Route planning method, device and equipment for garbage truck and storage medium

Abstract

The invention discloses a garbage truck route planning method and device, equipment and a storage medium. The method comprises the steps that a target garbage can meeting the recycling condition in a first time period is determined; determining a first driving route of a garbage truck starting from a garbage station, passing through the target garbage can for garbage collection and returning to the garbage station; obtaining a garbage can disturbance event occurring in the first time period; if the garbage can disturbance event meets a route invariant condition, the first driving route is sent to the garbage truck, so that the garbage truck executes the first driving route; the problem that the path planning of the garbage truck is not matched with the actual demand in the prior art is solved, the garbage recycling path of the garbage truck is rapidly formulated, and the path is dynamically adjusted, so that the formulated path planning of the garbage truck is matched with the actual demand.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a route planning method, device, equipment and storage medium for a garbage truck. Background Art

[0002] Rural residents live in relatively scattered areas, with long distances between adjacent villages, and garbage bins are scattered throughout the countryside. Given the rural environment, how to develop reasonable garbage recycling routes for garbage trucks has become an urgent problem to be solved.

[0003] In the related art, the solution based on the weight of the garbage bin actually depends on various indicators such as the garbage bin stacking rate and the community population. It is difficult for people to set reasonable and practical weights based on experience, resulting in the manual setting of garbage truck route planning not matching actual needs. In the related art, the solution based on the big data model requires the collection of a large amount of data information in the early stage, and if the data changes, it needs to collect data again. At this time, the automatically set garbage truck route planning also does not match actual needs. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment and storage medium for route planning of a garbage truck, which solves the problem that the route planning of the garbage truck provided in the related art does not match the actual demand.

[0005] To achieve the above purpose, the technical solution of this application is implemented as follows:

[0006] A route planning method for a garbage truck, comprising:

[0007] Determine the target trash bin that meets the recycling conditions within the first time period;

[0008] Determining a first driving route for the garbage truck to collect garbage through the target garbage bin according to the relevant information of the target garbage bin and the relevant information of the garbage truck;

[0009] Obtaining trash can disturbance events occurring during the first time period;

[0010] According to the conditions satisfied by the garbage bin disturbance event, a target driving route is sent to the garbage truck so that the garbage truck executes the target driving route; the target driving route includes the first driving route or a route different from the first driving route.

[0011] A route planning device for a garbage truck, the device comprising:

[0012] A first determining unit, used to determine a target trash bin that meets a recycling condition within a first time period;

[0013] A second determining unit is used to determine a first driving route for the garbage truck to pass through the target garbage bin for garbage collection based on the relevant information of the target garbage bin and the relevant information of the garbage truck;

[0014] An acquisition unit, configured to acquire a trash can disturbance event occurring during the first time period;

[0015] A sending unit is used to send a target driving route to the garbage truck according to the conditions satisfied by the garbage bin disturbance event, so that the garbage truck executes the target driving route; the target driving route includes the first driving route or a route different from the first driving route.

[0016] An electronic device, characterized in that the electronic device comprises:

[0017] A memory for storing executable instructions;

[0018] The processor is used to implement the steps in any of the above-mentioned methods for planning the route of a garbage truck when executing the executable instructions stored in the memory.

[0019] A storage medium stores computer executable instructions, wherein the computer executable instructions are configured to execute any of the above-mentioned methods for planning a route for a garbage truck.

[0020] The route planning method, device, equipment and storage medium for garbage trucks provided in the embodiments of the present application determine the target garbage bin that meets the recycling conditions within a first time period; determine the first driving route for the garbage truck to recycle garbage through the target garbage bin based on the relevant information of the target garbage bin and the relevant information of the garbage truck; obtain the garbage bin disturbance event that occurs within the first time period; send the target driving route to the garbage truck based on the conditions satisfied by the garbage bin disturbance event, so that the garbage truck executes the target driving route; the target driving route includes the first driving route or a route different from the first driving route. That is to say, in the embodiments of the present application, by determining the target garbage bin that meets the recycling conditions within the first time period and the first driving route for recycling the target garbage bin, obtain the garbage bin disturbance event that occurs within the first time period, and send the target driving route to the garbage truck based on the conditions satisfied by the garbage bin disturbance event, so that the garbage truck executes the target driving route;; solves the problem that the route planning of garbage trucks in the related art does not match the actual needs, realizes the rapid formulation of garbage recycling routes for garbage trucks, and dynamically adjusts the routes so that the formulated route planning of garbage trucks matches the actual needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A schematic flow chart of a method for route planning of a garbage truck provided by an embodiment of the present invention;

[0022] Figure 2 A schematic diagram of the distribution of trash cans with serial number marks provided by an embodiment of the present invention;

[0023] Figure 3 A schematic diagram of a garbage truck recycling route scheme provided by an embodiment of the present invention;

[0024] Figure 4 A schematic diagram of a situation in which a garbage truck changes its route at a disturbance moment provided by an embodiment of the present invention;

[0025] Figure 5 A schematic diagram of another situation where a garbage truck changes its route at a disturbance moment provided by an embodiment of the present invention;

[0026] Figure 6 A schematic diagram of a route adjustment method provided by an embodiment of the present invention;

[0027] Figure 7 A schematic diagram of another route adjustment method provided by an embodiment of the present invention;

[0028] Figure 8 A schematic diagram of another route adjustment method provided by an embodiment of the present invention;

[0029] Fig. 9 A schematic structural diagram of a route planning device for a garbage truck provided by an embodiment of the present invention;

[0030] Fig.10 A schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions of the present application are further elaborated in detail below in conjunction with the drawings and embodiments. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0032] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0033] The terms "first / second / third" involved in the present application are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first / second / third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0035] The present application is further described in detail below in conjunction with the accompanying drawings and various embodiments.

[0036] The embodiment of the present application provides a route planning method for a garbage truck, referring to Figure 1 As shown, the method comprises the following steps:

[0037] Step 101: Determine a target trash can that meets recycling conditions within a first time period.

[0038] It is understandable that the first time period can be any time period in daily life, and this application does not limit this. For example, the start time of the first time period can be set as T 始 , the end time is T 终 . The recycling conditions can be set according to actual needs, and this application does not limit this. The actual need can be the need to determine that the trash can is recycled; illustratively, the recycling condition can be that at the time of recycling, the garbage storage volume of the trash can exceeds the percentage threshold of the maximum storage volume of the trash can. The target trash can can be understood as a set of trash cans whose garbage storage volume exceeds the percentage threshold of the maximum storage volume of the trash can in the first time period.

[0039] The garbage storage capacity of the garbage bin can be collected in real time using various sensors in the Internet of Things. The sensors can be deployed according to the placement of the garbage bin in the recycling area, and the collected data can be sent to a platform that can process the data; for example: a data analysis center. At the same time, the data analysis center can also collect and record current external conditions information, including but not limited to weather conditions, date, population density, and establish a garbage storage capacity assessment model.

[0040] In the embodiment of the present application, a camera is used as an example to illustrate the three-dimensional target detection method based on depth vision, and the camera identifies the depth of the garbage pile. Figure 2 As shown in the figure, it is assumed that there is only one garbage truck dispatch center in the deployment area, represented by serial number 0. The garbage truck dispatch center is the starting and ending station of the garbage truck. The garbage bins can be numbered from 1 in order from the distance to the garbage truck dispatch center from near to far on the map. The distance d between any garbage bin numbered i and garbage bin numbered j is ij , if there is no direct route between the locations of the trash cans, then d ij Set to a very large value (N_max).

[0041] Assume that the current observation time is T, the bottom area of ​​the trash can is S, and the depth of garbage in trash can i is h i (T), then the current garbage storage capacity of garbage bin i is D i (T) is:

[0042] D i (T) = S * h i (T) (Formula 1)

[0043] Start time T 始 The garbage storage capacity D of the garbage bin i i (T 始 ), the data analysis center predicts that the trash bin will end at the current time period T 终 The amount of garbage storage D′ i (T 终 ); then the average garbage stacking rate of trash can i in the current time period and current external conditions is set to vq i :

[0044]

[0045] The maximum garbage storage capacity of the trash can is D max , for trash bin i, satisfying the recycling condition in the first time period can be understood as satisfying the following formula:

[0046] D i (T 始 )+vq i *(T 终 -T 始 )≥0.9D max (Formula 3)

[0047] Determining the target trash cans that meet the recycling conditions in the first time period can be understood as determining the set of trash cans whose predicted garbage storage volume exceeds 90% of the maximum garbage storage volume at the end time point; if the above formula is not satisfied, it means that the trash can does not need to be recycled during this time period. It should be noted that 90% of the maximum garbage storage volume is only used as an example in this application. The specific percentage threshold can be adjusted according to population density, distance from the garbage dispatch center, etc., and different benchmark conditions for judging whether to recycle garbage cans in different situations can be set to improve the utilization rate of the trash cans.

[0048] Step 102: Determine a first driving route for the garbage truck to collect garbage through the target garbage bin based on the relevant information of the target garbage bin and the relevant information of the garbage truck.

[0049] Understandably, the relevant information of the garbage truck includes the capacity information of the garbage truck; the garbage truck is a garbage transport truck, and the garbage transport truck has a maximum garbage storage capacity limit, that is, a vehicle capacity limit; and when the garbage transport truck performs the garbage collection task, it should try to ensure that the garbage storage capacity of the garbage bin does not exceed D max Therefore, the garbage collection time of the trash can has a time window requirement; the relevant information of the target trash can includes the recycling time information of the trash can; if the garbage collection time is early, the utilization efficiency of the trash can is low; if the garbage collection time is late, the garbage storage capacity of the trash can has a high probability of exceeding D max .

[0050] In an embodiment of the present application, it is assumed that a garbage truck starts from a garbage truck dispatching center, completes the collection of garbage in each garbage bin, and finally returns to the garbage truck dispatching center, and only one garbage truck can pass through a garbage bin. The first driving route can be understood as a garbage truck driving route that can meet the vehicle capacity limit and the garbage bin recycling time window requirements.

[0051] Step 103: Obtain trash can disturbance events occurring within the first time period.

[0052] It is understandable that the average garbage stacking rate of the garbage bin can be obtained according to Formula 2, and the garbage storage capacity of the garbage bin at each time can be predicted based on this. In real life, the garbage storage capacity may increase rapidly in a short period of time due to emergency dumping or other situations by the user, and needs to be quickly recycled. Taking garbage bin X as an example, one situation may be that garbage bin X is not in the first driving route, and the predicted garbage storage capacity at the end of the recycling time period is 0.5D max When the garbage truck collects garbage along the first driving route, the garbage storage capacity of garbage bin X increases sharply to 0.9D max , then it is necessary to temporarily recycle garbage bin X; another case may be that garbage bin X is in the first driving route, and the predicted garbage storage capacity when garbage is recycled according to the first driving route is 0.5D max However, during the garbage collection process of the garbage truck, the garbage storage capacity of garbage bin X suddenly increased to 0.9D at a certain moment. max If recycling is carried out along the original route, there is a high probability that the garbage in trash can X will overflow.

[0053] A trash can disturbance event can be understood as a disturbance event in which the trash storage volume of the trash can exceeds the predicted storage volume. The judgment criteria for the occurrence of disturbance can be set according to actual conditions, and this application does not limit this.

[0054] In the embodiment of the present application, for ease of understanding, at time T, the garbage storage capacity of garbage bin i is D i (T), the starting time is T 始At the start time, the amount of garbage stored in bin i is D i , then the garbage storage prediction value at the current moment is D i +vq i *(TT 始 ), the criterion for judging whether a disturbance occurs is as follows:

[0055]

[0056] The above formula represents that if the ratio of the difference between the predicted value of the garbage storage capacity of garbage bin i at the current moment and the actual garbage storage capacity of garbage bin i to the predicted garbage storage capacity is greater than 20%, it is considered that a disturbance has occurred.

[0057] Acquiring the trash can disturbance event occurring in the first time period may be understood as acquiring the disturbance event in which the ratio of the difference between the predicted trash storage amount of the trash can and the actual trash storage amount compared to the predicted trash storage amount is greater than 20% in the first time period.

[0058] Step 104: according to the conditions satisfied by the trash can disturbance event, a target driving route is sent to the garbage truck so that the garbage truck executes the target driving route; the target driving route includes the first driving route or a route different from the first driving route.

[0059] It can be understood that the conditions satisfied by the trash can disturbance event can be understood as the conditions for determining whether the route has changed after the disturbance occurs. This condition can be set according to the specific situation, and this application does not limit this. Based on the generation of disturbances, disturbances can be divided into two types. One is that the disturbed trash can does not belong to the trash can set in the original recycling task, which is disturbance one; the other is that the disturbed trash can belongs to the trash can set in the original recycling task, which is disturbance two.

[0060] In the embodiment of the present application, if the disturbance type is one, the newly added trash can enters the scope of route planning, and the original driving route of the garbage truck needs to be changed; if the disturbance type is two, taking trash can i as an example, T 扰 is the time when the disturbance occurs; T i The time when the garbage truck reaches the garbage bin numbered i in the original garbage truck dispatching plan; the following criteria can be set to determine whether to change the original driving route:

[0061] D i (T 扰 )+vq i *(T i -T 扰 )≥D max (Formula 5)

[0062] According to formula 4, the new trash can that has been disturbed can be confirmed. If the disturbance type is one, the newly added trash can enters the scope of route planning, and the original driving route of the garbage truck needs to be changed. The garbage truck executes a route different from the first driving route. If the disturbance type is two, that is, the new trash can belongs to the set of trash cans in the original recycling task, it can be determined according to formula 5 that the garbage truck recycles according to the original route. When it reaches, whether the garbage storage capacity of the new trash can exceeds the preset storage capacity, and the preset storage capacity can be D in formula 5. max If it does not exceed the limit, then when the new trash can is collected according to the original route, the trash can will not overflow, and there is no need to change the original recycling route. The garbage truck will execute the first driving route; if it exceeds the limit, then when the new trash can is collected according to the original route, the trash can will overflow, and the original recycling route needs to be changed. The garbage truck will execute a route different from the first driving route.

[0063] It can be seen from the above content that the route planning method for a garbage truck provided in the present application determines a set of garbage bins that meet the recycling conditions within a first time period and a first driving route for the recycling garbage bin set. During the recycling process of the garbage truck, a garbage bin disturbance event that meets the disturbance generation standard is obtained, and it is determined whether the disturbance event that occurs requires changing the first driving route for the original recycling task. If there is no need to change the first driving route, the first driving route is sent to the garbage truck so that the garbage truck executes the first driving route; if the first driving route needs to be changed, a route different from the first driving route is sent to the garbage truck to complete garbage recycling. This solves the problem of mismatch between route planning of garbage trucks and actual needs in related technologies, realizes the rapid formulation of garbage recycling routes for garbage trucks, and dynamically adjusts routes so that the formulated route planning of garbage trucks matches actual needs.

[0064] In some embodiments of the present application, after step 103 acquires the trash can disturbance event occurring in the first time period, the following steps are included:

[0065] It is determined whether the garbage storage capacity of the new garbage bin corresponding to the garbage bin disturbance event exceeds the preset storage capacity during recycling. If not, it is determined that the disturbance event meets the route unchanged condition.

[0066] In the embodiment of the present application, the trash can disturbance event satisfies the route invariance condition, which can be understood as the trash can that generates the disturbance belongs to the trash can set in the original recycling task, and when the garbage truck recycles the trash can according to the original plan, the storage capacity of the trash can will not exceed the D of the trash can. max .

[0067] In some embodiments of the present application, there are N garbage trucks, and step 102 determines a first driving route of the garbage truck passing through a target garbage bin for garbage collection, which can be achieved by the following steps:

[0068] Determine that N garbage trucks start from the garbage station, and each garbage truck passes through a corresponding garbage bin for garbage collection, and a second driving route is composed of N paths corresponding to the N garbage trucks; between the starting point and the end point of each of the N paths are multiple garbage bins passed by on each path;

[0069] Perform the Mth route update, select a trash can on the i-th path included in the second driving route, and randomly insert it into the j-th path to obtain the second driving route after the Mth route update; M is a positive integer greater than 1, i and j are positive integers greater than or equal to 1 and less than or equal to N;

[0070] The evaluation function is called to determine the solution corresponding to the second driving route after the Mth route update, until the solution satisfies the first stop updating condition, and the driving route corresponding to the solution satisfying the first stop updating condition is determined to be the first driving route.

[0071] It can be understood that N can be a positive integer greater than or equal to 1; the second driving route can be planned by a metaheuristic algorithm. This application takes the simulated annealing algorithm in the metaheuristic algorithm as an example, and obtains an arbitrary initial plan, i.e., the second driving route, according to the recycling time of the garbage bin and the capacity limit of the garbage truck; the evaluation function can confirm the priority of different driving routes, which can be confirmed by the evaluation values ​​corresponding to different driving routes; the first stop update condition can be a route evaluation value set according to the vehicle recycling efficiency, garbage bin utilization rate, etc. that the driving route needs to achieve.

[0072] In an embodiment of the present application, on the second driving route obtained by the simulated annealing algorithm, an insertion algorithm can be used to perform M updates of the second driving route, and a trash can is selected from the i-th path and randomly inserted into the j-th path. An evaluation value corresponding to the second driving route after M updates is obtained according to the evaluation function. When the evaluation value meets the route evaluation value, the second driving route after M updates is used as the first driving route.

[0073] In a realistic scenario, refer to Figure 3 As shown in the figure, the garbage truck dispatch center dispatches 3 garbage trucks to carry out garbage collection tasks. The routes of these three vehicles in the second driving route obtained by the simulated annealing algorithm are: 0-1-10-12-9-0, 0-3-6-2-0, 0-4-7-8-11-5-0. Randomly select garbage bin 12 and insert it between the garbage dispatch center and garbage bin i in route 2. The new route plan is 0-1-10-9-0, 0-12-2-6-3-0, 0-4-7-8-11-5-0. After multiple attempts, the highest priority driving route under the current conditions is obtained and used as the first driving route for the garbage truck.

[0074] In some embodiments of the present application, calling the evaluation function to determine the solution corresponding to the second driving route after the Mth route update includes:

[0075] Obtain the efficiency evaluation value, capacity evaluation value and time evaluation value corresponding to the second driving route after the Mth route update; wherein the efficiency evaluation value is the recycling efficiency value of dispatching N garbage trucks; the capacity evaluation value is the capacity load value of N garbage trucks exceeding the capacity threshold; and the time evaluation value is the service time cost value of the target garbage bin that does not meet the recycling time;

[0076] Based on the efficiency evaluation value, the capacity evaluation value and the time evaluation value, an evaluation function is constructed;

[0077] The constructed evaluation function is called to determine the solution corresponding to the second driving route after the Mth route update.

[0078] It can be understood that the evaluation function can include three parts. The first part is the cost evaluation value C for garbage collection efficiency. 效 ,The lower garbage collection efficiency means that more vehicles are dispatched, the vehicle use cost increases, and the scheduling resources are wasted.,The capacity threshold can be understood as the vehicle capacity limit value.,The second part is the cost evaluation value C for exceeding the vehicle garbage capacity 容 The third part is the cost evaluation value C for the garbage collection service time window that is not met 时 .

[0079] In the embodiment of the present application, if the vehicle route plan that meets the requirements is set to s, the evaluation function f(s) of plan s is:

[0080] f(s)=C 效 +C 容 +C 时 (Formula 6)

[0081] For garbage truck i, its garbage collection efficiency is η i , if the garbage storage capacity of garbage truck i when it returns to the garbage truck dispatch center is The maximum load of garbage collected by the garbage truck is Q max , then the cost evaluation value C for garbage collection efficiency is 效 It is the sum of (1-garbage collection efficiency) of all garbage trucks, that is:

[0082]

[0083] C 效 =∑ i (1-η i ) (Formula 8)

[0084] The set of garbage bins involved in the garbage collection task of the i-th garbage truck in scheme s is Si , the time point at which the garbage truck performs the garbage collection task for garbage bin j under the current plan is T j Then C 容 The sum of the part of each garbage truck that exceeds the maximum garbage load multiplied by the corresponding weight is:

[0085]

[0086] in, is the amount of garbage that exceeds the maximum load for each vehicle. The weight of this amount is determined by Determine, the function value of α changes with The value of α increases with the increase of The former is because the larger the capacity deviation, the greater the probability of garbage overflow when the garbage bin is actually reached, and the latter is because the larger the average garbage stacking rate and the larger the garbage bin that the vehicle passes by, the smaller the probability of garbage overflow when the garbage bin is actually reached under the same capacity deviation.

[0087] Each garbage bin j generates a serviceable time window [AT j ,LT j ].in:

[0088] D j (T 始 )+vq j *(AT j -T 始 )=0.7D max (Formula 10)

[0089] D j (T 始 )+vq j *(LT j -T 始 )=0.9D max (Formula 11)

[0090] The time cost evaluation value is determined by the specific recycling time of each trash bin and the serviceable time window, that is:

[0091]

[0092] in,

[0093]

[0094] In the above formula, δ1, δ2, δ3, and δ4 are weighted coefficients of the time cost evaluation value under different circumstances. If the garbage collection truck collects garbage from garbage bin j in advance relative to the service time window of garbage bin j, that is, T j <AT j When the end time is reached, the predicted garbage storage capacity of garbage bin j is less than the maximum garbage storage capacity D of the garbage bin. max , then the weight is δ1, otherwise it is δ2. Since the earlier the garbage collection time is, the more likely it is to happen, so δ2>δ1. If the garbage collection time of trash can j is delayed, it is very likely to cause the garbage to overflow. When the garbage can j performs the garbage collection task at time T j Satisfy(T j -LT j )*vq j Less than or equal to 0.1*D max When , the weight is δ3, otherwise it is δ4. Since the later the garbage collection time is, the more likely it is that the garbage will overflow, so δ4>δ3.

[0095] In the embodiment of the present application, the solution corresponding to the second driving route after the Mth route update can be obtained according to Formula 6 to determine the route priority of the second driving route after the Mth update.

[0096] In some embodiments of the present application, obtaining the efficiency evaluation value, capacity evaluation value, and time evaluation value corresponding to the second driving route after the Mth route update includes:

[0097] Obtaining a first storage capacity of each trash can in the target trash cans and a second storage capacity of each trash can in the target trash cans corresponding to different times; the first storage capacity is a maximum trash storage capacity of each trash can in the target trash cans;

[0098] Obtain the third storage capacity of each of the N garbage trucks and the fourth storage capacity of each of the N garbage trucks when it returns to the garbage station; the third storage capacity is the maximum garbage storage capacity of each of the N garbage trucks;

[0099] calculating an efficiency evaluation value based on the fourth storage amount and the third storage amount;

[0100] calculating a capacity evaluation value based on the second storage amount and the third storage amount;

[0101] The time evaluation value is calculated based on the first storage amount and the second storage amount.

[0102] It can be understood that, taking trash can i as an example, the observation time is T, and the first storage volume is D max , the second storage capacity is Di (T), the third storage capacity is Q max , the fourth storage capacity is

[0103] In the embodiment of the present application, the efficiency evaluation value can be obtained by using formula 8: max and Calculated; the capacity evaluation value can be obtained by D according to formula 9 i (T) and Q max The time evaluation value can be calculated by D according to formula 12 max and D i (T) is calculated.

[0104] In some embodiments of the present application, after step 103 acquires the trash can disturbance event occurring in the first time period, the method further includes:

[0105] If the garbage storage capacity of the new garbage bin during recycling exceeds the preset storage capacity, it is determined that the disturbance event meets the route change condition;

[0106] Determine whether the garbage truck in the first driving route can be used to complete the garbage collection task, and if not, send a new garbage truck to collect the garbage;

[0107] If so, according to the conditions satisfied by the trash can disturbance event, sending the target driving route to the garbage truck includes: adjusting the first driving route to obtain a third driving route, and sending the third driving route to the garbage truck so that the garbage truck executes the third driving route.

[0108] It can be understood that the garbage capacity of the garbage truck can be used to determine whether the garbage storage capacity of any garbage truck that is performing recycling tasks exceeds the capacity of the garbage truck when it passes through a new garbage bin for recycling. If so, a new garbage truck needs to be dispatched.

[0109] If it does not exceed the limit, you can use the garbage truck that is performing the recycling task for rescue. There are two situations where the garbage truck that is performing the garbage recycling task is located; the first situation, refer to Figure 4 As shown, when a disturbance occurs, p k represents the specific location of the garbage truck k that was in motion at the time of the disturbance. The dotted line is the original route. k →g→j is the new route after the disturbance occurs; in the second case, refer to Figure 5 As shown, It means that the garbage truck k has just completed the garbage collection task of the garbage bin object i at the time of disturbance. The dotted line is the original route. represents the new route after the disturbance. In both cases, the travel distance of the new route has changed.

[0110] For ease of understanding, the parameters when the disturbance occurs are listed as follows:

[0111] N: The number of garbage bins that have not yet been recycled when the disturbance occurs, and their numbering set is {1, 2, 3, ... N}.

[0112] v: average speed of garbage trucks.

[0113] Q k : The garbage capacity that can be loaded by garbage truck k at the time of disturbance.

[0114] D′ j (T j ) is the estimated garbage storage capacity of the garbage bin j that was not served in the original solution at the time when the disturbance occurred.

[0115] D′ j (T′ j ): The estimated garbage storage capacity of the unserved garbage bin j in the new solution at the time when the disturbance occurs.

[0116] L: The number of garbage bins that are performing garbage collection tasks at the time the disturbance occurs, the numbered set is {1, 2, 3, …L}.

[0117] K: The number of garbage trucks remaining in the garbage truck dispatch center at the time the disturbance occurs, and the number set is {L+1, L+2,…L+K}.

[0118]

[0119] When a new garbage truck needs to be dispatched for rescue, the first part of Formula 14 represents the evaluation value of the dispatch cost of a new garbage collection truck dispatched from the dispatch center, the second part represents the evaluation value of the driving distance cost increased by the new driving route strategy, and the third part represents the time cost evaluation value of violating the service time window of the garbage bin. The constraints of the above parameters are as follows:

[0120]

[0121]

[0122] Formula 15 and Formula 16 indicate that the total distance traveled by the vehicle needs to be less than the maximum drivable distance of the vehicle.

[0123]

[0124]

[0125] Formula 17 and Formula 18 indicate that the new route satisfies the requirement that only one garbage truck passes by a garbage bin and is responsible for garbage collection.

[0126]

[0127]

[0128] Formula 19 and Formula 20 indicate that for vehicles on mission and newly dispatched vehicles, the garbage carrying capacity of each garbage truck must not exceed the maximum carrying capacity of the vehicle.

[0129]

[0130] Formula 21 indicates that when garbage truck k collects garbage from garbage bin i to j to h, after completing the garbage collection of garbage bin j, the garbage carrying capacity on the way to garbage bin h is equal to the garbage carrying capacity of garbage truck k from garbage bin i to garbage bin j minus the garbage storage capacity of garbage bin j.

[0131]

[0132] Formula 22 indicates that when there is a route from garbage bin i to j, the garbage carrying capacity of the garbage truck when traveling along the route needs to be less than the maximum load capacity of the garbage truck.

[0133]

[0134] Formula 23 indicates that the number of new garbage trucks dispatched from the dispatch center should be less than the total number of vehicles currently remaining in the vehicle dispatch center.

[0135]

[0136] Formula 24 represents the garbage collection time limit constraint, and the service time point must be earlier than the end time of the current time period.

[0137]

[0138] Formula 25 represents the time constraint for the garbage truck to arrive at garbage bin j, that is, in the new garbage truck scheduling plan, the time when the garbage truck arrives at garbage bin j for service is equal to the time when it arrives at garbage bin i plus the time it travels on the road.

[0139]

[0140] Formula 26 represents the time cost evaluation value of violating the time window, wherein δ1, δ2, δ3, and δ4 are weighted coefficients of the time cost evaluation value under different circumstances, which are the same as the values ​​in Formula 13.

[0141]

[0142] Formula 27 represents the value constraints of the path parameters.

[0143] In the embodiment of the present application, after determining that the route needs to be changed, it is determined whether the garbage truck in the mission can be used to recycle the disturbed garbage truck, which can effectively reduce the cost of the garbage truck. When it is confirmed that the garbage truck in the mission can be used for recycling, the first driving route is quickly adjusted to improve the utilization rate of the garbage truck and reduce the probability of the garbage bin overflowing.

[0144] In some embodiments of the present application, adjusting the first driving route to obtain the third driving route includes:

[0145] Perform K route updates on the first driving route to obtain an updated first driving route;

[0146] A solution corresponding to the updated first driving route is determined until the solution satisfies a second stop updating condition, and the driving route corresponding to the solution satisfying the second stop updating condition is determined to be the third driving route.

[0147] It is understandable that the first driving route can be updated by using a taboo search algorithm to obtain a domain candidate solution. The second stop update condition can be set according to the contempt rule of the taboo search algorithm, and the present application does not limit this. Exemplarily, the length of the taboo table in the taboo search algorithm can be set to determine the second stop update condition.

[0148] In the embodiment of the present application, if disturbance 2 occurs, there are three ways to generate domain candidate solutions: (1) insertion between different routes; (2) exchange within the same route; (3) exchange between routes.

[0149] refer to Figure 3 As shown in the figure, the garbage truck dispatch center dispatches 3 garbage trucks to carry out garbage collection tasks. The routes of these three trucks are: 0-1-10-12-9-0, 0-4-7-8-11-5-0, and 0-3-6-2-0. If garbage bin No. 12 is disturbed and garbage truck No. 2 is collecting garbage in garbage bin No. 4, the domain candidate solutions are generated in the following ways:

[0150] (1) Insertion between different routes, reference Figure 6 As shown, the disturbing trash can is placed in other routes, and the disturbing trash can is set as the next service trash can of the route garbage truck. At this time, a domain candidate solution that meets the requirements is 0-1-10-9-0, 0-4-12-7-8-11-5-0, and 0-3-6-2-0.

[0151] (2) Exchange within the same route, refer to Figure 7 As shown, the order of trash can services within the same route is exchanged. At this time, a candidate solution that meets the requirements is: 0-1-12-10-9-0, 0-4-7-8-11-5-0, 0-3-6-2-0.

[0152] (3) Exchange within the same route, refer to Figure 8 As shown, the order of trash can services within the same route is exchanged. At this time, a candidate solution that meets the requirements is: 0-1-12-10-9-0, 0-4-7-8-11-5-0, 0-3-6-2-0.

[0153] If perturbation 1 occurs, the new trash can of the perturbation is inserted into the reasonable path, and then the domain candidate solution search is adopted. For example, if the original route planning of the three vehicles in the original plan is: 0-1-10-9-0, 0-4-7-8-11-5-0, 0-3-6-2-0. If it is inserted into the path of 10-9, the new routes generated are 0-1-10-12-9-0, 0-4-7-8-11-5-0, 0-3-6-2-0. At this time, the solution can use the same domain candidate solution generation method as perturbation 2.

[0154] After generating the domain candidate solution, it can be determined whether the solution triggers the contempt criterion. If not, the best non-taboo candidate solution is used as the current solution and the taboo table is updated; if so, the taboo table and the optimal solution are updated, and the cycle is repeated until the termination condition is met.

[0155] Based on the same inventive concept as above, Fig. 9 A schematic diagram of the structure of a route planning device for a garbage truck provided in an embodiment of the present invention, the route planning device 900 includes:

[0156] A first determining unit, used to determine a target trash bin that meets a recycling condition within a first time period;

[0157] A second determining unit is used to determine a first driving route for the garbage truck to pass through the target garbage bin for garbage collection based on the relevant information of the target garbage bin and the relevant information of the garbage truck;

[0158] An acquisition unit, used for acquiring a trash can disturbance event occurring within a first time period;

[0159] A sending unit is used to send a target driving route to the garbage truck according to the conditions satisfied by the garbage bin disturbance event, so that the garbage truck executes the target driving route; the target driving route includes the first driving route or a route different from the first driving route.

[0160] In some embodiments of the present application, the second determination unit is further used to determine whether the garbage storage capacity of the new garbage bin corresponding to the garbage bin disturbance event exceeds the preset storage capacity during recycling. If not, it is determined that the disturbance event meets the route unchanged condition.

[0161] In some embodiments of the present application, there are N garbage trucks; the second determination unit is further used to determine that N garbage trucks start from a garbage station, and each garbage truck passes through a corresponding garbage bin for garbage collection, and a second driving route is composed of N paths corresponding to the N garbage trucks; between the starting point and the end point of each of the N paths are multiple garbage bins passed by on each path; the Mth route update is performed, and a garbage bin is selected on the i-th path included in the second driving route, and randomly inserted into the j-th path to obtain the second driving route after the Mth route update; M is a positive integer greater than 1, and i and j are positive integers greater than or equal to 1 and less than or equal to N; the evaluation function is called to determine the solution corresponding to the second driving route after the Mth route update, until the solution satisfies the first stop update condition, and the driving route corresponding to the solution that satisfies the first stop update condition is determined to be the first driving route.

[0162] In some embodiments of the present application, the second determination unit is also used to obtain the efficiency evaluation value, capacity evaluation value and time evaluation value corresponding to the second driving route after the Mth route update; wherein the efficiency evaluation value is the recycling efficiency value of scheduling N garbage trucks; the capacity evaluation value is the capacity load value of N garbage trucks exceeding the capacity threshold; the time evaluation value is the service time cost value of the target garbage bin that does not meet the recycling time; based on the efficiency evaluation value, the capacity evaluation value and the time evaluation value, an evaluation function is constructed; and the constructed evaluation function is called to determine the solution corresponding to the second driving route after the Mth route update.

[0163] In some embodiments of the present application, the second determination unit is also used to obtain the first storage capacity of each garbage bin in the target garbage bin and the second storage capacity of each garbage bin in the target garbage bin at different times; the first storage capacity is the maximum garbage storage capacity of each garbage bin in the target garbage bin; obtain the third storage capacity of each garbage truck in N garbage trucks and the fourth storage capacity of each garbage truck in N garbage trucks when they return to the garbage station; the third storage capacity is the maximum garbage storage capacity of each garbage truck in N garbage trucks; calculate the efficiency evaluation value based on the fourth storage capacity and the third storage capacity; calculate the capacity evaluation value based on the second storage capacity and the third storage capacity; calculate the time evaluation value based on the first storage capacity and the second storage capacity.

[0164] In some embodiments of the present application, the second determination unit is also used to determine that the disturbance event meets the route change condition if the garbage storage capacity of the new garbage bin during recycling exceeds the preset storage capacity; determine whether the garbage recycling task can be completed by the garbage truck in the first driving route, and if not, send a new garbage truck to carry out garbage recycling; if so, adjust the first driving route to obtain a third driving route, and send the third driving route to the garbage truck so that the garbage truck executes the third driving route.

[0165] In some embodiments of the present application, the second determination unit is further used to perform K route updates on the first driving route to obtain an updated first driving route; determine a solution corresponding to the updated first driving route until the solution satisfies a second stop update condition, and determine that the driving route corresponding to the solution that satisfies the second stop update condition is the third driving route.

[0166] Based on the foregoing embodiments, an embodiment of the present application provides an electronic device, Fig.10 1 is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. The electronic device 1000 includes: at least one processor 1001, a memory 1002, and optionally, the electronic device 1000 may further include at least one communication interface 1003. The various components in the electronic device 1000 are coupled together via a bus system 1004. It can be understood that the bus system 1004 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 1004 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Fig.10 Various buses are labeled as bus system 1004 .

[0167] It can be understood that the memory 1002 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Sync Link Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 1002 described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memories.

[0168] The memory 1002 in the embodiment of the present invention is used to store various types of data to support the operation of the electronic device 1000. Examples of such data include: any computer program for operating on the electronic device 1000. The program for implementing the method of the embodiment of the present invention may be included in the memory 1002.

[0169] The method disclosed in the above embodiment of the present invention can be applied to the processor 1001, or implemented by the processor 1001. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0170] In an exemplary embodiment, the electronic device 1000 can be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), field programmable gate array (FPGA), general processor, controller, microcontroller (MCU), microprocessor, or other electronic components to execute the above method.

[0171] Based on the above embodiments, the embodiments of the present application provide a storage medium, wherein the storage medium stores computer executable instructions, and the computer executable instructions are configured to execute Figure 1 The corresponding embodiment provides a route planning method for a garbage truck.

[0172] It should be noted that the above-mentioned computer storage medium can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory (Flash Memory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM) and other memories; it can also be various electronic devices including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0173] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0174] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0175] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0176] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0177] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0178] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0179] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A route planning method for a garbage truck, characterized in that: The method comprises: Determine the target trash bin that meets the recycling conditions within the first time period; Determining a first driving route for the garbage truck to collect garbage through the target garbage bin according to the relevant information of the target garbage bin and the relevant information of the garbage truck; Obtaining trash can disturbance events occurring during the first time period; According to the conditions satisfied by the garbage bin disturbance event, a target driving route is sent to the garbage truck so that the garbage truck executes the target driving route; the target driving route includes the first driving route or a route different from the first driving route.

2. The method according to claim 1, characterized in that After obtaining the trash can disturbance event occurring in the first time period, the method includes: It is determined whether the garbage storage capacity of the new garbage bin corresponding to the garbage bin disturbance event exceeds the preset storage capacity during recycling. If not, it is determined that the disturbance event satisfies the route unchanged condition.

3. The method according to claim 1, characterized in that There are N garbage trucks; determining a first driving route for the garbage truck to pass through the target garbage bin for garbage collection includes: Determine that N garbage trucks start from the garbage station, each garbage truck passes through a corresponding garbage bin for garbage collection, and the N paths corresponding to the N garbage trucks form a second driving route; between the starting point and the end point of each of the N paths are multiple garbage bins passed by on each path; Performing the Mth route update, selecting a trash can on the i-th path included in the second driving route, and randomly inserting it into the j-th path, to obtain the second driving route after the Mth route update; M is a positive integer greater than 1, and i and j are positive integers greater than or equal to 1 and less than or equal to N; An evaluation function is called to determine a solution corresponding to the second driving route after the M-th route update, until the solution satisfies a first stop updating condition, and the driving route corresponding to the solution that satisfies the first stop updating condition is determined to be the first driving route.

4. The method according to claim 3, characterized in that The calling of the evaluation function to determine a solution corresponding to the second driving route after the M-th route update includes: Obtaining the efficiency evaluation value, capacity evaluation value and time evaluation value corresponding to the second driving route after the M-th route update; wherein the efficiency evaluation value is the recycling efficiency value of scheduling the N garbage trucks; the capacity evaluation value is the capacity load value of the N garbage trucks exceeding the capacity threshold; and the time evaluation value is the service time cost value of the target garbage bin that does not meet the recycling time; constructing the evaluation function based on the efficiency evaluation value, the capacity evaluation value and the time evaluation value; The constructed evaluation function is called to determine a solution corresponding to the second driving route after the M-th route update.

5. The method according to claim 4, characterized in that The obtaining of the efficiency evaluation value, the capacity evaluation value, and the time evaluation value corresponding to the second driving route after the M-th route update includes: Obtaining a first storage capacity of each trash can in the target trash cans and a second storage capacity of each trash can in the target trash cans corresponding to different times; the first storage capacity is a maximum trash storage capacity of each trash can in the target trash cans; Obtaining a third storage capacity of each of the N garbage trucks and a fourth storage capacity of each of the N garbage trucks when it returns to the garbage station; the third storage capacity is the maximum garbage storage capacity of each of the N garbage trucks; calculating the efficiency evaluation value based on the fourth storage amount and the third storage amount; calculating the capacity evaluation value based on the second storage amount and the third storage amount; The time evaluation value is calculated based on the first storage amount and the second storage amount.

6. The method according to claim 2, characterized in that After obtaining the trash can disturbance event occurring in the first time period, the method further includes: If the garbage storage capacity of the new garbage bin during recycling exceeds the preset storage capacity, determining that the disturbance event meets the route change condition; Determine whether the garbage truck in the first driving route can be used to complete the garbage collection task, and if not, send a new garbage truck to collect the garbage; If so, sending the target driving route to the garbage truck based on the conditions satisfied by the garbage bin disturbance event includes: adjusting the first driving route to obtain a third driving route, and sending the third driving route to the garbage truck so that the garbage truck executes the third driving route.

7. The method according to claim 6, characterized in that The adjusting the first driving route to obtain a third driving route includes: Performing K route updates on the first driving route to obtain an updated first driving route; A solution corresponding to the updated first driving route is determined until the solution satisfies a second stop updating condition, and the driving route corresponding to the solution satisfying the second stop updating condition is determined to be the third driving route.

8. A route planning device for a garbage truck, characterized in that: The device comprises: A first determining unit, used to determine a target trash bin that meets a recycling condition within a first time period; A second determining unit is used to determine a first driving route for the garbage truck to pass through the target garbage bin for garbage collection based on the relevant information of the target garbage bin and the relevant information of the garbage truck; An acquisition unit, configured to acquire a trash can disturbance event occurring during the first time period; A sending unit is used to send a target driving route to the garbage truck according to the conditions satisfied by the garbage bin disturbance event, so that the garbage truck executes the target driving route; the target driving route includes the first driving route or a route different from the first driving route.

9. An electronic device, characterized in that: The electronic device comprises: A memory for storing executable instructions; The processor is used to implement the steps of the route planning method for a garbage truck according to any one of claims 1 to 7 when executing the executable instructions stored in the memory.

10. A storage medium storing computer executable instructions, wherein the computer executable instructions are configured to execute the route planning method for a garbage truck provided in any one of claims 1 to 7.

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