风险预测到风险溯源:大数据赋能城市安全管理的行动设计研究", 管理世界, vol. 36, no. 08, pages 189 - 202 * |
李淑庆;彭囿朗;肖莉英;孟思梦;王鹏;徐继鹏: "道路交通事故发生机理研究现状与趋势分析", 安全与环境学报, no. 003, pages 14 - 19 * |
王鹏;卢小钊;闫章存;张敏捷: "基于Ordered Probit模型的追尾事故严重性影响因素分析", 公路交通科技, no. 004, pages 102 - 107 * |
胡少帅: "区域道路交通安全云模型-模糊综合评判研究", 公路与汽运, pages 26 - 29 * |
胡峰;张玉姗;王怀御;牛妍;: "基于Floyd算法下小区开放对道路通行的研究", 电子测试, no. 16, pages 53 - 54 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117475646A (en) * | 2023-10-06 | 2024-01-30 | 纬创软件(武汉)有限公司 | Pedestrian detection method based on artificial intelligence |
CN117475646B (en) * | 2023-10-06 | 2024-03-29 | 纬创软件(武汉)有限公司 | Pedestrian detection method based on artificial intelligence |
Also Published As
Publication number | Publication date |
---|---|
CN116721550B (en) | 2023-10-24 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN116721550B (en) | Traffic management system based on grid computing | |
CN101882374A (en) | System and method for analysis of comprehensive information on vehicle trip distribution | |
CN116631186B (en) | Expressway traffic accident risk assessment method and system based on dangerous driving event data | |
CN112134871A (en) | Abnormal flow detection device and method for energy internet information support network | |
CN117746626A (en) | Intelligent traffic management method and system based on traffic flow | |
CN117935561B (en) | Intelligent traffic flow analysis method based on Beidou data | |
CN210865032U (en) | Urban waterlogging monitoring and early warning system | |
CN117314709A (en) | Intelligent monitoring system for sewage treatment progress | |
CN210183356U (en) | Sponge city rainstorm detection early warning system | |
CN115585731A (en) | Space-air-ground integrated hydropower station space state intelligent monitoring management system and method thereof | |
CN117291551B (en) | Environmental monitoring early warning system based on digital visualization | |
CN114565210A (en) | Urban rail transit risk assessment method and system based on fault tree analysis | |
CN117475608A (en) | Multi-scene security monitoring method based on unmanned aerial vehicle cluster | |
CN110060370B (en) | Equivalent statistical method for times of rapid acceleration and rapid deceleration of vehicle | |
CN116895134A (en) | Hydropower station downstream water level sudden rise early warning method and system based on 5G technology | |
CN116625324A (en) | Water conservancy monitoring method based on digital twinning | |
CN113137983B (en) | Self-learning well lid posture monitoring method and monitoring system | |
CN112529366A (en) | Remote engineering supervision and coordination management and control system based on machine vision | |
CN112032567A (en) | Buried gas pipeline leakage risk prediction system | |
CN113361730A (en) | Risk early warning method, device, equipment and medium for maintenance plan | |
CN117827990B (en) | Data processing method and system suitable for hydraulic engineering | |
CN111932877A (en) | Road section traffic abnormal state identification method based on license plate data | |
CN114879784A (en) | Big data real-time monitoring system and method | |
CN117173899B (en) | Smart city traffic travel quality evaluation method | |
CN111860997B (en) | Cross-data, information, knowledge modality and dimension early warning method and component |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |