Method and system for obtaining highway traffic flow parameters

Abstract

The present invention discloses a method for obtaining traffic flow parameters of a highway, comprising: dividing the highway into unit grids of uniform size; calibrating the coordinates of highway lane lines at preset intervals; determining the unit grid where the vehicle is located according to the lane line coordinates and the vehicle coordinates, constructing a vehicle trajectory according to the vehicle coordinates, and estimating preliminary traffic flow parameters of the unit grid according to the vehicle trajectory and the unit grid where the vehicle is located; for unit grids equipped with fixed detection equipment, obtaining cross-sectional traffic flow data through the fixed detection equipment, calculating Beidou GPS vehicle trajectory penetration rate based on the cross-sectional traffic flow data, and correcting the preliminary traffic flow parameters of the unit grid according to the Beidou GPS vehicle trajectory penetration rate; for unit grids not equipped with fixed detection equipment, correcting the preliminary traffic flow parameters of the unit grid through adjacent unit grids whose preliminary traffic flow parameters have been corrected. The present invention has low requirements for fixed detection equipment and very low operation and maintenance costs. By combining with Beidou GPS vehicle trajectory, high-precision traffic flow parameter data of a large range of highways can be obtained.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent transportation technology, and in particular relates to a method and system for acquiring highway traffic flow parameters. Background Art

[0002] Traffic flow information is fundamental to daily highway operations management, road condition monitoring, and emergency response. Accurately and rapidly acquiring traffic flow information across large sections of highways is crucial for achieving the informatization and digitization of highways. Currently, obtaining traffic flow information on highways both domestically and internationally relies almost exclusively on fixed-point detection technologies (such as video, coils, microwaves, and radar) to monitor key locations and sections of highways. The coverage of the traffic flow information obtained is very limited, and the construction and maintenance costs of fixed-point detection equipment are high. The existence of large-scale monitoring blind spots on highways has significantly hindered the development and construction of informatization and digitization on highways.

[0003] With the completion of the global network of my country's Beidou satellite navigation system, high-precision navigation and positioning services can be provided for vehicles, with centimeter-level positioning accuracy. Real-time vehicle positioning using the Beidou system allows for precise reconstruction of vehicle trajectories, providing solid technical and data support for acquiring traffic flow information over large areas of highways. Achieving precise control of all highway sections and coverage will be a key direction for the informatization and digitalization of my country's highways. Considering the current practical application of the Beidou system, the penetration rate of Beidou GPS vehicle trajectories is still relatively low. This means that the acquisition of highway traffic flow information cannot yet rely solely on the Beidou system and must rely on traditional fixed-point detection technologies. Therefore, developing a method for acquiring traffic flow data on long highway sections based on a combination of Beidou positioning and fixed-point detection technologies is extremely important and urgent. Summary of the Invention

[0004] In order to solve the problems existing in the prior art, the present invention provides a method for obtaining highway traffic flow parameters, which can realize the acquisition of traffic flow parameters when Beidou GPS is incomplete.

[0005] The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0006] In a first aspect, a method for obtaining highway traffic flow parameters is provided, comprising:

[0007] A method for obtaining highway traffic flow parameters, characterized by comprising:

[0008] Divide the highway into a grid of uniformly sized cells;

[0009] Demarcate the coordinates of highway lane lines according to preset intervals;

[0010] Determine the unit grid where the vehicle is located based on the lane line coordinates and the vehicle coordinates, construct the vehicle trajectory based on the vehicle coordinates, and estimate the preliminary traffic flow parameters of the unit grid based on the vehicle trajectory and the unit grid where the vehicle is located;

[0011] For unit grids equipped with fixed detection equipment, cross-sectional traffic flow data is obtained through the fixed detection equipment, and the Beidou GPS vehicle trajectory penetration rate is calculated based on this data. The preliminary traffic flow parameters of the unit grid are then corrected according to the Beidou GPS vehicle trajectory penetration rate.

[0012] For a unit grid that is not equipped with a fixed detection device, the preliminary traffic flow parameters of the unit grid are corrected through the adjacent unit grids that have had their preliminary traffic flow parameters corrected.

[0013] In combination with the first aspect, further, the conditions that the unit grid division should satisfy are shown in the following formula (1):

[0014]

[0015] Among them, L S is the total length of the expressway, L i is the length of the road in the i-th unit grid, N is the number of unit grids, N F is the number of unit grids with fixed detection equipment, N E It is the number of unit grids without fixed detection equipment.

[0016] In combination with the first aspect, further, the lane line coordinates are shown as formula (2):

[0017]

[0018] Among them, Loc i is the set of lane line coordinates in the i-th unit grid on the highway, (x m ,y m ) k are the horizontal and vertical coordinates of the mth point on the kth lane line.

[0019] In combination with the first aspect, further, the estimation unit grid preliminary traffic flow parameters include:

[0020] The preliminary traffic flow parameters of the unit grid are calculated by formula (3)

[0021]

[0022] Where Num represents the number of Beidou vehicles traveling in the i-th unit grid from time t to time t+Δt. Beidou vehicles entering or leaving during this period are not counted. represents the vehicle density of the i-th unit grid before correction at time t, represents the traffic flow speed on the i-th unit grid before correction at time t, represents the flow rate on the i-th unit grid before correction at time t, represents the vehicle density on the i-th unit grid before correction within the T time period, represents the traffic flow speed before correction in the T time period on the i-th unit grid, represents the traffic volume before correction on the i-th unit grid in the T time period, in vehicles / hour; M represents the number of times the vehicle trajectory data is updated in the time period, represents the number of vehicles in the i-th unit grid at time t, L i represents the length of the road section in the i-th unit grid, represents the X coordinate value of the jth vehicle in the i-th unit grid at time t, represents the Y coordinate value of the jth vehicle in the i-th unit grid at time t, Δt represents the minimum time interval for updating Beidou GPS vehicle trajectory data, n represents the ordinal number of Beidou GPS vehicle trajectory data update, t end Indicates the end time.

[0023] Combined with the first aspect, further, the traffic flow data of the section on the i-th unit grid obtained by the fixed detection equipment is shown in formula (4):

[0024]

[0025] in, It represents the number of vehicles passing through the fixed detection equipment on the i-th unit grid within the time period T, in vehicles / hour; represents the number of vehicles passing through the fixed detection device on the jth lane in the i-th unit grid within the time period T, T l It represents the length of time period T in seconds, and W represents the number of lanes.

[0026] In combination with the first aspect, further calculating the Beidou GPS vehicle trajectory penetration rate and correcting the unit grid preliminary traffic flow parameters according to the Beidou GPS vehicle trajectory penetration rate include:

[0027] According to formula (5), the penetration rate of Beidou GPS vehicle trajectory on the unit grid is calculated

[0028]

[0029] in, represents the penetration rate of BeiDou GPS vehicle trajectory on the i-th unit grid in the T time period, represents the traffic volume obtained from BeiDou GPS vehicle trajectory statistics on the i-th unit grid during the T time period;

[0030] The preliminary traffic flow parameters of the unit grid are modified according to the BeiDou GPS vehicle trajectory penetration rate. The modification process is shown in formula (6):

[0031]

[0032] in, Respectively represent the vehicle density of the i-th unit grid after and before correction in the T time period; and They represent the velocity of the i-th unit grid after and before correction in the T time period; represents the flow of the i-th unit grid after correction in the T time period; represents the penetration rate of BeiDou GPS vehicle trajectories on the i-th unit grid in the T time period; Represents the correction coefficient of vehicle speed on the i-th unit grid during the T time period.

[0033] For a unit grid without fixed detection equipment, the preliminary traffic flow parameters of the unit grid are corrected by using the adjacent unit grids that have corrected preliminary traffic flow parameters, including:

[0034] For unit grids without fixed detection equipment, the BeiDou GPS vehicle trajectory penetration rate of the adjacent unit grids is used as the BeiDou GPS vehicle trajectory penetration rate of the unit grid, as shown in formula (7):

[0035]

[0036] in, represents the penetration rate of BeiDou GPS vehicle trajectories on the i-th unit grid in the T time period; and represents the BeiDou GPS vehicle trajectory penetration rate of the downstream and upstream unit grids of the i-th unit grid in the T time period; ρ i+1 and ρ i-1 They represent the influence coefficients of the i+1th unit grid and the i-1th unit grid on the i-th unit grid respectively.

[0037] In a second aspect, a highway traffic flow parameter acquisition system is provided, comprising:

[0038] Grid division unit, used to divide the highway into unit grids of uniform size;

[0039] A preliminary traffic flow parameter calculation module is used to calibrate the coordinates of highway lane lines according to preset intervals;

[0040] Determine the unit grid where the vehicle is located based on the lane line coordinates and the vehicle coordinates, construct the vehicle trajectory based on the vehicle coordinates, and estimate the preliminary traffic flow parameters of the unit grid based on the vehicle trajectory and the unit grid where the vehicle is located;

[0041] The traffic flow parameter correction module is used to obtain cross-sectional traffic flow data from fixed detection equipment for unit grids equipped with fixed detection equipment, calculate the Beidou GPS vehicle trajectory penetration rate based on the data, and correct the preliminary traffic flow parameters of the unit grid according to the Beidou GPS vehicle trajectory penetration rate;

[0042] For a unit grid that is not equipped with a fixed detection device, the preliminary traffic flow parameters of the unit grid are corrected through the adjacent unit grids that have had their preliminary traffic flow parameters corrected.

[0043] The beneficial effects of the present invention include:

[0044] Based on the existing fixed detection equipment, there is no need to install a large number of fixed detection equipment, which can greatly improve the coverage of highway traffic flow information acquisition. The requirements for fixed detection equipment are not high, and the operation and maintenance costs are very low. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of the method for obtaining highway traffic flow parameters according to the present invention;

[0046] Figure 2 This is a flowchart for obtaining preliminary traffic flow parameters of a unit grid in the present invention;

[0047] Figure 3 Schematic diagram of traffic flow parameter correction for a unit grid without fixed detection equipment in the present invention;

[0048] Figure 4 A schematic diagram of a highway section;

[0049] Figure 5 This is a schematic diagram of the highway lane line coordinate section. DETAILED DESCRIPTION

[0050] In order to further illustrate the technical features and effects of the present invention, the present invention is further described below with reference to the accompanying drawings and specific implementation methods.

[0051] Example 1

[0052] like Figure 1-Figure 5 As shown, the present invention provides a method for obtaining traffic flow parameters of long sections of highways based on incomplete Beidou GPS vehicle trajectories, the process is as follows Figure 1 As shown, Figure 4The figure shows a highway section of about 45 km in length. In order to facilitate the description of the implementation process of the present invention, the following is selected: Figure 4 The specific implementation steps are as follows:

[0053] Step 1: Divide the highway into unit grids of uniform size and calibrate the coordinates of the highway lane lines according to the preset intervals;

[0054] like Figure 4 As shown by the dashed line in the middle, the expressway section is gridded and divided into unit grids of uniform length, so that each unit grid contains only basic sections or interwoven sections. The conditions that the unit grid division should meet are shown in the following formula (1):

[0055]

[0056] Among them, L S is the total length of the expressway, L i is the length of the road in the i-th unit grid, N is the number of unit grids, N F is the number of unit grids with fixed detection equipment, N E It is the number of unit grids without fixed detection equipment.

[0057] and Figure 4 There is a fixed detection device installed in the unit grid 1 marked in the figure, and no fixed detection device is installed in the unit grid 2. The lane line coordinates are calibrated at a certain distance interval. The calibration process is as follows: Figure 5 The lane line coordinates are shown in formula (2):

[0058]

[0059] Among them, Loc i is the set of lane line coordinates in the i-th unit grid on the highway, (x m ,y m ) k are the horizontal and vertical coordinates of the mth point on the kth lane line.

[0060] For the convenience of subsequent calculations, the distance between lane lines is 3.75 meters, and the distance between adjacent coordinates on the same lane line is 150 meters. Figure 4 The lane line coordinate calibration results in unit grid 1 and unit grid 2 are shown in Table 1 below.

[0061] Table 1

[0062]

[0063] Step 2: Estimate the preliminary traffic flow parameters of the unit grid;

[0064] To illustrate the estimation process of the unit grid traffic flow parameters, it is assumed that the Beidou GPS vehicle trajectory data traveling in unit grid 1 between 12:00:00 and 12:00:40 is recorded, as shown in Table 2 below.

[0065] Serial number time Vehicle ID X coordinate (meters) Y coordinate (meters) Lane number 1 12:00:00 BVeh-01 20.0 3.5 1 2 12:00:00 BVeh-02 250 2.8 1 3 12:00:00 BVeh-03 80 7 2 4 12:00:00 BVeh-04 200 7.1 2 5 12:00:00 BVeh-05 100 10 3 6 12:00:00 BVeh-06 1450 11.0 3 7 12:00:20 BVeh-01 340 3.5 1 8 12:00:20 BVeh-02 800 3.0 1 9 12:00:20 BVeh-03 530 7.2 2 10 12:00:20 BVeh-04 720 7.0 2 11 12:00:20 BVeh-05 650 11.0 3 12 12:00:40 BVeh-01 720 6.9 2 13 12:00:40 BVeh-02 1100 3.1 1 14 12:00:40 BVeh-03 1200 6.8 2 15 12:00:40 BVeh-04 1000 7.0 2 16 12:00:40 BVeh-05 1320 10.8 3 17 12:00:40 BVeh-07 0 7.2 2 18 12:00:40 BVeh-08 10 3.0 1

[0066] Determine the unit grid where the vehicle is located according to Tables 1 and 2, construct the vehicle trajectory according to the vehicle coordinates, and calculate the preliminary traffic flow parameters of the unit grid using formula (3)

[0067]

[0068] Where Num represents the number of Beidou vehicles traveling in the i-th unit grid from time t to time t+Δt. Beidou vehicles entering or leaving during this period are not counted. represents the vehicle density of the i-th unit grid before correction at time t, represents the traffic flow speed on the i-th unit grid before correction at time t, represents the flow rate on the i-th unit grid before correction at time t, represents the vehicle density on the i-th unit grid before correction within the T time period, represents the traffic flow speed before correction in the T time period on the i-th unit grid, represents the traffic volume before correction on the i-th unit grid in the T time period, in vehicles / hour; M represents the number of times the vehicle trajectory data is updated in the time period, represents the number of vehicles in the i-th unit grid at time t, L i represents the length of the road section in the i-th unit grid, represents the X coordinate value of the jth vehicle in the i-th unit grid at time t, represents the Y coordinate value of the jth vehicle in the i-th unit grid at time t, Δt represents the minimum time interval for updating Beidou GPS vehicle trajectory data, n represents the ordinal number of Beidou GPS vehicle trajectory data update, t end Indicates the end time.

[0069]

[0070] Based on the lane line coordinates and Beidou GPS vehicle trajectory data, the traffic flow parameters of unit grid 2 can also be preliminarily estimated. For the sake of simplicity, the vehicle trajectory coordinates within unit grid 2 are not listed here one by one. Assume that the traffic flow parameters of unit grid 2 during the period of 12:00:00 to 12:00:40 are:

[0071]

[0072]

[0073] Step 3: Modification of preliminary traffic flow parameters in unit grids equipped with fixed detection equipment

[0074] For unit grid 1, the cross-sectional traffic flow data collected by the fixed detection equipment is counted. It is assumed that the cross-sectional vehicle passing data recorded by the fixed detection equipment is as shown in Table 3 below.

[0075] Table 3

[0076]

[0077] According to the vehicle passing record information shown in Table 3, the cross-section traffic flow parameters are directly counted. The cross-section traffic flow data obtained by the fixed detection equipment include: cross-section flow and location speed, as shown in formula (4):

[0078]

[0079] in, It represents the number of vehicles passing through the fixed detection equipment on the i-th unit grid within the time period T, in vehicles / hour; represents the number of vehicles passing through the fixed detection device on the jth lane in the i-th unit grid within the time period T, T l represents the length of the time period T in seconds, and W represents the number of lanes, as shown below:

[0080]

[0081] According to the unit grid traffic flow parameters and cross-section traffic flow parameters, the Beidou GPS vehicle trajectory penetration rate in this period is calculated. The Beidou GPS vehicle trajectory penetration rate is calculated according to formula (5):

[0082]

[0083] in, represents the penetration rate of BeiDou GPS vehicle trajectory on the i-th unit grid in the T time period, represents the cell grid flow on the i-th cell grid in the T time period, It represents the road section flow on the i-th unit grid in the T time period, as shown below:

[0084]

[0085] Based on the calculated Beidou GPS vehicle trajectory penetration rate, the traffic flow parameter data for unit grid 1 between 12:00:00 and 12:00:40 is corrected. The correction coefficient for vehicle speed in the unit grid can be obtained by calibration from historical traffic flow data. Here, we directly assume that the correction coefficient for vehicle speed is 0.95. The correction process for the unit grid traffic flow parameters is shown in Equation (6):

[0086]

[0087] in, They represent the vehicle density of the i-th unit grid after and before correction in the T time period; and They represent the velocity of the i-th unit grid after and before correction in the T time period; and represent the flow of the i-th unit grid after and before correction in the T time period, respectively; represents the penetration rate of BeiDou GPS vehicle trajectories on the i-th unit grid in the T time period; It represents the correction coefficient of vehicle speed on the i-th unit grid in the T time period, as shown below:

[0088]

[0089]

[0090] Step 4: Modification of preliminary traffic flow parameters for unit grids without fixed detection equipment

[0091] Based on the BeiDou GPS vehicle trajectory penetration rate in unit grid 1, the BeiDou GPS vehicle trajectory penetration rate in unit grid 2 is calculated. The calculation method is shown in formula (7):

[0092]

[0093] in, represents the penetration rate of BeiDou GPS vehicle trajectories on the i-th unit grid in the T time period; and represents the BeiDou GPS vehicle trajectory penetration rate of the downstream and upstream unit grids of the i-th unit grid in the T time period; ρ i+1 and ρ i-1 They represent the influence coefficients of the i+1th unit grid and the i-1th unit grid on the ith unit grid, as shown below:

[0094]

[0095] ρ1=1

[0096] Based on the calculated Beidou GPS vehicle trajectory penetration rate, the traffic flow parameter data of unit grid 2 is corrected. The influence coefficient of the traffic flow speed of the unit grid and the downstream unit grid can be obtained by calibration from the historical traffic flow data. Here, it is directly assumed that the influence coefficient is 0.85. The traffic flow parameter correction of unit grid 2 is as follows:

[0097]

[0098] Example 2

[0099] The present invention provides a highway traffic flow parameter acquisition system, comprising:

[0100] Grid division unit, used to divide the highway into unit grids of uniform size;

[0101] A preliminary traffic flow parameter calculation module is used to calibrate the coordinates of highway lane lines according to preset intervals;

[0102] Determine the unit grid where the vehicle is located based on the lane line coordinates and the vehicle coordinates, construct the vehicle trajectory based on the vehicle coordinates, and estimate the preliminary traffic flow parameters of the unit grid based on the vehicle trajectory and the unit grid where the vehicle is located;

[0103] The traffic flow parameter correction module is used to obtain cross-sectional traffic flow data from fixed detection equipment for unit grids equipped with fixed detection equipment, calculate the Beidou GPS vehicle trajectory penetration rate based on the data, and correct the preliminary traffic flow parameters of the unit grid according to the Beidou GPS vehicle trajectory penetration rate;

[0104] For a unit grid that is not equipped with a fixed detection device, the preliminary traffic flow parameters of the unit grid are corrected through the adjacent unit grids that have had their preliminary traffic flow parameters corrected.

[0105] As can be seen from the above embodiments, the method for obtaining traffic flow parameters on ultra-long sections of highways based on incomplete Beidou GPS vehicle trajectories provided by the present invention can obtain traffic flow parameters on a large range of highways by relying on only a small amount of fixed detection equipment without the need for complete Beidou GPS vehicle trajectories, and has low construction and operation and maintenance costs.

[0106] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0107] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0108] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0109] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for obtaining highway traffic flow parameters, characterized in that: include: Divide the highway into a grid of uniformly sized cells; Demarcate the coordinates of highway lane lines according to preset intervals; Determine the unit grid where the vehicle is located based on the lane line coordinates and the vehicle coordinates, construct the vehicle trajectory based on the vehicle coordinates, and estimate the preliminary traffic flow parameters of the unit grid based on the vehicle trajectory and the unit grid where the vehicle is located; For unit grids equipped with fixed detection equipment, cross-sectional traffic flow data is obtained through the fixed detection equipment, and the Beidou GPS vehicle trajectory penetration rate is calculated based on this data. The preliminary traffic flow parameters of the unit grid are then corrected according to the Beidou GPS vehicle trajectory penetration rate. For unit grids that are not equipped with fixed detection equipment, the preliminary traffic flow parameters of the unit grids are corrected through the adjacent unit grids that have already corrected preliminary traffic flow parameters; The traffic flow data of the section on the i-th unit grid obtained by the fixed detection equipment is shown in formula (4): in, It represents the number of vehicles passing through the fixed detection equipment on the i-th unit grid within the time period T, in vehicles / hour; represents the number of vehicles passing through the fixed detection device on the jth lane in the i-th unit grid within the time period T, T l represents the length of the time period T in seconds, and W represents the number of lanes; Calculate the BeiDou GPS vehicle trajectory penetration rate and modify the unit grid preliminary traffic flow parameters based on the BeiDou GPS vehicle trajectory penetration rate, including: According to formula (5), the penetration rate of Beidou GPS vehicle trajectory on the unit grid is calculated in, represents the penetration rate of BeiDou GPS vehicle trajectory on the i-th unit grid in the T time period, represents the traffic volume obtained from BeiDou GPS vehicle trajectory statistics on the i-th unit grid during the T time period, The preliminary traffic flow parameters of the unit grid are corrected according to the BeiDou GPS vehicle trajectory penetration rate. The correction process is shown in formula (6): in, Respectively represent the vehicle density of the i-th unit grid after and before correction in the T time period; and They represent the velocity of the i-th unit grid after and before correction in the T time period; represents the flow of the i-th unit grid after correction in the T time period; represents the penetration rate of BeiDou GPS vehicle trajectories on the i-th unit grid in the T time period; Represents the correction coefficient of vehicle speed on the i-th unit grid during the T time period; For a unit grid without fixed detection equipment, the preliminary traffic flow parameters of the unit grid are corrected by using the adjacent unit grids that have corrected preliminary traffic flow parameters, including: For unit grids without fixed detection equipment, the BeiDou GPS vehicle trajectory penetration rate of the adjacent unit grids is used as the BeiDou GPS vehicle trajectory penetration rate of the unit grid, as shown in formula (7): in, represents the penetration rate of BeiDou GPS vehicle trajectories on the i-th unit grid in the T time period; and represents the BeiDou GPS vehicle trajectory penetration rate of the downstream and upstream unit grids of the i-th unit grid in the T time period; ρ i+1 and ρ i-1 They represent the influence coefficients of the i+1th unit grid and the i-1th unit grid on the i-th unit grid respectively.

2. A method for obtaining highway traffic flow parameters according to claim 1, characterized in that: The preliminary traffic flow parameters of the estimation unit grid include: The preliminary traffic flow parameters of the unit grid are calculated by formula (3) Where Num represents the number of Beidou vehicles traveling in the i-th unit grid from time t to time t+Δt. represents the vehicle density of the i-th unit grid before correction at time t, represents the traffic flow speed on the i-th unit grid before correction at time t, represents the flow rate on the i-th unit grid before correction at time t, represents the vehicle density on the i-th unit grid before correction within the T time period, represents the traffic flow speed before correction in the T time period on the i-th unit grid, represents the traffic volume before correction on the i-th unit grid in the T time period, in vehicles / hour; M represents the number of times the vehicle trajectory data is updated in the time period, represents the number of vehicles in the i-th unit grid at time t, L i represents the length of the road section in the i-th unit grid, represents the X coordinate value of the jth vehicle in the i-th unit grid at time t, represents the Y coordinate value of the jth vehicle in the i-th unit grid at time t, Δt represents the minimum time interval for updating Beidou GPS vehicle trajectory data, n represents the ordinal number of Beidou GPS vehicle trajectory data update, t end Indicates the end time; 3. The method for obtaining highway traffic flow parameters according to claim 1, characterized in that: The conditions that the unit grid should meet are shown in the following formula (1): Among them, L S is the total length of the expressway, L i is the length of the road section in the i-th unit grid, N is the number of unit grids, N F is the number of unit grids with fixed detection equipment, N E It is the number of unit grids without fixed detection equipment.

4. The method for obtaining highway traffic flow parameters according to claim 1, characterized in that: The lane line coordinates are shown in formula (2): Among them, Loc i is the set of lane line coordinates in the i-th unit grid on the highway, (x m ,y m ) k are the horizontal and vertical coordinates of the mth point on the kth lane line.

5. A highway traffic flow parameter acquisition system, characterized in that: include: Grid division unit, used to divide the highway into unit grids of uniform size; A preliminary traffic flow parameter calculation module is used to calibrate the coordinates of highway lane lines according to preset intervals; Determine the unit grid where the vehicle is located based on the lane line coordinates and the vehicle coordinates, construct the vehicle trajectory based on the vehicle coordinates, and estimate the preliminary traffic flow parameters of the unit grid based on the vehicle trajectory and the unit grid where the vehicle is located; The traffic flow parameter correction module is used to obtain cross-sectional traffic flow data from fixed detection equipment for unit grids equipped with fixed detection equipment, calculate the Beidou GPS vehicle trajectory penetration rate based on the data, and correct the preliminary traffic flow parameters of the unit grid according to the Beidou GPS vehicle trajectory penetration rate; For unit grids that are not equipped with fixed detection equipment, the preliminary traffic flow parameters of the unit grids are corrected through the adjacent unit grids that have already corrected preliminary traffic flow parameters; The traffic flow data of the section on the i-th unit grid obtained by the fixed detection equipment is shown in formula (4): in, It represents the number of vehicles passing through the fixed detection equipment on the i-th unit grid within the time period T, in vehicles / hour; represents the number of vehicles passing through the fixed detection device on the jth lane in the i-th unit grid within the time period T, T l represents the length of the time period T in seconds, and W represents the number of lanes; Calculate the BeiDou GPS vehicle trajectory penetration rate and modify the unit grid preliminary traffic flow parameters based on the BeiDou GPS vehicle trajectory penetration rate, including: According to formula (5), the penetration rate of Beidou GPS vehicle trajectory on the unit grid is calculated in, represents the penetration rate of BeiDou GPS vehicle trajectory on the i-th unit grid in the T time period, represents the traffic volume obtained from BeiDou GPS vehicle trajectory statistics on the i-th unit grid during the T time period, The preliminary traffic flow parameters of the unit grid are corrected according to the BeiDou GPS vehicle trajectory penetration rate. The correction process is shown in formula (6): in, Respectively represent the vehicle density of the i-th unit grid after and before correction in the T time period; and They represent the velocity of the i-th unit grid after and before correction in the T time period; represents the flow of the i-th unit grid after correction in the T time period; represents the penetration rate of BeiDou GPS vehicle trajectories on the i-th unit grid in the T time period; Represents the correction coefficient of vehicle speed on the i-th unit grid during the T time period; For a unit grid without fixed detection equipment, the preliminary traffic flow parameters of the unit grid are corrected by using the adjacent unit grids that have corrected preliminary traffic flow parameters, including: For unit grids without fixed detection equipment, the BeiDou GPS vehicle trajectory penetration rate of the adjacent unit grids is used as the BeiDou GPS vehicle trajectory penetration rate of the unit grid, as shown in formula (7): in, represents the penetration rate of BeiDou GPS vehicle trajectories on the i-th unit grid in the T time period; and represents the BeiDou GPS vehicle trajectory penetration rate of the downstream and upstream unit grids of the i-th unit grid in the T time period; ρ i+1 and ρ i-1 They represent the influence coefficients of the i+1th unit grid and the i-1th unit grid on the i-th unit grid respectively.

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