System and method for collecting traffic data based on 5G network

Abstract

The invention discloses a 5G network-based traffic data acquisition system and method, and the method comprises the steps: obtaining the driving speeds of vehicles passing through a road section in different time periods, obtaining the flow of the vehicles passing through the road section in different time periods, obtaining the distribution number of the vehicles in the road section in different time periods, and obtaining the traffic of the vehicles in the road section in different time periods; the method comprises the following steps of: establishing a three-dimensional coordinate system, and marking the vehicle distribution quantity of the road section in different time periods as follows: marking point connecting lines one by one on the coordinate system for representing the driving speed of the detected vehicles passing through the road section, the flow of the detected vehicles passing through the road section and the vehicle distribution quantity of the road section; the areas of triangles formed in different time periods on the three-dimensional coordinate system are calculated, the areas of the triangles are compared with a comparison reference, the time period with the larger area of the comparison triangles is judged as the vehicle driving peak time period of the road section, and the time period is uploaded to a network platform, so that vehicle owners of the vehicles needing to pass know the time period in advance; and the vehicle can conveniently avoid the vehicle driving peak period of the road section.

Description

Technical Field

[0001] The present invention relates to the field of traffic technology, and in particular to a traffic data collection system and method based on a 5G network. Background Art

[0002] With the acceleration of urbanization and the development of intelligent transportation systems (ITS), the demand for the collection, transmission and processing of traffic data is growing exponentially. Traditional traffic data collection methods, such as circular induction coils and video surveillance, face problems such as low data transmission rate, poor real-time performance, and insufficient data processing capabilities. Compared with 5G network technology, the rapid development of 5G network technology can provide new solutions for the collection of traffic data.

[0003] The existing urban traffic data collection method, device, and equipment with publication number CN117058887A uses computer vision to analyze traffic monitoring videos, determines the traffic data corresponding to main roads and auxiliary roads, analyzes urban traffic by comparing them with each other, and updates the urban traffic status in real time.

[0004] However, the urban traffic data collection methods, devices and equipment do not conduct detailed analysis and processing on the vehicle speed, traffic distribution number and vehicle flow on a certain road section, and cannot provide the traffic information of the road section to the vehicle driver. Moreover, when a traffic accident occurs on the road section, the monitoring data cannot be used to assist the traffic police in determining the cause of the traffic accident. Summary of the invention

[0005] The purpose of the present invention is to provide a traffic data collection system and method based on a 5G network to solve the above-mentioned problems that the vehicle speed, traffic gate position and vehicle flow on a certain road section cannot be analyzed and processed in detail, the traffic information of the road section cannot be provided to the vehicle driver after analyzing and processing the information data of the vehicles passing through the road section, and when a traffic accident occurs on the road section, the traffic police cannot be assisted in determining the cause of the traffic accident by monitoring the processed data.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A traffic data collection system and method based on 5G network, comprising the following steps:

[0008] Step 1: Obtain the speed of the vehicle passing through the road section, which is represented by the vehicle speed frame value Vit of the driving lane;

[0009] Step 2: Obtain the flow rate of vehicles passing through the road section, and mark the flow rate of vehicles passing through the road section as Pi;

[0010] Step 3: Obtain the number of vehicles distributed on the road section, and mark the number of vehicles distributed on the road section as C ij, where j represents different lanes of the road section;

[0011] Step 4: Establish multiple three-dimensional coordinate systems, each of which represents vehicle traffic data in different characteristic time periods, and represent the speed Vit of vehicles passing through the road section within a specific time period, the flow rate Pi of vehicles passing through the road section, and the number of vehicles distributed on the road section Cij one by one on the three-dimensional coordinate system;

[0012] Step 5: By calculating the areas of triangles formed in different time periods on the three-dimensional coordinate system, the areas of triangles in different specific time periods on multiple three-dimensional coordinate systems are compared with the comparison benchmark to determine the congestion level of the road section in a certain time period;

[0013] By comparing the time period with a larger triangle area, it will be determined as the peak driving period of the road section;

[0014] By comparing the time periods with smaller triangle areas, it can be determined as the off-peak period for vehicle traffic on this road section.

[0015] In step 1, by detecting the total number of vehicles passing through a fixed time period, the average speed of all vehicles in the fixed time period is calculated, and the calculated average speed is defined as Vy, where y represents the types of different vehicles passing through the fixed time period. The average speeds of the vehicles passing through the fixed time period are summed and averaged, and the calculated average value is used as the speed frame value of all vehicles passing through the time period, and the speed of the road section in the fixed time period is marked as Vit, where i represents different vehicles and t represents different time periods;

[0016] In step three, the number of vehicles passing through different lanes of the road section is monitored by the coil monitoring system at the entrance of each lane. Whenever a vehicle enters the lane, the induction coil in the coil monitoring system will produce an inductance change, giving a signal to the coil system. By counting the number of signals received in a specific time period, the number of vehicles passing through different lanes in a specific time period is statistically summed.

[0017] In step 4, the X-axis on the three-dimensional coordinate system is the speed Vit of the vehicle passing through the road section within a specific time, the Y-axis is the flow Pi of the vehicle passing through the road section, and the Z-axis is the number of vehicles distributed on the road section C ij. After marking the collected vehicle information on the coordinate system, three markings are connected to form a triangle on the three-dimensional coordinate system;

[0018] In step 5, after calculating the triangle areas in different specific time periods on the three-dimensional coordinate system, the triangle areas are integrated and arranged in descending order, and the calculated triangle areas are summed and averaged. The average value is used as a comparison benchmark, and the triangle areas in different specific time periods are compared with the comparison benchmark;

[0019] The period with the larger triangle area after comparison is regarded as the peak period of the road section;

[0020] The time period with a smaller triangle area after comparison is regarded as the off-peak period of the road section.

[0021] When a rear-end collision occurs within a specific time period on the road section, the vehicle data information within the specific time period on the road section where the rear-end collision occurs is analyzed and processed. The specific analysis and processing process is as follows:

[0022] S1: Determine the traffic lanes during the time period when the rear-end collision occurs on the road section;

[0023] S2: by processing the speed of all vehicles in the lane during the time period passing through the road section, the speed of the vehicles passing through is marked as Vh, where h represents the speed of different vehicles;

[0024] S3: The speeds of all the vehicles passing through the road section are summed up and averaged, and the average value is the safe speed for vehicles passing through the road section in this time period;

[0025] S4: comparing the speed of all vehicles passing through the road section in the time period with the safe speed of vehicles passing through the road section in the time period;

[0026] If the speed of the measured vehicle passing through the road section is greater than the safe speed of the vehicle passing through the road section in the required time period, the vehicle can be marked as exceeding the safe speed when passing through the road section in the time period;

[0027] If the speed of the measured vehicle passing through the road section is less than or equal to the safe speed of vehicles passing through the road section during the time period, the vehicle will not be marked.

[0028] In S4, the marked vehicles are checked to determine the lane in which the marked vehicles traveled through the road section, and the vehicles on the lane where the traffic accident occurred on the road section are determined.

[0029] As a further solution of the present invention: comprising a network platform, a data acquisition module, a data processing module, a data transmission module, a data analysis module and a data storage module;

[0030] The data acquisition module is connected to the road section camera, and is used to collect vehicle data passing through the road section in different time periods. The vehicle data includes the speed of vehicles passing through the road section in different time periods, the flow of vehicles passing through the road section in different time periods, and the number of vehicles distributed in the road section in different time periods. The collected vehicle data passing through the road section is transmitted to the data processing module.

[0031] As a further solution of the present invention: the data processing module is used to calculate the area of ​​the triangle on each three-dimensional coordinate system, and to judge the congestion level of the road section in a certain time period by comparing the triangle areas in different specific time periods on multiple three-dimensional coordinate systems with a comparison benchmark. If the time period has a larger comparison triangle area, it will be determined as the peak period of vehicle travel on the road section; if the time period has a smaller comparison triangle area, it will be determined as the off-peak period of vehicle travel on the road section.

[0032] As a further solution of the present invention: the data analysis module is used to analyze and process the vehicle data information in the specific time period when the traffic accident occurs on the road section, sum and average the speeds of all the vehicles passing through the road section, the average value is the safe speed for the vehicles to pass through the road section in the time period, and compare the speeds of all the vehicles passing through the road section in the time period with the safe speed for the vehicles to pass through the road section in the time period;

[0033] If the speed of the measured vehicle passing through the road section is greater than the safe speed of the vehicle passing through the road section in the required time period, the vehicle can be marked as exceeding the safe speed when passing through the road section in the time period;

[0034] If the speed of the measured vehicle passing through the road section is less than or equal to the safe speed of vehicles passing through the road section during the time period, the vehicle will not be marked.

[0035] Beneficial effects of the present invention:

[0036] (1) The present invention obtains the speed of vehicles passing through the road section, which is expressed as the vehicle speed frame value of the passing lane, obtains the flow of vehicles passing through the road section during the monitoring time period, and marks the flow of vehicles passing through the road section during the monitoring time period as Pi, obtains the number of vehicles passing through different lanes of the road section during the monitoring time period, and marks the number of vehicles passing through different lanes of the road section during the monitoring time period as Ci, establishes multiple three-dimensional coordinate systems, each of which represents vehicle traffic data in different characteristic time periods, and represents the speed Vi of vehicles passing through the road section within a specific time period, the flow Pi of vehicles passing through the road section, and the number of vehicles distributed on the road section Ci one by one on the three-dimensional coordinate system, calculates the area of ​​triangles formed in different time periods on the three-dimensional coordinate system, compares the areas of triangles in different specific time periods on multiple three-dimensional coordinate systems with comparison benchmarks, and judges the congestion degree of the road section within a certain time period, and uploads it to a network platform so that vehicle owners who need to pass through can know it in advance, which is convenient for vehicles to avoid the peak period of vehicle driving on the road section;

[0037] (2) The present invention analyzes and processes the vehicle speed during the time period when the traffic accident occurs through a data processing module, and analyzes and processes the vehicle speed during the time period when the traffic accident occurs on the road section; by processing the speed of all vehicles passing through the road section during the time period, the speed of the vehicles passing through the road section is marked as Vh, where h represents the speed of different vehicles; by using the data processing module, the speed of all vehicles passing through the road section is summed and averaged, and the average value is the safe speed of the vehicles passing through the road section during the time period; by comparing the speed of all vehicles passing through the road section during the time period with the safe speed of the vehicles passing through the road section during the time period; if the speed of the measured vehicle passing through the road section is greater than the safe speed of the vehicles passing through the road section during the time period, the vehicle can be marked, and the vehicle exceeds the safe speed when passing through the road section during the time period; if the speed of the measured vehicle passing through the road section is less than or equal to the safe speed of the vehicles passing through the road section during the time period, the vehicle will not be marked; thereby facilitating the traffic police to judge and handle the traffic accident based on the data, thereby improving the efficiency of handling traffic accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The present invention will be further described below in conjunction with the accompanying drawings.

[0039] Figure 1 It is a schematic diagram of the principle flow of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Example 1

[0042] See also Figure 1 As shown, the present invention is a traffic data collection method based on 5G network, comprising the following steps:

[0043] Step 1: Obtain the speed of the vehicle passing through the road section, which is represented by the vehicle speed frame value Vi t of the traffic lane, where i=1, 2, 3, ..., n, t represents different time periods, with two hours as a specific time period;

[0044] In some specific embodiments, the time subunits include 8:00-10:00, 10:00-12:00, 15:00-17:00, and 17:00-19:00, etc.;

[0045] Step 2: Obtain the traffic volume of vehicles passing through the road section in different time periods, and mark the traffic volume of vehicles passing through the road section in different time periods as Pi;

[0046] Step 3: Obtain the number of vehicles distributed on the road section in different time periods, and mark the number of vehicles distributed on the road section in different time periods as Ci j, where j represents different lanes of the road section;

[0047] Step 4: by establishing multiple three-dimensional coordinate systems, each three-dimensional coordinate system represents the vehicle traffic data in different characteristic time periods, the speed Vi of the vehicles passing through the road section within the specific time period, the flow Pi of the vehicles passing through the road section and the number of vehicles distributed on the road section Ci are punctuated one by one on the three-dimensional coordinate system;

[0048] Step 5: By calculating the areas of triangles formed in different time periods on the three-dimensional coordinate system, the areas of triangles in different specific time periods on multiple three-dimensional coordinate systems are compared with the comparison benchmark to determine the congestion level of the road section in a certain time period;

[0049] By comparing the time period with a larger triangle area, it will be determined as the peak driving period of the road section;

[0050] By comparing the time periods with smaller triangle areas, it can be determined as the off-peak period for vehicle traffic on this road section.

[0051] Divide the daily operation time of the road section into a number of time sub-units of equal length;

[0052] In step 1, within a specific time period, a number of vehicles of the same type are selected, and their instantaneous speeds within the solid line range of the lane entering and the instantaneous speeds within the solid line range of the lane leaving are collected, and the difference is made respectively, and the larger and smaller difference values ​​are removed, and then the remaining data are summed and averaged, and the average value is taken as the vehicle speed frame value within the solid line range of the passing lane;

[0053] In step three, the number of vehicles passing through different lanes of the road section is monitored by the coil monitoring system at the entrance of each lane. Whenever a vehicle enters the lane, the induction coil in the coil monitoring system will produce an inductance change, giving a signal to the coil system. By counting the number of signals received in a specific time period, the number of vehicles passing through different lanes in a specific time period is statistically summed.

[0054] When the traffic light on the road section is red, the number of vehicles passing through each lane is counted, and then the number of vehicles passing through each lane is summed up and counted;

[0055] In step 4, the X-axis on the three-dimensional coordinate system is the speed Vit of the vehicle passing through the road section within a specific time, the Y-axis is the flow rate Pi of the vehicle passing through the road section, and the Z-axis is the number of vehicles distributed on the road section Cij. After marking the vehicle traffic information on the coordinate system, three marks are connected to form a triangle on the three-dimensional coordinate system.

[0056] In step 5, after calculating the triangle areas in different specific time periods on the three-dimensional coordinate system, the triangle areas are integrated and arranged in descending order, and the calculated triangle areas are summed and averaged. The average value is used as a comparison benchmark, and the triangle areas in different specific time periods are compared with the comparison base;

[0057] The triangle period with the larger area after comparison is determined as the peak period of the road section;

[0058] The triangular period with a smaller area after comparison is regarded as the low-peak period of the road section.

[0059] When a traffic accident occurs during the time period of the road section, the vehicle data information during the specific time period of the road section where the traffic accident occurs is analyzed and processed. The specific analysis and processing process is as follows:

[0060] S1: Analyze and process the vehicle speed during the time period when the traffic accident occurred on the road section;

[0061] S2: by processing the speed of all vehicles passing through the road section in the time period, the speed of the vehicles passing through is marked as Vh, where h is 1, 2, 3, ..., n;

[0062] S3: The data processing module is used to sum and average the speeds of all vehicles passing through the road section, and the average value is the safe speed for vehicles passing through the road section in this time period;

[0063] S4: comparing the speed of all vehicles passing through the road section in the time period with the safe speed of vehicles passing through the road section in the time period;

[0064] If the speed of the measured vehicle passing through the road section is greater than the safe speed of the vehicle passing through the road section in the required time period, the vehicle can be marked as exceeding the safe speed when passing through the road section in the time period;

[0065] If the speed of the measured vehicle passing through the road section is less than or equal to the safe speed of vehicles passing through the road section during the time period, the vehicle will not be marked.

[0066] In S4, the marked vehicles are checked to determine the lane in which the marked vehicles travel through the road section, and the vehicles on the lane where the rear-end collision occurred on the road section are determined.

[0067] Embodiment 2

[0068] A traffic data collection system based on a 5G network, comprising a network platform, a data collection module, a data processing module, a data transmission module, a data analysis module and a data storage module;

[0069] The data acquisition module is used to collect vehicle data passing through the road section in different time periods. The vehicle data includes the speed of vehicles passing through the road section in a specific time period, the flow of vehicles passing through the road section in a specific time period, and the number of vehicles distributed in the road section in a specific time period. The collected vehicle data passing through the road section is transmitted to the data processing module.

[0070] The data processing module is used to calculate the area of ​​the triangles in each three-dimensional coordinate system. By comparing the areas of the triangles in different specific time periods on multiple three-dimensional coordinate systems with the comparison benchmark, the congestion level of the road section in a certain time period is judged. If the time period has a larger triangle area, it will be judged as the peak period of vehicle traffic on the road section; if the time period has a smaller triangle area, it will be judged as the off-peak period of vehicle traffic on the road section.

[0071] The data analysis module is used for analyzing and processing the vehicle data information in the specific time period when the rear-end collision occurs on the road section, summing up and averaging the speeds of all the vehicles passing through the road section, and the average value is the safe speed for the vehicles passing through the road section in the time period, and comparing the speeds of all the vehicles passing through the road section in the time period with the safe speed for the vehicles passing through the road section in the time period;

[0072] If the speed of the measured vehicle passing through the road section is greater than the safe speed of the vehicle passing through the road section in the required time period, the vehicle can be marked as exceeding the safe speed when passing through the road section in the time period;

[0073] If the speed of the measured vehicle passing through the road section is less than or equal to the safe speed of vehicles passing through the road section during the time period, the vehicle will not be marked.

[0074] The working principle of the present invention is as follows: when in use, the vehicle data on the road section is photographed by a road section camera and transmitted to a data acquisition module, and the speed of vehicles passing through the road section in different time periods, the flow of vehicles passing through the road section in different time periods and the positions of vehicles passing through the road section in different time periods are marked and processed by a data processing module. The specific collection and analysis process is as follows: the speed of vehicles passing through the road section in a specific time period is obtained, and the speed of vehicles passing through the road section in the specific time period is marked as Vit, i=1, 2, 3, ..., n; the flow of vehicles passing through the road section in the specific time period is obtained, and the flow of vehicles passing through the road section in the specific time period is marked as Pi; the number of vehicles distributed on the road section in the specific time period is obtained, and the number of vehicles distributed on the road section in the specific time period is marked as C ij, i=1, 2, 3, ..., n, j represents different lanes of the road section, j=1, 2, 3, ..., n; by establishing multiple three-dimensional coordinate systems, each three-dimensional coordinate system represents the vehicle traffic data in different characteristic time periods, and the speed Vi of the vehicles passing through the road section within the detected specific time period, the flow rate Pi of the vehicles passing through the road section and the number of vehicles distributed in the road section Ci are punctuated one by one on the three-dimensional coordinate system; after calculating the triangular areas of different specific time periods on the three-dimensional coordinate system, the triangular areas are integrated and arranged in order from large to small, and the calculated triangular areas are summed and averaged, and the average value is used as a comparison benchmark, and the triangular areas in different specific time periods are compared with the comparison benchmark; when the traffic light of the road section is green, the average value when it is green is compared, and the triangle area with a larger area is determined as a peak period, and the triangle area with a smaller area is determined as a low peak period; when the traffic light of the road section is red, the average value when it is red is compared, and the triangle area with a larger area is determined as a peak period, and the triangle area with a smaller area is determined as a low peak period.

[0075] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A traffic data collection method based on 5G network, characterized in that: The following steps are involved: Step 1: Obtain the speed of the vehicle passing through the monitored road section, and the speed is expressed as the vehicle speed frame value Vit of the driving lane; Step 2: Obtain the flow rate of vehicles passing through the monitoring period, and mark the flow rate of vehicles passing through the road section within the monitoring period as Pi; Step 3: Obtain the number of vehicles passing through different lanes of the road section during the monitoring period, and mark the number of vehicles passing through different lanes of the road section during the monitoring period as Cij, where j represents different lanes of the road section; Step 4: by establishing multiple three-dimensional coordinate systems, each three-dimensional coordinate system represents the vehicle traffic data in different characteristic time periods, the speed Vi of the vehicles passing through the road section within the specific time period, the flow Pi of the vehicles passing through the road section and the number of vehicles distributed on the road section Ci are punctuated one by one on the three-dimensional coordinate system; Step 5: By calculating the areas of triangles formed in different time periods on the three-dimensional coordinate system, the areas of triangles in different specific time periods on multiple three-dimensional coordinate systems are compared with the comparison benchmark to determine the congestion level of the road section in a certain time period.

2. According to a 5G network-based traffic data collection method according to claim 1, it is characterized in that: In step one, by detecting the total number of passing vehicles in a specific time period, the average speed of all vehicles in the fixed time period is calculated, and the calculated average speed is defined as Vy, where y represents the types of different passing vehicles in the fixed time period. The average speeds of the passing vehicles in the fixed time period are summed and averaged, and the calculated average value is used as the speed frame value of all passing vehicles in the time period, and the speed of passing the road section in the fixed time period is marked as Vit, where i represents different vehicles and t represents different time periods.

3. According to a 5G network-based traffic data collection method according to claim 1, it is characterized in that: In step three, the number of passing vehicles on different lanes of the road section is monitored by the coil monitoring system at the entrance of each lane. Whenever a passing vehicle enters the lane, the induction coil in the coil monitoring system will produce an inductance change, giving a signal to the coil system. By counting the number of signals received within a specific time period, the number of passing vehicles on different lanes within a specific time period is statistically summed.

4. According to a 5G network-based traffic data collection method according to claim 1, it is characterized in that: In step 4, the X-axis on the three-dimensional coordinate system is the speed Vit of vehicles passing through the road section within a specific time detected, the Y-axis is the flow rate Pi of vehicles passing through the road section, and the Z-axis is the number of vehicles distributed on the road section Cij. After marking the vehicle traffic information on the coordinate system, a triangle is formed on the three-dimensional coordinate system by connecting the three marks.

5. The method for collecting traffic data based on 5G network according to claim 1, characterized in that: In step 5, after calculating the triangle areas in different specific time periods on the three-dimensional coordinate system, the triangle areas are integrated and arranged in descending order, and the calculated triangle areas are summed and averaged. The average value is used as a comparison benchmark, and the triangle areas in different specific time periods are compared with the comparison base; The period with the larger triangle area after comparison is regarded as the peak period of the road section; The time period with a smaller triangle area after comparison is regarded as the low-peak period of the road section.

6. The method for collecting traffic data based on 5G network according to claim 1, characterized in that: When a traffic accident occurs during a road section time period, the vehicle data information during the specific time period of the road section where the traffic accident occurs is analyzed and processed. The specific analysis and processing process is as follows: S1: Analyze and process the vehicle speed during the time period when the traffic accident occurred on the road section; S2: By processing the speed of all vehicles passing through the road section during the time period, the speed is marked as Vh, where h represents the speed of different vehicles; S3: The speeds of all the vehicles passing through the road section are summed and averaged by the data processing module, and the average value is the safe speed of the vehicles passing through the road section in the time period; S4: comparing the speed of all vehicles passing through the road section in the time period with the safe speed of vehicles passing through the road section in the required time period; If the speed of the measured vehicle passing through the road section is greater than the safe speed of the vehicle passing through the road section in the time period, the vehicle can be marked as exceeding the safe speed when passing through the road section in the time period; If the speed of the measured vehicle on the road section is less than or equal to the safe speed of the vehicle on the road section during the time period, the vehicle will not be marked.

7. The method for collecting traffic data based on 5G network according to claim 1, characterized in that: In S4, the marked vehicles are checked to determine the lanes on the road section through which the marked vehicles passed, and the vehicles on the lanes where the traffic accident occurred on the road section are determined.

8. A traffic data collection system based on 5G network, characterized in that: It includes a network platform, a data acquisition module, a data processing module, a data transmission module, a data analysis module and a data storage module; The data processing module is used to calculate the area of ​​the triangles in each three-dimensional coordinate system. By comparing the areas of the triangles in different specific time periods on multiple three-dimensional coordinate systems with the comparison benchmark, the congestion level of the road section in a certain time period is judged. If the time period with a larger comparison triangle area is determined to be the peak period of vehicle traffic on the road section; if the time period with a smaller comparison triangle area is determined to be the off-peak period of vehicle traffic on the road section.

9. A traffic data collection system based on 5G network according to claim 8, characterized in that: The data processing module is used to calculate the area of ​​the triangles on each three-dimensional coordinate system, and to judge the congestion level of the road section in a certain time period by comparing the areas of the triangles in different specific time periods on multiple three-dimensional coordinate systems with a comparison benchmark. If the time period with a larger comparison triangle area is determined to be the peak period of vehicle travel on the road section; if the time period with a smaller comparison triangle area is determined to be the off-peak period of vehicle travel on the road section.

10. A traffic data collection system based on 5G network according to claim 9, characterized in that: The data analysis module is used to analyze and process the vehicle data information in a specific time period when a traffic rear-end collision occurs on the road section, sum up and average the speeds of all vehicles passing through the road section, and the average value is the safe speed of vehicles passing through the road section in the time period, and compare the speed of all vehicles passing through the road section in the time period with the safe speed of vehicles passing through the road section in the required time period; If the speed of the measured vehicle passing through the road section is greater than the safe speed of the vehicle passing through the road section in the time period, the vehicle can be marked as exceeding the safe speed when passing through the road section in the time period; If the speed of the measured vehicle passing through the road section is less than or equal to the safe speed of vehicles passing through the road section during the time period, the vehicle will not be marked.

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