High-precision positioning method and system for vehicle running on road surface

Abstract

The invention provides a high-precision positioning method and system for a vehicle running on a road surface, and relates to the technical field of vehicle positioning, and the method comprises the steps: burying a fiber bragg grating sensing unit at a central position in the road surface of a lane along the direction of the lane, acquiring real-time strain information generated by a vehicle in a detection area of the fiber grating sensing unit and a road surface in a driving process; analyzing static strain information of the vehicle and the road surface under the action of the static load; introducing a vehicle running speed to correct the static strain information to obtain dynamic strain information; drawing a strain distribution curve in the detection area according to the dynamic strain information; and determining the position information of the vehicle according to the relationship between the real-time strain information and the strain distribution curve. The method can achieve the full-time and full-domain acquisition of the ground strain information on the vehicle driving path, determines the positioning information of the vehicle through the strain information, avoids the influence of severe weather and environment, and is higher in precision.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle positioning, and particularly to a high-precision positioning method and system for vehicles traveling on the road surface. Background Art

[0002] With the rapid development of autonomous driving technology, the requirements for vehicle positioning technology have also increased accordingly. Precise vehicle positioning is the key to automatic collision avoidance. When satellite signals fail, other technologies are needed to achieve redundant positioning to prevent vehicle positioning failures in multiple scenarios.

[0003] However, traditional vehicle positioning usually locates the vehicle position through positioning means such as GPS and lidar. These methods are easily affected by bad weather and environment, and the positioning signal aging is likely to occur. Therefore, due to the various limitations of the existing vehicle positioning methods, it is urgent to study a vehicle positioning method that is stable and applicable to various environments. Summary of the Invention

[0004] The purpose of the present invention is to provide a high-precision positioning method and system for vehicles traveling on the road surface to solve the problem that the traditional vehicle positioning method is easily affected by bad weather and environment and has limitations mentioned in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A high-precision positioning method for vehicles traveling on the road surface, the steps include: burying a fiber Bragg grating sensing unit along the lane direction at the center position inside the road surface to obtain real-time strain information generated by the vehicle and the road surface during the driving process within the detection area of the fiber Bragg grating sensing unit; analyzing the static strain information of the vehicle and the road surface under the action of static load; introducing the vehicle driving speed to correct the static strain information to obtain dynamic strain information; drawing a strain distribution curve within the detection area according to the dynamic strain information; determining the position information of the vehicle through the relationship between the real-time strain information and the strain distribution curve.

[0006] Optionally, the fiber Bragg grating sensing unit includes an interferometric grating array optical fiber, and the interferometric grating array optical fiber includes a plurality of gratings distributed at equal intervals.

[0007] Optionally, the step of determining the position information of the vehicle based on the relationship between the real-time strain information and the strain distribution curve specifically includes: determining the minimum point A and the minimum point B in the strain distribution curve; when the real-time strain information corresponds to the minimum point A, it is determined that the vehicle is close to the detection area and the distance from the detection area is a, and the vehicle position at this time is determined as the positioning point A; when the real-time strain information corresponds to the minimum point B, it is determined that the vehicle leaves the detection area and the distance from the detection area is a, and the vehicle position at this time is determined as the positioning point B.

[0008] Optionally, the step of determining the minimum point A and the minimum point B in the strain distribution curve specifically includes: dividing the area of the strain generated by the vehicle and the road surface into a tensile state strain area and a compressive state strain area, where the tensile state strain area corresponds to the vehicle position, and the compressive state strain areas are distributed at the front and rear ends of the vehicle driving direction, and the maximum values of the compressive states of the compressive state strain areas at the front and rear ends of the vehicle driving direction respectively correspond to the minimum point A and the minimum point B in the strain distribution curve.

[0009] Optionally, the distance a is half of the length of the tensile state strain area.

[0010] Optionally, the method steps further include: determining discrete positioning points of the vehicle during driving on the road surface through the fiber Bragg grating sensing unit; calculating the driving speed of the vehicle by segments through the discrete positioning points; establishing a state transition model, predicting the driving trajectory of the vehicle based on the discrete positioning points, and further judging the vehicle position information corresponding to each time point during the vehicle driving process.

[0011] Optionally, the step of predicting the driving trajectory of the vehicle based on the discrete positioning points specifically includes: in the initial stage of the vehicle driving, obtaining the initial positioning point information of the vehicle, and using the extended Kalman filter algorithm to predict the position information of the vehicle at the next moment; during the vehicle driving process, when the vehicle reaches the next positioning point, using the extended Kalman filter algorithm to update the prediction information.

[0012] Optionally, the step of predicting the driving trajectory of the vehicle further includes: inputting the two-dimensional position, driving speed and acceleration of the vehicle into the state transition model as state vectors for predicting the driving trajectory of the vehicle, and the state vectors are: where x k is the state vector, p x is the vehicle driving direction position information, p y is the vehicle lateral position information, v x is the vehicle driving direction speed information, v y is the vehicle lateral speed information, ax is the acceleration information in the vehicle driving direction, a y is the lateral acceleration information of the vehicle.

[0013] Optionally, the interferometric grating array optical fiber is encapsulated by pre-stretching and is armored with at least one outer sheath.

[0014] On the other hand, the present invention also provides a high-precision positioning system for a vehicle driving on a road surface, including: an acquisition module for burying a fiber Bragg grating sensing unit along the lane direction at the center position inside the road surface of the lane to acquire real-time strain information generated between the vehicle and the road surface during the driving process within the detection area of the fiber Bragg grating sensing unit; an analysis module for analyzing the static strain information between the vehicle and the road surface under the action of a static load; a correction module for introducing the vehicle driving speed to correct the static strain information to obtain dynamic strain information, and drawing a strain distribution curve within the detection area according to the dynamic strain information; a determination module for determining the position information of the vehicle through the relationship between the real-time strain information and the strain distribution curve.

[0015] Compared with the prior art, the beneficial effects of the present invention are:

[0016] In this application, the fiber Bragg grating sensing unit is buried along the lane direction at the center position inside the road surface of the lane to acquire real-time strain information generated between the vehicle and the road surface; and the strain distribution curve between the vehicle and the road surface is analyzed; through the relationship between the real-time strain information and the strain distribution curve, the position information of the vehicle is determined, which can realize the acquisition of ground strain information on the vehicle driving path in real time and all regions, and further determine the positioning information of the vehicle through the strain information, avoiding being affected by bad weather and environment, and having high precision.

[0017] By calculating the corresponding relationship between the minimum points A and B in the strain distribution curve and the maximum values of the compression state strain regions at the front and rear ends of the vehicle, the vehicle position can be accurately located, with high accuracy.

[0018] Based on the accurately monitored discrete positioning points, substituting them into the extended Kalman filter algorithm to calculate the vehicle driving trajectory, and through the predicted motion trajectory during the vehicle driving process, high-precision positioning of the entire vehicle driving process can be realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic flow chart of the method steps of the present invention.

[0020] Figure 2 is a schematic diagram of the relationship between the strain distribution curve of the present invention and the vehicle position.

[0021] Figure 3Schematic diagram of the relationship between the minimum value and the vehicle position in the strain distribution curve of the present invention.

[0022] Figure 4 Schematic diagram of the demodulation principle of the interferometric grating array optical fiber of the present invention.

[0023] Figure 5 Schematic diagram of the layout of the fiber grating sensing unit of the present invention.

[0024] Figure 6 Schematic diagram of the distribution of discrete positioning points of the present invention.

[0025] Figure 7 Schematic diagram of the relationship between the position and time of the positioning points of the present invention.

[0026] Figure 8 Schematic diagram of the predicted driving trajectory of the vehicle of the present invention.

[0027] Figure 9 Schematic diagram of the system structure of the present invention.

[0028] In the figure: 10 - acquisition module, 20 - analysis module, 30 - correction module, 40 - determination module. Detailed implementation manner

[0029] Next, the solutions 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 embodiments.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of this application and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances, so as to implement the embodiments of the present application described here. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0031] Those skilled in the art of the present technology can understand that, unless specifically stated otherwise, the singular forms "a", "an", "the" and "said" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the specification of the present application means the presence of features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or their groups. It should be understood that when we say an element is "connected" or "coupled" to another element, it can be directly connected or coupled to other elements, or there may also be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The phrase "and / or" used herein includes all or any unit and all combinations of one or more related listed items.

[0032] Those skilled in the art of the present technology can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as the general understanding of those of ordinary skill in the art to which the present application belongs. It should also be understood that terms such as those defined in a general dictionary should be understood to have a meaning consistent with the meaning in the context of the prior art, and will not be interpreted with an idealized or overly formal meaning unless specifically defined as here.

[0033] It should be understood that the sequence numbers and magnitudes of the steps in this embodiment do not mean the order of execution. The order of execution of each process is determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0034] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0035] Please refer to Figure 1 - Figure 2 , a high-precision positioning method for a vehicle traveling on a road surface according to the present invention, the steps include: burying a fiber Bragg grating sensing unit along the lane direction at the central position inside the road surface of the lane to obtain real-time strain information generated by the vehicle during driving and the road surface within the detection area of the fiber Bragg grating sensing unit; analyzing the static strain information of the vehicle and the road surface under the action of a static load; introducing the vehicle driving speed to correct the static strain information to obtain dynamic strain information; drawing a strain distribution curve within the detection area according to the dynamic strain information; and determining the position information of the vehicle through the relationship between the real-time strain information and the strain distribution curve.

[0036] It should be understood that during the vehicle's driving process, when the wheels come into contact with the ground, vibrations and strain signals will be generated in the contact area. It can be understood that taking the vehicle as the excitation source, the strain and vibration are transmitted to the ground structure. The vibration signal attenuates less with the increase of distance and has a large propagation range; the strain signal attenuates more significantly with the increase of distance and has a small propagation range. The vibration signal and the strain signal reflect the vehicle's position information, and from the action range of the strain signal, it can be seen that the strain signal reflects the vehicle's position information more accurately; during the vehicle's driving process, the ground synchronously generates a strain response. Therefore, in this application, the strain response under the static load of the ground is first analyzed, and then the analysis result is corrected by introducing the vehicle's driving speed.

[0037] Specifically, a ground coordinate system is established, where the X-axis of the coordinate system is the vehicle driving direction, the Y-axis is the vehicle's lateral direction, and the Z-axis direction is the vertical downward ground longitudinal strain direction, which is the gravity direction; then the center coordinate point of the whole vehicle is (x AGV , 0). Considering the viscoelastic foundation, according to the elastic half-space theory, the static strain information of the vehicle and the road surface under the static load is analyzed, and the longitudinal strain expression of the ground is: In the formula, ε x is the static strain information, (x, y) is the coordinate point in the road plane of the coordinate system, v is the Poisson's ratio, E is the elastic modulus, σ x is the stress in the X-axis direction, σ y is the stress in the Y-axis direction, and σ z is the stress in the Z-axis direction.

[0038] Specifically, the Boussinesq-Cerruti solution of the stress component in the X direction is:

[0039]

[0040] In the formula, σ x is the stress in the X-axis direction, is the double integral over the region A, A is the region where the road surface is subjected to the load, q is the simplified vehicle uniform load, and q = P 车轮 / S 车轮 , P 车轮 is the wheel load, S 车轮 is the contact area between the wheel and the ground, x, y, and z are the coordinates of the three-axis coordinate system, ξ and η are the integration variables, and v is the Poisson's ratio.

[0041] Specifically, due to the vehicle having a certain driving speed, a speed-related term is introduced. At this time, the strain response is converted from the static strain expression to the dynamic strain expression: In the formula is the dynamic strain information, and ε xis static strain information, α is the damping coefficient of the road surface material, ν is the Poisson's ratio, and ν R is the Rayleigh wave velocity, and E is the elastic modulus, ρ is the density of the road surface material. The elastic modulus E of a common asphalt road surface is 1.2 GPa, the Poisson's ratio ν is 0.35, and the load under the working condition of a vehicle of about 400 Kg.

[0042] It can be understood that in this application, the fiber Bragg grating sensing unit is buried along the lane direction at the center position inside the road surface of the lane to obtain the real-time strain information generated by the vehicle and the road surface; and analyze the strain distribution curve between the vehicle and the road surface; through the relationship between the real-time strain information and the strain distribution curve, determine the position information of the vehicle, which can realize the acquisition of the ground strain information on the vehicle driving path in the whole time and the whole area, and then determine the positioning information of the vehicle through the strain information, avoiding being affected by bad weather and environment, and having high accuracy.

[0043] In some embodiments, the fiber Bragg grating sensing unit includes an interferometric grating array optical fiber, and the interferometric grating array optical fiber includes a plurality of gratings distributed at equal intervals.

[0044] Specifically, in order to detect the ground response signal during the driving process of the vehicle and thus realize the position positioning of the vehicle, this application selects an interferometric grating array optical fiber, specifically including an array formed by a plurality of gratings distributed at equal intervals. The adjacent two gratings are arranged at intervals to meet the sectional strain detection; the demodulation principle is specifically referred to Figure 4 As shown, the demodulation is through the phase-sensitive optical time domain reflectometry technology. The fiber Bragg grating sensing unit uses an interferometric grating array optical fiber. When an external interference signal acts on the optical fiber section between the gratings, it will cause a slight change in the length between the two gratings. The two pulse optical signals reflected back from the two gratings interfere, and the phase of the interference light is related to the slight strain in the fiber axial direction. And by this method, the interference signal can be detected extremely sensitively, and a slight strain signal can be detected.

[0045] In some embodiments, the step of determining the position information of the vehicle through the relationship between the real-time strain information and the strain distribution curve specifically includes: determining the minimum value points A and B in the strain distribution curve; when the real-time strain information corresponds to the minimum value point A, it is determined that the vehicle is close to the detection area and is at an interval distance a from the detection area, and the vehicle position at this time is determined as the positioning point A; when the real-time strain information corresponds to the minimum value point B, it is determined that the vehicle leaves the detection area and is at an interval distance a from the detection area, and the vehicle position at this time is determined as the positioning point B.

[0046] Specifically, the ground strain information during vehicle driving calculated by the strain response model is used to draw the strain information distribution curve of vehicle driving. Specifically, refer to Figure 2 As shown, the action range of the strain signal generated on the ground when the vehicle is driving is greater than the vehicle length. When the vehicle weight is small, the strain signal response caused by it on the ground is also small. Therefore, the strain detection area can be increased to improve the magnitude of the strain detection signal. When detecting the strain signals in a section of the ground area, the relationship between the strain information and the vehicle position in a detection area can be calculated from the strain distribution curve of the ground when the vehicle is driving in Figure 2 . The relationship between the strain information and the vehicle position under the detection of the measurement area is specifically referred to Figure 3 As shown, at this time, it can be observed that there are two minimum value points in the strain signal under the measurement area detection. Through analysis, it can be known that they respectively correspond to the vehicle approaching the measurement area and being at a distance of a from the edge of the measurement area, and the vehicle leaving the measurement area and being at a distance of a from the edge of the measurement area. At this time, the accurate detection of the vehicle position can be realized.

[0047] In some embodiments, the steps of determining the minimum value point A and the minimum value point B in the strain distribution curve specifically include: dividing the area of the strain generated by the vehicle and the road surface into a tensile state strain area and a compressive state strain area. Among them, the tensile state strain area corresponds to the vehicle position, and the compressive state strain areas are distributed at the front and rear ends in the vehicle driving direction. The maximum values of the compressive states of the compressive state strain areas at the front and rear ends in the vehicle driving direction respectively correspond one-to-one to the minimum value point A and the minimum value point B in the strain distribution curve.

[0048] Specifically, the strain is generated by the wheels and conducted through the ground. During the whole vehicle driving process, the strain signal distribution on the ground shows that the strain of the ground directly below the vehicle is in a tensile state, and the strain of the ground within a certain distance before and after the vehicle is in a compressive state. The maximum values of the compressive states of the compressive state strain areas at the front and rear ends in the vehicle driving direction respectively correspond one-to-one to the minimum value point A and the minimum value point B in the strain distribution curve.

[0049] In some embodiments, the interval distance a is half of the length of the tensile state strain area.

[0050] Specifically, the minimum value point A and the minimum value point B in the strain distribution curve respectively correspond to the maximum value of the compressive state strain area at the front end of the vehicle before entering the detection area, and the maximum value of the compressive state strain area at the rear end of the vehicle after leaving the detection area. Therefore, it can be calculated that the interval distance a is half of the length of the tensile state strain area. By calculating the corresponding relationship between the minimum value point A and the minimum value point B in the strain distribution curve and the maximum values of the compressive state strain areas at the front and rear ends of the vehicle, the vehicle position can be accurately located, with high accuracy.

[0051] In some embodiments, the method steps further include: determining discrete positioning points of the vehicle during driving on the road surface through a fiber Bragg grating sensing unit; calculating the driving speed of the vehicle by segments through the discrete positioning points; establishing a state transition model, predicting the driving trajectory of the vehicle based on the discrete positioning points, and further judging the vehicle position information corresponding to each time point during the vehicle driving process.

[0052] Specifically, the interferometric grating array optical fiber includes a plurality of gratings distributed at equal intervals. Two positioning points can be recognized between every two adjacent gratings during the vehicle driving process. Therefore, the interferometric grating array optical fiber can determine a plurality of discrete positioning points, and these discrete positioning points can be used as position data points during the vehicle movement process. The distribution of the positioning points on the vehicle driving path is as Figure Seven shown; since the corresponding relationship between the positioning points and the vehicle position is relatively accurate, therefore, the vehicle speed can be accurately calculated by segments through the positioning points on the vehicle driving path. Moreover, every time a new positioning point is passed, the vehicle speed is recalculated immediately. The distance between the positioning points is short, and the vehicle speed remains basically stable within this segmented distance. Therefore, the vehicle speed can be accurately calculated through two nearest positioning points. And in this method, there are a large number of accurate positioning points, and the speed of the vehicle in different position segments can be calculated at high frequency, so as to realize the high-speed update of the monitored vehicle speed.

[0053] In some embodiments, the position and time of reaching the positioning point are obtained through the proposed detection method. Through the position and time difference between the two positioning points, the average speed of the vehicle passing through the previous interval can be calculated as: v = (P2 - P1) / (t2 - t1), where P i is the positioning point position, and t i is the positioning point time.

[0054] In some embodiments, please refer to Figure 6 and Figure 7 , the step of predicting the vehicle driving trajectory based on the discrete positioning points specifically includes: in the initial stage of vehicle driving, obtaining the initial positioning point information of the vehicle, and predicting the position information of the vehicle at the next moment by using the extended Kalman filter algorithm; during the vehicle driving process, when the vehicle reaches the next positioning point, updating the prediction information by using the extended Kalman filter algorithm.

[0055] In some embodiments, the step of predicting the vehicle driving trajectory further includes: inputting the two-dimensional position, driving speed and acceleration of the vehicle into the state transition model as state vectors for predicting the vehicle driving trajectory, and the state vectors are: where x k is the state vector, and px is the vehicle driving direction position information, p y is the vehicle lateral position information, v x is the vehicle driving direction speed information, v y is the vehicle lateral speed information, a x is the vehicle driving direction acceleration information, a y is the vehicle lateral acceleration information.

[0056] In some embodiments, calculate the observation vector: z k = Hx k + v k ; wherein, z k is the observation vector, H is the observation matrix, x k is the state vector, v k is the observation noise covariance.

[0057] In some embodiments, the prediction step calculation formula is: P k|k-1 = FP k-1 F T + Q; wherein, is the prediction state at time k based on time k - 1, F is the state transition matrix, P k is the state covariance matrix at time k, Q is the process noise covariance, F T is the transposed state transition matrix.

[0058] In some embodiments, when the vehicle reaches the positioning point during driving, calculate the Kalman gain and correct the prediction information, and its calculation formula is: K k = P k|k-1 H T (HP k|k-1 H T + R) -1 ; P k = (I - K k H)P k|k-1 , wherein, K k is the Kalman gain, P k|k-1 is the prior error covariance matrix at time k, H T is the transposed observation matrix, H is the observation matrix, R is the observation noise covariance, reflecting the positioning point measurement error, is the prediction state at time k, is the prediction state at time k based on time k - 1, P kis the state covariance matrix at time k, and I is the identity matrix. Therefore, by substituting the positioning data points and the times when the vehicle arrives at each positioning data point, the prediction of the vehicle motion state curve can be obtained through the calculation of the extended Kalman filter algorithm.

[0059] The motion trajectory of the vehicle during driving is specifically referred to Figure 8 As shown, based on the monitored discrete positioning points of the vehicle, the vehicle driving trajectory is calculated by substituting into the extended Kalman filter algorithm. Through its motion trajectory during driving, high-precision positioning of the vehicle throughout the process can be achieved. According to the requirements of the actual positioning system time resolution, the calculation step size of the algorithm can be selected, and the corresponding vehicle position detection time resolution will be obtained.

[0060] In some embodiments, the interferometric grating array optical fiber is encapsulated by pre-stretching and is armored with at least one outer sheath.

[0061] Specifically, for the interferometric grating array optical fiber sensor proposed in this application, the sensitivity of strain sensing is improved through the pre-stretching encapsulation method, and through the armored outer sheath, the grating array sensor is suitable for harsh construction environments such as cement concrete; for the distributed optical fiber sensor laid underground, specifically refer to Figure 5 As shown, the detection range based on the interferometric grating array optical fiber is sufficient to cover the width of the vehicle driving lane. For better detection effects, the detection optical cable can be laid at the center position of the vehicle driving lane to facilitate subsequent signal differentiation of vehicles in different lanes.

[0062] On the other hand, please refer to Figure 9 , the present invention also provides a high-precision positioning system for vehicles driving on the road surface, including: an acquisition module 10, configured to bury the fiber grating sensing unit along the lane direction at the center position inside the road surface of the lane to acquire real-time strain information generated between the vehicle and the road surface during driving within the detection area of the fiber grating sensing unit; an analysis module 20, configured to analyze the static strain information between the vehicle and the road surface under the action of static load; a correction module 30, configured to introduce the vehicle driving speed to correct the static strain information to obtain dynamic strain information, and draw a strain distribution curve within the detection area according to the dynamic strain information; a determination module 40, configured to determine the position information of the vehicle through the relationship between the real-time strain information and the strain distribution curve.

[0063] This application designs a sensor and a layout method for distributed strain detection, which realizes full-time and full-domain strain perception of the ground along the driving path by using fiber Bragg grating sensors and demodulators, and realizes the position detection of vehicles in the driving path through the relationship between strain and vehicle position; a state transition model is established, and an extended Kalman filtering algorithm is proposed. Based on the positioning points in the detection signal, a vehicle motion position model is constructed to realize high-precision detection of the vehicle at various positions in the driving path.

[0064] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs, etc., which can store program codes.

[0065] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods; among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided by the present invention can include non-volatile and / or volatile memories; non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory; volatile memories can include random access memory (RAM) or external cache memories; by way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0066] The above are only embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in the relevant technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A high-precision positioning method for vehicles traveling on a road surface, characterized in that the steps Including: Buried the fiber Bragg grating sensing unit along the lane direction at the center position inside the road surface to obtain the real-time strain information generated between the vehicle and the road surface within the detection area of the fiber Bragg grating sensing unit during vehicle driving; Analyze the static strain information of the vehicle and the road surface under the action of static load; Introduce the vehicle driving speed to correct the static strain information to obtain dynamic strain information, and draw a strain distribution curve within the detection area according to the dynamic strain information; Determine the position information of the vehicle through the relationship between the real-time strain information and the strain distribution curve.

2. The high-precision positioning method for a vehicle traveling on a road surface according to claim 1, characterized in that, The fiber Bragg grating sensing unit includes an interferometric grating array optical fiber, and the interferometric grating array optical fiber includes a plurality of equally spaced gratings.

3. The high-precision positioning method for a vehicle traveling on a road surface according to claim 2, characterized in that, The step of determining the position information of the vehicle through the relationship between the real-time strain information and the strain distribution curve specifically includes: Determine the minimum value point A and the minimum value point B in the strain distribution curve; When the real-time strain information corresponds to the minimum value point A, it is determined that the vehicle is close to the detection area and is spaced from the detection area by a distance a, and the vehicle position at this time is determined as the positioning point A; When the real-time strain information corresponds to the minimum value point B, it is determined that the vehicle leaves the detection area and is spaced from the detection area by a distance a, and the vehicle position at this time is determined as the positioning point B.

4. The high-precision positioning method for a road vehicle according to claim 3, characterized in that, The step of determining the minimum value point A and the minimum value point B in the strain distribution curve specifically includes: Divide the area of the strain generated between the vehicle and the road surface into a tensile state strain area and a compressive state strain area. Among them, the tensile state strain area corresponds to the vehicle position, and the compressive state strain areas are distributed at the front and rear ends in the vehicle driving direction. The maximum compressive state values of the compressive state strain areas at the front and rear ends in the vehicle driving direction respectively correspond one-to-one to the minimum value point A and the minimum value point B in the strain distribution curve.

5. The high-precision positioning method for a vehicle traveling on a road surface according to claim 4, wherein The interval distance a is half of the length of the tensile state strain area.

6. The high-precision positioning method for a vehicle traveling on a road surface according to claim 2, wherein The method steps further include: Determine the discrete positioning points of the vehicle during driving on the road surface through the fiber Bragg grating sensing unit; Calculate the vehicle driving speed in segments through the discrete positioning points; Establish a state transition model, predict the vehicle driving trajectory based on the discrete positioning points, and further judge the vehicle position information corresponding to each time point during vehicle driving.

7. The high-precision positioning method for a road vehicle according to claim 6, wherein The step of predicting the vehicle driving trajectory based on the discrete positioning points specifically includes: In the initial stage of vehicle driving, obtain the initial positioning point information of the vehicle, and use the extended Kalman filter algorithm to predict the position information of the vehicle at the next moment; During vehicle driving, when the vehicle reaches the next positioning point, use the extended Kalman filter algorithm to update the prediction information.

8. The high-precision positioning method for a vehicle traveling on a road surface according to claim 7, wherein, The step of predicting the vehicle driving trajectory further includes: Input the two-dimensional position, vehicle driving speed, and acceleration of the vehicle into the state transition model for vehicle driving trajectory prediction. The state vector is: x k = [p x , p y , v x , v y , a x , v y , where x k is the state vector, p x is the vehicle driving direction position information, p y is the vehicle lateral position information, v x is the vehicle driving direction speed information, v y is the vehicle lateral speed information, a x is the vehicle driving direction acceleration information, a y is the vehicle lateral acceleration information.

9. The high-precision positioning method for a vehicle traveling on a road surface according to claim 2, wherein The interferometric grating array optical fiber is encapsulated by pre-tensioning and is armored with at least one outer sheath.

10. A high-precision positioning system for vehicles traveling on the road, characterized in that, Including: An acquisition module, configured to bury the fiber Bragg grating sensing unit along the lane direction at the center position inside the road surface to obtain the real-time strain information generated between the vehicle and the road surface within the detection area of the fiber Bragg grating sensing unit during vehicle driving; An analysis module for analyzing the static strain information of the vehicle and the road surface under static load; A correction module for introducing the vehicle driving speed to correct the static strain information to obtain dynamic strain information, and drawing a strain distribution curve in the detection area according to the dynamic strain information; A determination module for determining the position information of the vehicle based on the relationship between the real-time strain information and the strain distribution curve.

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