A road geometry parameter fitting method based on vehicle trajectory

Abstract

The present invention discloses a method for fitting road geometric parameters based on vehicle trajectories, comprising: obtaining vehicle trajectory geospatial information and converting the vehicle trajectory geospatial information into a local projected coordinate system of the road; obtaining the vehicle's tangential heading angle based on the vehicle trajectory information in the projected coordinates; establishing a relationship between the tangential heading angle and mileage traveled on different road line elements based on the characteristics of the tangential heading angle for each road line element, and obtaining a parametric expression for the tangential heading angle equation; optimizing and fitting the road line element demarcation points based on the parametric expression for the tangential heading angle equation to determine the demarcation points for different road line elements; and performing parameter compliance checks on the road line elements to obtain road parameters. This invention can improve computational analysis accuracy while reducing labor costs, helping road maintenance departments obtain alignment information for in-service roads and providing a theoretical basis for road reconstruction, expansion, and safety assessment.

Description

Technical Field

[0001] The present invention belongs to the field of road safety evaluation and reconstruction and expansion, and in particular relates to a road geometric parameter fitting method based on vehicle trajectory. Background Art

[0002] Road alignment geometry is an important parameter for road design. With the economic and social development of my country, existing roads are facing a large number of upgrading, reconstruction and expansion tasks. In the process of road reconstruction and expansion, it is necessary to accurately obtain the geometric alignment parameters of existing roads. At the same time, road alignment geometry is also an important parameter for road safety evaluation. Local area corrections during road construction lead to certain differences between road design documents and actual alignment parameters. At present, the determination of existing road alignment parameters is mostly based on manual measurement, satellite image recognition and other methods, but these methods are cumbersome and labor-intensive, and are easily affected by image accuracy. In the current research on vehicle trajectory characteristics, more attention is paid to the study of the impact of vehicle driving characteristics on road alignment design and traffic safety evaluation. Vehicle trajectories are used to obtain road alignment geometry parameters. Generally, an association model between parameters such as vehicle trajectory curvature and road alignment geometry parameters is established to determine the road geometry parameters. The current method has the following deficiencies:

[0003] (1) Traditional manual measurement methods are susceptible to manual reading errors and require a lot of manual labor, resulting in low work efficiency;

[0004] (2) When using image recognition algorithms to calculate road linear parameters, lighting, stains, resolution, etc. will lead to poor image quality, affecting the accuracy of the results. At the same time, high-precision images have high requirements for equipment and increase costs.

[0005] (3) Currently, driving trajectories are more commonly used in the study of driving characteristics. In terms of obtaining road linear parameters, parameters such as trajectory curvature are used, which are easily affected by measurement errors and affect the analysis accuracy.

[0006] Therefore, a road geometry parameter fitting method based on vehicle trajectory is urgently needed. Summary of the Invention

[0007] To solve the above technical problems, the present invention proposes a road geometry parameter fitting method based on vehicle trajectories, which can reduce labor costs while improving the accuracy of calculation and analysis, helping road maintenance departments to obtain the linear information of in-service roads, and providing a theoretical basis for road reconstruction, expansion and safety evaluation.

[0008] To achieve the above object, the present invention provides a road geometry parameter fitting method based on vehicle trajectory, comprising:

[0009] Acquiring vehicle travel trajectory geospatial information, and converting the vehicle travel trajectory geospatial information into a local projection coordinate system;

[0010] Based on the trajectory data in the projected coordinates, obtaining a tangential heading angle of the vehicle;

[0011] According to the characteristics of the tangential heading angle at different road line elements, a relationship model between the tangential heading angle and the travel distance on the road line element is established to obtain a parameter model of the tangential heading angle equation;

[0012] Based on the parameter model of the tangential heading angle equation, the road line element dividing points are optimized and fitted to obtain the dividing points of different road line elements;

[0013] Perform parameter compliance check on the road line element to obtain road parameters.

[0014] Optionally, obtaining the tangential heading angle of the vehicle based on the projection coordinates includes:

[0015] Based on the trajectory point of the vehicle in the projection coordinates; calculating the center coordinates of the trajectory point and the curvature at the trajectory point;

[0016] The tangential heading angle is obtained based on the circle center coordinates and the curvature.

[0017] Optionally, the road line elements include: straight lines, circular curves and transition curves.

[0018] Optionally, the characteristics of the tangential heading angle at different road line elements include:

[0019] Within the straight line, the vehicle's tangential heading angle is the same as the vehicle's traveling direction;

[0020] In the circular curve, the tangential heading angle changes linearly with the increase of travel distance;

[0021] In the relaxation curve, the tangential heading angle shows a nonlinear increasing trend as the mileage increases.

[0022] Optionally, establishing the relationship between the tangential heading angle and the traveled mileage on the road plane alignment includes:

[0023] If the road plane line shape is a straight line, the relationship model between the tangential heading angle and the travel distance on the straight line is:

[0024]

[0025] If the road plane line shape is a transition curve, the relationship model between the tangential heading angle on the transition curve and the travel mileage is:

[0026]

[0027] If the road plane line shape is a circular curve, the relationship between the tangential heading angle on the circular curve and the travel mileage is:

[0028] θ Ci =b i+2 l+c i+2

[0029] in, is the tangential heading angle on the straight line, is the tangential heading angle on the transition curve, θ Ci is the tangential heading angle on the circular curve, l is the mileage, and a, b, and c are parameters.

[0030] Optionally, the parameter model for obtaining the tangential heading angle equation includes:

[0031] A constraint condition is set for the tangential heading angle at the boundary of the basic line element, and the parameter model is obtained using the constraint condition.

[0032] Optionally, based on the parameter model of the tangential heading angle equation, optimizing and fitting the road line element demarcation points to obtain the demarcation points of different road line elements includes:

[0033] Obtaining a basic road line shape, and combining the basic line elements to obtain a number of line element boundary points;

[0034] Using the parameter expression, obtaining an error value;

[0035] The line element demarcation points are optimized using the error values ​​to obtain different line element demarcation points on the road.

[0036] Optionally, optimizing the line element demarcation point using the error value to obtain the road line element parameters includes:

[0037] S1, moving the first line element demarcation point between the starting point and the second line element demarcation point by a preset distance each time, obtaining an error value based on the preset distance, and determining the first line element demarcation point when the error value is minimized;

[0038] S2, moving the second line element demarcation point between the first line element demarcation point and the third line element demarcation point by a preset distance each time, obtaining an error value based on the preset distance, and determining the second line element demarcation point when the error value is minimized;

[0039] S3, moving the nth line element demarcation point between the (n-1)th line element demarcation point and the end point, each time by a preset distance, obtaining an error value based on the preset distance, and determining the nth line element demarcation point when the error value is minimized;

[0040] S4, updating the line element demarcation point, determining the line element demarcation point corresponding to the maximum error value, and re-dividing the line elements adjacent to the line element demarcation point to obtain a plurality of line element demarcation points;

[0041] S5. Repeat steps S1-S4 until the maximum error value meets the preset value, completing the line element demarcation point optimization and obtaining different line element demarcation points of the road.

[0042] Optionally, a parameter compliance check is performed on the road line element, and the parameter compliance check includes:

[0043] If the road line element does not meet the standard value, the basic line element is eliminated to obtain a new road line element;

[0044] The new road line element dividing point is re-optimized and fitted to obtain the road parameters. Compared with the existing technology, the present invention has the following advantages and technical effects:

[0045] This method uses vehicle GPS data to obtain road alignment geometry, eliminating the need for extensive manual work. Furthermore, the tangential heading angle measurement results are relatively stable and less susceptible to measurement errors. This reduces labor costs while improving computational analysis accuracy, helping road maintenance departments obtain alignment information for in-service roads and providing a theoretical basis for road reconstruction, expansion, and safety assessments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0047] Figure 1 This is a flow chart of a method for fitting road geometry parameters based on vehicle trajectories according to an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of a circle center calculation method according to an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of an experimental road section according to an embodiment of the present invention;

[0050] Figure 4 This is the raw data display of the embodiment of the present invention;

[0051] Figure 5 This is a diagram of heading angle data according to an embodiment of the present invention;

[0052] Figure 6 This is a curvature data diagram of an embodiment of the present invention;

[0053] Figure 7 This is a comparison diagram of heading angle data and azimuth angle according to an embodiment of the present invention;

[0054] Figure 8 This is a diagram showing the iterative effect of an embodiment of the present invention;

[0055] Figure 9 Schematic diagram of the final segmentation result of an embodiment of the present invention. DETAILED DESCRIPTION

[0056] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0057] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0058] This paper proposes a road geometry parameter fitting method based on vehicle trajectory. For two-lane roads, the latitude and longitude information of the vehicle position during driving is collected. After coordinate system conversion, the adjacent position information is used to calculate the driving heading angle information. The tangential heading angle and driving mileage are used as a bridge to fit the road linear geometry parameters. Figure 1 As shown, the specific steps include:

[0059] Step 1: Obtain the geographic information of the vehicle's driving trajectory and convert it into a local projection coordinate system.

[0060] Specifically, in order to more accurately process and analyze vehicle driving trajectory data, the present invention first performs projection coordinate conversion on the vehicle driving trajectory geographic information. Specifically, the geographic coordinate system coordinates (such as WGS 84, EPSG:4326) collected by the Global Positioning System (GPS) are converted into a local projection coordinate system suitable for calculation. The conversion method uses the "pyproj" function package in the Python language, and the function call method is:

[0061] p1=pyproj.Proj(init='epsg:old_epsg_value')

[0062] p2=pyproj.Proj(init='epsg:new_epsg_value')

[0063] new_lon,new_lat=pyproj.transform(p1,p2,old_lon,old_lat)

[0064] Among them, p1 is the measurement reference coordinate system, p2 is the coordinate system used for data analysis, new_lon, new_lat, old_lon, old_lat are the latitude and longitude of the analysis reference coordinate system and the measurement reference coordinate system respectively.

[0065] Step 2: Based on the vehicle trajectory information in the projected coordinates, obtain the vehicle's tangential heading angle;

[0066] Furthermore, based on the projection coordinates, obtaining the tangential heading angle of the vehicle includes:

[0067] Based on the projected coordinate system, obtain the vehicle's trajectory points;

[0068] Calculate the coordinates of the center of the trajectory point and the curvature at the trajectory point;

[0069] Get the tangential heading angle based on the circle center coordinates and curvature.

[0070] Specifically, after obtaining the vehicle's driving trajectory points in the calculation reference coordinate system, the present invention fits a circle based on three consecutive data points to calculate key indicators such as the vehicle's tangential heading angle and curvature at each point. The specific method is as follows:

[0071] (1) Data accuracy adjustment. According to the data analysis accuracy requirements, the trajectory resolution is determined according to the driving speed and sampling frequency. The trajectory information that meets the accuracy is averaged and aggregated to eliminate random errors and improve analysis accuracy.

[0072] (2) Curvature and tangential heading angle traversal solution: In this step, the curvature and tangential heading angle at each trajectory point are calculated according to the measured data sequence in chronological order. Assuming that three adjacent trajectory measurement points are located on a circular curve, due to the geometric properties of the circle, the perpendicular bisector of any chord will pass through the center of the circle. Figure 2 In the equation, the perpendicular bisectors of the line segments ab and bc formed by the adjacent trajectory points intersect at point M, which is the center of the circle. The coordinates of the center of the circle, the curvature γ at the trajectory point, and the tangential heading angle θ are calculated as follows:

[0073] Calculating the coordinates of the circle's center M (XM, YM): The coordinates of the circle's center M can be solved using analytical geometry, using the equations of the two perpendicular bisectors. In the following formula, the subscripts p and q denote the midpoints of ab and bc, respectively.

[0074]

[0075] Calculation of the curvature γ at point b: After obtaining the coordinates of the center M, the distance between the two points is calculated based on the coordinates of the center and point b, which is the radius of the curve. The reciprocal of the radius is taken to obtain the curvature at point b. The curvature γ is the reciprocal of the radius r (γ = 1 / r), which reflects the degree of curvature of the curve at that point. It should be noted that when the three points are almost collinear, the radius r will tend to infinity. At this time, the curvature γ defaults to 0, indicating that the curve near this point is close to a straight line. Once the coordinates of the center M are estimated, this embodiment can use the distance from the center to point b (i.e., the radius r) to calculate the curvature γ at point b.

[0076]

[0077] Calculation of the tangential heading angle θ: The present invention defines the angle of the vehicle's tangent direction at the current trajectory point as the tangential heading angle. Based on the coordinates of the center point of the circle, the radius vector of any trajectory point and the center of the circle can be calculated. Based on the geometric characteristics of the circular curve, the tangent at the trajectory point is perpendicular to the radius, and the magnitude of the tangential heading angle is ±90° of the radius azimuth, and its direction is determined according to the direction of vehicle travel. The present invention uses the tangential heading angle as the driving heading angle, which can more accurately characterize the actual direction of travel of the vehicle compared to the traditional azimuth method, thereby improving the analysis accuracy.

[0078] θ=[arctan2(x M -x b ,y M -y b )±90]mod360 (5)

[0079] When the three points are almost collinear, the traditional tangent direction calculation may no longer be applicable, and it is more reasonable to directly use the direction of the line connecting the adjacent points as the approximate driving direction. Therefore, in the present invention, the driving direction θ is directly set to the direction of ac (or the direction of bc, depending on the definition and context).

[0080] The driving direction θ is the tangent direction of the vehicle when it is at point b. First, it is necessary to determine the direction of the vector Mb from the center M to point b. Then, according to the properties of the circle, the tangent and the radius are perpendicular at the tangent point, so the tangent direction can be obtained by rotating the Mb direction 90 degrees. The choice of rotation direction is based on the actual path of the vehicle: since the vehicle's driving direction is usually closer to the direction of bc, this embodiment selects a rotation method that makes the tangent direction closer to the bc direction (+90 degrees or -90 degrees). Use the vector dot product or cross product to determine which rotation direction makes the angle between the tangent direction and the bc direction smaller.

[0081] This method uses the tangent direction when calculating the heading angle. Compared with the direction of the line connecting the front and rear points (i.e., the azimuth angle) used in traditional methods, it can more accurately reflect the actual direction of vehicle travel, thereby improving the accuracy and reliability of road linear geometric parameter identification.

[0082] Step 3: Based on the vehicle's tangential heading angle, obtain the parameter expression of the tangential heading angle and mileage.

[0083] Furthermore, the road plane alignment includes: straight lines, circular curves and transition curves;

[0084] In the straight line segment, the vehicle’s tangential heading angle is the same as the vehicle’s direction of travel;

[0085] In the circular curve segment, the tangential heading angle changes linearly with the increase of mileage;

[0086] In the transition curve section, the tangential heading angle shows a nonlinear increasing trend with the increase of mileage.

[0087] Specifically, the basic elements of road alignment include straight lines, circular curves, and transition curves. Vehicle trajectories are the foundation of road alignment design, and they exhibit distinct characteristics across different line elements. On straight lines, the radius is infinite, and the vehicle's tangential heading angle is the same as the vehicle's direction of travel—the direction of the line connecting the two points. On circular curves, the tangential heading angle varies linearly with mileage. On transition curves, the tangential heading angle exhibits a nonlinear trend with increasing mileage. The following describes the relationship between the tangential heading angle θ and mileage l for straight lines, circular curves, and transition curves.

[0088] Straight line: When traveling on a straight line, the tangential heading angle θ remains constant, that is, θ = c, where c is a constant.

[0089] Easing curve: Easing curve is often described by geometric clothoid, and its characteristics can be expressed by rl=A 2 Description, where r is the radius of curvature, l is the distance traveled, and A is the clothoid parameter. In differential geometry, the curvature γ is related to the rate of change of the azimuth angle ɑ, that is, (ɑ represents the azimuth angle, to avoid confusion with the tangential heading angle θ). Substituting into the above formula we get: Solving this differential equation yields: If the heading angle at the starting point is known (let θ0), and the tangent direction angle at the starting point is also ɑ0 = 0. (That is, the curve coincides with a fixed direction at the starting point), then ɑ and θ can be considered the same (in a two-dimensional plane and when there are no sudden changes in direction). Therefore, the relationship between the tangent heading angle θ and the distance traveled l can be expressed as:

[0090] θ=al 2 +c (6)

[0091] Circular curve: On a circular curve, the curvature γ is a constant, and the change in heading angle is proportional to the mileage, which can be expressed as

[0092] θ=bl+c (7)

[0093] For the basic road line shape (straight line 1 - transition curve segment 1 - circular curve segment - transition curve segment 2 - straight line segment 2), where the transition curve is represented by a clothoid, the relationship model between the cumulative tangential heading angle θ(l) and the mileage l is:

[0094] Line segment 1:

[0095]

[0096] Transition curve segment 1:

[0097]

[0098] Circular curve:

[0099] θ C =b3l+c3 (10)

[0100] Transition curve segment 2:

[0101]

[0102] Line segment 2:

[0103]

[0104] Furthermore, the method for establishing the relationship between the tangential heading angle and the mileage on the basic element is:

[0105] In a straight line segment, the relationship between the tangential heading angle and the mileage is:

[0106]

[0107] In the transition curve section, the relationship between the tangential heading angle and the mileage is:

[0108]

[0109] In a circular curve segment, the relationship between the tangential heading angle and the mileage is:

[0110] θ Ci =b i+2 l+c i+2 (15)

[0111] in, is the tangential heading angle in the straight line segment, is the tangential heading angle in the transition curve segment, θ Ci is the tangential heading angle within the circular curve segment, l is the mileage, and a, b, and c are parameters.

[0112] Furthermore, the parameter expression for obtaining the tangential heading angle equation includes:

[0113] Set the constraints of the tangential heading angle at the boundary of the basic line element, and use the constraints to obtain the parameter expression.

[0114] Specifically, based on the continuity characteristics of the vehicle's trajectory, the vehicle trajectory and tangential heading angle should satisfy the following two continuity conditions: (a) the vehicle's cumulative tangential heading angle is equal at different line element boundaries; (b) the first-order derivative of the vehicle trajectory is continuous. Therefore, the vehicle's tangential heading angle equation should satisfy the following equation at different line element boundaries:

[0115]

[0116] Based on the continuity equation, we can get the analytical expressions of the parameters of the tangential heading angle equation corresponding to different line elements. For a single basic line shape, the expressions of each parameter are as follows:

[0117]

[0118] Among them, l1 to l4 are the dividing points of straight line segment 1-transition curve segment 1, transition curve segment 1-circular curve, circular curve-transition curve segment 2, and transition curve segment 2-straight line segment 2 in the basic linear combination.

[0119] For a continuous route, assuming that the route is composed of n basic linear segments, according to the continuity condition of the cumulative tangential heading angle, the analytical expression of the equation parameters can be obtained as shown below:

[0120]

[0121] (4) Calculate the error function:

[0122]

[0123] Among them, i is the number of original data points, θ n (l) is the predicted value of the tangential heading angle at each point of the fitting curve, θ original Calculate the initial tangential heading angle.

[0124] Step 4: Based on the parameter expression of the tangential heading angle equation, optimize the fitting of the road line element dividing points.

[0125] Specifically, obtaining road line elements includes:

[0126] Obtain the basic line shape of the road, combine it with the basic line elements, and obtain several line element dividing points;

[0127] Use parameter expressions to obtain error values;

[0128] The error value is used to optimize the line element dividing point to obtain the road line element.

[0129] Furthermore, the error value is used to optimize the line element demarcation point, and the road line element is obtained including:

[0130] S1, moving the first line element demarcation point between the starting point and the second line element demarcation point, each time by a preset distance, obtaining an error value based on the preset distance, and determining the first line element demarcation point when the error value is minimized;

[0131] S2, moving the second line element demarcation point between the first line element demarcation point and the third line element demarcation point, each time by a preset distance, obtaining an error value based on the preset distance, and determining the second line element demarcation point when the error value is minimized;

[0132] S3, moving the nth line element demarcation point between the (n-1)th line element demarcation point and the end point, each time by a preset distance, obtaining an error value based on the preset distance, and determining the nth line element demarcation point when the error value is minimized;

[0133] S4. Update the line element demarcation point, determine the line element demarcation point corresponding to the maximum error value, re-divide the line elements adjacent to the line element demarcation point, and obtain several line element demarcation points;

[0134] S5. Repeat steps S1-S4 until the maximum error value meets the preset value, completing the line element demarcation point optimization and obtaining the road line element.

[0135] Specifically, (1) Assuming the route is basically linear, there are four line element dividing points: l1, l2, l3, l4

[0136] (2) Randomly assign initial values ​​to them (using equal points) to calculate the values ​​of a2, c2, b3, c3, a4, c4, and calculate the total error E.

[0137] (3) Iterative optimization of line element dividing points:

[0138] ① Let l1 move between the starting point and l2. According to the distance between the starting point and l2, the iterative step length Δx is determined by the equal division method. The optimal position of l1 is determined based on the principle of minimum total error.

[0139] ② Let l2 move between l1 and l3, moving a distance of Δx each time, and find the value of l2 when the total error is minimized.

[0140] ③ Let l3 move between l2 and l4, moving a distance of Δx each time, and find the value of l3 when the total error is minimized.

[0141] ④ Let l4 move between l3 and the end point, moving a distance of Δx each time, and find the value of l4 when the total error is minimized.

[0142] ⑤Update the values ​​of l1, l2, l3, and l4, and repeat steps ①-④ until the values ​​of l1, l2, l3, and l4 are no longer updated.

[0143] ⑥ Find the single point with the largest error e ln =θ n (l)-θ original , add 4 segmentation points near it (for example, l n -10,l n -5,l n +5,l n +10).

[0144] ⑦ Update l1-l8 in sequence. The position close to the starting point is l1, and the position close to the end point is l8. Repeat steps ①-⑤ to update the positions of l1-l8 in sequence.

[0145] ⑧Repeat ⑥-⑦ until e ln Less than a certain value (adjusted according to the precision of the data, such as 1, 2, 3, etc.).

[0146] Step 5: Normalize the parameters of road line elements.

[0147] Obtaining road parameters includes:

[0148] If the road line element does not meet the standard value, the basic line element is eliminated and a new road line element is obtained;

[0149] Re-optimize and fit the new road line element dividing points to obtain road parameters.

[0150] Specifically, according to route design specifications, the shortest lengths of straight segments, curved segments, and transition curve segments in the road alignment are determined as control indicators. The length of each line element is calculated. When the line element length is less than the specified value, the adjacent line elements at that point are merged. For groups with transition curves that are too short, the transition curves are deleted, and the alignment becomes a simple combination of straight segment 1-circular curve-straight segment 2, with each group becoming 4 points. The corresponding formula becomes:

[0151] Line segment 1:

[0152]

[0153] Circular curve:

[0154] θ C =b2 l+c2 (33)

[0155] Line segment 2:

[0156]

[0157] The corresponding analytical expression is:

[0158]

[0159] Recalculate the position of each segmentation point according to the previous method of iterative optimization of line element dividing points.

[0160] Step 6: Calculate the parameters of each road section.

[0161] For straight line segments, the length of each segment is l n+1 -l n , slope and other parameter indicators.

[0162] For circular curves:

[0163] θ C =b2 l+c2 (37)

[0164] Where b is the curvature.

[0165] For spirals:

[0166]

[0167] Among them, the transition curve parameter A = 1 / 2a.

[0168] This embodiment was field tested on Liuxin Road in Bulaotun, a district in Beijing. Liuxin Road is a Class IV highway with two lanes in both directions. The test section was from K53+340 to K57+240. The experimental vehicle's speed was set at 40 km / h. The GPS data had an accuracy of approximately 10 cm and a sampling frequency of up to 100 Hz. To ensure high data accuracy and reliability, a highly sensitive GPS receiver and accelerometer module were deployed on the vehicle, combined with a 4G data transmission module. This high-frequency data acquisition significantly improved the accuracy and reliability of subsequent data processing and provided a solid foundation for the precise reconstruction of road alignment parameters.

[0169] Figure 3 The data visualization results after road section collection are shown. Figure 4 The data used in the analysis of this embodiment include key parameters such as latitude and longitude, speed and time.

[0170] Optimizing Heading Angle Calculation: Based on a sequence of GPS point coordinates, the optimization algorithm proposed in this embodiment is used to calculate heading angle. Experimental results show that this algorithm effectively reduces noise interference during processing and smoothes heading angle variations, resulting in a more accurate reflection of the vehicle's actual direction of travel. Compared to traditional methods, this optimization algorithm demonstrates significant advantages in heading angle calculation.

[0171] Figure 5 and Figure 6The comparison between the heading angle data and the curvature data used in this embodiment is shown. The results show that the noise in the heading angle data is significantly lower than that in the curvature data, and has higher reliability. Figure 7 The comparative analysis of the tangential heading angle used in this embodiment and the traditional azimuth angle is presented. The results show that the tangential heading angle is more advantageous in reflecting the true direction of the vehicle, with less noise and higher accuracy.

[0172] Road Alignment Data Generation: After obtaining a continuous and accurate sequence of heading angles, this embodiment uses the heuristic iterative method proposed in this paper to convert this heading angle data into a geometric description of the road alignment. This includes parameter generation for straight segments, arc segments, and complex curves. This method, through iterative optimization, makes the geometric description of the road alignment more accurate and detailed. Figure 8 The effect comparison of different numbers of iterations is shown. Figure 9 The final calculated piecewise fitting results are shown.

[0173] Data Storage and Sharing: Processed road alignment data is stored in a standardized format to facilitate subsequent data analysis, visualization, and sharing. This standardized data storage method not only improves data usability but also facilitates multi-party collaboration and data sharing. Table 1 shows the fitting results, demonstrating that this method produces good fitting results in most cases, providing a reliable data foundation for further research and application.

[0174] Table 1

[0175]

[0176] Through the implementation of the above optimization measures, this embodiment can efficiently collect and process vehicle driving data, generate high-precision road alignment data, and provide strong support for traffic planning, autonomous driving, intelligent navigation and other fields.

[0177] The above are merely preferred embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A road geometry parameter fitting method based on vehicle trajectory, characterized in that: include: Acquiring vehicle travel trajectory geospatial information, and converting the vehicle travel trajectory geospatial information into a local projection coordinate system; Based on the trajectory data in the projected coordinates, obtaining a tangential heading angle of the vehicle; According to the characteristics of the tangential heading angle at different road line elements, a relationship model between the tangential heading angle and the travel distance on the road line element is established to obtain a parameter model of the tangential heading angle equation; Based on the parameter model of the tangential heading angle equation, the road line element dividing points are optimized and fitted to obtain the dividing points of different road line elements; Performing parameter compliance check on the road line element to obtain road parameters; Based on the projection coordinates, obtaining the tangential heading angle of the vehicle includes: Based on the trajectory point of the vehicle in the projection coordinates; calculating the center coordinates of the trajectory point and the curvature at the trajectory point; Obtaining the tangential heading angle based on the circle center coordinates and the curvature; θ=[arctan2(x M -x b ,and M -and b )±90]mod360 Where θ is the tangential heading angle, x M is the horizontal coordinate of the center of the circle, y M is the ordinate of the circle center; The road line elements include: straight lines, circular curves and transition curves; The characteristics of the tangential heading angle at different road line elements include: Within the straight line, the vehicle's tangential heading angle is the same as the vehicle's traveling direction; In the circular curve, the tangential heading angle changes linearly with the increase of travel distance; In the said transition curve, the tangential heading angle shows a nonlinear increasing trend with the increase of the mileage; Establishing the relationship between the tangential heading angle and the travel distance on the road plane alignment includes: If the road plane line shape is a straight line, the relationship model between the tangential heading angle and the travel distance on the straight line is: If the road plane line shape is a transition curve, the relationship model between the tangential heading angle on the transition curve and the travel mileage is: If the road plane line shape is a circular curve, the relationship between the tangential heading angle on the circular curve and the travel mileage is: i Ci =b i+2 l+c i+2 in, is the tangential heading angle on the straight line, is the tangential heading angle on the transition curve, θ Ci is the tangential heading angle on the circular curve, l is the mileage, and a, b, and c are parameters; The parameter model for obtaining the tangential heading angle equation includes: Setting a constraint condition for the tangential heading angle at a boundary of a basic line element, and obtaining the parameter model using the constraint condition; The constraints are: Where l is the distance traveled, θ is the tangential heading angle; Based on the parameter model of the tangential heading angle equation, the road line element demarcation points are optimized and fitted to obtain the demarcation points of different road line elements, including: Obtaining a basic road line shape, and combining the basic line elements to obtain a number of line element boundary points; Obtaining an error value using the parameter model; Optimizing the line element demarcation points using the error values ​​to obtain different line element demarcation points on the road; Optimizing the line element demarcation point using the error value to obtain the demarcation points of different line elements on the road includes: S1, moving the first line element demarcation point between the starting point and the second line element demarcation point by a preset distance each time, obtaining an error value based on the preset distance, and determining the first line element demarcation point when the error value is minimized; S2, moving the second line element demarcation point between the first line element demarcation point and the third line element demarcation point by a preset distance each time, obtaining an error value based on the preset distance, and determining the second line element demarcation point when the error value is minimized; S3, moving the nth line element demarcation point between the (n-1)th line element demarcation point and the end point, each time by a preset distance, obtaining an error value based on the preset distance, and determining the nth line element demarcation point when the error value is minimized; S4, updating the line element demarcation point, determining the line element demarcation point corresponding to the maximum error value, and re-dividing the line elements adjacent to the line element demarcation point to obtain a plurality of line element demarcation points; S5, repeating steps S1-S4 until the maximum error value meets the preset value, completing the line element demarcation point optimization, and obtaining different line element demarcation points of the road; Performing a parameter compliance check on the road line element, the parameter compliance check comprising: If the road line element does not meet the standard value, the basic line element is eliminated to obtain a new road line element; The new road line element dividing point is re-optimized and fitted to obtain the road parameters.

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