Method and device for planning road surface cleaning scheme of urban road

Abstract

The invention provides a road surface cleaning scheme planning method and device for urban roads, and relates to the field of environmental sanitation management. The method comprises the following steps: a target patrol vehicle acquires road surface environment information and overflow data based on road image data of each node on each road in a sub-region acquired by vehicle-mounted dust retention detection equipment; determining a target pollution category and a target pollution position of each node based on the pavement environment information and the overflow data; on the basis of the function types of the corresponding sub-regions and the target pollution types of the nodes on the roads, a road surface cleaning scheme is planned, the road surface cleaning scheme comprises planning of a cleaning route, the cleaning and maintenance route can be rapidly planned, and meanwhile the working efficiency of cleaning personnel is improved.

Description

Technical Field

[0001] This application relates to the field of environmental sanitation management. Specifically, it relates to a method and device for planning a road surface cleaning plan for urban roads. Background Art

[0002] In the current environmental sanitation industry, project companies arrange work shifts for cleaners according to specific requirements, and cleaners perform full-coverage cleaning and maintenance on the responsible areas according to the established plan. However, in actual operation, the cleanliness of the road is unknown to the cleaners performing the cleaning tasks. This means that cleaners may repeat work in areas that are actually already clean, while areas that really need to be cleaned are not dealt with in a timely manner. This situation leads to waste of resources and low efficiency, namely the so-called "area empty running" phenomenon, and the problem that areas to be cleaned cannot be responded to in a timely manner. Summary of the Invention

[0003] The purpose of the embodiments of this application is to provide a method and device for planning a road surface cleaning plan for urban roads, which are used to solve the above problems existing in the prior art, can quickly plan the cleaning and maintenance route, and improve the work efficiency of cleaners at the same time.

[0004] In a first aspect, a method for planning a road surface cleaning plan for urban roads is provided. This method can be applied to a route planning system, including a route planning platform and a regional division platform; each divided region includes multiple sub-regions, each region corresponds to a first processing component, the first processing component includes second processing components corresponding to multiple sub-regions, and multiple patrol vehicles equipped with in-vehicle dust detection devices and trash cans equipped with overflow sensors are configured for each sub-region; the method includes:

[0005] Based on the urban layout information of the current target city, the regional division platform divides the urban area of the target city to obtain the first regional information of different functional types of regions and the second regional information of each sub-region of different functional types within the corresponding region, and sends the first regional information and the second regional information to the corresponding first processing component, so that the first processing component sends the second regional information to the corresponding second processing component;

[0006] After receiving the second regional information through the second processing component corresponding to each sub-region, obtain the current vehicle information of multiple patrol vehicles, and based on the obtained current vehicle information, determine the target patrol vehicle for the corresponding second regional information;

[0007] The target patrol vehicle obtains road surface environment information and overflow data based on the road image data of each node on each road in the sub-region collected by the vehicle-mounted dust detection device; based on the road surface environment information and overflow data, determines the target pollution category and target pollution location of each node; each node is a road segment obtained by equally dividing the corresponding road.

[0008] The route planning platform plans a road surface cleaning plan based on the functional type of the corresponding sub-region and the target pollution category of each node on each road, and the road surface cleaning plan includes planning a cleaning route.

[0009] In a possible implementation, the route planning platform plans a road surface cleaning plan based on the functional type of the corresponding sub-region and the target pollution category of each node on each road, including:

[0010] For the target road to which any node belongs, the route planning platform determines the target coefficient corresponding to the target road based on the corresponding relationship between different sub-regions and different coefficients configured; and, determines the target basic value corresponding to the target pollution category based on the corresponding relationship between different pollution categories and different basic values configured; determines the detection score according to the target coefficient and the target basic value;

[0011] Based on the detection scores of each node, determines the average detection score of a preset number of consecutive nodes in the target road;

[0012] If the average detection score of a preset number of consecutive nodes reaches the first score threshold configured, determines the cleaning route according to the node set composed of the preset number of consecutive nodes and the target pollution location corresponding to each node;

[0013] If the average detection score does not reach the first score threshold configured and there is at least one node whose detection score reaches the second score threshold configured, determines this node and the target pollution location corresponding to this node as the cleaning route.

[0014] In a possible implementation, determining the detection score according to the target coefficient and the target basic value includes:

[0015] Adopts a preset score algorithm to calculate the target coefficient, the target basic value and the pollution quantity to obtain the detection score.

[0016] In a possible implementation, the preset score algorithm includes a first score algorithm and a second score algorithm;

[0017] Adopts the first score algorithm to calculate the pollutant quantity and the target basic value of pollutants of the same pollution category to obtain the pollutant score;

[0018] Using the second scoring algorithm, calculate the pollutant scores for different pollution categories to obtain the detection score.

[0019] In a possible implementation, the first scoring algorithm is:

[0020] F = (n / y) × β

[0021] Where F is the pollutant score, n is the number of pollutants, y is the target base value, and β is the coefficient. In a possible implementation, the second scoring algorithm is:

[0022] W = ∑(Fi × Ki)

[0023] Where W is the detection score, Fi is the pollutant score of the pollutants in the i-th pollution category, and Ki is the weight of the pollutants in the corresponding pollution category.

[0024] In a possible implementation, the area includes industrial areas, commercial centers, and residential areas.

[0025] In a second aspect, a device for planning a road surface cleaning plan for an urban road is provided. The device is applied to a route planning system and includes a route planning platform and a regional division platform; each divided area includes multiple sub-areas, each area corresponds to a first processing component, the first processing component includes second processing components corresponding to multiple sub-areas, and each sub-area is configured with multiple patrol vehicles equipped with in-vehicle dust detection devices and trash cans equipped with overflow sensors; the device may include:

[0026] A processing unit, configured to divide the urban area of the target city through the regional division platform based on the urban layout information of the current target city, obtain the first area information of different functional types of areas and the second area information of each sub-area of different functional types within the corresponding area, and send the first area information and the second area information to the corresponding first processing component, so that the first processing component sends the second area information to the corresponding second processing component;

[0027] A determination unit, configured to, after receiving the second area information through the second processing component corresponding to each sub-area, obtain the current vehicle information of multiple patrol vehicles, and determine the target patrol vehicle for the corresponding second area information based on the obtained current vehicle information;

[0028] And, the target patrol vehicle obtains road surface environment information and overflow data based on the road image data of each node on each road in the sub-area collected by the in-vehicle dust detection device; based on the road surface environment information and the overflow data, determine the target pollution category and the target pollution location of each node; each node is a road segment obtained by equally dividing the corresponding road.

[0029] A planning unit is used for a route planning platform to plan a road surface cleaning plan based on the functional types of corresponding sub-regions and the target pollution categories of each node on each road. The road surface cleaning plan includes a planned cleaning route.

[0030] In a third aspect, an electronic device is provided. The electronic device includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus;

[0031] The memory is used for storing a computer program;

[0032] The processor is used to implement the method steps described in any one of the first aspects when executing the program stored on the memory.

[0033] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and the computer program realizes the method steps described in any one of the first aspects when executed by a processor.

[0034] The present application provides a method for planning a road surface cleaning plan for urban roads. The method includes: a target patrol vehicle obtains road surface environment information and overflow data based on the road image data of each node on each road in the sub-region collected by an in-vehicle dust detection device; based on the road surface environment information and the overflow data, determines the target pollution category and the target pollution location of each node; based on the functional type of the corresponding sub-region and the target pollution category of each node on each road, plans a road surface cleaning plan, and the road surface cleaning plan includes a planned cleaning route. The present application evaluates the detection scores of each node in the target road from two dimensions simultaneously, can accurately determine the nodes that need to be cleaned, thereby generating a cleaning route, and further improves the work efficiency of cleaning personnel. Description of the Drawings

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can also be obtained based on these drawings without creative efforts.

[0036] Figure 1 It is a system architecture diagram of the route planning system provided by the embodiment of the present application;

[0037] Figure 2 It is a flowchart of a method for planning a road surface cleaning plan for urban roads provided by the embodiment of the present application;

[0038] Figure 3A structural schematic diagram of a road surface cleaning plan planning device for an urban road provided by an embodiment of the present application;

[0039] Figure 4 A structural schematic diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0040] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0041] In the current field of environmental sanitation management, the project company will formulate work schedules for cleaning personnel according to specific needs, and the cleaning personnel will thoroughly clean and maintain the designated areas according to these plans. However, in the actual operation process, it is difficult for the cleaning personnel to understand the actual cleaning status of the road in real time. Therefore, the following situation may occur: the cleaning personnel repeatedly operate in an area that is actually quite clean, while the places that really need to be cleaned do not receive timely attention and cleaning. This situation not only causes waste of human and time resources, but also reduces the overall work efficiency, and leads to the problem that the areas in urgent need of cleaning cannot be quickly responded to and processed. In other words, the current practice may lead to an unbalanced distribution of cleaning work, wasting resources and affecting the quality and efficiency of services.

[0042] Therefore, the present application provides a method for planning a road surface cleaning plan for an urban road, which solves the above problems existing in the prior art, can quickly plan the cleaning and maintenance route, and improve the work efficiency of the cleaning personnel at the same time.

[0043] The following describes the preferred embodiments of the present application in conjunction with the accompanying drawings of the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application. And without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0044] A method for planning a road surface cleaning plan for an urban road provided by an embodiment of the present application can be applied to Figure 1 The route planning system shown.

[0045] The route planning system includes a route planning platform and a regional division platform; each region divided by the regional division platform includes multiple sub-regions, each region corresponds to a first processing component, the first processing component includes second processing components corresponding to multiple sub-regions, and each sub-region is configured with multiple patrol vehicles equipped with on-vehicle dust detection devices and trash cans equipped with overflow sensors.

[0046] Figure 2 This is a schematic flowchart of a method for planning a road surface cleaning plan for urban roads provided by an embodiment of the present application. As Figure 2 shown, the method may include:

[0047] Step S210: Based on the urban layout information of the current target city through the regional division platform, divide the urban areas of the target city to obtain the first area information of different functional types of areas and the second area information of each sub-area of different functional types within the corresponding area, and send the first area information and the second area information to the corresponding first processing component, so that the first processing component sends the second area information to the corresponding second processing component.

[0048] Step S220: After receiving the second area information through the second processing component corresponding to each sub-area, obtain the current vehicle information of multiple patrol vehicles, and determine the target patrol vehicles for the corresponding second area information based on the obtained current vehicle information.

[0049] Step S230: The target patrol vehicle obtains road surface environment information and overflow data based on the road image data of each node on each road in the sub-area collected by the on-vehicle dust accumulation detection device; based on the road surface environment information and the overflow data, determine the target pollution category and target pollution location of each node; each node is a road section obtained by equally dividing the corresponding road.

[0050] Step S240: The route planning platform plans a road surface cleaning plan based on the functional type of the corresponding sub-area and the target pollution category of each node on each road, and the road surface cleaning plan includes planning a cleaning route.

[0051] Among them, planning the cleaning route may include: determining the target pollution category and target pollution location of each node through the road image data of multiple nodes of the target road.

[0052] Among them, each node is a road section determined by equally dividing the target road.

[0053] Specifically, the patrol vehicle equipped with the vehicle-mounted dust detection device advances at a constant speed on the target road. According to a predetermined time interval, road images of each node on the target road and detection data of the garbage material are collected. The time interval mentioned here does not refer to the specific time when the patrol vehicle equipped with the vehicle-mounted dust detection device actually arrives at each node. Instead, this time interval is set to ensure that the road image data of the designated road section can be comprehensively and systematically collected. Specifically, the most suitable data collection time interval can be determined according to the actual length or area of the target road and the time required to use the vehicle-mounted dust detection device to capture a complete road image. The purpose of doing this is to ensure detailed and uniform data coverage of the entire target road, thereby supporting more effective environmental monitoring and management.

[0054] Analyze and process the collected road images and garbage material detection data to determine the main pollution types and specific locations of pollution at each node. By combining the detection data of the garbage material with the road image data, the target pollution categories of pollution can be more accurately identified. This is because the detection data of the garbage material provides information about the physical properties of the pollutants, while the road images show the actual distribution of the pollutants on the road. The combination of the two can not only improve the accuracy of identifying pollution types but also precisely locate the location where the pollution occurs, thereby providing strong support for targeted cleaning and maintenance work. Such comprehensive analysis helps to formulate more effective environmental protection measures and management strategies.

[0055] For the target road to which any node belongs, determine the target coefficient and target base value of this node.

[0056] Specifically, for the target road to which any node belongs, based on the corresponding relationship between different regions and different coefficients configured, determine the target coefficient corresponding to the target road.

[0057] Among them, the regions can include industrial areas, commercial centers, and residential areas. It should be noted that during the process of configuring coefficients, the environmental cleanliness required for different regions needs to be considered. For example, since the residential area is a region where a large number of residents live, good environmental information is required, so the corresponding coefficient is set relatively larger. The regions can also include some key street areas, which can be the areas where schools are located or areas with complex traffic, etc.

[0058] In some embodiments, any region can also be divided into sub-regions. For example, the residential area is divided into: garbage storage area, passage area, activity area, etc.; among them, the coefficient of the garbage storage area should be less than the coefficient of the resident passage area, and the coefficients of each sub-region are configured according to the impact of the garbage on the lives of residents.

[0059] In short, based on the area where the currently detected target road is located, determine the target coefficient corresponding to the target road; the area it belongs to is determined according to the node position (latitude and longitude coordinates) of any node of the target road detected by the patrol vehicle equipped with the vehicle-mounted dust detection device.

[0060] The corresponding relationships between different areas and different coefficients are shown in Table 1:

[0061] Area Coefficient Area 1 (Factory Area) 0.8 Area 2 (Commercial Area) 0.5 Area 3 (Key Street Area) 1.2 Area 4 (Residential Area) 1 …… ……

[0062] Moreover, as shown in Table 2, based on the corresponding relationships between different pollution categories and different basic values (pollution degrees) configured, determine the target basic value corresponding to the target pollution category.

[0063]

[0064]

[0065] Among them, the pollution categories include: white garbage, daily garbage, chemical substances, and floating objects. Floating objects can be understood as dust pollutants covering the road.

[0066] In one example, the trash can can also be regarded as a pollution category. When the overflow sensor installed detects that the trash can is full, the basic value of the trash storage area is 1; when the trash can is not full, the basic value is 0. It is also possible to set the corresponding basic value according to the overflow degree of the trash can. For example, when the trash can is full, the basic value of the trash storage area is 100 points; when the remaining space of the trash can is half of the trash can, the basic value of the trash storage area is 50 points.

[0067] Determine the detection score according to the target coefficient and the target basic value, and determine the cleaning route that needs to be cleaned according to the detection score.

[0068] Specifically, determine the detection score according to the target coefficient and the target basic value; this process can specifically be: use a preset score algorithm to calculate the target coefficient, the target basic value, and the pollution quantity to obtain the detection score.

[0069] The expression of the preset score algorithm can be:

[0070] W = n × α × A

[0071] Among them, W is the detection score, n is the pollution quantity, A is the target basic value, and α is the target coefficient.

[0072] The pollution quantity can be understood as the quantity of the identified pollutants.

[0073] In some embodiments, n can also be the percentage of the pollution area in the corresponding node.

[0074] It should be noted that for the detection score of the trash can, n is the number of trash cans at the corresponding node. The detection score of the trash can can be the urgency of cleaning the trash can at the corresponding node of the target road. For example, this location is a residential area, and the detection score of the trash can reaches the first score threshold of the corresponding area, indicating that this node needs to be processed; the detection score of the trash can reaches the first score threshold of the corresponding area, indicating that this node needs to be processed immediately.

[0075] After determining the detection score, determine whether the detection score of each node exceeds the second score threshold. When it exceeds the second score threshold, the corresponding node is determined as the node to be processed.

[0076] Since in the detection process, it is easy to have detection errors, resulting in the detection score of the node exceeding the second score threshold; or there is no detection score of the corresponding node exceeding the second score threshold, but there is also a slightly higher detection score of the corresponding node. In this case, the corresponding node also needs to be cleaned; for the above situations, the present application considers whether each node needs to be cleaned from different dimensions. Dimension 1: Determine whether the detection score of each node exceeds the second score threshold. Dimension 2: Determine whether there is an average detection score of a preset number of consecutive nodes exceeding the first score threshold. Among them, the first score threshold is less than the second score threshold.

[0077] Specifically, based on the detection scores of each node, determine the average detection score of a preset number of consecutive nodes in the target road;

[0078] If among a number of consecutive nodes, their average detection score exceeds the preset first score threshold, then these consecutive nodes will be combined into a node set. Then, plan the cleaning route according to the target pollution locations corresponding to each node in this node set. In other words, once it is found that the pollution level of some consecutive nodes (the number reaches the preset standard) has reached the level that needs attention (that is, exceeds the set pollution score threshold), a dedicated cleaning path will be designed for these nodes and their specific pollution locations. The purpose of doing this is to ensure that the cleaning work can be carried out efficiently, giving priority to dealing with areas with more serious pollution, thereby effectively improving the overall environmental hygiene quality.

[0079] If the average detection score of all nodes does not reach the preset first score threshold, but the detection score of at least one node reaches a higher second score threshold, then this node and its corresponding target pollution location will be directly included in the cleaning route. This means that even if the overall pollution level is not high, as long as the pollution degree of any one node reaches the level that requires immediate treatment, this point will be regarded as a key area that needs to be cleaned, and the cleaning route will be adjusted accordingly to ensure its timely cleaning. In other words, when the pollution situation at a specific location is relatively serious, regardless of the overall average score, this node will be added as a priority cleaning object to the cleaning plan.

[0080] When the overall pollution level of a continuous area (consisting of a specific number of nodes) on the target road is low and does not reach the standard that requires immediate cleaning, and no node in this area shows signs of serious pollution, the system will prompt that this road does not need to be cleaned temporarily. This means that cleaning work will only be arranged when the pollution degree exceeds a certain standard, thus optimizing the allocation of cleaning resources.

[0081] In this method, by considering Dimension 1 and Dimension 2, the first score threshold and the second score threshold corresponding to each node are used to determine whether cleaning is required. Only when a node does not meet the preset cleaning standard in the performance of these two dimensions will it be considered that this node does not need to be cleaned. If this is the case for all inspection nodes on the target road, then the entire target road is regarded as not requiring immediate cleaning. This can ensure the efficiency of the cleaning work and the effective utilization of resources.

[0082] In some embodiments, according to the area to which the target road belongs, the corresponding relationships between different areas and different first score thresholds and different second score thresholds are configured. That is to say, the first threshold and the second threshold are different between different areas.

[0083] In another example, when the detection score of any one node is higher than the second score threshold, taking this node as the target node, determine the average detection scores of the N nodes before the target node, the N nodes after the target node, and the target node. If this average detection score reaches the preset second score threshold, then determine the cleaning route for the node set composed of the N nodes before the target node, the N nodes after the target node, and the target node, as well as the target pollution locations corresponding to each node.

[0084] In one example, the first score threshold and the second score threshold can also be the criteria for verifying the dust accumulation evaluation level. For example, there are floating objects on the target road. When the detection score of the corresponding node is less than the first score threshold, it indicates that the dust accumulation evaluation level of the corresponding node on the target road is clean; when the detection score of the corresponding node is not less than the first score threshold and less than the second score threshold, it indicates that the dust accumulation evaluation level of the corresponding node on the target road is slightly polluted; when the detection score of the corresponding node is not less than the second score threshold, it indicates that the dust accumulation evaluation level of the corresponding node on the target road is highly polluted. It can be understood that more score thresholds can also be set to further divide the dust accumulation evaluation level. After that, the urgency of cleaning can be determined according to the dust accumulation evaluation level; for example: the road cleaning levels are set from high to low according to the urgency of cleaning: level one > level two > level three.

[0085] Furthermore, in the case of limited cleaning staff, the cleaning level of the road can be determined by comprehensively evaluating the pollution intensity of different regions and their pollutants. This can help the cleaning staff quickly decide on the routes that need to be cleaned first. Specifically, according to the method of the present application, the pollution categories and different regions are first identified and divided to clarify the types of pollutants and the environments to which they belong. This approach enables the cleaning staff to understand the overall situation of the pollutants in advance, thus preparing for the cleaning work. For example, before dealing with chemical pollutants, the corresponding protective measures must be prepared first. This method not only improves work efficiency but also ensures the safety and health of the cleaning staff.

[0086] In another embodiment, the preset score algorithm can also include a first score algorithm and a second score algorithm;

[0087] Using the first score algorithm, the number of pollutants and the target base value of pollutants of the same pollution category are calculated to obtain the pollutant score;

[0088] Using the second score algorithm, the pollutant scores of different pollution categories are calculated to obtain the detection score.

[0089] Among them, the first score algorithm is:

[0090] F = (n / y) × β

[0091] Among them, F is the pollutant score, n is the number of pollutants, y is the target base value, and β is the coefficient.

[0092] For each pollutant, its score is calculated using the first score algorithm. This score reflects the degree of deviation of the actual quantity of pollutants from the base value, as well as the impact of this deviation on the environment and health.

[0093] The second score algorithm is:

[0094] W = ∑(Fi × Ki)

[0095] Where, W is the detection score, Fi is the pollutant score of the i-th type of pollution category, and Ki is the weight of the pollutant in the corresponding pollution category.

[0096] In a specific example, to evaluate the pollution situation of particulate matter (PM2.5) and sulfur dioxide (SO2) on a certain road section, the basic values are 10 μg / m 3 and 50 μg / m 3 , and the coefficients are 1.5 and 1.0 respectively. Through the monitoring equipment, we obtain the concentration of PM2.5 as 15 μg / m 3 , and the concentration of SO2 as 60 μg / m 3 .

[0097] PM2.5 score = (15 / 10) × 1.5 = 2.25

[0098] SO2 score = (60 / 50) × 1.0 = 1.2

[0099] Detection score = 2.25 × 0.6 (assuming the weight of PM2.5 is 0.6) + 1.2 × 0.4 (assuming the weight of SO2 is 0.4) = 1.83

[0100] This detection score reflects the comprehensive pollution situation of PM2.5 and SO2 on the road, and the pollution degree can be evaluated based on this score and corresponding treatment measures can be formulated.

[0101] This application provides a method for planning a road surface cleaning plan for urban roads. The method includes: the target patrol vehicle obtains road surface environment information and overflow data based on the road image data of each node on each road in the sub-region collected by the in-vehicle dust detection equipment; based on the road surface environment information and overflow data, determines the target pollution category and target pollution location of each node; based on the functional type of the corresponding sub-region and the target pollution category of each node on each road, plans a road surface cleaning plan, and the road surface cleaning plan includes planning a cleaning route. This application can accurately determine the nodes that need to be cleaned and generate a cleaning route by evaluating the detection scores of each node in the target road from two dimensions, further improving the work efficiency of the cleaning personnel.

[0102] Corresponding to the above method, an embodiment of this application also provides a device for planning a road surface cleaning plan for urban roads, as Figure 3 shown. The device includes:

[0103] A processing unit 310 is configured to divide the urban areas of a target city based on the urban layout information of the current target city through a regional division platform, obtain first regional information of regions of different functional types and second regional information of each sub-region of different functional types within the corresponding region, and send the first regional information and the second regional information to the corresponding first processing components, so that the first processing components send the second regional information to the corresponding second processing components;

[0104] A determination unit 320 is configured to, after receiving the second regional information through the second processing components corresponding to each sub-region, obtain the current vehicle information of multiple patrol vehicles, and determine the target patrol vehicles for the corresponding second regional information based on the obtained current vehicle information;

[0105] Moreover, the target patrol vehicles obtain road surface environment information and overflow data based on the road image data of each node on each road in the sub-region collected by on-vehicle dust detection devices; based on the road surface environment information and the overflow data, determine the target pollution categories and target pollution locations of each node; each node is a road segment obtained by equally dividing the corresponding road;

[0106] A planning unit 330 is configured to plan a road surface cleaning plan through a route planning platform based on the functional type of the corresponding sub-region and the target pollution categories of each node on each road, and the road surface cleaning plan includes planning a cleaning route.

[0107] The functions of each functional unit of the road surface cleaning plan planning device for urban roads provided in the above embodiments of the present application can be implemented by the above method steps. Therefore, the specific working processes and beneficial effects of each unit in the road surface cleaning plan planning device for urban roads provided in the embodiments of the present application will not be elaborated here.

[0108] The embodiments of the present application also provide an electronic device, as Figure 4 shown, including a processor 410, a communication interface 420, a memory 430, and a communication bus 440. Among them, the processor 410, the communication interface 420, and the memory 430 complete mutual communication through the communication bus 440.

[0109] The memory 430 is used to store a computer program;

[0110] The processor 410, when executing the program stored on the memory 430, implements the following steps:

[0111] The area division platform divides the urban areas of the target city based on the urban layout information of the current target city, obtains the first area information of areas of different functional types and the second area information of each sub-area of different functional types within the corresponding area, and sends the first area information and the second area information to the corresponding first processing component, so that the first processing component sends the second area information to the corresponding second processing component;

[0112] After receiving the second area information through the second processing component corresponding to each sub-area, obtain the current vehicle information of multiple patrol vehicles, and determine the target patrol vehicles for the corresponding second area information based on the obtained current vehicle information;

[0113] The target patrol vehicle obtains road surface environment information and overflow data based on the road image data of each node on each road in the sub-area collected by the on-vehicle dust accumulation detection device; based on the road surface environment information and the overflow data, determine the target pollution category and the target pollution location of each node; each node is a road section obtained by equally dividing the corresponding road;

[0114] The route planning platform plans a road surface cleaning plan based on the functional type of the corresponding sub-area and the target pollution category of each node on each road, and the road surface cleaning plan includes planning a cleaning route.

[0115] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, only a thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0116] The communication interface is used for communication between the above-mentioned electronic device and other devices.

[0117] The memory can include a Random Access Memory (RAM), and can also include a Non-Volatile Memory (NVM), such as at least one disk memory. Optionally, the memory can also be at least one storage device located far from the aforementioned processor.

[0118] The above-mentioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0119] Since the implementation manners and beneficial effects of the components of the electronic device in the above embodiments for solving problems can be realized by referring to the steps in the embodiments shown in Figure 2 Therefore, the specific working process and beneficial effects of the electronic device provided in the embodiments of the present application will not be repeated here.

[0120] In another embodiment provided by the present application, there is also provided a computer-readable storage medium storing instructions, which when running on a computer, cause the computer to execute the method for planning a road surface cleaning plan for an urban road described in any one of the above embodiments.

[0121] In another embodiment provided by the present application, there is also provided a computer program product containing instructions, which when running on a computer, cause the computer to execute the method for planning a road surface cleaning plan for an urban road described in any one of the above embodiments.

[0122] Those skilled in the art should understand that the embodiments in the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the embodiments in the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments in the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0123] In the embodiments of the present application, it is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments in the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the processes and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in one process Figure 1 or multiple processes and / or blocks Figure 1 or a device for implementing the functions specified in one block or multiple blocks.

[0124] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in one process Figure 1 or multiple processes and / or blocks Figure 1 or a device for implementing the functions specified in one block or multiple blocks.

[0125] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one process Figure 1 or multiple processes and / or blocks Figure 1 or a device for implementing the functions specified in one block or multiple blocks.

[0126] Unless otherwise defined, the technical terms or scientific terms used in the present application should have the ordinary meaning understood by those of ordinary skill in the art to which the present invention belongs. The "first", "second", and similar terms used in the present application do not indicate any order, quantity, or importance, but are only used to distinguish different components. Words such as "including" or "comprising" mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connected", "coupled", or "linked" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right", etc. are only used to represent relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0127] Although the preferred embodiments in the embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the embodiments of the present application are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0128] Obviously, those skilled in the art can make various changes and modifications to the embodiments in the embodiments of the present application without departing from the spirit and scope of the embodiments in the embodiments of the present application. Thus, if these modifications and variations of the embodiments in the embodiments of the present application fall within the scope of the embodiments of the present application and their equivalent technologies, the embodiments of the present application are also intended to include these changes and modifications.

Claims

1. A method for planning a road cleaning scheme for urban roads, characterized in that: The method is applied to a route planning system, comprising a route planning platform and an area division platform; each divided area comprises a plurality of sub-areas, each area corresponds to a first processing component, the first processing component comprises a plurality of second processing components corresponding to the sub-areas, and each sub-area is configured with a plurality of patrol vehicles equipped with vehicle-mounted dust accumulation detection equipment and a trash can equipped with an overflow sensor; the method comprises: Based on the current urban layout information of the target city, the urban area of ​​the target city is divided by the regional division platform to obtain first regional information of regions with different functional types and second regional information of sub-regions with different functional types in the corresponding regions, and the first regional information and the second regional information are sent to the corresponding first processing component, so that the first processing component sends the second regional information to the corresponding second processing component; After receiving the second area information through the second processing component corresponding to each sub-area, current vehicle information of multiple patrol vehicles is obtained, and based on the obtained current vehicle information, a target patrol vehicle corresponding to the second area information is determined; The target patrol vehicle obtains road surface environment information and overflow data based on the road image data of each node on each road in the sub-area collected by the vehicle-mounted dust detection equipment; based on the road surface environment information and overflow data, the target pollution category and target pollution location of each node are determined; each node is a road segment divided at equal distances on the corresponding road; The route planning platform plans a road cleaning plan based on the functional type of the corresponding sub-area and the target pollution category of each node on each road. The road cleaning plan includes planning a cleaning route.

2. The method according to claim 1, characterized in that The route planning platform plans a road cleaning plan based on the functional type of the corresponding sub-area and the target pollution category of each node on each road, including: For a target road belonging to any node, the route planning platform determines the target coefficient corresponding to the target road based on the correspondence between different configured sub-areas and different coefficients; and determines the target basic value corresponding to the target pollution category based on the correspondence between different configured pollution categories and different basic values; determines the detection score according to the target coefficient and the target basic value; Determining an average detection score of a preset number of consecutive nodes in the target road based on the detection score of each node; If there are a preset number of consecutive nodes whose average detection scores reach the configured first score threshold, a cleaning route is determined according to a node set composed of the preset number of consecutive nodes and a target pollution position corresponding to each node; If the average detection score does not reach the configured first score threshold, and there is at least one node whose detection score reaches the configured second score threshold, the node and the target contaminated position corresponding to the node are determined as the cleaning route.

3. The method according to claim 2, characterized in that Determining a detection score according to the target coefficient and the target basic value includes: The target coefficient, the target basic value and the amount of pollution are calculated using a preset score algorithm to obtain a detection score.

4. The method according to claim 3, characterized in that The preset score algorithm includes a first score algorithm and a second score algorithm; The first score algorithm is used to calculate the pollutant quantity and target base value of pollutants of the same pollution category to obtain the pollutant score; The second score algorithm is used to calculate the pollutant scores of different pollution categories to obtain the detection score.

5. The method according to claim 4, characterized in that The first score algorithm is: F=(n / y)×β Among them, F is the pollutant score, n is the number of pollutants, y is the target basic value, and β is the coefficient.

6. The method according to claim 4, characterized in that The second fraction algorithm is: W = ∑(Fi × Ki) Among them, W is the detection score, Fi is the pollutant score of the i-th pollution category, and i is the weight of the pollutant in the corresponding pollution category.

7. The method according to claim 5, characterized in that The area includes industrial areas, commercial centers and residential areas.

8. A road cleaning program planning device for urban roads, characterized in that: Applied to a route planning system, comprising a route planning platform and an area division platform; each divided area comprises a plurality of sub-areas, each area corresponds to a first processing component, the first processing component comprises a plurality of second processing components corresponding to the sub-areas, and each sub-area is configured with a plurality of patrol vehicles equipped with vehicle-mounted dust accumulation detection equipment and a trash can equipped with an overflow sensor; the device comprises: A processing unit, configured to divide the urban area of ​​the target city based on the current urban layout information of the target city through the area division platform, obtain first area information of areas of different functional types and second area information of sub-areas of different functional types in the corresponding areas, and send the first area information and the second area information to the corresponding first processing component, so that the first processing component sends the second area information to the corresponding second processing component; A determination unit, configured to obtain current vehicle information of a plurality of patrol vehicles after receiving the second area information through the second processing component corresponding to each sub-area, and determine a target patrol vehicle corresponding to the second area information based on the obtained current vehicle information; And, the target patrol vehicle obtains road surface environment information and overflow data based on the road image data of each node on each road in the sub-area collected by the vehicle-mounted dust detection equipment; based on the road surface environment information and overflow data, determines the target pollution category and target pollution location of each node; each node is a road segment divided equally on the corresponding road; The planning unit is used for the route planning platform to plan a road cleaning plan based on the functional type of the corresponding sub-area and the target pollution category of each node on each road, and the road cleaning plan includes planning a cleaning route.

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