Vehicle driving mileage estimation method based on UWB positioning technology

Abstract

The invention relates to the technical field of coal mine underground trackless rubber-tyred vehicle travelled distance estimation, in particular to a vehicle travelled distance estimation method based on a UWB positioning technology, which comprises the following steps: step 1, acquiring vehicle position information data through a UWB positioning base station, forming vehicle track data, and filtering the track data; 2, estimating the track mileage of the vehicle running in the signal coverage range of the UWB base station by adopting the mileage based on positioning data; and step 3, adopting a graph-based A * search algorithm to obtain a path plan for entering and leaving the blind area road section, obtaining mileage estimation of the vehicle in the blind area, and finally obtaining the complete driving mileage of the vehicle. Under the condition of not depending on complex acquisition and transmission devices, data barriers are effectively broken, the mileage value is dynamically obtained by adopting a path planning algorithm, the mileage of a signal blind area is estimated, accurate calculation of mileage data is realized, and support is provided for dynamic supervision and operation efficiency evaluation of mine vehicles.

Description

Technical Field

[0001] The present application relates to the technical field of estimating the driving mileage of trackless rubber-tyred vehicles underground in coal mines, and particularly to a method for estimating the driving mileage of vehicles based on UWB positioning technology. Background Art

[0002] The vehicle driving mileage data is one of the important parameters of the vehicle operation state. It can not only directly reflect the usage situation of the vehicle, but also be a key indicator for evaluating the effect of the transportation system. At present, although the vast majority of vehicles are equipped with odometer sensors, in the actual data integration process, additional acquisition and transmission devices are required, which increases the project construction and maintenance costs. At the same time, since the vehicles and systems are provided by different manufacturers respectively, there are differences in the data formats, interface standards, and communication protocols of each manufacturer, which increases the difficulty of data integration and results in a relatively serious phenomenon of data islands. Therefore, at the present stage, mine users have all proposed to obtain vehicle driving mileage data in other more convenient and economical ways to meet the needs of supervision.

[0003] At present, the path monitoring of vehicles underground in mines is usually achieved through the signal transmission between the in-vehicle communication system and the UWB positioning base station. However, the signal coverage range of the UWB positioning base station is limited, and it is difficult to monitor the vehicles in all areas underground in mines. Therefore, the monitoring of vehicle trajectories, paths, and the estimation accuracy of vehicle driving paths are relatively poor. In the prior art, in order to estimate the complete driving mileage of vehicles underground in mines, it is also necessary to rely on acquisition and transmission devices and use data-driven technology to output the vehicle mileage data from the odometer sensor to the auxiliary transportation system, and this method is cumbersome. Summary of the Invention

[0004] The present invention aims to solve one of the problems existing in the background art.

[0005] For this reason, the present invention provides a method for estimating the driving mileage of vehicles based on UWB positioning technology. Without relying on complex acquisition and transmission devices, it effectively breaks the data barrier. For signal blind areas, a path planning algorithm is used to dynamically obtain mileage values, realizing the accurate calculation of mileage data, and providing support for the dynamic supervision of mine vehicles and the evaluation of operation efficiency.

[0006] The technical solution adopted by the present invention to solve its technical problems is:

[0007] A method for estimating the driving mileage of vehicles based on UWB positioning technology includes:

[0008] Step 1, obtaining vehicle position information data through a UWB positioning base station to form vehicle trajectory data, and filtering the trajectory data;

[0009] Step 2: The trajectory mileage of the vehicle driving within the signal coverage range of the UWB base station is estimated based on the positioning data.

[0010] Step 3: Use the graph-based A* search algorithm to obtain the path planning for entering and leaving the blind area section, obtain the mileage estimation of the vehicle within the blind area, and finally obtain the complete driving mileage of the vehicle.

[0011] Further, in Step 1, the sliding window filtering algorithm is used to filter the trajectory data, and the arithmetic mean value of the data within the filtering window period is calculated.

[0012] Further, in Step 1, the threshold value △x of the ranging distance difference between the current moment and the previous moment's trajectory points is defined as 7m as the noise judgment threshold, and if it is greater than this threshold, it is judged as noise.

[0013] Further, in Step 2, with the base station as the origin, it is defined that the vehicle gradually enters the signal coverage area of the base station to the base station. With the base station as the origin, the distance from the vehicle driving into the signal coverage area to the origin is the negative distance L 负 , and the distance from the vehicle driving out of the signal coverage area in the original direction from the origin position is the positive distance L 正 , and the trajectory mileage of the vehicle within the signal coverage range should be: m 轨 =max(|L 负 |)+max(|L 正 |).

[0014] Further, in Step 3, based on the directed graph, the global path planning of the vehicle driving in the blind area is carried out.

[0015] Further, in Step 3, the center line points of the roadway, the points entering the blind area, and the points leaving the blind area are used to form a directed graph, and its structure is described by G=(V, E), where V is the vertex set and E is the edge set; the weight of E is the distance from vertex i to vertex j, and its distance formula is: In the formula: d is the distance value, (x i , y i , z i ) is the coordinate of vertex i, (x j , y j , z j ) is the coordinate of vertex j.

[0016] Further, in Step 3, the evaluation function of the A* algorithm is f(n)=g(n)+α×h(n), where g(n) is the actual consumption from the starting node to the current node, that is, the shortest distance between vertices in the directed graph, α is the artificially set road section weight value, and h(n) is calculated using the Manhattan distance, and its calculation formula is: h(n)=|x i -x j |+|y i-y j |+|z i -z j |, where: h(n) is the distance value, (x i , y i , z i ) is the coordinate of vertex i, (x j , y j , z j ) is the coordinate of vertex j.

[0017] Furthermore, the road segment weight value satisfies the following conditions:

[0018] Furthermore, the total mileage of the vehicle's complete travel is: P i is the track mileage of the blind area road segment, that is, min(f(n)).

[0019] The beneficial effect of the present invention is that based on the existing UWB positioning base stations and positioning data, this application does not require adding any additional hardware devices to the vehicle or the driving environment. It only relies on the existing hardware and realizes mileage statistics through software algorithms. Without relying on complex acquisition and transmission devices, it can accurately calculate mileage data, effectively break data barriers, and provide support for the dynamic supervision and operation efficiency evaluation of mine vehicles.

[0020] In the signal blind area road segment of this application, a path planning algorithm is used to dynamically obtain mileage values and realize full-path mileage statistics. Thus, the accuracy of mileage statistics is effectively improved, which has high economy, high application value and promotion potential. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The present invention will be further described below in conjunction with the drawings and embodiments.

[0022] Figure 1 is a schematic diagram of the UWB positioning system in the present invention.

[0023] Figure 2 is a schematic flow diagram of the vehicle travel mileage estimation method based on UWB positioning technology in the present invention.

[0024] Figure 3 is a schematic diagram of the structure of the filtering window in the present invention.

[0025] Figure 4 is a schematic diagram of the processing principle of the filtering window in the present invention.

[0026] Figure 5 is a schematic diagram of the vehicle travel path in the present invention.

[0027] Figure 6It is a schematic structural diagram of the driving path of the vehicle in the signal coverage area in the present invention.

[0028] Figure 7 It is a schematic diagram of the directed graph in the present invention. Detailed implementation manners

[0029] Now, the present invention will be further described in detail with reference to the accompanying drawings. These drawings are all simplified schematic diagrams, only illustrating the basic structure of the present invention in a schematic manner, so they only show the components related to the present invention.

[0030] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, so it should not be construed as a limitation to the present invention. In addition, the features defined as "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise stated, the meaning of "a plurality" is two or more.

[0031] In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0032] Refer to Figure 1 , the UWB positioning system includes an above-ground part and an underground part. Among them, the underground part has devices such as a core switch, multiple sub-switches, and UWB positioning base stations. The UWB positioning base stations and the trackless rubber-tired vehicles realize signal transmission to collect and transmit the vehicle position information. The above-ground part is mainly the industrial control computer of the auxiliary transportation system, which contains the vehicle driving mileage estimation algorithm. The above-ground and underground parts realize the interaction of data information through the industrial Ethernet. In the system architecture, the core switch and the UWB positioning base stations are essential conditions for an intelligent mine. The solution is all based on the existing hardware conditions and realizes the purpose of mileage estimation by means of software algorithms.

[0033] Refer to Figure 2, A method for estimating the driving mileage of a vehicle based on UWB positioning technology, comprising the following steps:

[0034] Step 1, trajectory filtering

[0035] The vehicle trajectory data is composed of trajectory points generated by the UWB positioning base station in chronological order, including time data and distance data. Affected by the non-line-of-sight propagation and multipath effects of the UWB positioning base station, there is a certain fluctuation in its positioning results. By performing a sliding window filtering algorithm on its trajectory data, noise point data is suppressed to improve the overall robustness of the algorithm.

[0036] Create a first-in-first-out queue (FIFO), set the filtering window period to 5 seconds, as follows Figure 3 shown. The vehicle trajectory data is filled into the queue at a rate of one trajectory point per second. When the number of trajectory points in the queue is less than or equal to the filtering window period, it continuously enters the queue. The processing principle is as Figure 4 (a), 4(b) shown. Conversely, when the number of trajectory points exceeds the filtering window period, the data that entered the queue first is dequeued, and then the subsequent data is enqueued. The processing principle is as Figure 4 (c) shown, Figure 4 In the small figure a, it is the filtering schematic diagram when the number of trajectory points is less than the filtering window period; the small figure b is the filtering schematic diagram when the number of trajectory points is equal to the filtering window period; the small figure c is the filtering schematic diagram when the number of trajectory points is greater than the filtering window period.

[0037] Calculate the arithmetic mean of the data within the filtering window period, and then compare it with the data to be enqueued. If it is within the noise threshold, it means the data is normal data and enters the queue normally; otherwise, it means the data is a noise point and the data is directly discarded.

[0038] Continuously execute the above steps until the trajectory data filtering is completed. The arithmetic mean of the data within the filtering window period is calculated using the following formula:

[0039]

[0040] In the formula: is the arithmetic mean of the data, n is the number of trajectory points within the filtering window, and x i is the trajectory point data within the filtering window.

[0041] According to the relevant regulations in the "Coal Mine Safety Regulations", when a trackless rubber-tired vehicle is transporting people, the speed shall not exceed 25 km / h. After conversion, the maximum driving speed is about 6.99 m / s. Therefore, 7 m is selected as the noise judgment threshold. Determine whether it is noise point data according to the following relationship.

[0042]

[0043] Among them, △x is the difference in the ranging distance between the trajectory points at the current moment and the previous moment.

[0044] Step 2, Trajectory mileage estimation

[0045] As Figure 5 shown, when the vehicle is driving underground, it will pass through the signal coverage area L of the positioning base station D i , and the signal blind area P i . Specifically, referring to Figure 6 , when the vehicle approaches a UWB positioning base station, the vehicle first gradually enters the signal coverage area of the base station (the range of T1-T2 in the figure). After passing through the base station D, it gradually drives away from the signal coverage area along the original direction (the range of T2-T3 in the figure). Taking the base station D as the origin, the distance from the vehicle to the origin when entering the signal coverage area is the negative distance L 负 , and the distance from the vehicle to the origin when driving out of the signal coverage area is the positive distance L 正 :

[0046] The trajectory mileage of the vehicle within the signal coverage range should be:

[0047] m 轨 = max(|L 负 |) + max(|L 正 |)

[0048] In the formula: m 轨 is the trajectory mileage within the signal coverage, L 负 is the ranging distance returned negatively by the positioning base station, and L 正 is the ranging distance returned positively by the positioning base station.

[0049] Step 3, Blind area mileage estimation

[0050] The blind area mileage estimation is divided into two steps: generating a directed graph and global path planning.

[0051] S3.1 Generating a directed graph

[0052] Construct a directed graph with the roadway centerline points, the points entering the blind area, and the points leaving the blind area. Refer to Figure 7 , and its structure is described by G=(V, E), where V is the vertex set and E is the edge set.

[0053] Among them, the vertex set of the schematic diagram is: {1, 2, 3... 6}. The weight of E is the distance from vertex i to vertex j, and its distance formula is:

[0054]

[0055] In the formula: d is the distance value, (x i , y i , z i ) is the coordinate of vertex i, (xj , y j , z j ) are the coordinates of vertex j.

[0056] S3.2 Perform global path planning in the blind area

[0057] Use the graph-based A* search algorithm to perform global path planning. The A* algorithm is a common heuristic search algorithm used to find the optimal path from the start node to the target node in a graph. Use the A* algorithm to obtain the path planning for entering and leaving the blind area section, and obtain the mileage estimation of the vehicle in the blind area. Its core idea is to guide the search direction through a heuristic evaluation function, and as much as possible preferentially select nodes with shorter estimated distances for exploration in order to expect to find the shortest path faster, thereby improving the path search efficiency. The evaluation function f(n) of the traditional A* algorithm is expressed as:

[0058] f(n) = g(n) + h(n)

[0059] In the formula: f(n) is the estimated cost from the start node to the target node; g(n) is the actual cost from the start node to the current node; h(n) is the estimated cost from the current node to the target node, also known as the heuristic function.

[0060] Generally, the conventional shortest path is not necessarily the optimal solution for the driving path. For example, there are some roadways in the mine where vehicles cannot drive, such as belt roadways, return air roadways, and sump areas, etc., which must be excluded in the path search algorithm. Therefore, the evaluation function in the above formula is optimized by introducing a manually set road section weight value, and the optimized evaluation function is:

[0061] f(n) = g(n) + α × h(n)

[0062] In the formula: f(n) is the estimated cost, g(n) is the actual cost from the start node to the current node, α is the manually set road section weight value, and h(n) is the heuristic function.

[0063] The road section weight value satisfies the following conditions:

[0064]

[0065] Specifically, the passage in the mine is difficult, and the roadways that cannot be passed are set as non-recommended routes; the conventional driving routes are set as recommended routes; for other roadways in the mine without weight settings, they are defaulted to normal routes.

[0066] h(n) is calculated using the Manhattan distance, and its calculation formula is:

[0067] h(n) = |x i - x j | + |y i-y j |+|z i -z j |

[0068] Where: h(n) is the distance value, (x i , y i , z i ) is the coordinate of vertex i, (x j , y j , z j ) is the coordinate of vertex j. Traverse all paths and calculate the path distance, and obtain the shortest path as the driving mileage in the blind area.

[0069] Step 4, Estimation of the complete driving mileage of the vehicle

[0070] The complete driving mileage of the vehicle includes the driving mileage within the signal coverage area of the base station and the driving mileage in the signal blind area. The formula for estimating the total complete driving mileage of the vehicle is:

[0071]

[0072] Where: m is the total driving mileage, m 轨 is the trajectory mileage within the positioning signal coverage range, P i is the trajectory mileage of the blind area section, that is, min(f(n)).

[0073] The algorithm process of this application does not require adding any additional hardware devices to the vehicle or the driving environment. It only relies on the existing hardware and realizes mileage statistics through software algorithms, which has high economy, high application value and promotion potential.

[0074] Specifically, based on the existing UWB positioning base stations and positioning data, this application effectively improves the accuracy of mileage statistics. In the signal blind area section, a path planning algorithm is used to dynamically obtain mileage values and realize full-path mileage statistics.

[0075] Inspired by the above ideal embodiments according to the present invention, through the above description, relevant staff can completely make various changes and modifications without departing from the technical idea of this invention. The technical scope of this invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A method for estimating the driving mileage of a vehicle based on UWB positioning technology, characterized in that, including Step 1: Obtain vehicle position information data through a UWB positioning base station, form vehicle trajectory data, and perform filtering processing on the trajectory data; Step 2: For the trajectory mileage of the vehicle driving within the signal coverage range of the UWB base station, use mileage estimation based on positioning data; Step 3: Use the graph-based A* search algorithm to obtain the path planning for entering and leaving the blind area section, obtain the mileage estimation of the vehicle in the blind area, and finally obtain the complete driving mileage of the vehicle.

2. The vehicle driving mileage estimation method based on UWB positioning technology according to claim 1, wherein In Step 1, use a sliding window filtering algorithm to filter the trajectory data and calculate the arithmetic mean of the data within the filtering window period.

3. The vehicle driving mileage estimation method based on UWB positioning technology according to claim 2, wherein In Step 1, define the ranging distance difference threshold Δx between the current moment and the previous moment's trajectory points as 7m as the noise judgment threshold, and if it is greater than this threshold, it is judged as noise.

4. The method for estimating the driving mileage of a vehicle based on the UWB positioning technology according to claim 1, characterized in that, In Step 2, with the base station as the origin, define the distance from when the vehicle gradually enters the signal coverage area of the base station to the base station. Taking the base station as the origin, the distance from when the vehicle drives into the signal coverage area to the origin is the negative distance L 负 , and the distance from when the vehicle drives out of the signal coverage area in the original direction from the origin position is the positive distance L 正 . The trajectory mileage of the vehicle within the signal coverage range should be: m 轨 = max(|L 负 |) + max(|L 正 |).

5. The method for estimating the driving mileage of a vehicle based on the UWB positioning technology according to claim 1, characterized in that In Step 3, based on a directed graph, perform global path planning for the vehicle's driving in the blind area.

6. The method for estimating the driving mileage of a vehicle based on the UWB positioning technology according to claim 5, characterized in that In step three, a directed graph is formed by the roadway centerline points, the entry blind zone points, and the departure blind zone points. Its structure is described by G = (V, E), where V is the vertex set and E is the edge set; the weight of E is the distance from vertex i to vertex j, and its distance formula is: In the formula: d is the distance value, (x i , y i , z i ) is the coordinate of vertex i, (x j , y j , z j ) is the coordinate of vertex j.

7. The method for estimating the driving mileage of a vehicle based on the UWB positioning technology according to claim 6, characterized in that, In Step 3, the evaluation function f(n) of the A* algorithm is f(n) = g(n) + α × h(n), where g(n) is the actual cost from the starting node to the current node, that is, the shortest distance between vertices in the directed graph, α is the road segment weight value set artificially, and h(n) is calculated using the Manhattan distance. Its calculation formula is: h(n) = |x i -x j | + |y i -y j | + |z i -z j |. In the formula: h(n) is the distance value, (x i , y i , z i ) are the coordinates of vertex i, and (x j , y j , z j ) are the coordinates of vertex j.

8. The method for estimating the driving mileage of a vehicle based on the UWB positioning technology according to claim 7, characterized in that, The weight value of the said road section satisfies the following conditions:

9. The method for estimating the driving mileage of a vehicle based on the UWB positioning technology according to claim 7, wherein When the total complete driving mileage of the vehicle is: P i is the trajectory mileage of the blind area section, that is, min(f(n)).

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