Vehicle positioning system based on single Beidou positioning

Abstract

The invention relates to the technical field of vehicle positioning. The invention relates to a vehicle positioning system based on single Beidou positioning. The system comprises a motorcade acquisition module, a truck queue combination module, an initial prediction position module, a driving prediction module, a distance prediction module and a standby position selection module. The fleet acquisition module is used for acquiring a transportation route of a logistics fleet; the truck queue combination module is used for monitoring Beidou positioning position data of each truck, acquiring a set following distance between the trucks, and then performing queue recombination by combining the position data between the trucks with the following distance; the driving speed and position data of a leading vehicle are combined with a following distance to carry out predicted position analysis on each truck in a motorcade, the driving speed and position data of a trailing vehicle are utilized to carry out the same operation, and then range overlapping extraction analysis is carried out on two predicted position results. The initial prediction 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 in particular to a vehicle positioning system based on single Beidou positioning. Background Art

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

[0003] At present, the vehicle positioning system can grasp the location and driving status of trucks in real time, and realize 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, the Beidou positioning system may have signal obstruction or interference in some complex environments, such as urban canyons with high-rise buildings, tunnels, underground parking lots, etc., resulting in inaccurate positioning. Secondly, when the Beidou positioning device is interfered with, it can only wait for the device to return to normal, resulting in insufficient precision and efficiency in logistics fleet management. In order to reduce this situation, a vehicle positioning system based on single Beidou positioning is proposed. Summary of the invention

[0004] The object 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 technology.

[0005] To achieve the above purpose, a vehicle positioning system based on single Beidou positioning is provided, including a fleet acquisition module, a 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 the queue sequence planned by the fleet during the journey;

[0007] The truck queue assembly module is used to monitor the position data of each truck based on Beidou positioning, and simultaneously obtain the set following distance between trucks, and then reorganize the queue based on the position data between trucks and the following distance;

[0008] The initial predicted position module is used to obtain the driving speed of the trucks in the convoy, and then perform predicted position analysis on each truck in the convoy by combining the position data of the leading truck with the position data of the trailing truck as well as the driving speed and following distance, and perform range overlap analysis on the analysis results, and obtain the initial predicted position range of each 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 signal fluctuation occurs, the subsequent driving of the truck is predicted based on the historical driving data combined with the transportation route to obtain the predicted driving position of each truck.

[0010] The distance prediction module is used to intercept the historical interval distance between trucks in the period before the signal fluctuation, and at the same time combine the historical interval distance with the initial prediction position range to perform distance prediction position analysis on the trucks;

[0011] The backup position selection module is used to compare the travel prediction position with the initial prediction position range, and prioritize the travel prediction position and the distance prediction position for position correction and backup according to the comparison result.

[0012] As a further improvement of the technical solution, the fleet acquisition module obtains the transportation route of each truck by associating data with the logistics management terminal, and 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;

[0013] Get the queue sequence planned by the fleet during its movement.

[0014] As a further improvement of the 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 to obtain the position data fed back by the Beidou positioning device corresponding to each truck;

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

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

[0018] As a further improvement of the present technical solution, the initial predicted position module includes a predicted position analysis module and a predicted position range acquisition module;

[0019] 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 predicted position analysis on 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 predicted position analysis on each truck in the convoy;

[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 the technical solution, the predicted position analysis formula based on the leading vehicle of the initial predicted position module is as follows:

[0022]

[0023]

[0024] Among them, X pred1 and Y pred1 is the predicted position coordinate of the truck relative to the leading vehicle, V lead is the speed of the leading vehicle, X lead and Y lead is the position data of the leading vehicle, D follwo is the set following distance, t 1 is the predicted time for the tail vehicle to complete the transport route, and the angle between the leading vehicle's driving direction and the positive direction of the x-axis is θ lead ;

[0025] The predicted position analysis formula based on the tail vehicle is as follows:

[0026]

[0027]

[0028] Among them, X pred2 and Y pred2 is the predicted position coordinate of the truck relative to the rear truck, V rear is the speed of the rear vehicle, X rear and Y rear is the position data of the rear vehicle, and the angle between the rear vehicle's travel direction and the positive direction of the x-axis is θ rear ;

[0029]

[0030] Wherein, d is the distance, and the overlap threshold is set to T. When d<T, the positions are considered to overlap. When the positions are determined to overlap, the overlapping position range is used as the initial predicted position range of the truck.

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

[0032]

[0033]

[0034] Among them, X 0 and Y 0 is the last stable position coordinate of the truck before the 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, and the predicted time for the tail truck to complete the transportation route after the signal fluctuation is t2, X t and Y t Predicted location for driving.

[0035] As a further improvement of the 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 historical interval data between trucks that have been saved recently when the Beidou positioning device of the truck is disturbed and the feedback data fluctuates, and extract the disturbed truck from the historical interval data to obtain the interval distance between the truck and the front and rear trucks;

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

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

[0039] The range comparison module is used to perform range comparison on the predicted driving position in combination with the initial predicted 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 prediction position is within the initial prediction position range, the driving prediction position has the highest priority and is used as the correction standby position. On the contrary, when the driving prediction position is not within the initial prediction position range, the distance prediction position has the highest priority and is used as the correction standby position.

[0041] When the position data fed back by the Beidou positioning device does not match the transportation route, the corrected backup 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 present invention has the following beneficial effects:

[0043] 1. In a vehicle positioning system based on single Beidou positioning, the predicted position analysis is performed on each truck in the fleet by combining the driving speed and position data of the leading vehicle with the following distance, and the same operation is performed using the driving speed and position data of the trailing vehicle. The range overlap extraction analysis is then performed on the two predicted position results, so that 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 certain complex environments, so that the position of the truck can still be determined more accurately when the Beidou positioning signal fluctuates or is temporarily lost. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0045] The meaning of each number in the figure is:

[0046] 10. Fleet acquisition module; 20. Truck queue combination module; 30. Initial prediction position module; 40. Driving prediction module; 50. Distance prediction module; 60. Backup position selection module. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

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

[0049] The fleet acquisition module 10 is used to acquire the transportation route of the logistics fleet and the queue sequence planned by the fleet during the journey;

[0050] The fleet acquisition module 10 obtains the transportation route of each truck by associating data with the logistics management terminal, and classifies trucks with the same transportation route and the same departure time into a logistics fleet, thereby obtaining the transportation route of each logistics fleet;

[0051] Get the queue sequence planned by the fleet during its movement. The specific steps are as follows:

[0052] Obtaining truck transportation routes: Establishing a communication interface with the logistics management end, data interaction can be achieved through API application program interface or database connection, and then obtaining relevant information of the truck from the logistics management end, including vehicle number, departure time, destination, etc.;

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

[0054] Determine the queue order of the fleet: the trucks can be arranged in the order of their arrival on the transport 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 is dynamically adjusted as the trucks travel and their positions change.

[0055] The truck queue assembly module 20 is used to monitor the position data of each truck based on Beidou positioning, and simultaneously obtain the set following distance between the trucks, and then reorganize the queue based on the position data between the trucks and the following distance;

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

[0057] The location 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 location data fed back by the Beidou positioning device corresponding to each truck.

[0058] The queue combination module is used to collect the following distance set between trucks from users on the logistics management end, and then reorganize the trucks in the process of driving according to the location data. When the intervals between different trucks are within the following distance, they are classified into the same queue. Conversely, when the intervals between different trucks are not within the following distance, they are not classified into the same queue. The specific working steps are as follows:

[0059] Collecting following distance: Design a user input interface on the logistics management end to allow users to input the set following distance between trucks, and store the following distance input by users in the database;

[0060] Obtaining truck location data: As before, by associating data with the Beidou positioning device on the truck, the location data of each truck is obtained in real time;

[0061] Calculate the distance between trucks: For any two trucks, use the geographic distance calculation formula to calculate the actual distance between them;

[0062] Perform queue reorganization: traverse all trucks, and 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 put into the same queue. Otherwise, if the distance between them is greater than the following distance, they are not put into the same queue.

[0063] As the truck moves and its position changes, this process is repeated continuously, and the truck’s queue affiliation is updated 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 perform predicted position analysis on each truck in the convoy by combining the position data of the leading truck with the position data of the trailing truck as well as 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 truck according to the analysis results;

[0065] The initial prediction position module 30 obtains the driving speed of the truck by installing a speed sensor on the truck and then uses the data fed back by the speed sensor to upload the data to the logistics management terminal.

[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 predicted position analysis on 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 predicted position analysis on each truck in the convoy;

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

[0069] 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;

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

[0071]

[0072]

[0073] Among them, X pred1 and Y pred1 is the predicted position coordinate of the truck relative to the leading vehicle, V lead is the speed of the leading vehicle, X lead and Y lead is the position data of the leading vehicle, Dfollwo is the set following distance, t 1 is the predicted time for the tail vehicle to complete the transport route, and the angle between the leading vehicle's driving direction and the positive direction of the x-axis is θ lead ;

[0074] The predicted position analysis formula based on the tail vehicle is as follows:

[0075]

[0076]

[0077] Among them, X pred2 and Y pred2 is the predicted position coordinate of the truck relative to the rear truck, V rear is the speed of the rear vehicle, X rear and Y rear is the position data of the rear vehicle, and the angle between the rear vehicle's travel direction and the positive direction of the x-axis is θ rear ;

[0078]

[0079] Wherein, d is the distance, and the overlap threshold is set to T. When d<T, the positions are considered to overlap. When the positions are determined to 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 the signal fluctuates, the subsequent driving of the truck is predicted based on the historical driving data combined with the transportation route to obtain the driving predicted position of each truck. The specific formula is as follows:

[0081]

[0082]

[0083] Among them, X 0 and Y 0 is the last stable position coordinate of the truck before the signal fluctuation, V hist is the average speed of the truck in similar situations in historical data, the angle between the driving direction and the positive direction of the x-axis is θ, and the predicted time for the tail truck to complete the transportation route after the signal fluctuation is t2, X t and Y t Predicted location for driving.

[0084] The distance prediction module 50 is used to intercept the historical interval distance between trucks in the period before the signal fluctuation, and at the same time combine the historical interval distance with the initial predicted position range to 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 collection module is used to collect the historical interval data between trucks that have been saved recently when the Beidou positioning device of the truck is disturbed and the feedback data fluctuates, and extract the disturbed truck from the historical interval data to obtain the interval distance between the truck and the trucks in front and behind;

[0087] When the location data fed back by the Beidou positioning device does not match the transportation route, it is determined that the Beidou positioning device is interfered with.

[0088] The distance position prediction module is used to perform distance prediction position analysis on the truck based on the interval distance between the truck and the front and rear trucks combined with the initial prediction position range, and perform accurate position prediction based on the interval distance within the initial prediction position range, thereby obtaining the distance prediction position;

[0089] The initial predicted position range of the truck is obtained through the previous method. The predicted position is adjusted based on the analysis of the interval distance and the initial predicted position range. If the relative position relationship of the truck in the fleet is known, this information can be used in combination with the interval distance to make a more accurate position prediction. Finally, the distance predicted position coordinates of the truck are determined by calculation.

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

[0091] The standby 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 driving prediction position has the highest priority and is used as a correction standby position. On the contrary, when the driving prediction position is not within the initial prediction position range, the distance prediction position has the highest priority and is used as a correction standby position.

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

[0095] When the position data fed back by the Beidou positioning device does not match the transportation route, the corrected backup position is used as the truck position until the position data fed back by the Beidou positioning device returns to normal.

[0096] The above shows and describes 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 descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A vehicle positioning system based on single Beidou positioning, Features: It comprises a fleet acquisition module (10), a truck queue combination module (20), an initial predicted position module (30), a travel prediction module (40), a distance prediction module (50) and a backup position selection module (60); The fleet acquisition module (10) is used to acquire the transportation route of the logistics fleet and simultaneously acquire the queue sequence planned by the fleet during the movement; The truck queue assembly module (20) is used to monitor the Beidou positioning position data of each truck, and simultaneously 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; The initial predicted position module (30) is used to obtain the driving speed of the trucks in the convoy, and then perform predicted position analysis on each truck in the convoy by combining the position data of the leading truck with the position data of the trailing truck as well as 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 truck according to the analysis results; The travel prediction module (40) is used to obtain historical travel data of the truck during this transportation, and when signal fluctuation occurs, the subsequent travel of the truck is predicted based on the historical travel data combined with the transportation route to obtain the predicted travel position of each truck; The distance prediction module (50) is used to intercept the historical interval distance between trucks in the period before the signal fluctuation, and to perform distance prediction position analysis on the trucks by combining the historical interval distance with the initial prediction position range; The standby position selection module (60) is used to compare the travel prediction position with the initial prediction position range, and to prioritize the travel prediction position and the distance prediction position for position correction and standby according to the comparison result.

2. A vehicle positioning system based on single Beidou positioning according to claim 1, Features: The fleet acquisition module (10) acquires the transportation route of each truck by associating data with the logistics management terminal, and classifies trucks with the same transportation route and the same departure time into a logistics fleet, thereby obtaining the transportation route of each logistics fleet; Get the queue sequence planned by the fleet during its movement.

3. A vehicle positioning system based on single Beidou positioning according to claim 1, Features: The truck queue assembly module (20) comprises a position monitoring module and a queue assembly 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 fed back by the Beidou positioning device corresponding to each truck; The queue combination module is used to collect the following distance set between trucks from the user at the logistics management end, and then reorganize the queue of trucks during driving according to the position data. When the intervals between different trucks are within the following distance, they are classified into the same queue. Conversely, when the intervals between different trucks are not within the following distance, they are not classified into the same queue.

4. A vehicle positioning system based on single Beidou positioning according to claim 1, Features: The initial predicted position module (30) obtains the travel speed of the truck by installing a speed sensor on the truck and then using data fed back by the speed sensor.

5. The vehicle positioning system based on single Beidou positioning according to claim 1, Features: The initial predicted position module (30) comprises a predicted position analysis module and a predicted position range acquisition module; 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 predicted position analysis on 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 predicted position analysis on each truck in the convoy; 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. A vehicle positioning system based on single Beidou positioning according to claim 1, Features: The analysis formula of the predicted position based on the leading vehicle of the initial predicted position module (30) is as follows: Among them, X pred1 and Y pred1 is the predicted position coordinate of the truck relative to the leading vehicle, V lead is the speed of the leading vehicle, X lead and Y lead is the position data of the leading vehicle, D follwo is the set following distance, t 1 is the predicted time for the tail vehicle to complete the transport route, and the angle between the leading vehicle's driving direction and the positive direction of the x-axis is θ lead ; The predicted position analysis formula based on the tail vehicle is as follows: Among them, X pred2 and Y pred2 is the predicted position coordinate of the truck relative to the rear truck, V rear is the speed of the rear vehicle, X rear and Y rear is the position data of the rear vehicle, and the angle between the rear vehicle's travel direction and the positive direction of the x-axis is θ rear ; Wherein, d is the distance, and the overlap threshold is set to T. When d<T, the positions are considered to overlap. When the positions are determined to 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, Features: The formula of the driving prediction module (40) is as follows: Among them, X 0 and Y 0 is the last stable position coordinate of the truck before the 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, and the predicted time for the tail truck to complete the transportation route after the signal fluctuation is t 2 , X t and Y t Predicted location for driving.

8. A vehicle positioning system based on single Beidou positioning according to claim 1, Features: The distance prediction module (50) comprises an interval distance acquisition module and a distance position prediction module; The interval distance acquisition module is used to collect historical interval data between trucks that have been saved recently when the Beidou positioning device of the truck is disturbed and the feedback data fluctuates, and extract the disturbed truck from the historical interval data to obtain the interval distance between the truck and the front and rear trucks; The distance position prediction module is used to perform distance prediction position analysis on the truck based on the interval distance between the truck and the front and rear trucks in combination with the initial prediction position range, and perform accurate position prediction based on the interval distance within the initial prediction position range to obtain the distance prediction position.

9. The vehicle positioning system based on single Beidou positioning according to claim 1, Features: The standby position selection module (60) comprises a range comparison module and a priority division module; The range comparison module is used to perform range comparison on the predicted driving position in combination 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 prediction position is within the initial prediction position range, the driving prediction position has the highest priority and is used as the correction standby position. On the contrary, when the driving prediction position is not within the initial prediction position range, the distance prediction position has the highest priority and is used as the correction standby position. When the position data fed back by the Beidou positioning device does not match the transportation route, the corrected 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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