Traffic management platform data collection method and system

Abstract

The invention is suitable for the technical field of data collection, and particularly relates to a traffic management platform data collection method and system, and the method comprises the steps: S100, delimiting a data collection region of a traffic management platform, marking a traffic light intersection, numbering the traffic light intersection, determining an identifier of each one-way road segment according to the number, and storing the identifier of each one-way road segment; and creating a plurality of blocks in one-to-one correspondence with the one-way road sections, and synchronizing the identifiers to the corresponding blocks. The traffic flow of each one-way road section can be collected and monitored in real time by determining the video monitoring equipment, the traffic management efficiency is greatly improved, the data collection accuracy can be ensured and the data processing amount can be reduced by clustering the plurality of blocks, and the abnormal blocks are processed by using the audio equipment, so that the traffic management efficiency is improved. Multi-source data can be fused, visual dependence is reduced, the adaptability of video monitoring equipment in severe weather is enhanced, and the accuracy of data collection is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data collection, and in particular to a method and system for collecting data on a traffic management platform. Background Art

[0002] Data collection on a traffic management platform refers to the process of acquiring real-time and historical data related to urban traffic through various channels and devices, thereby providing data support for traffic monitoring, scheduling, optimization and planning; for example, using traffic control cameras installed on major roads and expressways to collect vehicle data and calculate real-time traffic data to optimize traffic light timing and provide data support for monitoring violations.

[0003] However, in bad weather such as rain or snow, traffic control cameras are prone to misjudgment, misjudging congested sections of road as smooth traffic, or taking the wrong photos or missing photos, which in turn affects the control efficiency of the traffic management platform and reduces the public's travel experience. Therefore, "how to use audio data to improve the recognition accuracy of traffic control cameras in bad weather" is a technical problem that needs to be solved by the present invention. Summary of the invention

[0004] The purpose of the present invention is to provide a traffic management platform data collection method and system to solve the problem of "how to use audio data to improve the recognition accuracy of traffic control cameras in bad weather" raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for collecting data from a traffic management platform, the method comprising:

[0007] S100: Delineating a data collection area of ​​a traffic management platform, marking traffic light intersections, numbering the traffic light intersections, and determining an identifier of each one-way road section according to the number, creating a number block corresponding to the one-way road section, and synchronizing the identifier to the corresponding number block;

[0008] S200: Obtaining the deployment position of the collection equipment in the data collection area, wherein each one-way road section corresponds to at least one collection equipment, and the collection equipment at least includes: a video monitoring device, through which the video monitoring device is used to collect the video monitoring data of the one-way road section, extract the traffic characteristics, and upload the traffic characteristics to the corresponding digital blocks, extract a number of snapshots from the video monitoring data, calculate the fuzzy value of each snapshot by using an image fuzziness detection algorithm, configure the corresponding relationship between the digital blocks and the fuzzy values, cluster the digital blocks into standard blocks and abnormal blocks based on the fuzzy values, and calculate the traffic flow of each standard block by using the traffic characteristics in the standard blocks;

[0009] S300: defining the video surveillance device corresponding to the abnormal block as a target device, obtaining data collection authority of the audio device pre-integrated in the target device, collecting audio data of the one-way road section corresponding to the abnormal block, pre-processing the audio data to obtain background noise, wherein the background noise is: the sound of vehicle tires in rain and snow, and extracting fuzzy features from the abnormal block, using the background noise for correction, and calculating the vehicle flow of each abnormal block;

[0010] S400: trace back the identifier, mark the traffic flow of each of the blocks to the corresponding one-way road section, generate a traffic density map, and push the traffic density map to a preset terminal.

[0011] Furthermore, the S100 includes:

[0012] Draw a traffic network map and extract the topological structure, and use the preset depth-first search algorithm to number all red light intersections in sequence;

[0013] An integrated direction is configured, and an identifier of each one-way road segment is determined according to the integrated direction and the number.

[0014] Furthermore, the S100 includes:

[0015] Using the identifier, generating a tag, and inserting the tag into a block;

[0016] Based on the traffic characteristics and fuzzy characteristics, the average vehicle speed of each block is estimated, and the blocks are clustered into several categories.

[0017] Further, the S200 includes:

[0018] With time as the horizontal axis and the traffic volume of several blocks as the vertical axis, draw a traffic flow trend chart of a one-way road section;

[0019] The predicted value of the traffic volume in each block is calculated and the predicted value is annotated into the traffic density map.

[0020] Further, the S300 includes:

[0021] Acquire meteorological data of the data collection area, and construct a trigger mechanism based on the meteorological data and the audio device;

[0022] According to the descending order of the fuzzy values, the abnormal blocks are divided into several levels, and the adjustment rules of each level are determined.

[0023] Further, the S300 includes:

[0024] Identify a number of sound features from the audio data, compare them with a pre-built noise data set, and extract background noise;

[0025] The appearance time of the fuzzy feature is recorded, and a mapping between the fuzzy feature, the appearance time and the background noise is configured.

[0026] Further, the S400 includes:

[0027] Annotating the vehicle flow into the traffic network map, generating a traffic density map, integrating the topological structure, calculating an optimal diversion path, and integrating the optimal diversion path into the traffic density map;

[0028] The optimal diversion path is used to generate an adjustment reference for the traffic light, and the adjustment reference is sent to a preset terminal.

[0029] Further, the synchronization module is used to delineate the data collection area of ​​the traffic management platform, mark the traffic light intersections, number the traffic light intersections, and determine the identifier of each one-way road section according to the number, create a number block corresponding to the one-way road section, and synchronize the identifier to the corresponding number block;

[0030] A standard module is used to obtain the deployment position of the collection equipment in the data collection area, wherein each one-way road section corresponds to at least one collection equipment, and the collection equipment at least includes: a video monitoring device, through which the video monitoring device is used to collect the video monitoring data of the one-way road section, extract the traffic characteristics, and upload the traffic characteristics to the corresponding digital blocks, extract a number of snapshots from the video monitoring data, calculate the fuzzy value of each snapshot by using an image fuzziness detection algorithm, configure the corresponding relationship between the digital blocks and the fuzzy values, cluster the digital blocks into standard blocks and abnormal blocks based on the fuzzy values, and calculate the traffic flow of each standard block by using the traffic characteristics in the standard blocks;

[0031] The abnormal module is used to define the video surveillance device corresponding to the abnormal block as a target device, obtain the data collection authority of the audio device pre-integrated in the target device, collect the audio data of the one-way road section corresponding to the abnormal block, pre-process the audio data to obtain background noise, wherein the background noise is: the sound of vehicle tires in rain and snow, and extract fuzzy features from the abnormal block, use the background noise for correction, and calculate the vehicle flow of each abnormal block;

[0032] The push module is used to trace back the identifier, mark the traffic flow of each of the blocks to the corresponding one-way road section, generate a traffic density map, and push the traffic density map to a preset terminal.

[0033] Furthermore, the synchronization module includes:

[0034] The numbering unit is used to draw a traffic network map and extract the topological structure, and use the preset depth-first search algorithm to number all red light intersections in sequence;

[0035] a determination unit, configured to configure an integrated direction, and determine an identifier of each one-way road segment according to the integrated direction and the number;

[0036] An inserting unit, used to generate a label using the identifier, and insert the label into the block;

[0037] The clustering unit is used to estimate the average vehicle speed of each block according to the traffic characteristics and fuzzy characteristics, and cluster the blocks into a plurality of categories.

[0038] Furthermore, the standard module includes:

[0039] A drawing unit is used to draw a traffic flow change trend diagram of a one-way road section with time as the horizontal coordinate and the traffic flow of several blocks as the vertical coordinate;

[0040] The marking unit is used to calculate the predicted value of the traffic flow in each block and mark the predicted value in the traffic density map.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] By numbering traffic light intersections, the traffic flow of each one-way section can be analyzed more accurately, greatly improving data management and analysis efficiency. By determining the video surveillance equipment, the traffic flow of each one-way section can be collected and monitored in real time, greatly improving traffic management efficiency. By clustering logarithmic blocks, the amount of data processing can be reduced while ensuring data accuracy. By using audio equipment to process abnormal blocks, multi-source data can be fused to reduce visual dependence. At the same time, the adaptability of video surveillance equipment in severe weather can be enhanced, greatly improving the accuracy of data collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flowchart of a method for collecting data on a traffic management platform provided by an embodiment of the present invention;

[0044] Figure 2 A first sub-process flowchart of the traffic management platform data collection method provided by an embodiment of the present invention;

[0045] Figure 3 A second sub-process flowchart of the traffic management platform data collection method provided by an embodiment of the present invention;

[0046] Figure 4A third sub-process flowchart of the traffic management platform data collection method provided by an embodiment of the present invention;

[0047] Figure 5 A fourth sub-process flowchart of the traffic management platform data collection method provided by an embodiment of the present invention;

[0048] Figure 6 A block diagram of the traffic management platform data collection system provided by an embodiment of the present invention;

[0049] Figure 7 A block diagram of the composition of a synchronization module in a traffic management platform data collection system provided in an embodiment of the present invention;

[0050] Figure 8 A block diagram of the composition of standard modules in the traffic management platform data collection system provided by an embodiment of the present invention;

[0051] Fig. 9 A block diagram of the composition of an abnormal module in a traffic management platform data collection system provided in an embodiment of the present invention;

[0052] Fig.10 A block diagram of the composition of the push module in the traffic management platform data collection system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0054] In Example 1, Figure 1 The implementation process of the traffic management platform data collection method provided by the embodiment of the present invention is shown, and is described in detail below:

[0055] S100: Delineate the data collection area of ​​the traffic management platform and mark the traffic light intersections, number the traffic light intersections, and determine the identifier of each one-way section based on the number, create a number block corresponding to the one-way section, and synchronize the identifier to the corresponding number block.

[0056] Delineate the area where data collection is required, determine the traffic light intersections, and number each traffic light intersection. The specific numbering process is as follows: take a certain traffic light intersection as the starting point, use the depth-first search algorithm to sequentially number all traffic light intersections in turn; integrate the numbers at both ends of the one-way section to generate an identifier, where each section is split into two one-way sections; create a number block for each one-way section. In other words, each number block represents a one-way section, where the number block is the basic structure for storing traffic data, and write the identifier of each section into the corresponding number block.

[0057] S200: Obtain the deployment position of the collection equipment in the data collection area, wherein each of the one-way road sections corresponds to at least one collection equipment, and the collection equipment at least includes: a video surveillance device, through which the video surveillance data of the one-way road section is collected, the traffic characteristics are extracted, and the traffic characteristics are uploaded to the corresponding digital blocks, a number of snapshots are extracted from the video surveillance data, and the fuzziness value of each snapshot is calculated using an image fuzziness detection algorithm, and a corresponding relationship between the digital blocks and the fuzzy values ​​is configured, and based on the fuzzy values, the digital blocks are clustered into standard blocks and abnormal blocks, and the traffic characteristics in the standard blocks are used to calculate the traffic flow of each standard block.

[0058] In each one-way road section, find out the deployment location of the collection equipment, where the collection equipment includes video surveillance equipment and traffic control cameras. In real life, there may be multiple collection devices in a one-way road section. In this case, the collection device with the widest monitoring range is selected for data processing. The collection equipment is used to collect video surveillance data of the one-way road section, and extract feature data related to traffic, such as vehicle logos and taillights.

[0059] The traffic characteristics of the one-way section are uploaded to the corresponding blocks; a number of snapshots are captured at preset time intervals from the video surveillance data collected by the video surveillance equipment. The snapshot is a static image captured from the dynamic video stream, and the snapshot can reflect the vehicle status of the one-way section at a certain moment; each snapshot is analyzed using the image blur detection algorithm in the prior art to calculate the blur value of the snapshot. The image blur detection algorithm can determine the detail distribution of the edge of the image based on methods such as gradient, frequency or Laplace transform; for example, the high-frequency information of the image can be detected using Laplace transform, and the total amount of high-frequency components can be calculated. The larger the total amount, the clearer the snapshot, and vice versa.

[0060] Determine the fuzzy value of each snapshot, where each block has multiple snapshots, perform weighted average on the fuzzy value of each snapshot, determine the calculated average value as the fuzzy value of the block, and divide all the blocks into standard blocks and abnormal blocks according to the fuzzy value and the preset setting value; in short, the standard block is the one-way section where the acquisition equipment with clearer video surveillance data is located, where the preset setting value should be determined by professionals based on the data throughput and the processing capacity of the hardware equipment; use the traffic characteristics in the standard block to calculate the vehicle flow of the standard block, and the specific calculation method is not limited, and can be obtained by superimposing the number of traffic characteristics.

[0061] S300: Define the video surveillance device corresponding to the abnormal block as a target device, obtain data collection authority of the audio device pre-integrated in the target device, collect audio data of the one-way road section corresponding to the abnormal block, pre-process the audio data to obtain background noise, wherein the background noise is: the sound of vehicle tires in rain and snow, and extract fuzzy features from the abnormal block, use the background noise for correction, and calculate the traffic flow of each abnormal block.

[0062] Define the target device from the exception block. It should be noted that each acquisition device is pre-integrated with an audio device. Obtain data acquisition permissions for the pre-integrated audio device in the target device. Collect audio data from each one-way road section through the data acquisition permissions and pre-process the audio data, including noise reduction and framing. Extract several sound features from the pre-processed audio data and find out the background noise in the sound features, including the sound of wheels crushing rain and snow.

[0063] The traffic features in the abnormal block are defined as fuzzy features, and the fuzzy features are corrected using background noise to calculate the traffic flow of the abnormal block.

[0064] S400: trace back the identifier, mark the traffic flow of each of the blocks to the corresponding one-way road section, generate a traffic density map, and push the traffic density map to a preset terminal.

[0065] The traffic flow of abnormal blocks and standard blocks is marked in the one-way road section, a traffic density map is generated, and the traffic density map is pushed to the preset terminal, where the preset terminal is the designated terminal of the traffic management platform.

[0066] In Example 2, Figure 2 The implementation process of the traffic management platform data collection method provided by the embodiment of the present invention is shown, and S100 is described in detail as follows:

[0067] S101: Draw a traffic network map and extract the topological structure, and use a preset depth-first search algorithm to number all red light intersections in sequence.

[0068] Collect traffic network data, including road sections, traffic light intersections, geographic locations and location relationships, visualize traffic light intersections as nodes, visualize each one-way road section as an edge, build a topological structure, and draw a traffic network diagram; use the preset depth-first search algorithm to traverse the topological structure, determine the starting node in the traffic light intersection, and start from an unvisited node in the traffic network diagram, visit the nodes directly connected to it in turn, and assign a unique number to it each time the traffic light intersection is visited.

[0069] S102: configuring an integrated direction, and determining an identifier of each one-way road section according to the integrated direction and number.

[0070] By integrating the numbers at both ends of the one-way section, the identifier corresponding to the one-way section can be obtained.

[0071] For example, a one-way road segment starts from the No. 13 traffic light intersection at the east end and ends at the No. 21 traffic light intersection at the west end, and the integration direction is from east to west. The identifier of the one-way road segment is 13-21.

[0072] In Example 3, Figure 2 The implementation process of the traffic management platform data collection method provided by the embodiment of the present invention is shown, and S100 is described in detail as follows:

[0073] S103: Generate a tag using the identifier, and insert the tag into a block.

[0074] Insert labels generated by identifiers into the blocks, wherein the benefit of inserting labels is that one-way road sections can be quickly located.

[0075] S104: Based on the traffic characteristics and fuzzy characteristics, an average vehicle speed of each block is estimated, and the blocks are clustered into a plurality of categories.

[0076] By combining image recognition algorithms and optical flow methods, the pixel motion in each block is calculated, the driving speed of each vehicle is estimated, and the average speed of the vehicles in each block is calculated. According to the average speed, the blocks are clustered into several categories. In other words, according to the average speed of each one-way road section, traffic congested sections can be quickly identified and corresponding optimization measures can be taken.

[0077] In Example 4, Figure 3 The implementation process of the traffic management platform data collection method provided by the embodiment of the present invention is shown, and S200 is described in detail as follows:

[0078] S201: Draw a traffic flow change trend graph of a one-way road section with time as the horizontal axis and the traffic flow of several blocks as the vertical axis.

[0079] With time as the horizontal axis and the average speed of several blocks as the vertical axis, draw a traffic flow trend chart for each one-way road section.

[0080] S202: Calculate the predicted value of the traffic volume in each block, and mark the predicted value on the traffic density map.

[0081] By analyzing the traffic flow trend chart, the periodic law of traffic flow is identified, and the prediction value of each one-way road section is determined by using the prediction model in the existing technology, and the prediction value is marked at the corresponding position of the traffic density map.

[0082] In Example 5, Figure 4 The implementation process of the traffic management platform data collection method provided by the embodiment of the present invention is shown, and S300 is described in detail as follows:

[0083] S301: Acquire meteorological data of the data collection area, and construct a trigger mechanism based on the meteorological data and audio equipment.

[0084] Collect meteorological data in the data collection area and build a trigger mechanism, where the trigger mechanism is: when the meteorological data in the data collection area is rain or snow, start the audio device in the video monitoring device to collect audio data on the one-way road section.

[0085] S302: Divide the abnormal block into several levels according to the order of the fuzzy values ​​from large to small, and determine the adjustment rule of each level.

[0086] According to the fuzzy value, the abnormal blocks are classified into several levels, each of which corresponds to an adjustment rule; for example, multiple thresholds are set for the fuzzy value, including a first threshold and a second threshold, etc. If the fuzzy value is less than the first threshold, a convolution algorithm can be used to restore a clear image; if the fuzzy value is greater than the first threshold but less than the second threshold, the audio device in the video surveillance device can be started.

[0087] In Example 6, Figure 4 The implementation process of the traffic management platform data collection method provided by the embodiment of the present invention is shown, and S300 is further described in detail as follows:

[0088] S303: Identify a number of sound features from the audio data, compare them with a pre-built noise data set, and extract background noise.

[0089] The audio data is processed to extract features such as frequency, amplitude, and time domain spectrum, and compared with a pre-constructed noise dataset to determine the background noise, where the background noise is the sound of wheels rolling over rain and snow.

[0090] S304: Record the appearance time of the fuzzy feature, and configure a mapping between the fuzzy feature, the appearance time, and the background noise.

[0091] Through the appearance time, the background noise is used to correct the fuzzy features, thereby improving the accuracy of the fuzzy features.

[0092] In Example 7, Figure 5 The implementation process of the traffic management platform data collection method provided by the embodiment of the present invention is shown, and S400 is described in detail as follows:

[0093] S401: marking the vehicle flow into the traffic network map, generating a traffic density map, integrating the topological structure, calculating an optimal diversion path, and integrating the optimal diversion path into the traffic density map.

[0094] The traffic flow of each one-way road section is marked on the traffic network map to generate a traffic density map. The optimal diversion path is calculated through the shortest path algorithm and integrated into the traffic density map. The determination of the optimal diversion path not only requires the consideration of traffic flow, but also the evaluation of factors such as the capacity of each road section, road restrictions and traffic signals.

[0095] S402: Generate an adjustment reference for a traffic light using the optimal diversion path, and send the adjustment reference to a preset terminal.

[0096] Based on the optimal diversion path and traffic volume, etc., an adjustment reference for the traffic signal timing at each traffic light intersection is generated and sent to a preset terminal, thereby providing decision support for the traffic signal timing adjustment; the preset terminal is the designated terminal of the traffic management platform.

[0097] Figure 6 The structure diagram of the traffic management platform data collection system provided by the embodiment of the present invention is shown. The traffic management platform data collection system 1 includes:

[0098] The synchronization module 11 is used to define the data collection area of ​​the traffic management platform, mark the traffic light intersections, number the traffic light intersections, and determine the identifier of each one-way road section according to the number, create a number block corresponding to the one-way road section, and synchronize the identifier to the corresponding number block;

[0099] The standard module 12 is used to obtain the deployment position of the collection equipment in the data collection area, wherein each one-way road section corresponds to at least one collection equipment, and the collection equipment at least includes: a video monitoring device, through which the video monitoring device is used to collect the video monitoring data of the one-way road section, extract the traffic characteristics, and upload the traffic characteristics to the corresponding digital blocks, extract a number of snapshots from the video monitoring data, calculate the fuzzy value of each snapshot by using the image fuzziness detection algorithm, configure the corresponding relationship between the digital blocks and the fuzzy values, cluster the digital blocks into standard blocks and abnormal blocks based on the fuzzy values, and calculate the traffic flow of each standard block by using the traffic characteristics in the standard blocks;

[0100] The abnormal module 13 is used to define the video surveillance device corresponding to the abnormal block as a target device, obtain the data collection authority of the audio device pre-integrated in the target device, collect the audio data of the single road section corresponding to the abnormal block, pre-process the audio data to obtain background noise, wherein the background noise is: the sound of vehicle tires in rain and snow, and extract fuzzy features from the abnormal block, use the background noise for correction, and calculate the vehicle flow of each abnormal block;

[0101] The push module 14 is used to trace back the identifier, mark the traffic flow of each of the blocks to the corresponding one-way road section, generate a traffic density map, and push the traffic density map to a preset terminal.

[0102] Figure 7 The structure diagram of the traffic management platform data collection system provided by the embodiment of the present invention is shown, and the synchronization module 11 includes:

[0103] The numbering unit 111 is used to draw a traffic network map and extract the topological structure, and use a preset depth-first search algorithm to number all red light intersections in sequence;

[0104] A determination unit 112, configured to configure an integrated direction, and determine an identifier of each one-way road segment according to the integrated direction and the number;

[0105] An inserting unit 113, configured to generate a label using the identifier, and insert the label into the data block;

[0106] The clustering unit 114 is used to estimate the average vehicle speed of each block according to the traffic characteristics and fuzzy characteristics, and cluster the blocks into a plurality of categories.

[0107] Figure 8 The structure diagram of the traffic management platform data collection system provided by the embodiment of the present invention is shown, and the standard module 12 includes:

[0108] A drawing unit 121 is used to draw a traffic flow change trend diagram of a one-way road section with time as the horizontal axis and the traffic flow of several blocks as the vertical axis;

[0109] The marking unit 122 is used to calculate the predicted value of the traffic flow in each block and mark the predicted value in the traffic density map.

[0110] Fig. 9 The structure diagram of the traffic management platform data collection system provided by the embodiment of the present invention is shown, and the abnormal module 13 includes:

[0111] A construction unit 131 is used to obtain meteorological data of the data collection area and construct a trigger mechanism based on the meteorological data and the audio device;

[0112] A segmentation unit 132, configured to segment the abnormal block into a plurality of levels in the descending order of the fuzzy values, and determine an adjustment rule for each level;

[0113] An extraction unit 133 is used to identify a number of sound features from the audio data, compare them with a pre-built noise data set, and extract background noise;

[0114] The mapping unit 134 is used to record the appearance time of the fuzzy feature and configure a mapping between the fuzzy feature, the appearance time and the background noise.

[0115] Fig.10 The structure diagram of the traffic management platform data collection system provided by the embodiment of the present invention is shown, and the push module 14 includes:

[0116] The integration unit 141 is used to mark the vehicle flow into the traffic network map, generate a traffic density map, integrate the topological structure, calculate the optimal diversion path, and integrate the optimal diversion path into the traffic density map;

[0117] The sending unit 142 is used to generate an adjustment reference for the traffic light by using the optimal diversion path, and send the adjustment reference to a preset terminal.

[0118] The synchronization module 11 is mainly used to complete step S100, the standard module 12 is mainly used to complete step S200, the abnormal module 13 is mainly used to complete step S300, and the push module 14 is mainly used to complete step S400;

[0119] The numbering unit 111 is mainly used to complete step S101, the determining unit 112 is mainly used to complete step S102, the inserting unit 113 is mainly used to complete step S103, and the clustering unit 114 is mainly used to complete step S104;

[0120] The drawing unit 121 is mainly used to complete step S201, and the marking unit 122 is mainly used to complete step S202;

[0121] The construction unit 131 is mainly used to complete step S301, the segmentation unit 132 is mainly used to complete step S302, the extraction unit 133 is mainly used to complete step S303, and the mapping unit 134 is mainly used to complete step S304;

[0122] The integration unit 141 is mainly used to complete step S401, and the sending unit 142 is mainly used to complete step S402.

[0123] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0125] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for collecting data on a traffic management platform, characterized in that: The method comprises: S100: Delineating a data collection area of ​​a traffic management platform, marking traffic light intersections, numbering the traffic light intersections, and determining an identifier of each one-way road section according to the number, creating a number block corresponding to the one-way road section, and synchronizing the identifier to the corresponding number block; S200: Obtaining the deployment position of the collection equipment in the data collection area, wherein each one-way road section corresponds to at least one collection equipment, and the collection equipment at least includes: a video monitoring device, through which the video monitoring device is used to collect the video monitoring data of the one-way road section, extract the traffic characteristics, and upload the traffic characteristics to the corresponding digital blocks, intercepting a number of snapshots from the video monitoring data, using an image blur detection algorithm to calculate the fuzzy value of each snapshot, configuring the corresponding relationship between the digital blocks and the fuzzy values, clustering the digital blocks into standard blocks and abnormal blocks based on the fuzzy values, and using the traffic characteristics in the standard blocks to calculate the vehicle flow of each standard block; S300: defining the video surveillance device corresponding to the abnormal block as a target device, obtaining data collection authority of the audio device pre-integrated in the target device, collecting audio data of the one-way road section corresponding to the abnormal block, pre-processing the audio data to obtain background noise, wherein the background noise is: the sound of vehicle tires in rain and snow, and extracting fuzzy features from the abnormal block, using the background noise for correction, and calculating the vehicle flow of each abnormal block; S400: trace back the identifier, mark the traffic flow of each of the blocks to the corresponding one-way road section, generate a traffic density map, and push the traffic density map to a preset terminal.

2. The method for collecting data from a traffic management platform according to claim 1, characterized in that: The S100 includes: Draw a traffic network map and extract the topological structure, and use the preset depth-first search algorithm to number all red light intersections in sequence; An integrated direction is configured, and an identifier of each one-way road segment is determined according to the integrated direction and the number.

3. The method for collecting data from a traffic management platform according to claim 2, characterized in that: The S100 includes: Using the identifier, generating a tag, and inserting the tag into a block; Based on the traffic characteristics and fuzzy characteristics, the average vehicle speed of each block is estimated, and the blocks are clustered into several categories.

4. The method for collecting data from a traffic management platform according to claim 1, characterized in that: The S200 includes: With time as the horizontal axis and the traffic volume of several blocks as the vertical axis, draw a traffic flow trend chart of a one-way road section; The predicted value of the traffic volume in each block is calculated and the predicted value is annotated into the traffic density map.

5. The method for collecting data from a traffic management platform according to claim 1, characterized in that: The S300 includes: Acquire meteorological data of the data collection area, and construct a trigger mechanism based on the meteorological data and the audio device; According to the descending order of the fuzzy values, the abnormal blocks are divided into several levels, and the adjustment rules of each level are determined.

6. The method for collecting data from a traffic management platform according to claim 1, characterized in that: The S300 includes: Identify a number of sound features from the audio data, compare them with a pre-built noise data set, and extract background noise; The appearance time of the fuzzy feature is recorded, and a mapping between the fuzzy feature, the appearance time and the background noise is configured.

7. The method for collecting data from a traffic management platform according to claim 2, characterized in that: The S400 includes: Annotating the vehicle flow into the traffic network map, generating a traffic density map, integrating the topological structure, calculating an optimal diversion path, and integrating the optimal diversion path into the traffic density map; The optimal diversion path is used to generate an adjustment reference for the traffic light, and the adjustment reference is sent to a preset terminal.

8. A traffic management platform data collection system, characterized in that: The system comprises: A synchronization module is used to define the data collection area of ​​the traffic management platform and mark the traffic light intersections, number the traffic light intersections, and determine the identifier of each one-way road section according to the number, create a number block corresponding to the one-way road section, and synchronize the identifier to the corresponding number block; A standard module is used to obtain the deployment position of the collection equipment in the data collection area, wherein each one-way road section corresponds to at least one collection equipment, and the collection equipment at least includes: a video monitoring device, through which the video monitoring device is used to collect the video monitoring data of the one-way road section, extract the traffic characteristics, and upload the traffic characteristics to the corresponding digital blocks, extract a number of snapshots from the video monitoring data, calculate the fuzzy value of each snapshot by using an image fuzziness detection algorithm, configure the corresponding relationship between the digital blocks and the fuzzy values, cluster the digital blocks into standard blocks and abnormal blocks based on the fuzzy values, and calculate the traffic flow of each standard block by using the traffic characteristics in the standard blocks; The abnormal module is used to define the video surveillance device corresponding to the abnormal block as a target device, obtain the data collection authority of the audio device pre-integrated in the target device, collect the audio data of the one-way road section corresponding to the abnormal block, pre-process the audio data to obtain background noise, wherein the background noise is: the sound of vehicle tires in rain and snow, and extract fuzzy features from the abnormal block, use the background noise for correction, and calculate the vehicle flow of each abnormal block; The push module is used to trace back the identifier, mark the traffic flow of each of the blocks to the corresponding one-way road section, generate a traffic density map, and push the traffic density map to a preset terminal.

9. The traffic management platform data collection system according to claim 8, characterized in that: The synchronization module comprises: The numbering unit is used to draw a traffic network map and extract the topological structure, and use the preset depth-first search algorithm to number all red light intersections in sequence; a determination unit, configured to configure an integrated direction, and determine an identifier of each one-way road segment according to the integrated direction and the number; An inserting unit, used to generate a label using the identifier, and insert the label into the data block; The clustering unit is used to estimate the average vehicle speed of each block according to the traffic characteristics and fuzzy characteristics, and cluster the blocks into several categories.

10. The traffic management platform data collection system according to claim 8, characterized in that: The standard modules include: A drawing unit is used to draw a traffic flow change trend diagram of a one-way road section with time as the horizontal axis and the traffic flow of several blocks as the vertical axis; The marking unit is used to calculate the predicted value of the traffic flow in each block and mark the predicted value in the traffic density map.

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