Map matching method, device, computer equipment and storage medium

Abstract

The embodiment of the present application relates to a map matching method, device, computer equipment and storage medium. If the driving path of a vehicle is a curved path, the trajectory distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section are obtained; and the matching evaluation value of each to-be-matched road section is determined according to the trajectory distance information, the diagonal information and the angle information; then, according to the matching evaluation value of each to-be-matched road section, the target matching road section of the vehicle's driving path in the map is determined. The accuracy of the distance from the vehicle to the road section obtained by this method during the map matching process is greatly improved, thereby improving the accuracy of the final map matching result.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of intelligent travel technology, and in particular, to a map matching method, apparatus, computer equipment and storage medium. Background Art

[0002] With the development of science and technology and society, road traffic safety and traffic efficiency issues have become increasingly prominent. V2X, as a system solution in vehicle-road collaboration, has been increasingly promoted.

[0003] As a basic supporting function of V2X, map matching has received more and more attention. Map matching in V2X is a technology that matches the road section based on the vehicle's GPS information and map information to obtain the node information of the road section where the vehicle is located. Specifically, map matching is to match the longitude, latitude, heading angle, speed and other information in the vehicle's GPS with the upstream and downstream node relationships, node longitude, node latitude and other information of multiple nodes in the map information to obtain the unique matching road section of the vehicle in the map.

[0004] However, in the current map matching method, accurate distance information cannot be obtained for the curved path, resulting in inaccurate map matching results. Summary of the invention

[0005] Based on this, it is necessary to provide a map matching method, apparatus, computer device and storage medium to address the above technical problems, which can improve the accuracy of the determined distance from the vehicle to the road section, thereby improving the accuracy of the final map matching result.

[0006] In a first aspect, an embodiment of the present application provides a map matching method, the method comprising:

[0007] If the driving path of the vehicle is a curved path, obtaining the track distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section;

[0008] Determine the matching evaluation value of each to-be-matched road section according to the trajectory distance information, diagonal information and included angle information;

[0009] According to the matching evaluation value of each to-be-matched road section, the target matching road section of the vehicle's driving path in the map is determined.

[0010] In one embodiment, the step of obtaining the trajectory distance information between the vehicle and at least one to-be-matched road segment in the target map search range includes:

[0011] Obtain the distances between the vehicle path sequence and the matching road segment sequence of each road segment to be matched at different times; the vehicle path sequence is a sequence composed of the current position of the vehicle and the historical trajectory of the vehicle; the matching road segment sequence is a sequence composed of the corresponding road segments to be matched;

[0012] The minimum distance among the distances at different times is determined as the trajectory distance information from the vehicle to each road section to be matched.

[0013] In one embodiment, the above-mentioned obtaining the diagonal information between the vehicle and each road section to be matched includes:

[0014] According to the diagonal angle formed by the current position of the vehicle and each to-be-matched road section, the diagonal angle value of each to-be-matched road section is obtained;

[0015] The ratio between the diagonal angle value of each to-be-matched road section and the maximum diagonal angle value among the diagonal angle values ​​is determined as the diagonal information between the vehicle and each to-be-matched road section.

[0016] In one embodiment, the above-mentioned obtaining of the angle information between the vehicle and each road section to be matched includes:

[0017] According to the angle formed by the current position of the vehicle and each road section to be matched, the supplementary angle value of the angle of each road section to be matched is obtained;

[0018] The ratio between the supplementary angle value of the angle of each to-be-matched road section and the maximum supplementary angle value among the supplementary angle values ​​of each angle is determined as the angle information between the vehicle and each to-be-matched road section.

[0019] In one of the embodiments, before obtaining the trajectory distance information between the vehicle and at least one to-be-matched road segment in the target map search range, the method further includes:

[0020] According to the track points in the historical track of the vehicle and the current position point of the vehicle, a path length formed by a preset number of track points in the historical track and the current position point is obtained;

[0021] If the path length and the number of trajectory points in the historical trajectory meet the first preset condition, it is determined that the driving path of the vehicle is a curved path.

[0022] In one embodiment, the process of generating the track points in the historical track of the vehicle includes:

[0023] Acquire first driving information of a first sampling point and second driving information of a second sampling point in a historical trajectory of the vehicle; the first sampling point and the second sampling point are any two sampling moments;

[0024] Determine, according to the first driving information and the second driving information, an actual maximum error between a distance from a straight line connecting the first sampling point and the second sampling point to a curved path and a radius of the curved path;

[0025] If the actual maximum error is greater than the preset value, the first sampling point and the second sampling point are determined to be trajectory points.

[0026] In one embodiment, determining the actual maximum error between the distance from the straight line connecting the first sampling point and the second sampling point to the curved path and the radius of the curved path according to the first driving information and the second driving information includes:

[0027] Determine a chord length between a first sampling point and a second sampling point according to the first driving information and the second driving information;

[0028] Determine the radius of curvature of the arc between the first sampling point and the second sampling point according to the chord length;

[0029] According to the radius of curvature of the arc, determine the vertical distance from the center of the circle to the chord length;

[0030] The difference between the arc curvature radius and the vertical distance is determined as the actual maximum error.

[0031] In one of the embodiments, before obtaining the trajectory distance information between the vehicle and at least one to-be-matched road segment in the target map search range, the method further includes:

[0032] Determine the target map search range based on the track points in the historical track of the vehicle and the current position point of the vehicle;

[0033] The road sections that meet the second preset condition in the target map search range are determined as the curved road sections to be matched; the second preset condition is that one of the end points of the curved road section to be matched is within the target search range.

[0034] In one embodiment, the target map search range is determined based on the track points in the historical track of the vehicle and the current position point of the vehicle, including:

[0035] Determine the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate according to the coordinates of a preset number of trajectory points in the historical trajectory, the coordinates of the current position point, and the preset search radius;

[0036] The range formed by the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate is determined as the target map search range.

[0037] In one embodiment, the above-mentioned determining the matching evaluation value of each to-be-matched road segment according to the trajectory distance information, the diagonal information and the included angle information includes:

[0038] Obtain the weights corresponding to the trajectory distance information, diagonal information and angle information;

[0039] The weighted sum of the trajectory distance information, the diagonal information and the included angle information is determined as the matching evaluation value of each to-be-matched road segment.

[0040] In one embodiment, the above-mentioned determining the target matching road segment of the vehicle's driving path in the map according to the matching evaluation value of each to-be-matched road segment includes:

[0041] The road section corresponding to the maximum value among the matching evaluation values ​​of each to-be-matched road section is determined as the target matching road section of the vehicle's driving path in the map.

[0042] In a second aspect, an embodiment of the present application provides a map matching device, the device comprising:

[0043] An acquisition module, for acquiring, if the driving path of the vehicle is a curved path, track distance information between the vehicle and at least one to-be-matched road section in the target map search range, diagonal information between the vehicle and each to-be-matched road section, and angle information between the vehicle and each to-be-matched road section;

[0044] A determination module, used to determine the matching evaluation value of each to-be-matched road section according to the trajectory distance information, diagonal information and angle information;

[0045] The matching module is used to determine the target matching section of the vehicle's driving path in the map according to the matching evaluation value of each to-be-matched section.

[0046] In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the method steps of any one of the embodiments of the first aspect when executing the computer program.

[0047] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method steps of any one of the embodiments of the first aspect above.

[0048] The map matching method, device, computer equipment and storage medium provided in the embodiment of the present application, if the driving path of the vehicle is a curved path, the trajectory distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section are obtained; and the matching evaluation value of each to-be-matched road section is determined according to the trajectory distance information, the diagonal information and the angle information; then, according to the matching evaluation value of each to-be-matched road section, the target matching road section of the vehicle's driving path in the map is determined. In this method, when obtaining the distance from the vehicle to each to-be-matched road section, the trajectory distance information is obtained, that is, the distance between two irregular sequences, so that the trajectory distance information can effectively reflect the distance between the vehicle's path and the to-be-matched road section, so that the accuracy of the distance from the vehicle to the road section obtained in the map matching process is greatly improved, thereby improving the accuracy of the final map matching result. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1a An application environment diagram of a map matching method provided in an embodiment;

[0050] Figure 1b is a schematic diagram of a curved path in one embodiment;

[0051] Figure 2 A flowchart of a map matching method provided in an embodiment;

[0052] Figure 3 A schematic flow chart of a map matching method provided in another embodiment;

[0053] Figure 4 A schematic diagram of a vehicle path sequence provided in one embodiment;

[0054] Figure 5 A schematic diagram of sequence trajectory distance provided in one embodiment;

[0055] Figure 6 A schematic flow chart of a map matching method provided in another embodiment;

[0056] Figure 7 A schematic flow chart of a map matching method provided in another embodiment;

[0057] Figure 8 A schematic flow chart of a map matching method provided in another embodiment;

[0058] Fig. 9 A schematic flow chart of a map matching method provided in another embodiment;

[0059] Fig.10A schematic flow chart of a map matching method provided in another embodiment;

[0060] Fig.11 A flowchart of a map matching method provided in one embodiment;

[0061] Fig.12 is a structural block diagram of a map matching device provided in one embodiment;

[0062] Fig.13 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0064] The map matching method provided in the embodiment of the present application can be applied to Figure 1a In the application environment shown. Among them, the processor in the computer device is used to provide computing and control capabilities; the memory includes a non-volatile storage medium and an internal memory; the non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium; the database of the computer device is used to store relevant data in the map matching process. The network interface of the computer device is used to communicate with other external devices through a network connection. Among them, the computer device can be installed in a vehicle, which can be but not limited to a vehicle-mounted navigation device or a personal computer, laptop computer, smart phone, tablet computer, portable wearable device, etc. with a built-in vehicle-mounted navigation system. Of course, the computer device can also be a server, and the server realizes map matching by wired or wireless communication with the navigation instrument in the vehicle.

[0065] First, before specifically introducing the technical solution of the embodiment of the present application, the technical background or technical evolution context based on the embodiment of the present application is introduced. In the prior art, when performing map matching, the map for the curve generally uses a sparse point set to represent the path, such as Figure 1b As shown in FIG. 1 , it is a schematic diagram of a curved path, where P1, P2, P3, P4, ..., Pn are trajectory points on the curved path. In practical applications, the trajectory point set on the curved path may not be dense enough, and the distance between the straight line connecting two sparse points and the actual road with the curvature radius is greater than the road radius (half the road width, not shown in the figure). For example, Figure 1bThe distance from the line between points P1 and P3 (i.e., the chord from point P1 to point P3) to the curved path is PH_ActualError, and the actual radius of the curved path is R in the figure, then there will be a situation where PH_ActualError is greater than R. In this case, when calculating the distance from the vehicle to the curved road section, the existing method of calculating the distance from the point to the road section cannot accurately calculate the distance from the vehicle to the road section, and it is difficult to provide sufficiently accurate information for map matching, so that the final map matching result is not accurate enough. Based on this, the embodiments of the present application provide a map matching method, apparatus, computer equipment and storage medium, which can improve the accuracy of the determined distance from the vehicle to the road section, thereby improving the accuracy of the final map matching result. In addition, it should be noted that the applicant has made a lot of creative work from the discovery of the above-mentioned technical defects and the technical solutions introduced in the following embodiments.

[0066] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems will be described in detail below through embodiments and in combination with the accompanying drawings. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. It should be noted that when describing a map matching method provided in an embodiment of the present application below, the execution subject is a computer device. In order to make the purpose, technical solution and advantages of the embodiment of the present application clearer, the technical solution in the embodiment of the present application will be clearly and completely described below in combination with the accompanying drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, not all of the embodiments.

[0067] In one embodiment, Figure 2 As shown, a map matching method is provided. This embodiment relates to a specific process of accurately obtaining the track distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section when the vehicle's formal path is a curved path, and then matching each to-be-matched road section according to the track distance information, the diagonal information, and the angle information, and finally determining the target matching road section; this embodiment includes the following steps:

[0068] S101, if the driving path of the vehicle is a curved path, obtain the trajectory distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section.

[0069] In an embodiment of the present application, it is necessary to first identify whether the vehicle is traveling on a curved path. After ensuring that the vehicle's driving path is a curved path, the computer device obtains the trajectory distance information between the vehicle and at least one to-be-matched section in the target map search range, the diagonal information between the vehicle and each to-be-matched section, and the angle information between the vehicle and each to-be-matched section.

[0070] The target map search range refers to the possible range of the vehicle's current driving path in the map, that is, any road section within the target map search range may be a matching road section of the vehicle's current driving path. The target map search range is predetermined, for example, the vehicle's current preliminary position is determined in advance based on the vehicle's historical driving data (including but not limited to trajectory, driving time, form speed, etc.) and combined with the vehicle's current driving time, and then the target map search range is determined in the map based on the preliminary position. The embodiment of the present application does not limit the method for determining the target search range; alternatively, based on the position of the vehicle's GPS positioning, a range is determined with the position as the center of the circle, and the range can be used as the target map search range.

[0071] The road section in the target map search range is the road section to be matched. There is at least one road section to be matched in the target map search range, for example, there are three road sections to be matched: I1, I2, and I3. Then, obtaining the trajectory distance information between the vehicle and at least one road section to be matched in the target map search range is to obtain the trajectory distance information of the vehicle to I1, I2, and I3 respectively. The trajectory distance information here can only refer to the distance itself (i.e., the length value), but it can also include other distance-related information other than the distance itself, such as a distance schematic diagram, etc. In the embodiment of the present application, the trajectory distance information will be explained by taking the length value as an example. It should also be emphasized that the trajectory distance information obtained in the embodiment of the present application is not a simple point-to-line distance, but can effectively reflect the distance between the path where the vehicle is located and the road section to be matched, that is, the distance between two irregular sequences. It is precisely because the trajectory distance information is obtained that it can provide sufficiently accurate distance information from the vehicle to the road section to be matched for map matching, so as to improve the accuracy of the map matching result.

[0072] For example, the method of obtaining the trajectory distance information between the vehicle and at least one to-be-matched road section in the target map search range can be to pre-train a neural network model, which takes the historical trajectory information of the vehicle and the current position of the vehicle, as well as the coordinate position of the to-be-matched road section in the map as input, and outputs the distance from the vehicle to the to-be-matched road section (i.e., trajectory distance information). In this way, the distance from the vehicle to each to-be-matched road section in the target map search range can be obtained through the neural network model. Of course, some trajectory distance algorithms can also be used to calculate, for example, Fréchet distance, Hausdorff distance, Hamming distance, etc. to calculate the trajectory distance information from the vehicle to each to-be-matched road section. This embodiment of the present application is not limited to this.

[0073] In addition to obtaining the trajectory distance information from the vehicle to each section to be matched, it is also necessary to obtain the diagonal information and angle information from the vehicle to each section to be matched. The diagonal information and angle information can reflect the positional relationship between the vehicle and each section to be matched. Determining the final matching section of the vehicle's driving path in combination with the positional relationship can greatly improve the matching accuracy. For example, the method of obtaining the diagonal information between the vehicle and each section to be matched and the angle information between the vehicle and each section to be matched can also be determined by a neural network model or by a geometric algorithm. For example, if it is determined by a neural network model, it is necessary to pre-train a neural network model, and the input of the neural network model is the current position of the vehicle, the direction of vehicle travel, and the coordinate position of the section to be matched; the output is the diagonal information between the vehicle and each section to be matched and / or the angle information between the vehicle and each section to be matched. That is to say, if the diagonal information and angle information from the vehicle to each to-be-matched road section are obtained through a neural network model, one neural network model can be used or they can be trained separately. Similarly, if a neural network model is used for the trajectory distance from the above-mentioned vehicle to the to-be-matched road section, it can be trained separately or in combination with the neural network model. This embodiment of the present application does not limit this.

[0074] S102: Determine a matching evaluation value of each to-be-matched road segment according to the trajectory distance information, the diagonal information and the included angle information.

[0075] Based on the above-obtained track distance information from the vehicle to each to-be-matched road section, diagonal information from the vehicle to each to-be-matched road section, and angle information from the vehicle to each to-be-matched road section, the matching evaluation value of each to-be-matched road section can be determined according to the track distance information, diagonal information, and angle information. Among them, the matching evaluation value of each to-be-matched road section reflects the reliability of the matching between each to-be-matched road section and the vehicle's driving path. The higher the matching evaluation value, the higher the matching reliability between the to-be-matched road section and the vehicle's driving path.

[0076] For example, the matching evaluation value of each to-be-matched section can be determined by taking the sum, weighted sum, weighted average, product, etc. of the trajectory distance information, diagonal information, and angle information of each to-be-matched section as the matching evaluation value of each to-be-matched section. Alternatively, the matching evaluation value of each to-be-matched section can be determined by analyzing the probability distribution graph of the trajectory distance information, diagonal information, and angle information of each to-be-matched section, such as a histogram, variance graph, etc., and analyzing the level value of the comprehensive information of the trajectory distance information, diagonal information, and angle information of each to-be-matched section according to the probability distribution graph, and taking the level value as the matching evaluation value of each to-be-matched section.

[0077] Taking the weighted sum as an example, in one embodiment, the matching evaluation value of each to-be-matched road section is determined according to the trajectory distance information, the diagonal information and the angle information, including: obtaining the weights corresponding to the trajectory distance information, the diagonal information and the angle information; and determining the weighted sum of the trajectory distance information, the diagonal information and the angle information as the matching evaluation value of each to-be-matched road section.

[0078] For example, any road segment among the road segments to be matched is represented as i, P i represents the matching evaluation value of any road segment to be matched; the trajectory distance information of the road segment to be matched is The diagonal information is The angle information is Assume that the weight of trajectory distance information is C1, the weight of diagonal information is C2, and the weight of angle information is C3; then In this way, the matching evaluation value of each to-be-matched road segment can be calculated in turn using this method.

[0079] S103: Determine a target matching road segment of the vehicle's driving path in the map according to the matching evaluation value of each to-be-matched road segment.

[0080] After the matching evaluation values ​​of the to-be-matched road sections are determined, the matching evaluation values ​​of the to-be-matched road sections are analyzed to determine the target matching road section of the vehicle's driving path in the map from the to-be-matched road sections.

[0081] Since the matching evaluation value reflects the reliability of the matching between each to-be-matched road segment and the vehicle's driving path, the larger the matching evaluation value, the higher the reliability. That is, for the road segment i, the larger the Pi, the higher the reliability of the matching of the road segment i. Based on this, in one implementation, the method of determining the target matching road segment is: the road segment corresponding to the maximum value of the matching evaluation value of each to-be-matched road segment is determined as the target matching road segment of the vehicle's driving path in the map. For example, among the to-be-matched road segments I1, I2, and I3, Pi is I2 >P I1 >P I3 , then the I2 section is the target matching section.

[0082] The embodiment of the present application provides a map matching method. If the driving path of a vehicle is a curved path, the trajectory distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section are obtained; and the matching evaluation value of each to-be-matched road section is determined according to the trajectory distance information, the diagonal information, and the angle information; and then the target matching road section of the vehicle's driving path in the map is determined according to the matching evaluation value of each to-be-matched road section. In this method, when obtaining the distance from the vehicle to each to-be-matched road section, the trajectory distance information is obtained, that is, the distance between two irregular sequences, so that the trajectory distance information can effectively reflect the distance between the vehicle's path and the to-be-matched road section, so that the accuracy of the distance from the vehicle to the road section obtained in the map matching process is greatly improved, thereby improving the accuracy of the final map matching result.

[0083] Based on the above embodiment, an embodiment is provided below to illustrate the trajectory distance information from the vehicle to the road section to be matched, the diagonal information between the vehicle and each road section to be matched, and the angle information between the vehicle and each road section to be matched.

[0084] like Figure 3 As shown, in one embodiment, an implementation method for obtaining trajectory distance information from a vehicle to a road section to be matched is provided, and the implementation method includes:

[0085] S201, obtaining the distances between the vehicle path sequence and the matching road segment sequence of each road segment to be matched at different times; the vehicle path sequence is a sequence composed of the current position of the vehicle and the historical trajectory of the vehicle; the matching road segment sequence is a sequence composed of the corresponding road segments to be matched.

[0086] The trajectory distance information is the distance between two sequences, so the distance between the sequence formed by the vehicle's driving path and the sequence formed by the road section to be matched. Specifically, the vehicle path sequence is the sequence formed by the vehicle's current position and the vehicle's historical trajectory, such as Figure 4 As shown, P N Point is the current position of the vehicle, P N P before the point N-1 , P N-2 , P N-3 ...... is a trajectory point in the vehicle's historical trajectory, then P N With P N-1 , P N-2 , P N-3 ......The sequence formed is the vehicle path sequence. Similarly, the road segment to be matched is itself a line segment, and the sequence formed by the points on the line segment is the matching road segment sequence. It should be noted that the road segments with the same ID in the map can form the same sequence.

[0087] Taking the time point as the sampling point, different time points correspond to a point in the vehicle path sequence and the matching road section sequence, such as Figure 5 As shown, assuming that the time points are t1, t2, t3, t4, and t5, the distances between the vehicle path sequence and the matching road segment sequence corresponding to each time point are obtained, that is, the distances d1, d2, d3, d4, and d5 between the vehicle path sequence and the matching road segment sequence corresponding to each time point t1, t2, t3, t4, and t5 are obtained respectively.

[0088] S202: Determine the minimum distance among the distances at different times as the trajectory distance information from the vehicle to each road section to be matched.

[0089] After determining the distances between the vehicle path sequence and the matching road segment sequence at different times, the minimum distance is determined as the trajectory distance information from the vehicle to each road segment to be matched.

[0090] For example, the vehicle path sequence is α, and the matching road segment sequence is β. Then the trajectory distance between the two sequences is determined by the following formula: δ F (P, Q) = min{maxd(P(α(t)), Q(β(t)))}, where α[0,1]→[0,N]; β[0,1]→[0,M]; t∈[0,1]. In this formula, P represents the vehicle's driving path trajectory, with a discarded length of N; Q represents the trajectory of the matching road segment sequence, with a length of M. Because the description of the position of each point on the vehicle path sequence and the matching road segment sequence can be characterized by a continuous increasing function with a time t as the variable, α(t) is used to represent the position description function at time t on the vehicle sequence, and β(t) is used to represent the position description function of the road segment to be matched at time t, and the variable t is constrained to the interval [0,1]. Then α(0) = 0, α(1) = N; β(0) = 0, β(0) = M. Let P(α(t)) and Q(β(t)) represent the spatial positions of the vehicle and each point on the to-be-matched road section at time t on their respective trajectories. Then the distance between the vehicle and the to-be-matched road section will vary with the differences in the α(t) and β(t) functions themselves and the change in the time variable t. Therefore, obtaining the trajectory distance information from the vehicle to each to-be-matched road section is equivalent to finding a pair of functions that minimize the maximum distance between the vehicle path sequence and the matching road section sequence, that is, determining the minimum distance among the distances at different times as the trajectory distance information from the vehicle to each to-be-matched road section.

[0091] In this embodiment, by obtaining the distances between the vehicle path sequence and the matching road section sequence of each road section to be matched at different times, and determining the minimum distance among the distances at different times as the trajectory distance information from the vehicle to each road section to be matched, when determining the distance from the vehicle to the road section to be matched, the distance between the vehicle driving sequence and the matching road section sequence is determined as a whole, rather than by the ordinary point-to-straight line distance, thereby greatly improving the accuracy of the distance from the vehicle to the road section.

[0092] like Figure 6 As shown, in one embodiment, an implementation method for obtaining diagonal information between a vehicle and each road section to be matched is provided, and the implementation method includes:

[0093] S301, obtaining the diagonal angle value of each to-be-matched road section according to the diagonal angle formed by the current position of the vehicle and each to-be-matched road section.

[0094] The diagonal angle formed by the current position of the vehicle and each road segment to be matched is equivalent to the diagonal angle of the midline of the triangle formed by the point and the line. For example, the current position of the vehicle is point P, and any road segment to be matched is the two end points A and B of i. Then, in the triangle formed by the two end points A and B of the road segment i and the vehicle point P, the diagonal angle of the road segment AB is ∠APB i .

[0095] For example, taking the to-be-matched road segment i as an example, obtain ∠APB i Angle value A i When the cos(∠APB i ) to determine, where So Among them, rad To deg means arccos(cos(∠APB i )) is converted into the corresponding value in degrees, that is, to calculate arccos(cos(∠APB i ))*180 / π.

[0096] S302: Determine the ratio between the diagonal angle value of each to-be-matched road section and the maximum diagonal angle value among the diagonal angle values ​​as the diagonal information between the vehicle and each to-be-matched road section.

[0097] After determining the diagonal angle value of each to-be-matched road section, the ratio between the diagonal angle value of each to-be-matched road section and the maximum diagonal angle value among all to-be-matched road sections is determined as the diagonal information between the vehicle and each to-be-matched road section. i The diagonal angle value of the road segment i to be matched, A max is the maximum diagonal angle value among all the road sections to be matched. Represents the diagonal information of the road segment i to be matched, then

[0098] For any road section i in each to-be-matched road section, the diagonal information can be calculated in this way, thereby obtaining the diagonal information between the vehicle and each to-be-matched road section. For the distance from the vehicle position point to the to-be-matched road section, the larger the diagonal angle value, the closer the vehicle is to the to-be-matched road section, so after calculating the diagonal information from the vehicle to each to-be-matched road section, the diagonal information itself can reflect the distance between the vehicle and each to-be-matched road section, so in the embodiment of the present application, the angle information is used as one of the factors of the matching evaluation value of each to-be-matched road section, which can greatly increase the accuracy of the matching evaluation value of each to-be-matched road section.

[0099] like Figure 7 As shown, in one embodiment, an implementation method for obtaining the angle information between the vehicle and each road section to be matched is provided, and the embodiment includes:

[0100] S401, obtaining the supplementary angle value of the angle of each to-be-matched road section according to the angle formed by the current position of the vehicle and each to-be-matched road section.

[0101] The angle between the current position of the vehicle and each road segment to be matched refers to the angle ∠PAB in the triangle formed by the line segment formed by the current position point P of the vehicle and the two endpoints AB of any road segment to be matched i. i , we can use H′ i Indicates that H′ i is the angle formed by the vehicle P and the road section AB. According to the angle, the angle value of the supplementary angle of the angle needs to be obtained, so for each road section to be matched, the angle value of the supplementary angle of the angle formed by the vehicle and the road section needs to be obtained.

[0102] Let H i is the supplementary angle of the angle formed by the vehicle and the road section AB, then H i =180-H′ i Among them, the angle H′ formed by vehicle P and road section AB i It can be calculated based on the angle formed by the road section AB and the true north direction and the angle formed by the vehicle and the true north direction (heading angle).

[0103] Specifically, For section AB and due north The angle formed by the vehicle and the north direction is ∠Veh, where The cosine value is:

[0104] So, That is, if If the difference with ∠Veh is greater than 180 degrees, then the angle H′ formed by vehicle P and road section AB is i For 360 degrees minus The difference between ∠Veh, otherwise, the angle H′ formed by vehicle P and road section AB i for The difference with ∠Veh.

[0105] S402: Determine the ratio between the supplementary angle value of the angle of each to-be-matched road section and the maximum supplementary angle value among the supplementary angle values ​​of each angle as the angle information between the vehicle and each to-be-matched road section.

[0106] After determining the supplementary angle value of each to-be-matched road section, the ratio between the supplementary angle value of each to-be-matched road section and the maximum supplementary angle value among all to-be-matched road sections is determined as the angle information between the vehicle and each to-be-matched road section.

[0107] For example, H i H is the complementary angle between the vehicle and the road section i to be matched, max is the maximum angle among all the angles in the road sections to be matched, is the angle information of the road section i to be matched, then

[0108] Similarly, for any road section i in each to-be-matched road section, the angle information can be calculated in this way, thereby obtaining the angle information between the vehicle and each to-be-matched road section. The angle information itself can also reflect the positional relationship between the vehicle and each to-be-matched road section, so in the embodiment of the present application, the angle information is used as one of the factors of the matching evaluation value of each to-be-matched road section, which can greatly increase the accuracy of the matching evaluation value of each to-be-matched road section.

[0109] The embodiment of the present application is aimed at the case where the driving path of the vehicle is a curved path, so it is necessary to determine whether the driving path of the vehicle is on a curved path. Based on this, Figure 8 As shown, in one embodiment, the process of determining whether the driving path of the vehicle is a curved path includes:

[0110] S501, according to the track points in the historical track of the vehicle and the current position point of the vehicle, obtaining the path length formed by a preset number of track points in the historical track and the current position point.

[0111] This embodiment may be performed before obtaining the track distance information between the vehicle and at least one to-be-matched road segment in the target map search range. Figure 4 The P shown N Point is the current position of the vehicle, P N P before the point N-1 , P N-2 , P N-3 ......are trajectory points in the historical trajectory of the vehicle.

[0112] When selecting a path to be evaluated, the trajectory point closest to the current position of the vehicle can be selected. For example, the four nearest trajectory points and the current position of the vehicle are used as the evaluation path from the historical trajectory, and then the total length of the evaluation path composed of the four trajectory points and the current position of the vehicle is obtained.

[0113] Specifically, the four trajectory points in the historical trajectory are P N-1 , P N-2 , P N-3 , P N-4 , then the four trajectory points form a small segment, and the distance from PN-1 to PN-4 is expressed as len PH ,but Among them, i represents the track point number, and Dist is the chord length formula. Similarly, among PN-1, PN-2, PN-3, and PN-4, PN-1 is the point closest to the current position PN of the vehicle among the four points, so the chord length Dist (P N-1 ,P N ), then Dist(P N-1 ,P N ) and len PH The sum of is determined as the total length of the entire evaluation path; that is, the path length consisting of the preset number of trajectory points and the current position point in the historical trajectory finally obtained is: len all =len PH +Dist(P1,P next ).

[0114] S502: If the path length and the number of track points in the historical track meet a first preset condition, it is determined that the driving path of the vehicle is a curved path.

[0115] After determining the path length formed by a preset number of trajectory points in the historical trajectory and the current position point, it is determined whether the path length and the number of trajectory points in the historical trajectory meet a first preset condition. Here, the first preset condition is pre-set and can be directly obtained for determination when used. For example, the first preset condition is that the derivative of the path length is less than or equal to 1, and the derivative of the number of trajectory points in the historical trajectory is not 0.

[0116] Specifically, let the curve flag be flagCurve, then:

[0117] That is, Pi represents a certain path, the derivative of the path length (total chord length) is greater than 1 and the derivative of the number of trajectory points PH stored in the historical trajectory is 0, then it is determined that the vehicle's driving path is not a curved path and the vehicle is driving on a straight road, otherwise, the vehicle's path is a curved path.

[0118] The embodiment of the present application uses the vehicle's current position point and a preset number of historical trajectory points as an evaluation path, and determines the shape of the evaluation path through the path length and storage points of the evaluation path, so that when the first preset condition is met, it is determined that the vehicle path is a curved path, making the result of determining whether the vehicle path is a curved path more accurate.

[0119] Each track point in the historical track of the vehicle can be determined in advance or in real time, such as Fig. 9 As shown, in one embodiment, the process of generating track points in the historical track of the vehicle includes:

[0120] S601, obtaining first driving information of a first sampling point and second driving information of a second sampling point in a historical trajectory of a vehicle; the first sampling point and the second sampling point are any two sampling moments.

[0121] The first sampling point and the second sampling point are any two sampling points in the historical trajectory of the vehicle. The present embodiment does not limit the location and sampling time of the sampling points. For example, there are three GNSS (Global Navigation Satellite System) data sampling points, which are sampling points P at the current sampling time. next , the sampling point P at the previous sampling time previous , the sampling point P at the last two sampling moments start , then the first sampling point and the second sampling point can be P start , P next .

[0122] The driving information may include but is not limited to the longitude and latitude information corresponding to each sampling point of the vehicle. Taking the longitude and latitude information as an example, the longitude and latitude information of the vehicle can be collected from the GPS of the vehicle to obtain the longitude and latitude information of the first sampling point and the longitude and latitude information of the second sampling point.

[0123] S602: Determine, based on the first driving information and the second driving information, an actual maximum error between a distance from a straight line connecting the first sampling point and the second sampling point to a curved path and a radius of the curved path.

[0124] According to the driving information of the vehicle at the first sampling point and the second sampling point, the distance from the straight line between the first sampling point and the second sampling point to the curved path is first determined, and then the actual maximum error between the distance and the radius of the curved path is determined. The actual maximum error here represents the error between the distance between the straight line (chord length) connecting the first sampling point and the second sampling point and the road (curved path) with an actual curvature radius, and the road radius (the actual half of the curved path). See Figure 1b The error between PH_ActualError in and the actual radius R of the curve path.

[0125] The straight line connecting the first sampling point and the second sampling point is equivalent to the chord length between the first sampling point and the second sampling point. Therefore, optionally, a method for determining the actual maximum error includes: determining the chord length between the first sampling point and the second sampling point according to the first driving information and the second driving information; determining the radius of curvature of the arc between the first sampling point and the second sampling point according to the chord length; determining the vertical distance from the center of the circle to the chord length according to the radius of curvature of the arc; and determining the difference between the radius of curvature of the arc and the vertical distance as the actual maximum error.

[0126] Specifically, the first sampling point and the second sampling point are P start , P next For example, let P start , P next The chord length between is expressed as PH_ActualChordLength, then PH_ActualChordLength = Dist(P start ,P next ), where Dist is the chord length. Then, combined with the aforementioned driving information of the vehicle at the first sampling point and the second sampling point, the driving information of the vehicle at the first sampling point and the second sampling point is substituted into the following formula Dist(P start ,P next )=REarthMeridian*cos -1 [cos(lat start )cos(lat next )cos(long start -long next )+sin(lat start )sin(lat next )], the P start , P next The length of the chord between. In this formula, lat start ,long start P start Latitude and longitude, lat next ,long next P next latitude and longitude, REarthMeridian represents the radius of the earth, which is a constant.

[0127] After obtaining the chord length between the first sampling point and the second sampling point (the straight-line distance between the first sampling point and the second sampling point), the curvature radius of the arc formed by the first sampling point and the second sampling point is calculated according to the chord length. start , P nextFor example, assuming the radius of curvature is PH_EstimatedR, then according to PH_EstimatedR = PH_ActualChordLength / (2*sin(ΔΦ / 2)), the radius of curvature of the arc formed by the first sampling point and the second sampling point can be determined by substituting the chord length. start and P next The angle between them and the line connecting the center of the circle is ΔΦ (radian), ΔΦ=H1-H2, H1 is P start The GNSS (Global Navigation Satellite System) positioning direction angle of the vehicle’s location, H2 is P next The GNSS (Global Navigation Satellite System) positioning direction angle of the vehicle's location, the positioning direction angle can be directly obtained through the Global Navigation Satellite System.

[0128] Furthermore, the vertical distance from the center of the circle to the chord length of the first sampling point and the second sampling point can be determined according to the radius of curvature of the arc formed by the first sampling point and the second sampling point. Let d represent the vertical distance, then according to the formula d=PH_EstimatedR*cos(ΔΦ / 2), the value of d can be obtained by substituting the radius of curvature and the value of the above ΔΦ. Finally, the difference between the radius of curvature PH_EstimatedR of the arc and the vertical distance d is determined as the actual maximum error PH_ActualError, PH_ActualError=PH_EstimatedR-d.

[0129] S603: If the actual maximum error is greater than a preset value, determine the first sampling point and the second sampling point as trajectory points.

[0130] Determine whether the first sampling point and the second sampling point are trajectory points according to the actual maximum error, and store the two trajectory points if they are trajectory points. For example, if ActualError>2(m), determine whether the first sampling point and the second sampling point are trajectory points, and store the first sampling point and the second sampling point in the historical trajectory. Since the first sampling point and the second sampling point represent any two sampling points, that is, each sampling point in the vehicle trajectory can be determined according to this method to determine whether to be stored as a trajectory point, and finally each trajectory point in the vehicle historical trajectory is a trajectory point that satisfies the actual maximum error greater than the preset value.

[0131] The trajectory point generation process provided in this embodiment determines that a sampling point is a trajectory point only if the actual maximum error of the sampling point is greater than a preset value, thereby ensuring that the selected historical trajectory points are all trajectory points on the curve path, thereby improving the accuracy of the distance from the vehicle to the road section.

[0132] In the process of map matching, it is necessary to determine each road section to be matched from the target map search range, so an embodiment is provided, such as Fig.10 As shown, this embodiment involves the specific process of determining the target map search range and determining each to-be-matched road segment from the target map search range. This embodiment includes:

[0133] S701, determining a target map search range according to the track points in the historical track of the vehicle and the current position point of the vehicle.

[0134] This embodiment can be executed before any step of using each road section to be matched and the target search map to facilitate timely data update. When determining the target search range, a target search radius can be determined by taking the current position point of the vehicle as the center of the circle, and then a target search range is formed. For example, the search radius can be determined based on the head and tail of the vehicle's historical trajectory points, or it can be set in advance based on an empirical value, which is not limited in this embodiment of the present application.

[0135] In one implementation, the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate can be determined based on the coordinates of a preset number of trajectory points in the historical trajectory, the coordinates of the current position point, and a preset search radius; and the range formed by the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate is determined as the target map search range.

[0136] For example, the four track points closest to the current position of the vehicle are determined from the historical track, and the coordinates of the four track points and the coordinates of the current position of the vehicle are obtained, wherein these coordinates represent the coordinate information in the map. For example, the coordinates of the current position of the vehicle are (X veh , Y veh ), the coordinates of the four historical trajectory points are expressed as (X ph(4) , Y ph(4) ), it should be noted that the coordinates of the four historical trajectory points are represented in an overall form here, but in actual application, each historical trajectory point can be used as a unit to calculate the target search range, or the four historical trajectory points with the largest X coordinate and the largest Y coordinate can be selected as representatives to participate in the calculation of the target search range, and the embodiments of the present application are not limited to this.

[0137] The following provides a specific calculation process for the target search range, with the preset search radius being R search , then first combine the vehicle's current position coordinate information (X veh , Y veh ) Determine the maximum X coordinate of the vehicle Minimum vehicle X coordinate Maximum value of vehicle Y coordinate Minimum vehicle Y coordinate

[0138]

[0139] Similarly, according to the coordinates of the four historical trajectory points (X ph(4) , Y ph(4) ), determine the maximum X coordinate of the trajectory point Minimum X coordinate of track point Maximum Y coordinate of the track point Minimum Y coordinate of track point

[0140]

[0141] Here (X ph(4) , Y ph(4) ) can be a value with the largest X coordinate and the largest Y coordinate selected from the four historical trajectory points, or it can represent the coordinate value of any trajectory point among the four historical trajectory points.

[0142] according to Select the final maximum X coordinate value X from the above calculated vehicle X, Y maximum values ​​and trajectory point X, Y maximum values max , minimum X coordinate value X min , Y coordinate maximum value Y max , minimum Y coordinate value Y min Thus, the range formed by the maximum and minimum values ​​of the X coordinate, and the maximum and minimum values ​​of the Y coordinate is determined as the target map search range.

[0143] S702: Determine the road sections that meet the second preset condition in the target map search range as the curved road sections to be matched; the second preset condition is that one of the endpoints of the curved road section to be matched is within the target search range.

[0144] After determining the maximum X coordinate X max , minimum X coordinate value X min , Y coordinate maximum value Y max , minimum Y coordinate value Y min After the target map search range is formed, the road sections in the target map search range that meet the second preset condition are determined as the curved road sections to be matched. The second preset condition here is that one of the endpoints of the curved road section to be matched is in the target search range.

[0145] For example: Based on the segment ID (each segment has an ID to distinguish different segments), the segments with the same upstream and downstream node IDs (segments with the same upstream and downstream node IDs are a segment sequence) and continuous segments are integrated into one path. Assuming that the endpoints of any segment are A and B, then the coordinates of the endpoint A of the segment are (X A , Y A ), the coordinates of the B endpoint of the segment are (XB , Y B ), as long as any coordinate meets the second preset condition, the road section is determined to be a road section to be matched. The second preset condition can be expressed as: That is, the coordinates of endpoint A are (X A , Y A ) is in X min and X max Or, the coordinate of endpoint B is Y max and Y min The road segments within the range belong to the road segments to be matched.

[0146] This embodiment determines all the road sections to be matched according to the determined target search range. The target search range is a range determined in combination with the current position of the vehicle. The road sections within the range are determined as the road sections to be matched, so that the road sections participating in the matching during map matching are all the road sections that are most likely to be the vehicle's travel path, avoiding the matching process on the road sections that are far away from the vehicle's position and cannot be the vehicle's path, saving resources, and thus improving map matching efficiency.

[0147] like Fig.11 As shown, in one embodiment, a map matching method is also provided, the method comprising:

[0148] S1, obtaining first driving information of a first sampling point and second driving information of a second sampling point in a historical trajectory of the vehicle; the first sampling point and the second sampling point are any two sampling moments; and determining a chord length between the first sampling point and the second sampling point according to the first driving information and the second driving information.

[0149] S2, determining the radius of curvature of the arc between the first sampling point and the second sampling point according to the chord length; and determining the vertical distance from the center of the circle to the chord length according to the radius of curvature of the arc.

[0150] S3, determining the difference between the arc curvature radius and the vertical distance as the actual maximum error; if the actual maximum error is greater than a preset value, determining the first sampling point and the second sampling point as trajectory points.

[0151] S4, determining the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate according to the coordinates of a preset number of trajectory points in the historical trajectory, the coordinates of the current position point, and the preset search radius; and determining the range formed by the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate as the target map search range.

[0152] S5, determining the road sections that meet the second preset condition in the target map search range as the curved road sections to be matched; the second preset condition is that one of the endpoints of the curved road section to be matched is within the target search range.

[0153] S6, based on the trajectory points in the historical trajectory of the vehicle and the current position points of the vehicle, obtain the path length formed by a preset number of trajectory points in the historical trajectory and the current position points; if the path length and the number of trajectory points in the historical trajectory meet a first preset condition, determine that the vehicle's driving path is a curved path.

[0154] S7, obtaining the track distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section.

[0155] Among them, obtaining trajectory distance information includes: obtaining the distances between the vehicle path sequence and the matching section sequence of each to-be-matched section at different times; the vehicle path sequence is a sequence composed of the current position of the vehicle and the historical trajectory of the vehicle; the matching section sequence is a sequence corresponding to each to-be-matched section; and the minimum distance among the distances at different times is determined as the trajectory distance information from the vehicle to each to-be-matched section.

[0156] The process of obtaining diagonal information: according to the diagonal formed by the current position of the vehicle and each road section to be matched, the diagonal angle value of each road section to be matched is obtained; the ratio between the diagonal angle value of each road section to be matched and the maximum diagonal angle value among the diagonal angle values ​​is determined as the diagonal information between the vehicle and each road section to be matched.

[0157] The process of obtaining the angle information: according to the angle formed by the current position of the vehicle and each road section to be matched, the supplementary angle value of the angle of each road section to be matched is obtained; the ratio between the supplementary angle value of the angle of each road section to be matched and the maximum supplementary angle value among the supplementary angle values ​​of each angle is determined as the angle information between the vehicle and each road section to be matched.

[0158] S8, obtaining weights corresponding to the trajectory distance information, the diagonal information and the angle information; and determining the weighted sum of the trajectory distance information, the diagonal information and the angle information as the matching evaluation value of each to-be-matched road segment.

[0159] S9, determining the road section corresponding to the maximum value among the matching evaluation values ​​of each to-be-matched road section as the target matching road section of the vehicle's driving path in the map.

[0160] It should be understood that, although the various steps in the flow chart of the above-described embodiment are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flow chart of the above-described embodiment may include a plurality of steps or a plurality of stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the steps or stages in other steps.

[0161] In one embodiment, Fig.12 As shown, a map matching device is provided, the device comprising: an acquisition module 10, a determination module 11 and a matching module 12, wherein:

[0162] The acquisition module 10 is used to acquire the track distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section if the driving path of the vehicle is a curved path;

[0163] A determination module 11 is used to determine the matching evaluation value of each to-be-matched road section according to the trajectory distance information, the diagonal information and the angle information;

[0164] The matching module 12 is used to determine the target matching road section of the vehicle's driving path in the map according to the matching evaluation value of each to-be-matched road section.

[0165] In one embodiment, the acquisition module 10 includes:

[0166] A distance acquisition unit is used to acquire the distance between the vehicle path sequence and the matching road segment sequence of each road segment to be matched at different times; the vehicle path sequence is a sequence composed of the current position of the vehicle and the historical trajectory of the vehicle; the matching road segment sequence is a sequence composed of each road segment to be matched;

[0167] The distance determination unit is used to determine the minimum distance among the distances at different times as the trajectory distance information from the vehicle to each road section to be matched.

[0168] In one embodiment, the acquisition module 10 includes:

[0169] A diagonal acquisition unit, used to acquire the diagonal angle value of each to-be-matched road section according to the diagonal formed by the current position of the vehicle and each to-be-matched road section;

[0170] The diagonal determination unit is used to determine the ratio between the diagonal angle value of each to-be-matched road section and the maximum diagonal angle value among the diagonal angle values ​​as the diagonal information between the vehicle and each to-be-matched road section.

[0171] In one embodiment, the acquisition module 10 includes:

[0172] An angle acquisition unit, used to acquire the supplementary angle value of the angle of each to-be-matched road section according to the angle formed by the current position of the vehicle and each to-be-matched road section;

[0173] The angle determination unit is used to determine the ratio between the supplementary angle value of the angle of each to-be-matched road section and the maximum supplementary angle value among the supplementary angle values ​​of each angle as the angle information between the vehicle and each to-be-matched road section.

[0174] In one embodiment, the apparatus further comprises:

[0175] A path length acquisition module, used to acquire the path length consisting of a preset number of trajectory points in the historical trajectory and the current position point according to the trajectory points in the historical trajectory of the vehicle and the current position point of the vehicle;

[0176] The curve path determination module is used to determine that the vehicle's driving path is a curve path if the path length and the number of trajectory points in the historical trajectory meet a first preset condition.

[0177] In one embodiment, the apparatus further comprises:

[0178] A driving information acquisition module, used to acquire first driving information of a first sampling point and second driving information of a second sampling point in a historical track of the vehicle; the first sampling point and the second sampling point are any two sampling moments;

[0179] An error determination module, used to determine an actual maximum error between a distance from a straight line connecting the first sampling point and the second sampling point to a curved path and a radius of the curved path according to the first driving information and the second driving information;

[0180] The trajectory point determination module is used to determine the first sampling point and the second sampling point as trajectory points if the actual maximum error is greater than a preset value.

[0181] In one embodiment, the error determination module is specifically used to determine the chord length between the first sampling point and the second sampling point based on the first driving information and the second driving information; determine the radius of curvature of the arc between the first sampling point and the second sampling point based on the chord length; determine the vertical distance from the center of the circle to the chord length based on the radius of curvature of the arc; and determine the difference between the radius of curvature of the arc and the vertical distance as the actual maximum error.

[0182] In one embodiment, the apparatus further comprises:

[0183] A search range determination module, used to determine the target map search range based on the track points in the historical track of the vehicle and the current position point of the vehicle;

[0184] The module for determining the curved road segment to be matched is used to determine the road segments in the target map search range that meet the second preset condition as the curved road segments to be matched; the second preset condition is that one of the endpoints of the curved road segment to be matched is in the target search range.

[0185] In one embodiment, the search range determination module is specifically used to determine the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate according to the coordinates of a preset number of trajectory points in the historical trajectory, the coordinates of the current position point, and a preset search radius; and determine the range formed by the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate as the target map search range.

[0186] In one embodiment, the determination module 11 includes:

[0187] A weight acquisition unit, used to acquire weights corresponding to the track distance information, the diagonal information and the angle information;

[0188] The evaluation value determination unit is used to determine the weighted sum of the trajectory distance information, the diagonal information and the included angle information as the matching evaluation value of each to-be-matched road section.

[0189] In one embodiment, the matching module 12 is specifically configured to determine the road section corresponding to the maximum value among the matching evaluation values ​​of each to-be-matched road section as the target matching road section of the vehicle's driving path in the map.

[0190] For the specific definition of the map matching device, please refer to the definition of the map matching method above, which will not be repeated here. Each module in the above-mentioned map matching device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0191] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.13As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a map matching method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0192] Those skilled in the art will understand that Fig.13 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0193] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0194] If the driving path of the vehicle is a curved path, obtaining the track distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section;

[0195] Determine the matching evaluation value of each to-be-matched road section according to the trajectory distance information, diagonal information and included angle information;

[0196] According to the matching evaluation value of each to-be-matched road section, the target matching road section of the vehicle's driving path in the map is determined.

[0197] The above embodiment provides a computer device, whose implementation principle and technical effect are similar to those of the above method embodiment, and will not be repeated here.

[0198] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0199] If the driving path of the vehicle is a curved path, obtaining the track distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section;

[0200] Determine the matching evaluation value of each to-be-matched road section according to the trajectory distance information, diagonal information and included angle information;

[0201] According to the matching evaluation value of each to-be-matched road section, the target matching road section of the vehicle's driving path in the map is determined.

[0202] The above embodiment provides a computer-readable storage medium, whose implementation principle and technical effect are similar to those of the above method embodiment, and will not be repeated here.

[0203] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0204] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0205] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A map matching method, characterized in that: The method comprises: If the driving path of the vehicle is a curved path, obtaining the track distance information between the vehicle and at least one to-be-matched road section in the target map search range, the diagonal information between the vehicle and each to-be-matched road section, and the angle information between the vehicle and each to-be-matched road section; According to the trajectory distance information, the diagonal information and the included angle information, the matching evaluation value of each of the to-be-matched sections is determined; the trajectory distance information is the minimum value of the distance between the vehicle path sequence and the matching section sequence of each of the to-be-matched sections at different times; the diagonal information is the ratio between the diagonal angle value of each of the to-be-matched sections and the maximum diagonal angle value among the diagonal angle values; the included angle information is the ratio between the supplementary angle value of the included angle of each of the to-be-matched sections and the maximum supplementary angle value among the supplementary angle values ​​of the included angles; According to the matching evaluation value of each of the to-be-matched road sections, a target matching road section of the vehicle's driving path in the map is determined.

2. The method according to claim 1, characterized in that The vehicle path sequence is a sequence formed by the current position of the vehicle and the historical trajectory of the vehicle; the matching road segment sequence is a sequence formed by the corresponding road segments to be matched.

3. The method according to claim 1, characterized in that The method further comprises: According to the diagonal angle formed by the current position of the vehicle and each of the to-be-matched road sections, the diagonal angle value of each of the to-be-matched road sections is obtained.

4. The method according to claim 1, characterized in that: The method further comprises: According to the angle formed by the current position of the vehicle and each of the to-be-matched road sections, the supplementary angle value of the angle of each of the to-be-matched road sections is obtained.

5. The method according to any one of claims 1 to 4, characterized in that: Before acquiring the trajectory distance information between the vehicle and at least one to-be-matched road section in the target map search range, the method further includes: According to the track points in the historical track of the vehicle and the current position point of the vehicle, obtaining a path length formed by a preset number of track points in the historical track and the current position point; If the path length and the number of trajectory points in the historical trajectory meet a first preset condition, it is determined that the driving path of the vehicle is a curved path.

6. The method according to claim 5, characterized in that The process of generating trajectory points in the historical trajectory of the vehicle includes: Acquire first driving information of a first sampling point and second driving information of a second sampling point in the historical trajectory of the vehicle; the first sampling point and the second sampling point are any two sampling moments; Determine, according to the first driving information and the second driving information, an actual maximum error between a distance from a straight line connecting the first sampling point and the second sampling point to the curved path and a radius of the curved path; If the actual maximum error is greater than a preset value, the first sampling point and the second sampling point are determined to be the trajectory points.

7. The method according to claim 6, characterized in that The determining, according to the first driving information and the second driving information, an actual maximum error between a distance from a straight line connecting the first sampling point and the second sampling point to the curved path and a radius of the curved path comprises: determining a chord length between the first sampling point and the second sampling point according to the first driving information and the second driving information; Determine, according to the chord length, a radius of curvature of an arc between the first sampling point and the second sampling point; Determine the vertical distance from the center of the circle to the chord length according to the arc curvature radius; The difference between the arc curvature radius and the vertical distance is determined as the actual maximum error.

8. The method according to any one of claims 1 to 4, characterized in that: Before acquiring the trajectory distance information between the vehicle and at least one to-be-matched road section in the target map search range, the method further includes: Determining the target map search range according to the track points in the historical track of the vehicle and the current position point of the vehicle; The road sections in the target map search range that meet the second preset condition are determined as the curved road sections to be matched; the second preset condition is that one of the endpoints of the curved road section to be matched is within the target search range.

9. The method according to claim 8, characterized in that The determining the target map search range according to the track points in the historical track of the vehicle and the current position point of the vehicle includes: Determine the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate according to the coordinates of a preset number of trajectory points in the historical trajectory, the coordinates of the current position point, and a preset search radius; The range formed by the maximum value and the minimum value of the X coordinate, and the maximum value and the minimum value of the Y coordinate is determined as the target map search range.

10. The method according to any one of claims 1 to 4, characterized in that: The determining, according to the trajectory distance information, the diagonal information and the included angle information, a matching evaluation value of each of the to-be-matched road sections comprises: Obtaining weights corresponding to the track distance information, the diagonal information, and the angle information; A weighted sum of the trajectory distance information, the diagonal information and the included angle information is determined as a matching evaluation value of each of the to-be-matched road sections.

11. The method according to any one of claims 1 to 4, characterized in that: Determining a target matching road segment of the vehicle's driving path in a map according to the matching evaluation value of each of the to-be-matched road segments includes: The road section corresponding to the maximum value among the matching evaluation values ​​of the to-be-matched road sections is determined as the target matching road section of the vehicle's driving path in the map.

12. A map matching device, characterized in that: The device comprises: an acquisition module, for acquiring, if the driving path of the vehicle is a curved path, track distance information between the vehicle and at least one to-be-matched road section in the target map search range, diagonal information between the vehicle and each to-be-matched road section, and angle information between the vehicle and each to-be-matched road section; A determination module, used to determine the matching evaluation value of each of the to-be-matched sections according to the trajectory distance information, the diagonal information and the included angle information; the trajectory distance information is the minimum value of the distance between the vehicle path sequence and the matching section sequence of each of the to-be-matched sections at different times; the diagonal information is the ratio between the diagonal angle value of each of the to-be-matched sections and the maximum diagonal angle value among the diagonal angle values; the included angle information is the ratio between the supplementary angle value of the included angle of each of the to-be-matched sections and the maximum supplementary angle value among the supplementary angle values ​​of the included angles; The matching module is used to determine the target matching section of the vehicle's driving path in the map according to the matching evaluation value of each of the to-be-matched sections.

13. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 11 are implemented.

14. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

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