A vehicle positioning system based on single Beidou positioning

Abstract

The present invention relates to the technical field of vehicle positioning. The present invention relates to a vehicle positioning system based on single Beidou positioning. It includes a fleet acquisition module, a truck queue combination module, an initial prediction position module, a driving prediction module, a distance prediction module, and a backup position selection module; the fleet acquisition module is used to obtain the transportation route of the logistics fleet; the truck queue combination module is used to monitor the position data of each truck's Beidou positioning, and at the same time obtain the set following distance between trucks, and then recombine the position data between trucks in combination with the following distance; by combining the driving speed and position data of the leading vehicle with the following distance to perform predictive position analysis on each truck in the fleet, and at the same time using the driving speed and position data of the trailing vehicle to perform the same operation, and then performing range overlap extraction analysis on the two predictive position results, the initial predictive position range of the truck can be determined more accurately.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle positioning, and specifically, to a vehicle positioning system based on single Beidou positioning. Background Art

[0002] In logistics transportation work, including scenarios such as long-distance freight transportation and urban distribution. In these scenarios, logistics enterprises need to monitor the positions of freight trucks in real time in order to coordinate transportation resources, arrange loading and unloading times, and respond to emergencies.

[0003] Currently, through the vehicle positioning system, the position and driving status of freight trucks can be mastered in real time, realizing effective monitoring and management of the logistics transportation process. Its purpose is to improve the efficiency of logistics transportation, ensure the safety of goods, and optimize transportation routes. However, in some complex environments, such as urban canyons with high-rise buildings, tunnels, underground parking lots, etc., the Beidou positioning system may experience signal occlusion or interference, resulting in inaccurate positioning. Secondly, when the Beidou positioning device is interfered, one can only wait for the device to return to normal, resulting in the management of the logistics fleet not being precise and efficient enough. In order to reduce this situation, a vehicle positioning system based on single Beidou positioning is proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a vehicle positioning system based on single Beidou positioning to solve the problems raised in the above background art.

[0005] To achieve the above purpose, a vehicle positioning system based on single Beidou positioning is provided, including a fleet acquisition module, a freight truck queue combination module, an initial predicted position module, a driving prediction module, a distance prediction module, and a backup position selection module;

[0006] The fleet acquisition module is used to acquire the transportation route of the logistics fleet and simultaneously acquire the planned queue order during the progress of the fleet;

[0007] The freight truck queue combination module is used to monitor the position data of each freight truck's Beidou positioning, and simultaneously acquire the set following distance between freight trucks, and then reorganize the queue by combining the position data between freight trucks with the following distance;

[0008] The initial predicted position module is used to acquire the driving speed of the freight trucks in the fleet, and then perform predicted position analysis on each freight truck in the fleet by combining the position data of the leading vehicle, the position data of the trailing vehicle, the driving speed, and the following distance, and perform range overlap analysis on the analysis results, and obtain the initial predicted position range of each freight truck according to the analysis results;

[0009] The driving prediction module is used to obtain the historical driving data of the truck during this transportation. When there is signal fluctuation, it predicts the subsequent driving of the truck based on the historical driving data and the transportation route, and obtains the predicted driving positions of each truck.

[0010] The distance prediction module is used to intercept the historical interval distances between trucks during the period before the signal fluctuation, and at the same time analyze the predicted distance positions of the trucks by combining the historical interval distances with the initial predicted position range.

[0011] The backup position selection module is used to compare the predicted driving positions with the initial predicted position range, and divide the priorities of position correction backup for the predicted driving positions and the predicted distance positions according to the comparison results.

[0012] As a further improvement of this technical solution, the fleet acquisition module obtains the transportation routes of each truck by associating data with the logistics management terminal, and at the same time classifies the trucks with the same transportation route and the same departure time into a logistics fleet, so as to obtain the transportation routes of each logistics fleet.

[0013] Obtain the planned queue order of the fleet during the driving process.

[0014] As a further improvement of this technical solution, the truck queue combination module includes a position monitoring module and a queue combination module.

[0015] The position monitoring module is used to install a Beidou positioning device on each truck, and then associate data with the Beidou positioning device, so as to obtain the position data fed back by the corresponding Beidou positioning device of each truck.

[0016] The queue combination module is used to collect the set following distances between trucks from the user at the logistics management terminal, and then reorganize the queues of the trucks during the driving process according to the position data. When the intervals between different trucks are within the following distances, they are classified into the same queue; otherwise, when the intervals between different trucks are not within the following distances, they are not classified into the same queue.

[0017] As a further improvement of this technical solution, the initial prediction position module obtains the driving speed of the truck by installing a speed sensor on the truck and then through the data fed back by the speed sensor.

[0018] As a further improvement of this technical solution, the initial prediction position module includes a prediction position analysis module and a prediction position range acquisition module.

[0019] The prediction position analysis module is used to analyze the predicted positions of each truck in the fleet by combining the driving speed and position data of the leading vehicle with the following distance, and at the same time analyze the predicted positions of each truck in the fleet by combining the driving speed and position data of the trailing vehicle with the following distance.

[0020] The predicted position range acquisition module is used to perform range overlap analysis on the two predicted position analysis results obtained by the predicted position analysis module, and use the same position prediction data in the two predicted position analysis results as the initial predicted position range of the truck.

[0021] As a further improvement of this technical solution, the prediction position analysis formula of the initial prediction position module based on the leading vehicle is as follows:

[0022]

[0023]

[0024] Among them, X pred1 and Y pred1 are the predicted position coordinates of the truck relative to the leading vehicle, V lead is the driving speed of the leading vehicle, X lead and Y lead are the position data of the leading vehicle, D follwo is the set following distance, t1 is the predicted time for the trailing vehicle to complete the transportation route, and the included angle between the driving direction of the leading vehicle and the positive direction of the x-axis is θ lead ;

[0025] The prediction position analysis formula based on the trailing vehicle is as follows:

[0026]

[0027]

[0028] Among them, X pred2 and Y pred2 are the predicted position coordinates of the truck relative to the trailing vehicle, V rear is the driving speed of the trailing vehicle, X rear and Y rear are the position data of the trailing vehicle, and the included angle between the driving direction of the trailing vehicle and the positive direction of the x-axis is θ rear ;

[0029]

[0030] Among them, d is the distance, the set overlap threshold is T. When d < T, it is considered that the positions overlap. After determining the position overlap, the overlapping position range is used as the initial predicted position range of the truck.

[0031] As a further improvement of this technical solution, the formula of the driving prediction module is as follows:

[0032]

[0033]

[0034] Among them, X0 and Y0 are the coordinates of the last stable position of the truck before signal fluctuation, V hist is the average speed of the truck in the historical data, the angle between the driving direction and the positive direction of the x-axis is θ, the predicted time for the rear truck to complete the transportation route after signal fluctuation is t2, X t and Y t are the predicted driving positions.

[0035] As a further improvement of this technical solution, the distance prediction module includes an interval distance acquisition module and a distance position prediction module;

[0036] The interval distance acquisition module is used to collect the historical interval data between the trucks saved most recently at the time of distance fluctuation when the Beidou positioning device of the truck is interfered and the feedback data fluctuates, and extract the trucks affected by the interference from the historical interval data to obtain the interval distances between this truck and the front and rear trucks;

[0037] The distance position prediction module is used to perform distance prediction position analysis on the truck according to the interval distances between this truck and the front and rear trucks in combination with the initial prediction position range, and perform accurate position prediction according to the interval distances within the initial prediction position range, so as to obtain the distance prediction position.

[0038] As a further improvement of this technical solution, the spare position selection module includes a range comparison module and a priority division module;

[0039] The range comparison module is used to compare the driving predicted position with the initial prediction position range;

[0040] The priority division module is used to perform priority division according to the display result of the range comparison module. When the driving predicted position is within the initial prediction position range, the priority of the driving predicted position is the highest, and the driving predicted position is used as the correction spare position. On the contrary, when the driving predicted position is not within the initial prediction position range, the priority of the distance prediction position is the highest, and the distance prediction position is used as the correction spare position;

[0041] When the position data fed back by the Beidou positioning device does not conform to the transportation route, the correction spare position is used as the truck position until the position data fed back by the Beidou positioning device returns to normal.

[0042] Compared with the prior art, the beneficial effects of the present invention:

[0043] 1. In the vehicle positioning system based on single Beidou positioning, by combining the driving speed and position data of the leading vehicle with the following distance to analyze the predicted positions of each truck in the convoy, and at the same time using the driving speed and position data of the trailing vehicle to perform the same operation, and then performing range overlap extraction analysis on the two predicted position results, the initial predicted position range of the truck can be determined more accurately. This multi-source data fusion method can effectively compensate for the errors that may occur in single Beidou positioning in some complex environments, enabling the position of the truck to be determined relatively accurately even when the Beidou positioning signal fluctuates or is temporarily lost. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is the overall structural schematic diagram of the present invention.

[0045] The meanings of the various reference numerals in the figure are as follows:

[0046] 10. Convoy acquisition module; 20. Truck queue combination module; 30. Initial predicted position module; 40. Driving prediction module; 50. Distance prediction module; 60. Spare position selection module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] Please refer to Figure 1 As shown, the purpose of this embodiment is to provide a vehicle positioning system based on single Beidou positioning, including a convoy acquisition module 10, a truck queue combination module 20, an initial predicted position module 30, a driving prediction module 40, a distance prediction module 50, and a spare position selection module 60;

[0049] The convoy acquisition module 10 is used to acquire the transportation route of the logistics convoy and at the same time acquire the planned queue order of the convoy during the driving process;

[0050] The convoy acquisition module 10 obtains the transportation route of each truck by associating data with the logistics management terminal. At the same time, the trucks with the same transportation route and the same departure time are classified into a logistics convoy, so as to obtain the transportation route of each logistics convoy;

[0051] To obtain the planned queue order of the convoy during the driving process, the specific working steps are as follows:

[0052] Obtain the truck transportation route: Establish a communication interface with the logistics management terminal. Data interaction can be achieved through methods such as API application programming interfaces or database connections, and then obtain relevant information about the trucks from the logistics management terminal, including vehicle numbers, departure times, destinations, etc.;

[0053] Induce the logistics fleet: For each truck, analyze its departure time and transportation route. If the departure times of two or more trucks are close, a time threshold can be set. For example, if the difference is no more than 15 minutes and the transportation routes are the same, then these trucks are induced into a logistics fleet;

[0054] Determine the fleet queue order: It can be arranged in the order of the trucks on the transportation route, or adjusted according to the distance and relative position between the trucks. The queue order of the fleet is updated in real time through the truck queue combination module 20, and dynamically adjusted as the trucks drive and their positions change.

[0055] The truck queue combination module 20 is used to monitor the position data of the Beidou positioning of each truck, and at the same time obtain the set following distance between the trucks, and then reorganize the queue by combining the position data between the trucks with the following distance;

[0056] The truck queue combination module 20 includes a position monitoring module and a queue combination module;

[0057] The position monitoring module is used to install a Beidou positioning device on each truck, and then associate with the Beidou positioning device to obtain the position data feedback by the corresponding Beidou positioning device of each truck.

[0058] The queue combination module is used to collect the set following distance between the trucks from the user at the logistics management terminal, and then reorganize the queue of the trucks during driving according to the position data. When the interval between different trucks is within the following distance, they are grouped into the same queue. Conversely, when the interval between different trucks is not within the following distance, they are not grouped into the same queue. The specific working steps are as follows:

[0059] Collect the following distance: Design a user input interface at the logistics management terminal to allow the user to input the set following distance between the trucks, and store the following distance input by the user in the database;

[0060] Obtain the truck position data: As before, through data association with the Beidou positioning device on the truck, obtain the position data of each truck in real time;

[0061] Calculate the interval distance between the trucks: Calculate the actual interval distance between any two trucks using the geographical distance calculation formula;

[0062] Perform queue reorganization: Traverse all trucks. For each truck, check whether the distance between it and other trucks is within the set following distance. If the distance between two trucks is less than or equal to the following distance, they are grouped into the same queue. Conversely, if the distance is greater than the following distance, they are not grouped into the same queue;

[0063] As the trucks move and their positions change, continuously repeat this process to update the queue membership of the trucks in real time.

[0064] The initial predicted position module 30 is used to obtain the driving speed of the trucks in the convoy, and then combines the position data of the leading vehicle, the position data of the trailing vehicle, the driving speed, and the following distance to perform an analysis of the predicted positions of each truck in the convoy, and perform a range overlap analysis on the analysis results. According to the analysis results, obtain the initial predicted position range of each truck;

[0065] The initial predicted position module 30 installs a speed sensor on the truck, and then obtains the driving speed of the truck through the data fed back by the speed sensor, and uploads it to the logistics management terminal at the same time.

[0066] The initial predicted position module 30 includes a predicted position analysis module and a predicted position range acquisition module;

[0067] The predicted position analysis module is used to combine the driving speed and position data of the leading vehicle with the following distance to perform an analysis of the predicted positions of each truck in the convoy, and at the same time combine the driving speed and position data of the trailing vehicle with the following distance to perform an analysis of the predicted positions of each truck in the convoy;

[0068] Obtain the driving speed, position data of the leading vehicle and the trailing vehicle, and the set following distance in real time from the logistics management terminal;

[0069] The predicted position range acquisition module is used to perform a range overlap analysis on the two predicted position analysis results obtained by the predicted position analysis module, and use the same position prediction data in the two predicted position analysis results as the initial predicted position range of the truck;

[0070] The prediction position analysis formula of the initial prediction position module 30 based on the leading vehicle is as follows:

[0071]

[0072]

[0073] Among them, X pred1 and Y pred1 are the predicted position coordinates of the truck relative to the leading vehicle, V lead is the driving speed of the leading vehicle, X lead and Y lead are the position data of the leading vehicle, Dfollwo is the set following distance, t1 is the predicted time for the trailing vehicle to complete the transportation route, and the angle between the driving direction of the leading vehicle and the positive x-axis is θ lead ;

[0074] The analysis formula for the predicted position of the trailing vehicle is as follows:

[0075]

[0076]

[0077] where X pred2 and Y pred2 are the predicted position coordinates of the truck relative to the trailing vehicle, V rear is the driving speed of the trailing vehicle, X rear and Y rear are the position data of the trailing vehicle, and the angle between the driving direction of the trailing vehicle and the positive x-axis is θ rear ;

[0078]

[0079] where d is the distance, and the set overlap threshold is T. When d < T, it is considered that the positions overlap. After determining the position overlap, the overlapping position range is used as the initial predicted position range of the truck.

[0080] The driving prediction module 40 is used to obtain the historical driving data of the truck for this transportation. When there is a signal fluctuation, based on the historical driving data and combined with the transportation route, the subsequent driving of the truck is predicted to obtain the predicted driving positions of each truck. The specific formula is as follows:

[0081]

[0082]

[0083] where X0 and Y0 are the last stable position coordinates of the truck before the signal fluctuation, V hist is the average speed of the truck in similar situations in the historical data, the driving direction forms an angle θ with the positive x-axis, the predicted time for the trailing vehicle to complete the transportation route after the signal fluctuation is t2, and X t and Y t are the predicted driving positions.

[0084] The distance prediction module 50 is used to intercept the historical interval distances between trucks in the period before the signal fluctuation, and at the same time, based on the historical interval distances and combined with the initial predicted position range, perform distance prediction position analysis on the trucks;

[0085] The distance prediction module 50 includes an interval distance acquisition module and a distance position prediction module;

[0086] The interval distance acquisition module is used to collect the historical interval data between trucks saved most recently during the time of distance fluctuation when the Beidou positioning device of the truck is interfered and the feedback data fluctuates, and extract the trucks under interference from the historical interval data to obtain the interval distances between the truck and the trucks in front and behind it;

[0087] When the position data feedback by the Beidou positioning device does not conform to the transportation route, it is determined that the Beidou positioning device is interfered.

[0088] The distance position prediction module is used to perform distance prediction position analysis on the truck according to the interval distances between the truck and the trucks in front and behind it in combination with the initial prediction position range, and perform precise position prediction according to the interval distances within the initial prediction position range, so as to obtain the distance prediction position;

[0089] The initial prediction position range of the truck is obtained through the previous method. Analyze according to the interval distances and the initial prediction position range, and adjust the prediction position. If the relative position relationship of the truck in the convoy is known, this information can be used in combination with the interval distances for more accurate position prediction. Finally, determine the distance prediction position coordinates of the truck through calculation.

[0090] The backup position selection module 60 is used to compare the driving prediction position with the initial prediction position range, and divide the priorities of position correction backup for the driving prediction position and the distance prediction position according to the comparison result.

[0091] The backup position selection module 60 includes a range comparison module and a priority division module;

[0092] The range comparison module is used to compare the driving prediction position with the initial prediction position range;

[0093] The priority division module is used to perform priority division according to the display result of the range comparison module. When the driving prediction position is within the initial prediction position range, the priority of the driving prediction position is the highest, and the driving prediction position is used as the correction backup position. On the contrary, when the driving prediction position is not within the initial prediction position range, the priority of the distance prediction position is the highest, and the distance prediction position is used as the correction backup position;

[0094] As the truck travels and new data is acquired, the prediction position and the position range are updated in a timely manner to more accurately determine the correction backup position.

[0095] When the position data feedback by the Beidou positioning device does not conform to the transportation route, the correction backup position is used as the truck position until the position data feedback by the Beidou positioning device returns to normal.

[0096] The above has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification are only preferred examples of the present invention and are not used to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A vehicle positioning system based on single Beidou positioning, characterized in that: It includes a fleet acquisition module (10), a truck queue combination module (20), an initial predicted position module (30), a driving prediction module (40), a distance prediction module (50), and a backup position selection module (60); The fleet acquisition module (10) is used to obtain the transportation route of the logistics fleet and simultaneously obtain the planned queue order during the fleet's travel; The truck queue combination module (20) is used to monitor the position data of each truck's Beidou positioning, simultaneously obtain the set following distance between trucks, and then reorganize the queues by combining the position data between trucks with the following distance; The initial predicted position module (30) is used to obtain the driving speed of the trucks in the fleet, and then combine the driving speed and position data of the leading vehicle with the following distance to perform predicted position analysis on each truck in the fleet. At the same time, combine the driving speed and position data of the trailing vehicle with the following distance to perform predicted position analysis on each truck in the fleet, and conduct a range overlap analysis on the analysis results. According to the analysis results, obtain the initial predicted position range of each truck; The driving prediction module (40) is used to obtain the historical driving data of the truck's current transportation. When signal fluctuations occur, predict the subsequent driving of the truck based on the historical driving data combined with the transportation route to obtain the driving predicted position of each truck; The distance prediction module (50) is used to intercept the historical interval distance between trucks during the period before signal fluctuations, and simultaneously perform distance predicted position analysis on the trucks by combining the historical interval distance with the initial predicted position range; The backup position selection module (60) is used to compare the ranges of the driving predicted position and the initial predicted position range, and prioritize the driving predicted position and the distance predicted position as corrected backup positions according to the comparison results.

2. The vehicle positioning system based on single Beidou positioning according to claim 1, wherein: The fleet acquisition module (10) obtains the transportation route of each truck by associating data with the logistics management terminal. At the same time, trucks with the same transportation route and the same departure time are grouped into a logistics fleet, thereby obtaining the transportation route of each logistics fleet; Obtain the planned queue order during the fleet's travel.

3. A vehicle positioning system based on single Beidou positioning according to claim 1, characterized in that: The truck queue combination module (20) includes a position monitoring module and a queue combination module; The position monitoring module is used to install a Beidou positioning device on each truck and then associate data with the Beidou positioning device to obtain the position data feedback by the corresponding Beidou positioning device of each truck; The queue combination module is used to collect the set following distance between trucks from the user at the logistics management terminal, and then reorganize the queues of the trucks during travel according to the position data. When the interval between different trucks is within the following distance, they are grouped into the same queue. Conversely, when the interval between different trucks is not within the following distance, they are not grouped into the same queue.

4. A vehicle positioning system based on single Beidou positioning according to claim 1, characterized in that: The initial predicted position module (30) obtains the driving speed of the truck by installing a speed sensor on the truck and then through the data feedback by the speed sensor; 5. A vehicle positioning system based on single Beidou positioning according to claim 1, characterized in that: The initial predicted position module (30) includes a predicted position analysis module and a predicted position range acquisition module; The predicted position analysis module is used to perform predicted position analysis on each truck in the convoy by combining the driving speed and position data of the leading vehicle with the following distance, and at the same time perform predicted position analysis on each truck in the convoy by combining the driving speed and position data of the trailing vehicle with the following distance; The predicted position range acquisition module is used to perform range overlap analysis on the two predicted position analysis results obtained by the predicted position analysis module, and use the same position prediction data in the two predicted position analysis results as the initial predicted position range of the truck.

6. The vehicle positioning system based on single Beidou positioning according to claim 1, characterized in that: The predicted position analysis formula of the initial predicted position module (30) based on the leading vehicle is as follows: ； ； Among them, X pred1 and Y pred1 are the predicted position coordinates of the truck relative to the leading vehicle, V lead is the driving speed of the leading vehicle, X lead and Y lead are the position data of the leading vehicle, D follwo is the set following distance, t1 is the predicted time for the trailing vehicle to complete the transportation route, and the angle between the driving direction of the leading vehicle and the positive direction of the x-axis is θ lead ; The predicted position analysis formula based on the trailing vehicle is as follows: ； ； Among them, X pred2 and Y pred2 are the predicted position coordinates of the truck relative to the trailing vehicle, V rear is the driving speed of the trailing vehicle, X rear and Y rear are the position data of the trailing vehicle, and the angle between the driving direction of the trailing vehicle and the positive direction of the x-axis is θ rear ; ； Where d is the distance, and the overlap threshold is set as T. When d < T, it is considered that the positions overlap. After determining the position overlap, the overlapping position range is used as the initial predicted position range of the truck.

7. A vehicle positioning system based on single Beidou positioning according to claim 1, characterized in that: The formula of the driving prediction module (40) is as follows: ； ； Among them, X0 and Y0 are the coordinates of the last stable position of the truck before signal fluctuation, V hist is the average speed of the truck in historical data, the angle between the driving direction and the positive direction of the x-axis is θ, the predicted time for the rear truck to complete the transportation route after signal fluctuation is t2, X t and Y t are the predicted driving positions.

8. The vehicle positioning system based on single Beidou positioning according to claim 1, wherein: The distance prediction module (50) includes an interval distance acquisition module and a distance position prediction module; The interval distance acquisition module is used to collect the historical interval data between the trucks saved most recently at the time of distance fluctuation when the Beidou positioning device of the truck is interfered and the feedback data fluctuates, and extract the trucks affected by the interference from the historical interval data to obtain the interval distances between the truck and the trucks in front and behind; The distance position prediction module is used to perform distance predicted position analysis on the truck by combining the interval distances between the truck and the trucks in front and behind with the initial predicted position range, and perform accurate position prediction according to the interval distances within the initial predicted position range, so as to obtain the distance predicted position.

9. The vehicle positioning system based on single Beidou positioning according to claim 1, characterized in that: The backup position selection module (60) includes a range comparison module and a priority division module; The range comparison module is used to compare the driving predicted position with the initial predicted position range; The priority division module is used to perform priority division according to the display result of the range comparison module. When the driving predicted position is within the initial predicted position range, the priority of the driving predicted position is the highest, and the driving predicted position is used as the correction backup position. On the contrary, when the driving predicted position is not within the initial predicted position range, the priority of the distance predicted position is the highest, and the distance predicted position is used as the correction backup position; When the position data fed back by the Beidou positioning device does not conform to the transportation route, the correction backup position is used as the truck position until the position data fed back by the Beidou positioning device returns to normal.

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