Vehicle driving path monitoring method based on satellite positioning data

Abstract

The invention belongs to the technical field of vehicle driving path monitoring, and particularly relates to a vehicle driving path monitoring method based on satellite positioning data, which comprises the following steps of: 1, acquiring positioning data of a plurality of known points on a specified path; step 2, acquiring satellite positioning data in a vehicle driving process; 3, the positioning data of the known points on the specified path and the satellite positioning data in the vehicle driving process are sequentially displayed according to the path direction; 4, acquiring data obtained by mixing the positioning data on the specified path and the satellite positioning data in the vehicle driving process; 5, judging whether the vehicle runs according to a specified path or not; whether the vehicle runs according to the specified path or not is judged by calculating the approximate length of the path, the calculation complexity is remarkably reduced, meanwhile, dependence on electronic map data is not needed, map matching operation is not needed, dependence on other external data resources is reduced, and application and popularization are facilitated.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle driving path monitoring, and particularly relates to a vehicle driving path monitoring method based on satellite positioning data. Background Art

[0002] Satellite positioning data has a wide range of applications, especially playing a crucial role in the field of transportation. It can be used for planning travel routes and navigation, optimizing traffic signal control to improve traffic efficiency, real-time tracking and monitoring of logistics to achieve precise logistics scheduling, and so on.

[0003] For vehicles engaged in dangerous goods transportation, garbage transportation, construction, or other special transportation matters, it is usually required that relevant vehicles drive along designated routes. Therefore, we need to monitor and supervise such vehicles. Currently, the main supervision method is: based on the satellite positioning data provided by the vehicle's on-board equipment or the driver's smartphone, determine its position on the map, and then judge whether it drives along the designated route.

[0004] This type of supervision method highly depends on electronic maps. Secondly, map matching operations also need to be performed when determining the vehicle's position. Without an electronic map (the designated road is not added to the electronic map, or there is no service provided by the map provider), this supervision work is very difficult to carry out. Even if there is a publicly available electronic map that can be used, it is also necessary to perform the matching of vehicle satellite positioning data to the roads on the map, and its computational complexity and cost are relatively high. Summary of the Invention

[0005] The purpose of the present invention is to provide a vehicle driving path monitoring method based on satellite positioning data to solve the problems existing in the background art.

[0006] To achieve the above technical purpose, the technical solution adopted by the present invention is as follows:

[0007] A vehicle driving path monitoring method based on satellite positioning data,

[0008] including step 1: obtaining the positioning data of several known points on the designated path;

[0009] step 2: obtaining the satellite positioning data during the vehicle's driving process;

[0010] step 3: arranging the two types of positioning data, namely the positioning data of the known points on the designated path and the satellite positioning data during the vehicle's driving process, in the order of the path direction;

[0011] step 4: obtaining the data after mixing the positioning data on the designated path and the satellite positioning data during the vehicle's driving process;

[0012] Step 5: Determine whether the vehicle is traveling along the specified path.

[0013] Step 1 includes recording the positioning data of several known points on the specified path as:

[0014] (lat1, lon1, alt1), (lat2, lon2, alt2), (lat3, lon3, alt3), ……, (lat m-1 , lon m-1 , alt m-1 ), (lat m , lon m , alt m ), where lat k represents the longitude of the k-th point on the specified path, lon k represents the latitude of the k-th point on the specified path, alt k represents the altitude of the k-th point on the specified path, k = 1, 2, …, m;

[0015] Calculate the approximate length of the specified path as

[0016]

[0017] Step 2 includes recording the satellite positioning data obtained during the vehicle's travel as

[0018] (T1, Lat1, Lon1, Alt1), (T2, Lat2, Lon2, Alt2), (T3, Lat3, Lon3, Alt3),......, (T n-1 , Lat n-1 , Lon n-1 , Alt n-1 ), (T n , Lat n , Lon n , Alt n ), where T k represents the moment when the vehicle is traveling,

[0019] Lat k represents the longitude of the vehicle at time T k , Lon k represents the latitude of the vehicle at time T k , Alt k represents the altitude of the vehicle at time T k , k = 1, 2, …, n;

[0020] Calculate the approximate length of the vehicle's travel distance as

[0021]

[0022] The specific mixing method in step 3 is as follows:

[0023] Step 301: Determine the dotted-line box areas in sequence according to the positioning data of adjacent points on the specified path, hereinafter referred to as sorting box areas; for example, (lat k-1 , lon k-1 , alt k-1 ), (lat k , lon k , alt k ) The sorting box area (dotted-line box area) determined by these two points is

[0024]

[0025] Step 302: Put the positioning data during the vehicle's travel process into the sorting box areas in sequence according to the time sequence, and the serial number of the sorting box area where the vehicle's satellite positioning data at the later time point is located is greater than or equal to the serial number of the sorting box area where the vehicle's satellite positioning data at the previous time point is located.

[0026] According to the error of the positioning data, the sorting box area can be enlarged:

[0027]

[0028] Step 4 includes recording the data after mixing the positioning data on the specified path and the satellite positioning data during the vehicle's travel as

[0029] (LAT1, LON1, ALT1), (LAT2, LON2, ALT2), (LAT3, LON3, ALT3),......, (LAT m+n-1 , LON m+n-1 , ALT m+n-1 ), (LAT m+n , LON m+n , ALT m+n ), where LAT k represents longitude, LON k represents latitude, ALT k represents altitude, k = 1, 2,..., m + n;

[0030] Calculate the approximate length of the specified path or the vehicle's travel distance according to the mixed data as

[0031]

[0032] The judgment method in step 5 is:

[0033] Determine a threshold value, denoted as F;

[0034] If there is (or ) then the vehicle is traveling along the specified path;

[0035] If there is (or ) then the vehicle is not traveling along the specified path.

[0036] The present invention can reduce the computational complexity. The present invention only utilizes the positioning data of several known points on the specified path and the satellite positioning data during the vehicle's travel, and determines whether the vehicle is traveling along the specified path by calculating the approximate length of the path, significantly reducing the computational complexity.

[0037] Meanwhile, it gets rid of the dependence on electronic maps: The present invention does not need to rely on electronic map data, nor does it need to perform map matching operations. It can complete the judgment only relying on the position data of several points on the pre-collected specified path and the satellite positioning data during the vehicle's travel. This method reduces the dependence on other external data resources and is convenient for popularization and use.

[0038] The present invention introduces the concept of a sorting frame domain, mixes the positioning data on the specified path with the satellite positioning data during the vehicle's travel, and ensures that the two types of data appear sequentially in the path direction. This method not only simplifies the data processing process, but also can effectively cope with the errors of the positioning data. It can not only efficiently mix the data, but also perform parallel computing to improve efficiency. Steps 1, 2, and 3 can be calculated in parallel without waiting for the previous steps to complete, further improving the computational efficiency and saving costs. Brief Description of the Drawings

[0039] The present invention can be further illustrated by the non-limiting embodiments given in the drawings.

[0040] Figure 1 It is a schematic diagram of the sparsity of the positioning data of the present invention;

[0041] Figure 2 It is a schematic diagram of the approximate length of the specified path of the present invention;

[0042] Figure 3 It is a schematic diagram of the approximate length of the vehicle's travel distance of the present invention;

[0043] Figure 4 It is a schematic diagram of the (k - 1)-th sorting frame domain determined by two adjacent points on the specified path of the present invention;

[0044] Figure 5 It is a schematic diagram of the mixing of the sorting frame domain (cross-sectional view) and the positioning data of the present invention;

[0045] Figure 6 It is a schematic diagram of the enlarged sorting frame domain of the present invention;

[0046] Figure 7Schematic diagram of the approximate length of the specified path or the driving distance of the vehicle according to the present invention;

[0047] Figure 8 Schematic diagram of continuously approximating the length of the curve (or path) of the present invention with the length of a broken line;

[0048] Figure 9 Schematic diagram showing that the length of the curve (or path) of the present invention cannot be continuously approximated with the length of a non-inscribed broken line;

[0049] Figure 10 Schematic diagram of the specified path and the positioning points on different vehicle driving trajectories in the embodiment of the present invention. Detailed implementation manners

[0050] In order to enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0051] Embodiment 1: As Figure 1-10 shown, a vehicle driving path monitoring method based on satellite positioning data of the present invention:

[0052] First of all, it should be noted that satellite positioning data is not available at every moment during the vehicle driving process. We usually obtain the positioning data during the vehicle driving process at interval time nodes, for example, obtaining data every 5 seconds or 10 seconds. For the positioning data on the specified path, we also cannot obtain the data at each position, but only the data at several positions on the path. Obviously, even when the vehicle is driving on the specified path, the vehicle satellite positioning data we obtain and the positioning data of several points on the road will hardly coincide (from the perspective of geometric probability, the coincidence probability is almost 0). Therefore, we cannot simply judge whether the vehicle is driving along the specified route by "comparing" whether the positioning data on the road and the positioning data during the vehicle driving are approximately the same (there is an error in the positioning data). See the appendix Figure 1 shown;

[0053] Can we obtain the (approximate) positioning data of all other points on the specified path by using interpolation or fitting methods based on the positioning data of the known points on the specified path, and then compare the satellite positioning data during the vehicle driving process with the positioning data on the specified path to make a judgment? This is possible, but the computational amount of obtaining the positioning data of all points on the specified path by interpolation or fitting methods and then comparing whether the vehicle's satellite positioning data is near it is relatively large.

[0054] The characteristic of the method of the present invention is that it can judge whether the vehicle is driving along the specified path only by calculating the approximate length of the path based on the positioning data of several known points on the specified path and the satellite positioning data during the vehicle driving process.

[0055] The specific steps are as follows:

[0056] Step 1.

[0057] Record the positioning data of several known points on the specified path as

[0058] (lat1, lon1, alt1), (lat2, lon2, alt2), (lat3, lon3, alt3),......, (lat m-1 , lon m-1 , alt m-1 ), (lat m , lon m , alt m ), where lat k represents the longitude of the k-th point on the specified path, lon k represents the

[0059] latitude of the k-th point on the specified path, alt k represents the altitude of the k-th point on the specified path, k = 1, 2,..., m.

[0060] As shown in the appendix Figure 2 , calculate the approximate length of the specified path as

[0061]

[0062] Appendix Figure 2 Based on the appendix Figure 1 , the approximate length of the specified path is added.

[0063] It should be noted that the above distance formula between two points is given in a rectangular coordinate system. As long as the longitude-latitude-altitude coordinates are converted into rectangular coordinates according to the existing method.

[0064] Step 2.

[0065] Record the satellite positioning data obtained during the vehicle's driving as

[0066] (T1, Lat1, Lon1, Alt1), (T2, Lat2, Lon2, Alt2), (T3, Lat3, Lon3, Alt3),......, (T n-1 , Lat n-1 , Lon n-1 , Alt n-1 ), (T n , Lat n , Lon n , Alt n ), where T k represents the moment when the vehicle is driving,

[0067] Lat k represents the longitude of the moving vehicle T k at time, Lon k represents the latitude of the moving vehicle T k at time, Alt k represents the altitude of the moving vehicle T k at time, k = 1, 2, …, n.

[0068] As shown in the appendix Figure 3 the approximate length of the vehicle's travel distance is calculated as

[0069]

[0070] Appendix Figure 3 Based on the appendix Figure 1 the approximate length of the vehicle's travel distance is added.

[0071] Step 3.

[0072] Mix the positioning data of the known points on the specified path and the satellite positioning data during the vehicle's travel so that the two types of positioning data appear sequentially in the path direction.

[0073] The specific mixing method is as follows. Determine the dotted box area in sequence according to the positioning data of two adjacent points on the specified path, which is hereinafter referred to as the sorting box area. For example, (lat k-1 , lon k-1 , alt k-1 ), (lat k , lon k , alt k ) the sorting box area (dotted box area) determined by the two points is

[0074]

[0075] For example, the k - 1th sorting box area, as shown in the appendix Figure 4 shown;

[0076] Then, put the positioning data during the vehicle's journey into the sorting box area in chronological order. The serial number of the sorting box area where the vehicle's satellite positioning data at the later time point is located is greater than or equal to the serial number of the sorting box area where the vehicle's satellite positioning data at the previous time point is located, as shown in the appendix Figure 5 shown, appendix Figure 5 is the mixing of the sorting box area (cross-sectional schematic diagram) and the positioning data;

[0077] It should be noted that according to the error of the positioning data, the sorting box area can be appropriately enlarged, for

[0078]

[0079] For example, according to the road width and positioning error, expand by 10 meters, take ε = 10, as shown in the attached Figure 6 expanded sorting box area. Since normal driving roads are regular curves, if the satellite positioning data of the driving vehicle cannot be placed within the sorting box area, it is certain that the vehicle is not driving along the specified path.

[0080] Step 4.

[0081] Record the data after mixing the positioning data on the specified path and the satellite positioning data during the vehicle's driving as

[0082] (LAT1, LON1, ALT1), (LAT2, LON2, ALT2), (LAT3, LON3, ALT3),....., (LAT m+n-1 , LON m+n-1 , ALT m+n-1 ), (LAT m+n , LON m+n , ALT m+n ), where LAT k represents longitude, LON k represents latitude, ALT k represents altitude, k = 1, 2,..., m + n.

[0083] As shown in the attachment Figure 7 shown, calculate the approximate length of the specified path or the vehicle's driving distance according to the mixed data as

[0084]

[0085] Step 5.

[0086] Judge whether the vehicle is driving along the specified path. Determine a threshold, denoted as F.

[0087] If there is (or ), then the vehicle is driving along the specified path;

[0088] If there is (or ), then the vehicle is not driving along the specified path.

[0089] The judgment principle is as follows: The length of a curve (corresponding to the path) can be approximated by an inscribed broken line (corresponding to the connection of the positioning data points on the specified route or the connection of the satellite positioning data points at intervals of the driving vehicle). The length of the broken line is always less than the length of the curve. The more sampling points there are on the curve, that is, the more vertices of the inscribed broken line, the closer the length of the inscribed broken line is to the length of the curve. Therefore (or ).

[0090] Generally, the specified path itself is not too short or overly tortuous, and the driver does not drive dangerously (such as twisting the steering wheel left and right to make the driving curve abnormal), otherwise it can be visually judged whether the vehicle is driving in accordance with the specified

[0091] path specification. The positioning data points on the specified route (it can be arranged in advance for a regulatory vehicle to drive along the specified path to collect data or use open maps to collect data to ensure that there are enough sampling points) and the satellite positioning data points collected at intervals of the driving vehicle (positioning data can be obtained every few seconds) are usually sufficient, so the length of the inscribed broken line is also basically close to the path length, and thus (or ) is generally approximately equal to 1, that is not much greater than 1. Usually, taking F ∈ (1, 1.2) is sufficient. In short, the more sampling points on the specified path or the more satellite positioning data of the driving vehicle, the closer the threshold F can be to 1, as shown in the appendix Figure 8 .

[0092] The positioning data on the specified path and the satellite positioning data of the driving vehicle cannot be mixed, because it is obvious that the vehicle is not driving along the specified path and there is no need to calculate (or ). If the positioning data can be mixed and the vehicle is not driving along the specified path, then (or ) will have a relatively large value, as shown in the appendix Figure 9 .

[0093] In the above steps for judging whether the vehicle is driving along the specified path, step 1 does not need to be repeated and only needs to be executed once, and its result can be reused in the future. Step 3 does not need to wait for steps 1 and 2 to be completed before execution, and step 2 does not need to wait for step 1 to be completed before execution. Steps 1, 2, and 3 can be calculated in parallel.

[0094] In the above process of judging whether the vehicle is driving along the specified path, only several positioning data on the specified path and the positioning data during the vehicle driving process are used, without involving the electronic map (electronic map data), nor performing map matching operations to display the vehicle driving path on the electronic map for judgment. In addition, the above judgment method does not find or supplement the position data of other points on the specified path through other methods and calculations, and only uses the position data of several points on the pre-collected specified road. Therefore, this judgment method can get rid of the dependence on the electronic map, because the dependence on other external data resources is small, and the main calculation only involves the distance calculation between two points, with a low calculation complexity, which can greatly save the judgment cost and is also convenient for popularization and use. Specific embodiments:

[0096] Obtain the positioning data on a specified path in an approximately flat area (with little altitude change) and the driving trajectories of two vehicles A and B.

[0097] The positioning data of points R1, R2, …, R 10 on the specified path are:

[0098] R1 = (0, 0, 0), R2 = (10, 10, 0.1), R3 = (20, 20, 0), R4 = (30, 30, 0.2), R5 = (40, 40, 0.2),

[0099] R6 = (50, 50, 0.3), R7 = (60, 60, 0.2), R8 = (70, 70, 0.1), R9 = (80, 80, 0.1), R 10 = (90, 90, 0)

[0100] The satellite positioning data of points A1, A2, …, A5 during the driving of vehicle A: A1 = (5, 5, 0.5), A2 = (25, 25, 0),

[0101] A3 = (46, 46, 0.25), A4 = (64, 64, 0.2), A5 = (87, 87, 0.1)

[0102] The satellite positioning data of points B1, B2, …, B6 during the driving of vehicle B: B1 = (0, 0, 0), B2 = (20, 10, 0.1),

[0103] B3 = (40, 30, 0.2), B4 = (60, 50, 0.2), B5 = (80, 70, 0.1), B6 = (90, 80, 0)

[0104] ① Determine the enlarged sorting box area according to the positioning data on the specified path, enlarged by 5 meters, i.e., ε = 5, obtained from formula (4). Take the first and the last sorting box areas as examples.

[0105] The 1st enlarged sorting box area

[0106]

[0107] The 9th enlarged sorting box area

[0108]

[0109] It can be seen that A1 = (5, 5, 0.5) and B1 = (0, 0, 0) fall within the 1st sorting box area, while A5 = (87, 87, 0.1) and B6 = (90, 80, 0) fall within the 9th sorting box area.

[0110] ②According to the above-expanded sorting box area, the positioning data on the specified path and the satellite positioning data during the driving of vehicle A are mixed as: R1=(0, 0, 0), A1=(5, 5, 0.5), R2=(10, 10, 0.1), R3=(20, 20, 0), A2=(25, 25, 0), R4=(30, 30, 0.2), R5=(40, 40, 0.2), A3=(46, 46, 0.25), R6=(50, 50, 0.3), R7=(60, 60, 0.2), A4=(64, 64, 0.2), R8=(70, 70, 0.1), R9=(80, 80, 0.1), A5=(87, 87, 0.1), R 10 =(90, 90, 0);

[0111] According to the above-expanded sorting box area, the positioning data on the specified path and the satellite positioning data during the driving of vehicle B are mixed as: R1=(0, 0, 0)(B1=(0, 0, 0)), R2=(10, 10, 0.1), B2=(20, 10, 0.1), R3=(20, 20, 0), R4=(30, 30, 0.2), B3=(40, 30, 0.2), R5=(40, 40, 0.2), R6=(50, 50, 0.3), B4=(60, 50, 0.2), R7=(60, 60, 0.2), R8=(70, 70, 0.1), B5=(80, 70, 0.1), R9=(80, 80, 0.1), B6=(90, 80, 0), R 10 =(90, 90, 0).

[0112] ③Since the specified path is an approximately straight line and the length of the broken line formed by the sampling points on it is already close to the length of the specified path, at this time the threshold F is close to 1, and F = 1.1 can be taken.

[0113] ④Calculate the approximate length of the path according to the points R1, R2, …, R on the specified path. From formula (1), we get 10 S

[0114] S 指定路径 ≈127.26

[0115] Calculate the approximate length of the driving path of vehicle A according to the satellite positioning data A1, A2, A3, A4, A5 during the driving of vehicle A. From formula (2), we get

[0116] S 行驶路径A ≈117.37

[0117] Calculate the approximate length of the driving path of vehicle B according to the satellite positioning data B1, B2, B3, B4, B5 during the driving of vehicle B. From formula (2), we get

[0118] S 行驶路径B ≈121.34

[0119] According to the mixed data R1, A1, R2, R3, A2, R4, R5, A3, R6, R7, A4, R8, R9, A5, R of the positioning data on the specified path and the satellite positioning data during the driving of vehicle A 10 Calculate the approximate length of the path. From formula (5), we get

[0120] S 混合A ≈127.31

[0121] According to the mixed data R1(B1), R2, B2, R3, R4, B3, R5, R6, B4, R7, R8, B5, R9, B6, R of the positioning data on the specified path and the satellite positioning data during the driving of vehicle B 10 Calculate the approximate length of the path. From formula (5), we get

[0122] S 混合B ≈157.56

[0123] ⑤ Calculate the ratio of the lengths of each path

[0124]

[0125] In fact, since S 混合B becomes much larger and the corresponding ratio is greater than F, it can be inferred that vehicle B does not drive along the specified path, which is consistent with the intuitive observation.

[0126] The present invention overcomes the problems of severe dependence on electronic maps and the complexity of map matching calculations in the existing vehicle driving path supervision methods. It is a supervision method that does not rely on electronic maps and does not require using open maps for road matching. It can determine whether a vehicle drives along the specified path only by using the sparse positioning data on the specified path and the sparse positioning data during the vehicle driving, reducing costs and calculation complexity.

[0127] The above embodiments are only used to exemplarily illustrate the principles and effects of the present invention, rather than to limit the present invention. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes completed by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A vehicle driving path monitoring method based on satellite positioning data, characterized in that: The method comprises the steps of: obtaining positioning data of a plurality of known points on a specified path; Step 2: Obtain satellite positioning data during vehicle driving; Step 3: The two types of positioning data, namely the positioning data of known points on the designated path and the satellite positioning data during the vehicle's travel, appear in order according to the path direction; Step 4: Obtain the mixed data of the positioning data on the specified path and the satellite positioning data during the vehicle's driving process; Step 5: Determine whether the vehicle is traveling along the specified path.

2. The vehicle driving path monitoring method based on satellite positioning data according to claim 1 is characterized in that: The step 1 includes recording the location data of several known points on the specified path as: (lat1,lon1,alt1), (lat2,lon2,alt2), (lat3,lon3,alt3),..., (lat m-1 ,lon m-1 ,alt m-1 ), (lat m ,lon m ,alt m ), where lat k Indicates the longitude of the kth point on the specified path, lon k Indicates the latitude of the kth point on the specified path, alt k Indicates the altitude of the kth point on the specified path, k = 1, 2, ..., m; Calculate the approximate length of the specified path as 3. The vehicle driving path monitoring method based on satellite positioning data according to claim 1 is characterized in that: The step 2 includes recording the satellite positioning data obtained during the vehicle driving process as (T1,Lat1,Lon1,Alt1), (T2,Lat2,Lon2,Alt2), (T3,Lat3,Lon3,Alt3),..., (T n-1 ,Lat n-1 ,Lon n-1 ,Alt n-1 ), (T n ,Lat n ,Lon n ,Alt n ), where T k Indicates the time at which the vehicle is traveling. Lat k Indicates the moving vehicle T k Longitude at the moment, Lon k Indicates the moving vehicle T k The latitude of the moment, Alt k Indicates that the vehicle is moving T k The altitude at the time, k = 1, 2, ..., n; Calculate the approximate length of the vehicle's journey as 4. The vehicle driving path monitoring method based on satellite positioning data according to claim 1 is characterized in that: The specific mixing method of step 3 is as follows: Step 301: Determine the dotted-line box domain in sequence according to the positioning data of two adjacent points on the specified path, which is referred to as the sorting box domain below; for example (lat k-1 ,lon k-1 ,alt k-1 ), (lat k ,lon k ,alt k ) The sorting box domain (dashed box domain) determined by the two points is Step 302: The positioning data during the vehicle journey are placed into the sorting boxes in chronological order, and the sequence number of the sorting box where the vehicle satellite positioning data at the later time point is located is greater than or equal to the sequence number of the sorting box where the vehicle satellite positioning data at the earlier time point is located.

5. The vehicle driving path monitoring method based on satellite positioning data according to claim 4 is characterized in that: According to the error of positioning data, the sorting box can be expanded:

6. The vehicle driving path monitoring method based on satellite positioning data according to claim 1 is characterized in that: The step 4 includes recording the mixed data of the positioning data on the designated path and the satellite positioning data during the vehicle driving as (LAT1, LON1, ALT1), (LAT2, LON2, ALT2), (LAT3, LON3, ALT3), ..., (LAT m+n-1 ,LON m+n-1 ,ALT m+n-1 ), (LAT m+n ,LON m+n ,ALT m+n ), where LAT k Indicates longitude, LON k Indicates latitude, ALT k represents altitude, k = 1, 2, ..., m + n; Calculate the approximate length of a given route or vehicle trip based on mixed data:

7. The vehicle driving path monitoring method based on satellite positioning data according to claim 1 is characterized in that: The judgment method of step 5 is: Determine a threshold, denoted as F; If you have (or ), the vehicle is traveling along the designated path; If you have (or ), the vehicle does not follow the designated path.

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