Watering route optimization method, system and device of watering cart and storage medium

Abstract

The invention relates to a watering route optimization method, system and device of a watering cart and a storage medium, and belongs to the technical field of route optimization, and the method comprises the steps that the target watering amount is calculated according to point cloud data and an initial humidity index of a to-be-watered road section, and the target watering amount is the water amount needed by the to-be-watered road section; a two-dimensional array is constructed according to a first identifier and a second identifier, the first identifier is used for representing an idle watering cart, and the second identifier is used for representing a road section to be watered; a target watering cart is determined according to the target watering amount and a coding value, the coding value corresponds to the two-dimensional array, the coding value comprises the initial water storage amount of the watering cart and the distance between the watering cart and the road section to be watered, and the target watering cart provides the target watering amount; the watering path can be optimized according to the distance between the watering cart and the to-be-watered road section and the initial water storage capacity which can be provided by the watering cart for the to-be-watered road section, and the effect of reducing the watering cost is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of route optimization, and in particular to a method, system, device and storage medium for optimizing a watering route of a sprinkler truck. Background Art

[0002] Self-driving cars use a variety of technologies including radar, laser, ultrasound, positioning systems, odometers, computer systems, etc. to sense the surrounding environment, and use advanced computer system calculations and control to identify obstacles and various signs, thus realizing the unmanned driving function of self-driving cars and saving labor costs. Therefore, it is widely used in many fields such as unmanned delivery, unmanned patrol, unmanned cleaning, and trunk logistics.

[0003] In a mining environment, for most common self-driving sprinkler trucks, the principle of generating watering paths is mostly to ensure that the vehicle has no collisions, at the expense of the shortest path length. This makes the self-driving sprinkler trucks tend to take some "shortcuts" and try to obtain the lowest possible cost. The working goal of the self-driving sprinkler truck is to fully cover the road section with water. At this time, evaluating the path planning only at the cost of path length is not a very appropriate solution. For example, when the demand for water on a road section is far greater than the amount of water that the self-driving sprinkler truck can carry, it may cause the self-driving sprinkler truck to make multiple round trips to achieve full coverage of watering, resulting in increased watering costs. Summary of the invention

[0004] In order to optimize the watering path of an autonomous driving sprinkler truck and reduce the cost of watering, the present application provides a method, system, device and storage medium for optimizing the watering route of a sprinkler truck.

[0005] In a first aspect of the present application, a method for optimizing a watering route of a watering truck is provided. The method comprises: Calculate the target watering amount according to the point cloud data of the road section to be watered and the initial humidity index, wherein the target watering amount is the amount of water required for the road section to be watered; Constructing a two-dimensional array according to a first identifier and a second identifier, wherein the first identifier is used to indicate an idle sprinkler truck, and the second identifier is used to indicate the road section to be sprinkled; The target sprinkler truck is determined according to the target watering volume and the coding value, wherein the coding value corresponds to the two-dimensional array, and the coding value includes the initial water storage capacity of the sprinkler truck and the distance from the sprinkler truck to the road section to be sprinkled. The target sprinkler truck is a sprinkler truck that provides the target watering volume.

[0006] By adopting the above technical solution, first, the required amount of water is calculated based on the point cloud data and initial humidity index of the road section to be sprinkled, and then a binding relationship is established between each road section to be sprinkled and an idle sprinkler truck, that is, a two-dimensional array is obtained, and the two-dimensional array is mapped to a coded value composed of the initial water storage capacity of the sprinkler truck and the distance from the sprinkler truck to the road section to be sprinkled. Then, for each road section to be sprinkled, it is comprehensively considered whether the initial water storage capacity of the sprinkler truck meets the demand and whether the distance from the sprinkler truck to the road section to be sprinkled is short enough, so that when the sprinkler truck performs the sprinkling task, the short distance is no longer simply used as a condition for selecting the sprinkling path, and the situation where the sprinkler truck has to go back and forth many times is avoided, thereby achieving the purpose of saving the sprinkling cost.

[0007] In a possible implementation, determining a target sprinkler truck according to the target watering amount and the coding value includes: Selecting a code value where the initial water storage amount is greater than or equal to the target watering amount as a pending code value; Determine whether the pending code value satisfies: F=1, where F is the number of the pending code values; If yes, the pending code value is determined as the target code value, and the sprinkler truck involved in the target code value is determined as the target sprinkler truck; If not, and F>1, then calculate the dispatching scores of the sprinkler trucks involved in the pending code value, and determine the sprinkler truck with the largest dispatching score as the target sprinkler truck, the dispatching score is used to reflect the compatibility of the sprinkler truck and the road section to be sprinkled; If not, and F=0, then calculate the total consumption score for each pair of sprinkler trucks, and determine the pair of sprinkler trucks with the smallest total consumption score as the target sprinkler trucks, each pair of sprinkler trucks consists of two sprinkler trucks, and the total consumption score is used to reflect the cost of each pair of sprinkler trucks when watering the road section to be watered.

[0008] By adopting the above technical solution, first, if the initial water storage capacity of only one sprinkler truck meets the water volume required by the road section to be sprinkled, the sprinkler truck is used to perform the watering task, avoiding the cost increase caused by using multiple sprinkler trucks to provide the target watering volume for the same road section to be sprinkled at the same time. When the initial water storage capacity of multiple sprinkler trucks meets the water volume required by the road section to be sprinkled, it is comprehensively considered whether the initial water storage capacity of the sprinkler truck meets the demand and whether the distance from the sprinkler truck to the road section to be sprinkled is short enough. In addition, when the initial water storage capacity of any sprinkler truck does not meet the water volume required by the road section to be sprinkled, it is comprehensively considered whether the initial water storage capacity of the two sprinkler trucks meets the demand and whether the distance from each sprinkler truck to the road section to be sprinkled is short enough, so as to ensure that the target sprinkler truck currently matched to the road section to be sprinkled is the best choice, thereby achieving the purpose of reducing the cost of watering.

[0009] In a possible implementation, the calculating of the dispatching score of the sprinkler truck involved in the pending code value includes: Obtaining a first score according to the distance from the watering vehicle to the road section to be watered; Calculate the difference between the initial water storage amount in the pending code value and the target watering amount to obtain a second score; Obtaining a water quantity weight according to the density of the road section to be watered in the area where the road section to be watered is located; The calculation formula for calculating the scheduling score is: , where S 总 is the scheduling score, S1 is the first score, S2 is the second score, and W is the water volume weight.

[0010] By adopting the above technical scheme, when there are multiple sprinkler trucks whose initial water storage capacity meets the water volume required by the road section to be sprinkled, the dispatch score of each sprinkler truck is calculated. The calculation process of the dispatch score involves the distance from the sprinkler truck to the road section to be sprinkled, the difference between the initial water storage capacity of the sprinkler truck and the target watering capacity, and the density of the road section to be sprinkled in the area where the road section to be sprinkled is located. The addition of multiple factors ensures the accuracy of the calculated dispatch score, so that even if the distance between the sprinkler truck and the road section to be sprinkled is not the shortest, the sprinkler truck can carry out watering operations on other road sections to be sprinkled nearby, thereby reducing the number of dispatching sprinkler trucks, improving the utilization rate of sprinkler trucks, and achieving the purpose of saving sprinkling costs.

[0011] In a possible implementation, the first score is obtained according to the distance from the sprinkler vehicle to the road section to be sprinkled, including: the calculation formula of the first score is: , where k is the maximum value of the distance involved in the undetermined encoding value, d i is the distance from the i-th sprinkler truck to the road section to be sprinkled.

[0012] In a possible implementation, the step of obtaining the water volume weight according to the density of the road section to be watered in the area where the road section to be watered is located includes: The calculation formula of the water volume weight is: , where m is the number of road sections to be watered whose distance to the road section to be watered is less than the distance threshold, and M is the total number of road sections to be watered.

[0013] In a possible implementation, the calculating of the total consumption score of each pair of sprinkler trucks includes: Calculate the sum of the initial water storage of the two sprinkler trucks in each pair of sprinkler trucks; Calculate the difference between the sum and the target watering amount, and use the difference as the initial score of each pair of sprinkler vehicles; Calculate the distances from the two sprinkler trucks in each pair of sprinkler trucks to the road section to be sprinkled; Add the two distances corresponding to each pair of sprinklers to get the additional score; The initial score and the additional score are added together to obtain the total consumption score.

[0014] By adopting the above technical solution, when the initial water storage capacity of two sprinkler trucks is needed to meet the water volume required by the road section to be sprinkled, it is necessary to consider the distance from each pair of sprinkler trucks to the road section to be sprinkled and the difference between the initial water storage capacity of each pair of sprinkler trucks and the target watering volume. The total consumption score is calculated based on these two factors. The longer the distance or the greater the difference in water volume, the greater the total consumption score obtained, and the smaller the probability of the corresponding pair of sprinkler trucks being selected, thereby ensuring that the two selected sprinkler trucks are the best choice to achieve the purpose of saving watering costs.

[0015] In a possible implementation, the method further includes: when there are multiple road sections to be watered: Retrieving historical traffic data of each road section to be watered, wherein the historical traffic data includes vehicle flow and pedestrian flow; Determine the watering time period of each road section to be watered according to the historical traffic data; Sorting the plurality of road sections to be watered according to the order of the watering time periods to obtain a data list; According to the order of the road sections to be watered in the data list, the target watering vehicle for each road section to be watered is determined in sequence.

[0016] By adopting the above technical solution and determining the watering time period based on historical traffic data, the time period with relatively low vehicle and pedestrian traffic can be selected as the watering time period to reduce the traffic impact caused by the execution of the watering task. In addition, after sorting the multiple sections to be watered according to the order of the watering time periods, the target watering truck for each section to be watered is determined in turn according to the new order, so that the sections to be watered that are ranked first are given priority for watering. The watering truck that has completed the watering operation can also be re-paired with other sections to be watered, thereby improving the utilization rate of the watering truck and reducing the demand for the number of watering trucks, thereby achieving the purpose of saving watering costs.

[0017] In a second aspect of the present application, a system for optimizing the watering route of a watering truck is provided. The system comprises: A data calculation module, used for calculating a target watering amount according to the point cloud data of the road section to be watered and the initial humidity index, wherein the target watering amount is the amount of water required for the road section to be watered; A data processing module, used for constructing a two-dimensional array according to a first identifier and a second identifier, wherein the first identifier is used for indicating an idle sprinkler truck, and the second identifier is used for indicating the road section to be sprinkled; A data determination module is used to determine a target sprinkler truck according to the target watering volume and a coding value, wherein the coding value corresponds to the two-dimensional array, and the coding value includes an initial water storage capacity of the sprinkler truck and a distance from the sprinkler truck to the road section to be sprinkled, and the target sprinkler truck is a sprinkler truck that provides the target watering volume.

[0018] In a third aspect of the present application, a device for optimizing a watering route of a watering truck is provided, which includes a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, any of the above methods for optimizing a watering route of a watering truck is implemented.

[0019] In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, any of the above-mentioned methods for optimizing the watering route of a sprinkler truck is implemented.

[0020] In summary, the present application includes at least one of the following beneficial technical effects: First, the required amount of water is calculated based on the point cloud data and initial humidity index of the road section to be sprinkled, and then a binding relationship is established between each road section to be sprinkled and an idle sprinkler truck, that is, a two-dimensional array is obtained, which is mapped to a coded value consisting of the initial water storage capacity of the sprinkler truck and the distance from the sprinkler truck to the road section to be sprinkled. Then, for each road section to be sprinkled, it is comprehensively considered whether the initial water storage capacity of the sprinkler truck meets the demand and whether the distance from the sprinkler truck to the road section to be sprinkled is short enough, so that when the sprinkler truck performs the sprinkling task, the short distance is no longer simply used as a condition for selecting the sprinkling path, avoiding the situation where the sprinkler truck has to go back and forth multiple times, thereby achieving the purpose of saving sprinkling costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flow chart of a method for optimizing a watering route of a sprinkler truck in an embodiment of the present application.

[0022] Figure 2 It is a block diagram of a watering route optimization system for a sprinkler truck according to an embodiment of the present application.

[0023] Explanation of the accompanying drawings: 1. Data calculation module; 2. Data processing module; 3. Data determination module. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] On the transportation roads in the mining area, a large amount of dust will be generated during mining and transportation operations. The dust will not only pollute the surrounding environment and damage the respiratory health of on-site workers, but also affect the driver's line of sight and the perception data of the on-board laser radar, endangering driving safety. Therefore, sprinkler trucks are usually arranged on the main transportation roads in the mining area to spray water on the road surface to suppress dust. The sprinkler truck uses an autonomous driving vehicle, which is also called an unmanned vehicle, a computer-driven vehicle, or a wheeled mobile robot. It is an intelligent vehicle that achieves unmanned driving through a computer system.

[0026] In order to adapt to the differences in dust levels and dust suppression requirements on various mining and transportation roads in the mining area, a variety of sprinkler trucks with different capacities are set up. Different sprinkler trucks may be parked at cleaning stations in different locations, and as the sprinkler truck moves while performing the sprinkler task, the distance between the sprinkler truck and some mining roads also changes. In order to quickly mobilize sprinkler trucks to perform sprinkler tasks and achieve the purpose of saving sprinkler costs, this application proposes a method for optimizing the sprinkler route of sprinkler trucks. Figure 1 As shown, the main process of the watering route optimization method of the sprinkler truck is described as follows.

[0027] Step S100, calculating a target watering amount according to the point cloud data of the road section to be watered and the initial humidity index, the target watering amount being the amount of water required for the road section to be watered.

[0028] First, a laser radar is installed at the rear of the mobile vehicle. The laser radar is configured to collect point cloud data of the mining road behind the vehicle. The point cloud data includes the three-dimensional coordinate information of the mining road and the reflection intensity information of the dust. The mobile vehicle is also provided with a dust concentration determination module used in conjunction with the laser radar. The dust concentration determination module is configured to perform dust concentration analysis based on the collected point cloud data located on the mining road to obtain a dust concentration index, that is, to obtain the dust concentration situation on the mining road. It should be noted that the mobile vehicle can be a sprinkler truck or other vehicles specifically used to detect the dust concentration index of mining roads.

[0029] At the same time, dust sensors can be deployed on the mine roads to monitor the dust situation and obtain the required dust concentration index. The specific deployment situation can be determined according to the mine roads. For example, the longer the mine road is and the wider the road surface is, the more dust sensors are deployed. The density of dust sensor deployment can also be set according to actual needs.

[0030] Then, the humidity parameters of the mining road are collected by the humidity sensor installed on the mining road. In this example, the humidity parameter collected by the humidity sensor is called the initial humidity index, and the mining road is referred to as the road section to be sprinkled with water.

[0031] Then, the mobile vehicle and the humidity sensor upload the data collected by each to the dispatch center, which is equipped with a server and a display. Among them, the server can calculate the amount of water required for the road section to be sprinkled with water based on the dust concentration index and the initial humidity index, which is called the target watering amount in this example. Specifically, the corresponding target humidity index is first matched according to the dust concentration index. The target humidity index refers to the increase in the viscosity of the wetted road surface and the reduction of the dust concentration to the preset concentration after the road surface is sprinkled with water to remove dust. The corresponding relationship can be obtained through a limited number of experimental calculations. Then, the difference between the target humidity index and the initial humidity index is calculated, and the target watering amount is obtained by dividing the area of ​​the road section to be sprinkled with water by the difference. The area of ​​the road section to be sprinkled with water can be obtained by synchronously collecting the mobile vehicle when collecting point cloud data, or it can be retrieved from the geographic information system, that is, the length, area and other information of each mining road are stored in the geographic information system.

[0032] Step S200: construct a two-dimensional array according to a first identifier and a second identifier, wherein the first identifier is used to indicate an idle sprinkler truck, and the second identifier is used to indicate a road section to be sprinkled.

[0033] Each watering truck has a unique corresponding identifier, and each road section to be watered is also provided with a unique corresponding identifier. The identifiers corresponding to the watering truck and the road section to be watered are respectively called the first identifier and the second identifier. The first identifier and the second identifier can be represented by English letters or numerical values, and in this example, they are represented by natural numbers.

[0034] For each idle sprinkler truck and each road section to be sprinkled, retrieve their corresponding identifiers, and construct multiple two-dimensional arrays by forming a team of any two identifiers. The format of the two-dimensional array is a[x][y], where x represents the identifier of the idle sprinkler truck, that is, x represents the first identifier, and y represents the identifier corresponding to the road section to be sprinkled, that is, y represents the second identifier. To facilitate the explanation of the process of constructing a two-dimensional array, an example is given: assuming that the identifiers of the idle sprinkler trucks are 0, 1, 2, and 3, and the identifiers of the road sections to be sprinkled are 0 and 1, the obtained two-dimensional arrays are a[0][0], a[0][1], a[1][0], a[1][1], a[2][0], a[2][1], a[3][0], a[3][1].

[0035] Based on each obtained two-dimensional array, the two-dimensional array is mapped to the corresponding code value. The code value corresponding to the two-dimensional array is composed of the current water storage capacity of the sprinkler in the two-dimensional array and the distance from the sprinkler to the road section to be sprinkled in the same two-dimensional array. In this example, the current water storage capacity of the sprinkler in the two-dimensional array is called the initial water storage capacity. In other words, according to the initial water storage capacity of the sprinkler in the two-dimensional array and the distance from the sprinkler to the road section to be sprinkled, the two are encoded to obtain the code value corresponding to the two-dimensional array. In a specific example, the format of the code value is 00000000, wherein the first four digits represent the initial water storage capacity, and the last four digits represent the distance from the sprinkler to the road section to be sprinkled. In other examples, the code value can also be set to other formats, so as to achieve that the code value represents the initial water storage capacity and the distance from the sprinkler to the road section to be sprinkled.

[0036] Step S300, determining a target sprinkler truck according to a target watering volume and a coding value, wherein the coding value corresponds to a two-dimensional array and includes an initial water storage volume of the sprinkler truck and a distance from the sprinkler truck to the road section to be sprinkled. The target sprinkler truck is a sprinkler truck that provides the target watering volume.

[0037] First, multiple road sections to be watered are sorted in the order of the watering time periods to obtain a data list. Specifically, based on the historical traffic data of each road section to be watered, which is the vehicle flow and pedestrian flow of the road section to be watered in the past, a time period with relatively low vehicle flow and pedestrian flow is selected as the watering time period to reduce the degree of traffic impact caused by the execution of the watering task.

[0038] Then, according to the order of the road sections to be watered in the data list, a target watering vehicle to be matched is selected for each road section to be watered. In order to facilitate the description of the specific matching process, steps S310 to S350 take a road section to be watered and the corresponding target watering vehicle as an example.

[0039] Step S310, select the code value whose initial water storage capacity is greater than or equal to the target watering capacity to be determined as the pending code value. Since there are many types of sprinkler trucks, and the watering time periods of the road section to be watered may be different, there are multiple idle sprinkler trucks in the same time period, and each idle sprinkler truck is combined with the road section to be watered to obtain a two-dimensional array, and each two-dimensional array has a corresponding code value. Therefore, a road section to be watered has multiple corresponding code values, and then select the code value whose initial water storage capacity is greater than or equal to the target watering capacity from the multiple code values ​​to be determined as the pending code value.

[0040] Step S320: determine whether the pending code value satisfies: F=1, where F is the number of pending code values.

[0041] Step S330, if yes, it means that only one sprinkler truck has an initial water storage capacity greater than or equal to the target watering capacity, which also means that only this sprinkler truck can be mobilized to perform the watering task of the road section to be watered. Therefore, at this time, a single pending code value is used as the target code value, and the sprinkler truck involved in the target code value is used as the target sprinkler truck, and the target sprinkler truck provides the required water volume for the road section to be watered.

[0042] Step S340, if not, and the number of pending code values ​​F>1, then calculate the difference between the initial water storage capacity and the target watering amount, and determine whether the minimum value of the difference and the minimum value of the distance in the pending code value are the same pending code value. If it is the same pending code value, then the pending code value is used as the target code value, and the sprinkler truck involved in the target code value is set as the target sprinkler truck, and the target sprinkler truck provides the target watering amount for the road section to be sprinkled. Otherwise, when the minimum value of the difference and the minimum value of the distance in the pending code value are not the same pending code value, it is necessary to calculate the scheduling score of the sprinkler truck involved in the pending code value, and then select a sprinkler truck with the largest scheduling score as the target sprinkler truck. Specifically, the process of calculating the scheduling score of the sprinkler truck involved in the pending code value is shown in steps S341 to S344.

[0043] Step S341: Obtain a first score according to the distance from the sprinkler to the road section to be sprinkled, the first score being represented by S1. In a specific example, the calculation formula for calculating the first score S1 is: , where k is the maximum value of the distance, which refers to the maximum value of the distance in the undetermined encoding value, d i is the distance from the i-th sprinkler truck to the road section to be sprinkled.

[0044] Step S342: Obtain a second score according to the target watering amount and the initial water storage amount in the to-be-determined coded value, the second score being represented by S2. In a specific example, the calculation formula for calculating the second score S2 is: , where L i is the initial watering amount of the i-th sprinkler truck, and L0 is the target watering amount.

[0045] Step S343: obtain a water volume weight according to the density of the road section to be watered in the area where the road section to be watered is located, and the water volume weight is represented by W. In a specific example, the calculation formula for calculating the water volume weight W is: , where m is the number of road sections to be watered whose distance to the road section to be watered is less than the distance threshold, and M is the total number of road sections to be watered.

[0046] Step S344: Calculate the dispatch score of the sprinkler truck according to the first score, the second score and the water volume weight. The dispatch score of the sprinkler truck is expressed as S 总 Indicates that .

[0047] In actual use, the dispatching score of the sprinkler truck involved in the pending code value is calculated according to the above steps S341 to S344, so that the sprinkler truck with the highest dispatching score can be selected as the target sprinkler truck, that is, the sprinkler truck whose initial water storage capacity meets the water volume required by the road section to be sprinkled is selected, and the sprinkler truck can also carry out watering operations on other road sections to be sprinkled nearby, thereby reducing the number of dispatching sprinkler trucks and saving watering costs.

[0048] Step S350, if not, and the number of pending code values ​​F=0, first sort the code values ​​in ascending or descending order according to the initial water storage capacity, then retrieve the initial water storage capacity in the code value in a cross-retrieval order from the beginning to the end, add the initial water storage capacity retrieved twice adjacently, that is, add the initial water storage capacity retrieved twice from the beginning to the end to obtain multiple groups of sum values, at this time, each group of sum values ​​corresponds to two sprinkler trucks, that is, one group of sum values ​​corresponds to a pair of sprinkler trucks. Then, calculate the difference between each group of sum values ​​and the target watering amount to obtain the initial score of each pair of sprinkler trucks. Secondly, calculate the distance from each pair of sprinkler trucks to the road section to be sprinkled, specifically, respectively calculate the distance from each sprinkler truck in each pair of sprinkler trucks to the road section to be sprinkled, and then add the two distances to obtain the additional score of the pair of sprinkler trucks. Finally, the initial score and additional score of each pair of sprinkler trucks are added together to get the total consumption score. The pair of sprinkler trucks with the smallest total consumption score is used as the target sprinkler trucks for the road section to be sprinkled, that is, the two sprinkler trucks provide the target watering volume for the road section to be sprinkled at the same time.

[0049] It should be noted that the capacity of the sprinkler truck is usually larger than the amount of water required for a single road section to be watered, so the number of pending code values ​​F=0 is rare. Basically, when the sprinkler truck completes the watering task and re-enters the idle state, the remaining water volume does not meet the water volume required for the road section to be watered.

[0050] Each road section to be watered in the data list can be matched to a corresponding target sprinkler truck according to the above steps. In the matching process, priority is given to sprinkler trucks with water volume that meets the demand and with a short distance. This allows the sprinkler truck to no longer simply use short distance as a condition for selecting a sprinkler route when performing a sprinkler task, thus avoiding the situation where the sprinkler truck has to make multiple round trips, thereby achieving the goal of saving sprinkler costs.

[0051] In summary, the present invention provides a method for optimizing the watering route of a mine sprinkler truck, and the implementation principle is as follows: first, based on the collected mine environment point cloud data and the initial humidity index of each road section to be sprinkled, the precise amount of water required is calculated, and then each road section to be sprinkled is bound to an idle sprinkler truck, that is, a two-dimensional array is obtained, and the two-dimensional array is mapped to a comprehensive coding value composed of parameters such as the initial water storage capacity of the sprinkler truck, the distance from the sprinkler truck to the road section to be sprinkled, the distance from the sprinkler truck to the nearest water filling station, and the estimated remaining water volume after the current road section is completed. Then, for each road section to be sprinkled, the method selects a coding value whose initial water storage capacity is greater than or equal to the required water volume of the road section to be sprinkled through an intelligent algorithm, and at the same time comprehensively considers the actual driving distance from the sprinkler truck to the road section to be sprinkled, the road section density distribution in the area where the road section to be sprinkled is located, the spatial distribution of the water filling station, and the distance from the sprinkler truck to the nearest water filling station after the current road section is completed, so as to reasonably evaluate and plan the cruising range and water filling time of the sprinkler truck.

[0052] For example, the initial information of the road sections and watering trucks to be sprinkled in the current mining area is obtained: Based on the collected mine environment point cloud data, the system obtains the specific conditions of 4 road sections to be sprinkled (respectively recorded as sections A, B, C, and D). Among them, section A is the main transportation road with a length of 2.5 kilometers; section B is the working platform of the mining site with an area of ​​about 3,000 square meters; section C is the spoil dump road with a length of 1.8 kilometers; section D is the access road to the mining site with a length of 1.2 kilometers. At the same time, the system shows that there are currently 3 idle watering trucks (numbered 1, 2, and 3), of which the water storage capacity of No. 1 watering truck is 15 tons, the water storage capacity of No. 2 watering truck is 12 tons, and the water storage capacity of No. 3 watering truck is 10 tons, and there are 2 water filling stations (recorded as S1 and S2) in the mining area.

[0053] Water demand is calculated based on point cloud data and the initial humidity index of each road section: the system detects that the average humidity index of section A is 0.3 (relatively dry), and the water demand is 8 tons; the average humidity index of section B is 0.5 (medium humidity), and the water demand is 5 tons; the average humidity index of section C is 0.2 (very dry), and the water demand is 7 tons; the average humidity index of section D is 0.4 (medium to dry), and the water demand is 4 tons.

[0054] Establish the position relationship matrix between the road sections to be sprinkled and the sprinkler trucks: The system obtains the actual distance data between each sprinkler truck and the road sections to be sprinkled. For example, the distance between sprinkler truck No. 1 and road sections A, B, C, and D is 1.2 km, 2.5 km, 3.8 km, and 2.0 km, respectively, and the distance to water filling stations S1 and S2 is 2.0 km and 3.5 km, respectively; the distance between sprinkler truck No. 2 and road sections A, B, C, and D is 2.8 km, 1.5 km, 2.2 km, and 3.0 km, respectively, and the distance to water filling stations S1 and S2 is 1.8 km and 2.5 km, respectively; the distance between sprinkler truck No. 3 and road sections A, B, C, and D is 3.0 km, 2.8 km, 1.5 km, and 2.6 km, respectively, and the distance to water filling stations S1 and S2 is 2.5 km and 1.6 km, respectively.

[0055] The system performs intelligent scheduling based on comprehensive evaluation: First, the priority of each road section is determined. Since Section A is the main road and relatively dry, it has the highest priority. The system analysis found that Sprinkler No. 1 is closest to Section A and has sufficient water (15 tons>8 tons), so Sprinkler No. 1 is arranged to perform the watering task of Section A. After completion, Sprinkler No. 1 has 7 tons of water remaining, and its location is 2.5 kilometers away from Section B. Considering that Section B only needs 5 tons of water and Sprinkler No. 1 has enough remaining water, the system continues to arrange Sprinkler No. 1 to complete Section B, and then immediately go to the water filling station S1 1.5 kilometers away to replenish water. At the same time, Sprinkler No. 3 is closest to Section C (1.5 kilometers) and the water volume meets the demand (10 tons>7 tons), so the system arranges it to perform the watering task of Section C. Sprinkler No. 2 is arranged to perform the watering task of Section D (4 tons of water required) because it has sufficient water (12 tons) and is in a moderate current position.

[0056] By incorporating key factors such as the location of the watering station and the density of the road section into the path planning, the target watering truck that matches the road section to be watered is the optimal choice. This not only optimizes the watering path of the watering truck, but more importantly, by rationally planning the watering route, the problem of frequent round trips of the watering truck to the watering station is avoided, and the empty driving distance is reduced, thereby achieving the purpose of reducing energy consumption, saving time and reducing operating costs. This method is particularly suitable for improving the efficiency of watering operations in complex mining terrain environments. This method realizes the intelligent scheduling of mine watering operations through intelligent algorithms, significantly improves the operating efficiency while ensuring the quality of watering, and has important practical value.

[0057] Figure 2 A block diagram of a watering route optimization system for a watering truck according to an embodiment of the present application is shown. The system includes a data calculation module 1, a data processing module 2 and a data determination module 3.

[0058] The data calculation module 1 is used to calculate the target watering amount according to the point cloud data of the road section to be watered and the initial humidity index. The target watering amount is the amount of water required for the road section to be watered.

[0059] The data processing module 2 is used to construct a two-dimensional array according to a first identifier and a second identifier, wherein the first identifier is used to indicate an idle sprinkler truck, and the second identifier is used to indicate a road section to be sprinkled.

[0060] Data determination module 3 is used to determine the target sprinkler truck according to the target watering volume and the coding value. The coding value corresponds to the two-dimensional array. The coding value includes the initial water storage capacity of the sprinkler truck and the distance from the sprinkler truck to the road section to be sprinkled. The target sprinkler truck is the sprinkler truck that provides the target watering volume.

[0061] The modules involved in the embodiments described in the present application may be implemented by software or hardware. The modules described may also be set in a processor, for example, it may be described as: a processor includes a data calculation module 1, a data processing module 2 and a data determination module 3. The names of these modules do not constitute a limitation on the modules themselves in some cases. For example, the data calculation module 1 may also be described as "a module for calculating the target watering amount based on the point cloud data of the road section to be watered and the initial humidity index".

[0062] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0063] In order to better execute the program of the above method, the present application also provides a watering route optimization device for a sprinkler truck, which includes a memory and a processor.

[0064] The memory may be used to store instructions, programs, codes, code sets or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the above-mentioned method for optimizing the watering route of a sprinkler truck, etc.; the data storage area may store data involved in the above-mentioned method for optimizing the watering route of a sprinkler truck, etc.

[0065] The processor may include one or more processing cores. The processor calls the data stored in the memory by running or executing the instructions, programs, code sets or instruction sets stored in the memory, performs various functions of the present application and processes data. The processor may be at least one of a special purpose integrated circuit, a digital signal processor, a digital signal processing device, a programmable logic device, a field programmable gate array, a central processing unit, a controller, a microcontroller and a microprocessor. It is understandable that for different devices, the electronic device used to implement the above-mentioned processor function can also be other, and the embodiments of the present application are not specifically limited.

[0066] The present application also provides a computer-readable storage medium, for example, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes. The computer-readable storage medium stores a computer program that can be loaded by a processor and execute the above-mentioned method for optimizing the watering route of a sprinkler truck.

[0067] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present application (but not limited to) by each other to form a technical solution.

Claims

1. A method for optimizing the watering route of a sprinkler truck, characterized in that: include: Calculate the target watering amount according to the point cloud data of the road section to be watered and the initial humidity index, wherein the target watering amount is the amount of water required for the road section to be watered; Constructing a two-dimensional array according to a first identifier and a second identifier, wherein the first identifier is used to indicate an idle sprinkler truck, and the second identifier is used to indicate the road section to be sprinkled; The target sprinkler truck is determined according to the target watering volume and the coding value, wherein the coding value corresponds to the two-dimensional array, and the coding value includes the initial water storage capacity of the sprinkler truck and the distance from the sprinkler truck to the road section to be sprinkled. The target sprinkler truck is a sprinkler truck that provides the target watering volume.

2. The method for optimizing the watering route of a sprinkler truck according to claim 1, characterized in that: The step of determining the target sprinkler truck according to the target watering amount and the coding value includes: Selecting a code value where the initial water storage amount is greater than or equal to the target watering amount as a pending code value; Determine whether the pending code value satisfies: F=1, where F is the number of the pending code values; If yes, the pending code value is determined as the target code value, and the sprinkler truck involved in the target code value is determined as the target sprinkler truck; If not, and F>1, then calculate the dispatching scores of the sprinkler trucks involved in the pending code value, and determine the sprinkler truck with the largest dispatching score as the target sprinkler truck, the dispatching score is used to reflect the compatibility of the sprinkler truck and the road section to be sprinkled; If not, and F=0, then calculate the total consumption score for each pair of sprinkler trucks, and determine the pair of sprinkler trucks with the smallest total consumption score as the target sprinkler trucks, each pair of sprinkler trucks consists of two sprinkler trucks, and the total consumption score is used to reflect the cost of each pair of sprinkler trucks when watering the road section to be watered.

3. The method for optimizing the watering route of a sprinkler truck according to claim 2, characterized in that: The calculating of the dispatching score of the sprinkler truck involved in the pending code value includes: Obtaining a first score according to the distance between the watering vehicle and the road section to be watered; Calculate the difference between the initial water storage amount in the pending code value and the target watering amount to obtain a second score; Obtaining a water quantity weight according to the density of the road section to be watered in the area where the road section to be watered is located; The calculation formula for calculating the scheduling score is: , where S 总 is the scheduling score, S1 is the first score, S2 is the second score, and W is the water volume weight.

4. The method for optimizing the watering route of a watering truck according to claim 3, characterized in that: The step of obtaining a first score according to the distance from the sprinkler vehicle to the road section to be sprinkled includes: a calculation formula for the first score is: , where k is the maximum value of the distance involved in the undetermined encoding value, d i is the distance from the i-th sprinkler truck to the road section to be sprinkled.

5. The method for optimizing the watering route of a watering truck according to claim 3, characterized in that: The water volume weight is obtained according to the density of the road section to be watered in the area where the road section to be watered is located, including: The calculation formula of the water volume weight is: , where m is the number of road sections to be watered whose distance is less than the distance threshold, and M is the total number of road sections to be watered.

6. The method for optimizing the watering route of a watering truck according to claim 2, characterized in that: The calculation of the total consumption score for each pair of sprinkler trucks includes: Calculate the sum of the initial water storage of the two sprinkler trucks in each pair of sprinkler trucks; Calculate the difference between the sum and the target watering amount, and use the difference as the initial score of each pair of sprinkler vehicles; Calculate the distances from the two sprinkler trucks in each pair of sprinkler trucks to the road section to be sprinkled; Add the two distances corresponding to each pair of sprinklers to get the additional score; The total consumption score is obtained by adding the initial score and the additional score.

7. The method for optimizing the watering route of a watering truck according to claim 1, characterized in that: The method further comprises: when there are multiple road sections to be watered: Retrieving the historical traffic data of each road section to be watered, wherein the historical traffic data includes vehicle flow and pedestrian flow; Determine the watering time period of each road section to be watered according to the historical traffic data; Sorting the plurality of road sections to be watered according to the order of the watering time periods to obtain a data list; According to the order of the road sections to be watered in the data list, the target watering vehicle for each road section to be watered is determined in sequence.

8. A watering route optimization system for a watering truck, characterized in that: include: A data calculation module (1) is used to calculate a target watering amount based on the point cloud data of the road section to be watered and an initial humidity index, wherein the target watering amount is the amount of water required for the road section to be watered; A data processing module (2) is used to construct a two-dimensional array according to a first identifier and a second identifier, wherein the first identifier is used to indicate an idle sprinkler truck, and the second identifier is used to indicate the road section to be sprinkled; A data determination module (3) is used to determine a target sprinkler truck according to the target watering amount and a coding value, wherein the coding value corresponds to the two-dimensional array, and the coding value includes an initial water storage capacity of the sprinkler truck and a distance from the sprinkler truck to the road section to be sprinkled, and the target sprinkler truck is a sprinkler truck that provides the target watering amount.

9. A watering route optimization device for a watering truck, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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