A traffic flow monitoring method and system based on visible light remote sensing technology

Abstract

The present invention relates to the field of traffic monitoring technology, and specifically to a traffic flow monitoring method and system based on visible light remote sensing technology. The traffic flow monitoring method based on visible light remote sensing technology provided by the present invention includes the following steps: obtaining a visible light remote sensing image of the area to be monitored; extracting road data information using the visible light remote sensing image; constructing a Young's index model based on the road data information; setting a judgment threshold interval of a comprehensive evaluation index of traffic flow based on the Young's index model; performing index judgment on the comprehensive evaluation index of traffic flow based on the threshold interval and obtaining a judgment result; obtaining traffic flow information through the judgment result. The present invention improves the efficiency and accuracy of traffic flow data collection, greatly enhances the real-time perception capability of traffic conditions, and realizes comprehensive, refined, and dynamic monitoring of traffic flow.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic monitoring, and in particular to a traffic flow monitoring method and system based on visible light remote sensing technology. Background Art

[0002] With the continuous development of urbanization, transportation has become a key factor in the operation of urbanization. However, the mismatch between road capacity and car usage has aggravated traffic congestion and greatly increased the safety risks of road traffic. In response to this problem, monitoring traffic flow has become an important means to improve the efficiency of traffic flow operation.

[0003] At present, traffic flow monitoring has become an important part of urban intelligent traffic management. Traditional traffic flow monitoring methods such as geomagnetic induction and microwave radar have problems such as complex installation, limited coverage, and susceptibility to environmental influences.

[0004] In the prior art, a method for monitoring traffic flow in a region is proposed. The method sets the upper and lower thresholds of the current cycle traffic flow based on the traffic flow monitoring data of the previous cycle, and compares the real-time traffic flow data of the current cycle with the upper and lower thresholds to determine whether the current traffic flow is normal or abnormal. On the one hand, since the setting of the current cycle threshold of this method will be affected by the traffic flow monitoring data of the previous cycle, the threshold will change over time, which may further lead to problems such as unstable and inaccurate monitoring results. On the other hand, this method does not fully consider factors such as the length and width of the road, the number of lanes, the length and width of the vehicle, and the distance between vehicles, making the monitoring results inaccurate. On the third hand, this method only studies the traffic flow conditions of the previous cycle and the current cycle, and does not clearly judge the changes in traffic flow in future cycles.

[0005] Visible light remote sensing technology has broad application prospects in traffic flow monitoring due to its non-contact, long-distance and high-resolution characteristics. At present, there are not many research works on traffic flow monitoring, and there is no specific traffic flow monitoring method based on visible light remote sensing technology. Summary of the invention

[0006] In view of the defects in the prior art, the present invention provides a traffic flow monitoring method and system based on visible light remote sensing technology.

[0007] On the one hand, the traffic flow monitoring method based on visible light remote sensing technology includes the following steps: obtaining visible light remote sensing images of the area to be monitored; using the visible light remote sensing images to extract road data information; constructing a Young's index model for traffic flow monitoring and analysis based on the road data information; setting a judgment threshold interval of the comprehensive evaluation index of traffic flow based on the Young's index model; performing index judgment on the comprehensive evaluation index of traffic flow and obtaining a judgment result based on the threshold interval; and obtaining traffic flow information through the judgment result. The present invention efficiently captures clear images of the area to be monitored through visible light remote sensing technology, accurately extracts key data information of the road network, constructs an innovative Young's index model, and uses the comprehensive evaluation index of traffic flow to judge and analyze traffic flow conditions and changes, thereby improving the real-time and accuracy of traffic flow monitoring, and also providing strong theoretical support for traffic management and planning, which helps to optimize resource allocation, alleviate traffic congestion, and improve the efficiency and safety of urban traffic operations.

[0008] Optionally, the acquisition of visible light remote sensing images of the area to be monitored includes: acquiring visible light remote sensing images of the area to be monitored at different times, the visible light remote sensing images including visible light remote sensing images when traffic flow is large; visible light remote sensing images when traffic flow is large; visible light remote sensing images when traffic flow is medium; visible light remote sensing images when traffic flow is small; visible light remote sensing images when traffic flow is small. The present invention achieves image acquisition covering the entire cycle of traffic flow by acquiring traffic flow that changes throughout the entire cycle from peak to trough at different times, providing rich and detailed basic support for traffic flow monitoring and analysis, making subsequent road data information extraction, Young's index model construction, and comprehensive traffic flow evaluation more accurate and reliable, which not only enhances the timeliness of monitoring, but also ensures the comprehensiveness and accuracy of monitoring results, and provides strong data support for urban traffic management and planning decisions.

[0009] Optionally, the extracting of road data information by using the visible light remote sensing image includes: using the visible light remote sensing image to obtain a new visible light remote sensing image after preprocessing; extracting road data information according to the new visible light remote sensing image, wherein the road data information includes: the length L of the road in the monitored area, the width D of the road in the monitored area, the number K of vehicles on the road in the monitored area, and the distance d between the front and rear ends of adjacent vehicles in the monitored area. i , the length of the vehicle in the monitoring area m i , the width of the vehicle in the monitoring area n i, the number of lanes a in the area to be monitored. The present invention effectively improves the quality of remote sensing images by performing a carefully designed preprocessing on the obtained visible light remote sensing images; the preprocessing includes selecting an area to be monitored that meets the conditions, image processing, etc., and the image processing includes image denoising, contrast enhancement, correction of geometric distortion, etc.; after the preprocessing, a high-quality image of the area to be monitored that meets the conditions can be obtained, which makes the extraction of road data information more accurate and efficient, whether it is the definition of road boundaries, the identification of lane lines, or the monitoring of the number, length, width, and spacing of vehicles, a higher accuracy rate can be achieved, thereby realizing comprehensive, reliable, and refined management of traffic.

[0010] Optionally, constructing a Young's index model for traffic flow monitoring and analysis based on the road data information includes: constructing a road transverse congestion index model based on the road data information; constructing a road longitudinal congestion index model based on the road data information; constructing a vehicle spatial distribution index model based on the road data information; constructing a Young's index model for traffic flow monitoring and analysis based on the road transverse congestion index model, the road longitudinal congestion index model and the vehicle spatial distribution index model. The road transverse congestion index model is:

[0011]

[0012] The road longitudinal congestion index model is:

[0013]

[0014] The vehicle spatial distribution index model is:

[0015]

[0016] Among them, P represents the lateral distribution index of vehicles in the monitored area, D represents the width of the road in the monitored area, and n i represents the width of the i-th vehicle in the area to be monitored, Q represents the spatial distribution index of road vehicles in the area to be monitored, K represents the number of vehicles in the area to be monitored, and d i Indicates the distance between the front and rear of the i-1th vehicle and the i-th vehicle in the monitoring area, m irepresents the length of the i-th vehicle in the area to be monitored, a represents the number of lanes in the area to be monitored, and L represents the length of the road in the area to be monitored. The present invention constructs a Young's index model for traffic flow monitoring and analysis by utilizing the road transverse congestion index model, the road longitudinal congestion index model, and the vehicle spatial distribution index model, which covers multiple key dimensions in traffic flow monitoring and analysis, including the transverse and longitudinal congestion of the road, and the spatial distribution of vehicles, ensuring the comprehensiveness and practicality of the Young's index model, and plays an important guiding role in promoting intelligent traffic management and improving the efficiency of urban traffic operation.

[0017] Optionally, the Young's index model is:

[0018]

[0019] Among them, H(t) represents the comprehensive evaluation index or Young's index of the road traffic flow in the monitored area at time t, t0 represents the initial monitoring time, n i represents the width of the i-th vehicle in the monitoring area at time t, d i represents the distance between the front and rear of the i-1th vehicle and the i-th vehicle in the monitored area at time t, K represents the number of vehicles in the monitored area at time t, a represents the number of lanes in the monitored area, L represents the length of the road in the monitored area, and D represents the width of the road in the monitored area. The present invention constructs a Young's index model that can comprehensively evaluate the traffic flow by comprehensively considering the influencing parameters of the traffic flow. The change trend of future traffic flow can be predicted only by the comprehensive evaluation index obtained under different time conditions, thereby optimizing the timing of signal lights, adjusting road layout, planning public transportation routes, etc., to alleviate traffic congestion and improve road traffic capacity.

[0020] Optionally, the index judgment threshold interval of the area to be monitored is set based on the Yang's index model, including: based on the Yang's index model, the traffic flow comprehensive evaluation index judgment threshold interval of the area to be monitored is set to [0, 0.2); based on the Yang's index model, the traffic flow comprehensive evaluation index judgment threshold interval of the area to be monitored is set to [0.2, 0.4); based on the Yang's index model, the traffic flow comprehensive evaluation index judgment threshold interval of the area to be monitored is set to [0.4, 0.6); based on the Yang's index model, the traffic flow comprehensive evaluation index judgment threshold interval of the area to be monitored is set to [0.6, 0.8); based on the Yang's index model, the traffic flow comprehensive evaluation index judgment threshold interval of the area to be monitored is set to [0.8, 1). The present invention sets five threshold intervals scientifically and reasonably through the Yang's index model, which is convenient for comparing and analyzing traffic flow data in different time periods and different areas, promotes the standardization and normalization of traffic flow data, and not only enhances the accuracy and effectiveness of traffic flow monitoring, but also provides strong support for traffic congestion warning, emergency response and daily traffic management decision-making.

[0021] Optionally, judging the comprehensive evaluation index of traffic flow and obtaining the judgment result according to the threshold interval includes: judging the situation that the comprehensive evaluation index of traffic flow in the monitored area at different times falls into the threshold interval according to the threshold interval and obtaining the judgment result; judging the size of the comprehensive evaluation index of traffic flow in the monitored area at different times according to the threshold interval and obtaining the judgment result. The present invention realizes the accurate classification and quantitative evaluation of the traffic flow conditions in the monitored area at different times by setting the threshold interval. On the one hand, according to whether the comprehensive evaluation index falls into a specific threshold interval, the traffic flow status can be quickly judged to provide an intuitive overview of the traffic conditions; on the other hand, by comparing the size of the comprehensive evaluation index at different times, the changing trend of traffic flow can be further analyzed, such as the comparison of peak hours, flat hours, and low hours, providing a scientific basis for the formulation of measures such as traffic diversion and signal control.

[0022] Optionally, the information of traffic flow obtained through the judgment result includes: obtaining the status information of traffic flow at different times through the judgment result; obtaining the change information of traffic flow at different times through the judgment result, and the change information includes the size change information of traffic flow in the same threshold interval and the status change information of traffic flow in different threshold intervals. The present invention comprehensively reveals the multi-dimensional information of traffic flow at different times by deeply analyzing the judgment results. On the one hand, the real-time status information of traffic flow is directly extracted to provide real-time road condition reference for public travel choices and traffic management departments. On the other hand, the dynamic changes of traffic flow are deeply excavated, including the slight increase or decrease of traffic flow in the same threshold interval, and the state transition when crossing different threshold intervals, which is crucial for predicting traffic trends, optimizing traffic signal control, and formulating emergency response plans. This method enhances the practicality and value of traffic flow data and provides strong support for the refinement and intelligence of urban traffic management.

[0023] Optionally, the traffic flow status information includes: when the comprehensive evaluation index of the traffic flow in the area to be monitored falls into the threshold interval [0,0.2), the traffic flow status at the current moment is low flow; when the comprehensive evaluation index of the traffic flow in the area to be monitored falls into the threshold interval [0.2,0.4), the traffic flow status at the current moment is relatively low flow; when the comprehensive evaluation index of the traffic flow in the area to be monitored falls into the threshold interval [0.4,0.6), the traffic flow status at the current moment is medium flow; when the comprehensive evaluation index of the traffic flow in the area to be monitored falls into the threshold interval [0.6,0.8), the traffic flow status at the current moment is relatively high flow; when the comprehensive evaluation index of the traffic flow in the area to be monitored falls into the threshold interval [0.8,1), the traffic flow status at the current moment is high flow. The present invention constructs a comprehensive and dynamic traffic flow monitoring and analysis system by combining the threshold interval of the comprehensive evaluation index of traffic flow with the status information of traffic flow. The system defines different states of traffic flow through clear threshold intervals, realizes real-time capture and feedback of the status information, can accurately judge the changing trend of traffic flow according to the changes in the threshold interval, and provides the public with an intuitive and accurate travel reference, which helps to alleviate traffic congestion, optimize resource allocation, and improve traffic operation efficiency.

[0024] In the second aspect, a traffic flow monitoring system based on visible light remote sensing technology provided by the present invention includes a scanning device, a processor, an output device, and a memory, wherein the scanning device, the processor, the output device, and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes a program instruction, the processor is configured to call the program instruction, and the system uses the traffic flow monitoring method based on visible light remote sensing technology. The traffic flow monitoring system based on visible light remote sensing technology provided by the present invention has high integration and smooth information transmission. It uses high-quality remote sensing equipment to capture road images in real time, uses image processing and pattern recognition technology to accurately extract road information and perform calculation analysis, improves the collection efficiency and accuracy of traffic flow data, greatly enhances the real-time perception ability of traffic conditions, and realizes comprehensive and dynamic monitoring of traffic flow; through visual display and data analysis, it can quickly grasp the changes in road conditions, scientifically formulate traffic control strategies, effectively alleviate traffic congestion, and improve road traffic efficiency. It also provides convenient information services for public travel and promotes the intelligent and refined management of urban transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flow chart of a traffic flow monitoring method based on visible light remote sensing technology according to an embodiment of the present invention;

[0026] Figure 2 A traffic schematic diagram of the area to be detected according to an embodiment of the present invention;

[0027] Figure 3 A remote sensing image of the area to be monitored according to an embodiment of the present invention;

[0028] Figure 4 Schematic diagram of the structure of a traffic flow monitoring system based on visible light remote sensing technology according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0030] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0031] See also Figure 1 The embodiment of the present invention provides a traffic flow monitoring method based on visible light remote sensing technology, the method comprising the following steps:

[0032] S1. Obtain a visible light remote sensing image of the area to be monitored.

[0033] In the process of acquiring visible light remote sensing images, the equipment used includes but is not limited to ultra-high-definition cameras that integrate optical sensing technology and image processing algorithms. The ultra-high-definition cameras not only have functions such as automatic focusing and anti-shake, but also integrate intelligent recognition and image processing technology. They can achieve image enhancement under special weather conditions such as rainy days and foggy days, ensuring the acquisition of clear and reliable image data.

[0034] In one embodiment, the ultra-high-definition camera is first selected and arranged in a suitable position, which fully considers the scope of the area to be monitored to ensure that the main roads, intersections, and surrounding congested sections of the area to be monitored can be covered.

[0035] Furthermore, in order to cope with monitoring needs in different time periods and weather conditions, a flexible shooting plan is set up. During peak traffic hours, the camera will automatically increase the shooting frequency to capture more details and dynamic changes; during low traffic hours, the camera will automatically reduce the shooting frequency to save resources.

[0036] Furthermore, a large number of visible light remote sensing images were acquired, including visible light remote sensing images of five traffic flow conditions: heavy, large, medium, small, and small.

[0037] See also Figure 3 , Figure 3 (a) is one of the large-scale remote sensing images scanned and recorded in real time by the ultra-high-definition camera, Figure 3 (b) and Figure 3 (c) is a locally enlarged remote sensing image containing main vehicle information scanned and recorded in real time by the ultra-high-definition camera, Figure 3 (a) includes road information and vehicle information. In the subsequent embodiments, one of the roads can be selected as the area to be monitored for implementation.

[0038] The advantage of this method is that the obtained visible light remote sensing images have high clarity, comprehensive coverage, strong real-time performance, and can fully display the overall morphological characteristics of the traffic.

[0039] S2. Extracting road data information using the visible light remote sensing image.

[0040] In one embodiment, the visible light remote sensing image is preprocessed to obtain a new visible light remote sensing image. First, by applying algorithms such as median filtering and Gaussian filtering, random noise in the image is effectively reduced and the signal-to-noise ratio of the image is improved.

[0041] Furthermore, multispectral analysis is performed on the visible light remote sensing image, and image removal technology is used to remove parts that affect image quality to achieve image enhancement.

[0042] Furthermore, repair is performed through interpolation or neighboring pixel filling to ensure the integrity of the monitored area.

[0043] Furthermore, by selecting ground control points and establishing a geometric transformation model, the image is accurately corrected for geometric distortion to make it conform to the geographic coordinate system.

[0044] This method achieves three beneficial effects by utilizing image preprocessing:

[0045] First, it eliminates or reduces interference from atmospheric disturbances, cloud obstructions, sensor noise, etc. to images during transmission and acquisition, thereby improving image clarity and availability.

[0046] Second, it ensures the precise positioning and brightness consistency of the image in the geographic coordinate system, improving the accuracy and reliability of the data.

[0047] Third, it optimizes the data structure of the image, reduces the amount of data, and improves the efficiency of subsequent processing and analysis.

[0048] In another embodiment, road data information is extracted based on the new visible light remote sensing image. In this embodiment, an automated method for extracting road data information is used. First, image processing technology is used to identify unique features of roads and vehicles in remote sensing images, such as linear features, brightness consistency, and contrast with the surrounding environment, and these features are enhanced through edge detection algorithms and morphological operations.

[0049] Furthermore, image classification techniques are used to distinguish roads, vehicles and other objects.

[0050] Furthermore, a neural network method is used to extract road data information, wherein the road data information includes: the road length L of the monitored area, the road width D of the monitored area, the number of road vehicles K in the monitored area, the distance d between the front and rear of the i-1th vehicle and the i-th vehicle in the monitored area i , the vehicle length m of the i-th vehicle in the monitoring area i , the vehicle width n of the i-th vehicle in the monitoring area i , the number of lanes in the area to be monitored a. See Figure 3 , Figure 3 This is a traffic schematic diagram of the area to be detected according to an embodiment of the present invention.

[0051] The advantage of this method is that the road data information extracted using remote sensing images is comprehensive, accurate, real-time, dynamic, economical, efficient, compatible and scalable, making visible light remote sensing technology play an increasingly important role in the acquisition and application of road data information.

[0052] S3. Constructing a Young's index model based on the road data information.

[0053] In one embodiment, firstly, a road lateral congestion index model is constructed according to the road data information, and the road lateral congestion index model is:

[0054]

[0055] Among them, P represents the lateral congestion index of the road in the monitored area, K represents the number of vehicles in the monitored area, and d i Indicates the distance between the front and rear of the i-1th vehicle and the i-th vehicle in the monitoring area, m i Represents the length of the i-th vehicle in the area to be monitored.

[0056] Furthermore, a road longitudinal congestion index model is constructed based on the road data information;

[0057]

[0058] Where W represents the longitudinal congestion index of the road in the monitored area, D represents the width of the road in the monitored area, and n i represents the width of the i-th vehicle in the area to be monitored, and K represents the number of vehicles in the area to be monitored.

[0059] Furthermore, a vehicle spatial distribution index model is constructed based on the road data information;

[0060]

[0061] Among them, Q represents the spatial distribution index of road vehicles in the monitored area, K represents the number of vehicles in the monitored area, and d i Indicates the distance between the front and rear of the i-1th vehicle and the i-th vehicle in the monitoring area, m i represents the length of the i-th vehicle in the area to be monitored, a represents the number of lanes in the area to be monitored, and L represents the length of the road in the area to be monitored.

[0062] Furthermore, a Young's index model for traffic flow monitoring and analysis is constructed based on the road transverse congestion index model, the road longitudinal congestion index model and the vehicle spatial distribution index model.

[0063]

[0064] Among them, H(t) represents the comprehensive evaluation index or Young's index of the road traffic flow in the monitored area at time t, t0 represents the initial monitoring time, n i represents the width of the i-th vehicle in the monitoring area at time t, d i represents the distance between the front and rear of the i-1th vehicle and the i-th vehicle in the monitored area at time t, K represents the number of vehicles in the monitored area at time t, a represents the number of lanes in the monitored area, L represents the length of the road in the monitored area, and D represents the width of the road in the monitored area.

[0065] The advantage of this method is that it reflects multi-dimensional and systematic thinking on traffic flow monitoring and analysis, highlights the importance of data-driven decision-making, can comprehensively and deeply reflect traffic flow conditions, and provides a more accurate and scientific basis for urban traffic management.

[0066] S4. Based on the Young's index model, a judgment threshold range of the comprehensive evaluation index of traffic flow is set.

[0067] In one embodiment, first, relevant road data parameters are defined using MATLAB software, and the Young's index model is constructed using the road data parameters.

[0068] Furthermore, specific road data extracted from visible light remote sensing images at five moments are imported into MATLAB software, and the visible light remote sensing images at five moments include visible light remote sensing images with large, large, medium, small, and small actual traffic flows.

[0069] Furthermore, the imported road specific data information is substituted into the Young's index model to calculate the comprehensive evaluation index of the traffic flow at the five moments. The corresponding comprehensive evaluation indexes of traffic flow at the five moments are 0.91, 0.74, 0.56, 0.29 and 0.11 respectively. By comparing the comprehensive evaluation indexes of traffic flow at the five moments, a conclusion is found: the larger the comprehensive evaluation index of traffic flow, the greater the actual traffic flow.

[0070] The advantage of this method is that it combines the calculation results of the Young's index model with the actual traffic flow situation for analysis, which increases the reliability and practicality of the index results.

[0071] In another embodiment, based on the method and conclusion of the previous embodiment, in order to obtain a reliable index range corresponding to the actual traffic flow, a large number of road-specific data information sets at different times are captured.

[0072] Furthermore, the road data information set is substituted into the Young's index model for calculation to obtain a large number of data sets of comprehensive evaluation indexes of traffic flow at different times, and the data sets are compared and analyzed with the actual traffic flow situation.

[0073] Furthermore, the correspondence between five actual traffic flow conditions and a large number of comprehensive traffic flow evaluation indexes was sorted and analyzed, and five threshold intervals were set according to the results of the sorting and analysis, namely [0, 0.2), [0.2, 0.4), [0.4, 0.6), [0.6, 0.8), and [0.8, 1), and the threshold intervals correspond to the actual traffic flow conditions of small, small, medium, large, and large, respectively.

[0074] The advantage of this method is that by obtaining a large amount of data, the impact of extreme values ​​is reduced, the robustness of the threshold interval setting is improved, and the accuracy and adaptability of the comprehensive evaluation index of traffic flow are further increased.

[0075] S5. Based on the threshold value interval, perform index judgment on the comprehensive evaluation index of traffic flow and obtain a judgment result.

[0076] In one embodiment, based on the threshold interval, the situation where the comprehensive evaluation index of the traffic flow in the monitored area at different times falls into the threshold interval is judged and a judgment result is obtained;

[0077] In this embodiment, the comprehensive evaluation index of traffic flow at seven consecutive moments from t1 to t7 is selected, and the situations falling within the threshold interval are analyzed and determined, as shown in Table 1.

[0078] Furthermore, the comprehensive evaluation indexes of traffic flow at the seven moments are judged and analyzed with the five threshold intervals to obtain a first judgment result, which is: the seven comprehensive evaluation indexes of traffic flow all fall within the threshold intervals, among which the H(t1) index falls within the threshold interval [0.2, 0.4), the H(t2) index falls within the threshold interval [0, 0.2), the H(t3) index falls within the threshold interval [0.4, 0.6), the H(t4) index falls within the threshold interval [0.6, 0.8), the H(t5) index falls within the threshold interval [0.8, 1), the H(t6) index falls within the threshold interval [0.6, 0.8), and the H(t7) index falls within the threshold interval [0.2, 0.4).

[0079] Table 1 The situation where the comprehensive evaluation index of traffic flow at different times falls into the threshold range

[0080]

[0081] The advantage of this method is that it uses the threshold interval to distinguish the comprehensive evaluation index of traffic flow at different times, so that the comprehensive evaluation index of traffic flow at different times is different, which is conducive to further distinguishing the conditions of traffic flow at different times.

[0082] In another embodiment, based on the threshold interval, the size of the comprehensive evaluation index of the traffic flow in the area to be monitored at different times is judged and a judgment result is obtained.

[0083] Please refer to Table 1. In this embodiment, the magnitudes of the comprehensive evaluation indexes of traffic flows at the seven moments are compared continuously.

[0084] Furthermore, the second judgment result is obtained: H(t1)>H(t2) <H(t3)<H(t4)<H(t5)> H(t6)>H(t7)

[0085] The advantage of this method is that on the one hand it is helpful to distinguish the traffic flow conditions at different times, and on the other hand it is helpful to further predict the changing trend of traffic flow in the short term.

[0086] S6. Obtaining traffic flow information based on the judgment result.

[0087] In one embodiment, the first judgment result is obtained, and the first judgment result is as follows: the H(t1) index falls within the threshold interval [0.2, 0.4), the H(t2) index falls within the threshold interval [0, 0.2), the H(t3) index falls within the threshold interval [0.4, 0.6), the H(t4) index falls within the threshold interval [0.6, 0.8), the H(t5) index falls within the threshold interval [0.8, 1), the H(t6) index falls within the threshold interval [0.6, 0.8), and the H(t7) index falls within the threshold interval [0.2, 0.4).

[0088] Furthermore, based on the first judgment result, traffic flow status information is obtained, and the status information is as follows: the traffic flow at time t1 is a small flow, the traffic flow at time t2 is a small flow, the traffic flow at time t3 is a medium flow, the traffic flow at time t4 is a large flow, the traffic flow at time t5 is a large flow, the traffic flow at time t6 is a large flow, and the traffic flow at time t7 is a small flow.

[0089] The advantage of this method is that it uses the threshold interval to limit the traffic flow conditions, ensures the stability of traffic flow monitoring, and realizes step-by-step monitoring of traffic flow.

[0090] In another embodiment, the second judgment result is obtained, and the second judgment result is as follows:

[0091] The magnitude of the comprehensive evaluation index of traffic flow at the seven moments is:

[0092] H(t1)>H(t2) <H(t3)<H(t4)<H(t5)> H(t6)>H(t7)

[0093] Furthermore, according to the magnitude relationship of the comprehensive traffic evaluation index, the change information of the traffic flow condition is obtained, and the change information is as follows:

[0094] During the time period t1 to t2, the traffic volume changes from small to small;

[0095] During the time period t2 to t3, the traffic flow changes from small to medium;

[0096] During the time period t3 to t4, the traffic volume changes from medium to large;

[0097] During the time period t4 to t5, the traffic volume changes from relatively large to large;

[0098] During the time period t5 to t6, the traffic volume changes from heavy to relatively large;

[0099] During the time period from t6 to t7, the traffic flow suddenly changes from large to small.

[0100] In summary, during the time period from t4 to t5, the traffic flow reaches its maximum and the traffic is most congested. During the time period from t2 to t5, the overall traffic flow shows a trend of gradually increasing. During the time period from t5 to t7, the overall traffic flow shows a trend of gradually decreasing.

[0101] The advantage of this method is that it uses the changes in the comprehensive evaluation index of traffic flow to predict the future trend of traffic flow, which has potential practical value.

[0102] See also Figure 4 , Figure 4 The structure diagram of a traffic flow monitoring system based on visible light remote sensing technology in one embodiment of the present invention is shown in FIG. In this embodiment, the system includes a scanning device, a processor, an output device, and a memory, wherein the scanning device, the processor, the output device, and the memory are interconnected, the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and the system uses the traffic flow monitoring method based on visible light remote sensing technology.

[0103] Furthermore, the scanning device uses a satellite remote sensing sensor. As a high-altitude scanning device, the remote sensing sensor carried by the satellite can capture high-resolution image data of urban roads. The sensor includes a multi-spectral, hyperspectral or radar sensor, which can capture light information in different bands to distinguish between vehicles and other objects on the road.

[0104] Furthermore, the processor has built-in image processing algorithms, including edge detection, feature extraction, target tracking, etc., for identifying road-related parameters and parameters such as the number, spacing and size of vehicles from the image.

[0105] Furthermore, the output device adopts a display screen, and the display screen is mainly used to display the traffic flow monitoring results in real time.

[0106] Furthermore, the memory adopts a high-speed solid-state hard disk to store the original images collected by the scanning device and the result data processed by the processor. The memory has the characteristics of fast reading and writing speed, large capacity and high reliability, and can meet the needs of large data storage.

[0107] The advantage of this system is that it improves the efficiency and accuracy of traffic flow data collection, greatly enhances the real-time perception of traffic conditions, and realizes comprehensive and dynamic monitoring of traffic flow.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A traffic flow monitoring method based on visible light remote sensing technology, characterized in that: The method comprises the following steps: Obtaining visible light remote sensing images of the area to be monitored at different times, the visible light remote sensing images including visible light remote sensing images when traffic flow is large, visible light remote sensing images when traffic flow is large, visible light remote sensing images when traffic flow is medium, visible light remote sensing images when traffic flow is small, and visible light remote sensing images when traffic flow is small; Using the visible light remote sensing images of the area to be monitored at different times, preprocessing is performed to obtain new visible light remote sensing images; Extracting road data information according to the new visible light remote sensing image, the road data information includes: the length of the road in the area to be monitored, the width of the road in the area to be monitored, the number of vehicles on the road in the area to be monitored, the distance between the front and rear of adjacent vehicles in the area to be monitored, the length of the vehicles in the area to be monitored, the width of the vehicles in the area to be monitored and the number of lanes in the area to be monitored; According to the road data information, a road transverse congestion index model is constructed; according to the road data information, a road longitudinal congestion index model is constructed; according to the road data information, a vehicle spatial distribution index model is constructed; according to the road transverse congestion index model, the road longitudinal congestion index model and the vehicle spatial distribution index model, a Young's index model for traffic flow monitoring and analysis is constructed, and the Young's index model is: in, express The comprehensive evaluation index or Young's index of the road traffic flow in the monitored area at all times, Indicates the time of initial monitoring, Indicates the area to be monitored. A car in The width of the moment, Indicates the area to be monitored. Car and A car in The distance between the front and rear of the car at the moment, express The number of vehicles in the area to be monitored at any time, Indicates the number of lanes in the area to be monitored, Indicates the length of the road in the area to be monitored, Indicates the width of the road in the area to be monitored; Based on the Yang index model, a judgment threshold range of the comprehensive evaluation index of traffic flow is set; According to the threshold range, the comprehensive evaluation index of the traffic flow is judged and a judgment result is obtained; The traffic flow information is obtained through the judgment result.

2. The traffic flow monitoring method based on visible light remote sensing technology according to claim 1 is characterized in that: The step of setting the index judgment threshold interval of the area to be monitored based on the Young's Index model includes: Based on the Young's index model, the judgment threshold interval of the comprehensive evaluation index of the traffic flow in the monitored area is set to [0, 0.2); Based on the Young's index model, the judgment threshold interval of the comprehensive evaluation index of the traffic flow in the monitored area is set to [0.2, 0.4); Based on the Young's index model, the judgment threshold interval of the comprehensive evaluation index of the traffic flow in the monitored area is set to [0.4, 0.6); Based on the Young's index model, the judgment threshold interval of the comprehensive evaluation index of the traffic flow in the monitored area is set to [0.6, 0.8); Based on the Young's index model, the judgment threshold interval of the comprehensive evaluation index of the traffic flow in the monitored area is set to [0.8, 1).

3. The traffic flow monitoring method based on visible light remote sensing technology according to claim 1 is characterized in that: The step of judging the comprehensive evaluation index of traffic flow and obtaining the judgment result based on the threshold interval includes: According to the threshold interval, judging whether the comprehensive evaluation index of the traffic flow in the monitored area at different times falls into the threshold interval and obtaining a judgment result; Based on the threshold interval, the size of the comprehensive evaluation index of the traffic flow in the area to be monitored at different times is judged and a judgment result is obtained.

4. The traffic flow monitoring method based on visible light remote sensing technology according to claim 1 is characterized in that: The information of traffic flow obtained through the judgment result includes: The traffic flow status information at different times is obtained through the judgment result; The traffic flow change information at different times is obtained through the judgment result, and the change information includes the size change information of the traffic flow in the same threshold interval and the status change information of the traffic flow in different threshold intervals.

5. The traffic flow monitoring method based on visible light remote sensing technology according to claim 4 is characterized in that: The traffic flow status information includes: When the comprehensive evaluation index of traffic flow in the monitored area falls into the threshold interval [0, 0.2), the current traffic flow condition is low flow; When the comprehensive evaluation index of traffic flow in the monitored area falls into the threshold interval [0.2, 0.4), the current traffic flow condition is low flow; When the comprehensive evaluation index of traffic flow in the monitored area falls into the threshold interval [0.4, 0.6), the current traffic flow is medium flow; When the comprehensive evaluation index of the traffic flow in the monitored area falls into the threshold interval [0.6, 0.8), the current traffic flow is a high flow; When the comprehensive evaluation index of the traffic flow in the monitored area falls into the threshold interval [0.8, 1), the current traffic flow condition is high flow.

6. A traffic flow monitoring system based on visible light remote sensing technology, the system using a traffic flow monitoring method based on visible light remote sensing technology as claimed in any one of claims 1 to 5, characterized in that: The system includes a scanning device, a processor, an output device, and a memory, which are interconnected. The memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions.

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