A garbage truck operation method and system based on route optimization

Abstract

The present invention relates to a garbage truck operation method and system based on route optimization. The garbage truck operation method based on route optimization includes obtaining abnormal garbage events, the information of which indicates the target location and the amount of garbage to be processed that require temporary dispatch of garbage trucks; determining a first area where the target location is located; determining a plurality of second areas around the first area according to the abnormal garbage events and the working conditions of the garbage trucks responsible for the first area; determining the first area and each second area as areas to be planned, recalculating the working routes of each garbage truck responsible for the area to be planned in the area to be planned based on a predetermined route planning algorithm; and notifying each garbage truck corresponding to the area to be planned of the newly planned working routes. It is possible to avoid global path planning for garbage trucks in all areas, avoid frequent changes in operation plans, thereby reducing the impact on the work of garbage truck drivers and reducing the increase in potential risks.

Description

Technical Field

[0001] The present invention relates to the field of garbage truck operation, and in particular to a garbage truck operation method and system based on route optimization. Background Art

[0002] The cost of fully real-time dynamic route planning is high and the benefits are small. Fixed routes are more efficient and basically meet the daily garbage disposal needs. Therefore, the operating routes of urban garbage trucks are usually calculated by path optimization algorithms and fixed within a certain period of time. In daily operations, when abnormal situations that require temporary handling occur, it is often necessary to make dynamic adjustments to the operating routes of garbage trucks in real time. However, abnormal situations may cause a large number of garbage truck routes to be replanned. Frequent and large-scale adjustments to the operating routes of garbage trucks may cause potential risks in the work. Summary of the invention

[0003] The purpose of this application is to propose a garbage truck operation method and system based on route optimization to solve the problem of potential risks in the work caused by frequent and large-scale adjustments to the operation routes of garbage trucks when abnormal situations that require temporary processing occur.

[0004] The garbage truck operation method based on route optimization of the present application includes:

[0005] Acquire an abnormal garbage event, wherein information of the abnormal garbage event indicates a target location where a garbage truck needs to be temporarily dispatched and an amount of garbage to be processed;

[0006] Determine a first area where the target location is located;

[0007] Determine a plurality of second areas around the first area according to the abnormal garbage event and the working conditions of the garbage trucks responsible for the first area;

[0008] The first area and each of the second areas are determined as areas to be planned, and the working routes of each garbage truck responsible for the areas to be planned in the areas to be planned are recalculated based on a predetermined route planning algorithm;

[0009] The newly planned work route is notified to each garbage truck corresponding to the area to be planned.

[0010] Furthermore, the determining of a plurality of second areas around the first area according to the abnormal garbage event and the working conditions of the garbage trucks responsible for the first area includes:

[0011] Obtaining a regional correlation coefficient between the first region and the second region;

[0012] Determining a workload impact coefficient of the abnormal garbage event according to the amount of garbage to be processed and the remaining processing capacity of the garbage truck responsible for the first area;

[0013] Determine the comprehensive impact coefficient;

[0014] A second area is determined according to the comprehensive influence coefficient.

[0015] Furthermore, the regional correlation coefficient is calculated by the following formula:

[0016] C ij =α d ·W d +α r ·W r +α h ·W h ;

[0017] Among them C ij represents the regional correlation coefficient between the first region and the second region; W d is the distance weight between the first area and the second area, and its value is negatively correlated with the distance; W r is the path connection weight between the first area and the second area, and its value reflects the path connection status between the first area and the second area. The more and smoother the paths between the first area and the second area, the larger the value; W h is the historical collaborative work weight, and its value reflects the historical collaborative work situation of the garbage trucks between the first area and the second area. The higher the historical collaborative work frequency, the larger the value; α d , α r and α h They are respectively the proportional coefficients of the distance weight, the path connection weight and the historical collaborative work weight.

[0018] Furthermore, the workload impact coefficient is calculated by the following formula:

[0019] L i =G i / M i ;

[0020] Where L i represents the workload impact coefficient of the first area; Gi is the amount of garbage to be processed in the abnormal garbage event in the first area; M i The remaining processing capacity of the garbage trucks responsible for the first area.

[0021] Further, determining the comprehensive influence coefficient includes:

[0022] Calculating the sum of the regional correlation coefficient and the workload influence coefficient as the comprehensive influence coefficient;

[0023] Determining the second area according to the comprehensive influence coefficient includes:

[0024] An area around the first area where the comprehensive influence coefficient is higher than a set threshold is determined as a second area.

[0025] Furthermore, the information of the abnormal junk event also indicates: factors causing the abnormal junk event;

[0026] Before determining the comprehensive influence coefficient according to the regional correlation coefficient and the workload influence coefficient, the method further includes:

[0027] According to the formation factors of the abnormal junk events, influence coefficients of the formation factors of the abnormal junk events are determined.

[0028] Further, determining the comprehensive influence coefficient includes:

[0029] Calculating the sum of the regional correlation coefficient, the workload influence coefficient and the formation factor influence coefficient as the comprehensive influence coefficient;

[0030] Determining the second area according to the comprehensive influence coefficient includes:

[0031] An area around the first area where the comprehensive influence coefficient is higher than a set threshold is determined as a second area.

[0032] Furthermore, the formation factors of the abnormal garbage event include at least one of the following: unexpected crowd gathering, temporary construction, weather disaster impact, and ordinary garbage gathering.

[0033] Further, after determining the first area and each of the second areas as areas to be planned, the method further includes:

[0034] Determining whether the processing capacity of all garbage trucks in the first area and the second area meets the needs of the abnormal garbage event;

[0035] If not, additional garbage trucks are dispatched during the recalculation of the work route to meet the needs of the abnormal garbage event.

[0036] On the other hand, the present application also provides a garbage truck operation system based on route optimization, comprising:

[0037] An event acquisition module, used to acquire abnormal garbage events, wherein information of the abnormal garbage events indicates a target location where a garbage truck needs to be temporarily dispatched and the amount of garbage to be processed;

[0038] An area demarcation module is used to determine a first area where the target location is located, and determine a plurality of second areas around the first area according to the abnormal garbage event and the working conditions of the garbage trucks responsible for the first area;

[0039] A path planning module, used for determining the first area and each of the second areas as areas to be planned, and recalculating the working routes of each garbage truck responsible for the area to be planned within the area to be planned based on a predetermined route planning algorithm;

[0040] The notification push module is used to notify each garbage truck corresponding to the area to be planned of the newly planned work route.

[0041] The garbage truck operation method based on route optimization provided by the present application determines the first area where the target location where the garbage truck needs to be temporarily dispatched is located by obtaining abnormal garbage events, and determines several second areas around the first area according to the abnormal garbage events and the working conditions of the garbage trucks responsible for the first area, and can determine the first area and each second area as the area to be planned, and recalculate the working routes of each garbage truck responsible for the area to be planned in the area to be planned based on a predetermined route planning algorithm, and notify each garbage truck corresponding to the area to be planned of the newly planned working route. When an abnormal situation that needs to be temporarily handled occurs, a smaller area to be planned is divided according to the actual situation, and the working route is replanned based on the area to be planned. It avoids global path planning for garbage trucks in all areas, thereby minimizing the number of garbage trucks that may adjust the operating routes due to abnormal garbage events, avoiding frequent changes in operating plans, thereby reducing the impact on the work of garbage truck drivers, and reducing the increase in potential risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A basic flow chart of the garbage truck operation method based on route optimization of this embodiment;

[0043] Figure 2 This is a schematic block diagram of a garbage truck operation system based on route optimization of this embodiment. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] Embodiment 1:

[0047] This embodiment provides a garbage truck operation method based on route optimization. Figure 1 , the method comprises the following steps:

[0048] S101, obtaining an abnormal garbage event, where the information of the abnormal garbage event indicates a target location where a garbage truck needs to be temporarily dispatched and the amount of garbage to be processed;

[0049] Generally speaking, since garbage generation has certain regularity, the amount of garbage in most areas is relatively stable over a certain period of time. Therefore, although fully real-time global route planning can dynamically plan the optimal path, it is costly and the benefits it brings are not significant.

[0050] During the operation of the garbage trucks in this embodiment, each garbage truck will perform fixed work according to the partition under normal operation. The division of the area is based on the amount of garbage in the city, road conditions and other factors, and is a pre-formed partitioning scheme based on the set path planning algorithm. Each area can be configured with one or more fixed paths to cover the garbage collection points therein. In practical applications, periodic evaluations and continuous optimization of the routes can be performed to ensure that efficiency is improved while meeting daily needs.

[0051] Abnormal garbage events refer to situations where garbage cannot be effectively and timely handled under the daily route planning. For example, during the current working hours, a large amount of garbage suddenly appears in a location that does not need to be cleared, causing the garbage bin to be full in advance; or for example, the amount of garbage in a certain area increases, causing the garbage truck originally configured for that area to be unable to complete the processing within the scheduled working times.

[0052] In actual applications, the method of obtaining abnormal garbage events may include but is not limited to at least one of the following: obtaining abnormal garbage events reported by sanitation workers, obtaining abnormal garbage events reported by other garbage trucks, obtaining abnormal garbage events reported by full smart garbage bins, and obtaining abnormal garbage events reported by real-time monitoring systems.

[0053] The amount of garbage to be processed in an abnormal garbage event reflects the amount of garbage that needs to be removed. For example, when a large amount of garbage suddenly appears in a location that does not need to be removed, causing the garbage bin to be full in advance, the amount of garbage to be processed is the amount of garbage in the garbage bin. Or, for example, when the amount of garbage in a certain area increases, causing the garbage truck originally configured for the area to be unable to complete the processing within the scheduled number of working times, the amount of garbage to be processed can be the amount of garbage that the garbage truck cannot complete the processing.

[0054] S102, determining a first area where the target location is located;

[0055] S103, determining a plurality of second areas around the first area according to the abnormal garbage event and the working conditions of the garbage trucks in charge of the first area;

[0056] The number of second areas can be determined according to actual conditions. If the impact of abnormal garbage events is greater, the number of second areas is usually greater. Otherwise, fewer second areas can be determined as much as possible to reduce the scope involved in route replanning.

[0057] S104, determining the first area and each second area as the areas to be planned, and recalculating the working routes of each garbage truck responsible for the areas to be planned in the areas to be planned based on a predetermined route planning algorithm;

[0058] In this embodiment, the work route is recalculated only within the area to be planned formed by the first area and the second area, so that the temporary adjustment of the work route can be limited to a relatively small range, thereby avoiding the need for a large number of garbage truck drivers to change their daily work routes, thereby reducing the risk of errors during work.

[0059] S105, notifying each garbage truck corresponding to the area to be planned of the newly planned work route;

[0060] The notification can be sent to the driver of the garbage truck or the corresponding terminal of the garbage truck, and displayed on the relevant path navigation software so that the driver can drive according to the newly planned work route.

[0061] Specifically, the second area is determined according to the impact of the abnormal junk event. Generally speaking, the greater the impact of the abnormal junk event, the more second areas are determined, and route planning in a larger range is achieved to improve work efficiency. The smaller the impact of the abnormal junk event, the fewer second areas can be used, reducing the scheduling scope.

[0062] According to the abnormal garbage incident and the working conditions of the garbage trucks in charge of the first area, several second areas around the first area are determined, including:

[0063] S201, obtaining a region correlation coefficient between a first region and a region to be confirmed;

[0064] The regional correlation coefficient reflects the correlation between two regions. The higher the value, the higher the correlation. Regions with a high correlation are more suitable for collaborative work. Exemplarily, the regional correlation coefficient can be determined based on the distance between the first region and the region to be confirmed, the road conditions, and the historical working conditions of the garbage trucks between the two regions.

[0065] In some embodiments, the regional correlation coefficient is calculated by the following formula:

[0066] C ij =α d ·W d +α r ·W r +α h ·W h ;

[0067] Among them C ij W represents the regional correlation coefficient between the first region and the region to be confirmed. d is the distance weight between the first area and the area to be confirmed, and its value is negatively correlated with the distance. r is the path connection weight between the first area and the area to be confirmed, and its value reflects the path connection between the first area and the area to be confirmed. The more paths there are between the first area and the area to be confirmed, and the smoother the paths are, the larger the value is. h is the historical collaborative work weight, and its value reflects the historical collaborative work of garbage trucks between the first area and the area to be confirmed. The higher the historical collaborative work frequency, the larger the value. d , α r and α h are the proportional coefficients of distance weight, path connection weight and historical collaborative work weight respectively. d , α r and α hThe sum can be 1. In actual work, the above weights can be pre-calculated in a GIS (Geographic Information System or Geo-Information system, Geographic Information System) system, that is, the relevant weights between the planned areas can be calculated and stored in advance.

[0068] S202, determining the workload impact coefficient of the abnormal garbage event according to the amount of garbage to be processed and the remaining processing capacity of the garbage truck responsible for the first area;

[0069] The workload impact coefficient is calculated using the following formula:

[0070] L i =G i / M i ;

[0071] Where L i represents the workload impact coefficient of the first area; Gi is the amount of garbage to be processed due to abnormal garbage events in the first area; M i is the remaining processing capacity of the garbage truck responsible for the first area. It can be understood that when L i When it is greater than 1, it indicates that the processing capacity of the garbage trucks in the area is no longer sufficient to handle the abnormal amount of garbage generated.

[0072] S203, determining a comprehensive influence coefficient;

[0073] Exemplarily, the sum of the coefficients can be used as the comprehensive influence coefficient.

[0074] For example, the sum of the regional correlation coefficient and the workload influence coefficient is calculated as the comprehensive influence coefficient.

[0075] S204, determining a second region according to the comprehensive influence coefficient;

[0076] Exemplarily, a to-be-confirmed area around the first area with a comprehensive influence coefficient higher than a set threshold may be determined as the second area.

[0077] The set threshold can be set to be no greater than 1. iWhen it is greater than 1, that is, the processing capacity of the garbage trucks in the first area is not enough to handle the abnormal amount of garbage generated, it is ensured that the surrounding area to be confirmed can be determined as the second area, and the garbage trucks in the surrounding area can be used to share the workload. In some examples, the set threshold can also be set to be slightly greater than 1. In actual applications, when the processing capacity of the garbage trucks in the first area is insufficient, only the area to be confirmed with better correlation around the first area may be selected as the second area, so as to reduce the scope of route planning as much as possible. The specific value of the set threshold can be set in actual applications through testing and simulation, and can be adjusted during daily evaluation and optimization.

[0078] It is understandable that the operation method of this embodiment does not consider the processing capacity of the garbage trucks in the area to be confirmed when determining the second area. Therefore, in some implementation processes, all garbage trucks in the first area and the second area may not be able to complete the processing of abnormal garbage events. In this embodiment, in order to reduce the impact of abnormal garbage events on daily work routes, when all garbage trucks in the first area and the surrounding second area are unable to complete the processing of the abnormal garbage event, the method of dispatching additional garbage trucks to perform operations can be selected.

[0079] That is, after the first area and each second area are determined as areas to be planned, it can also include: judging whether the processing capacity of all garbage trucks in the first area and the second area meets the needs of abnormal garbage events; if not, additional garbage trucks are dispatched during the recalculation of the working routes to meet the needs of abnormal garbage events.

[0080] This can prevent the expansion of the scope of impact caused by complex abnormal garbage events during actual work, that is, the need to re-route garbage trucks in a large area. The additional garbage trucks will plan their work routes in the planned area formed by the first area and each second area, ensuring that the impact of abnormal garbage events that are difficult to handle can still be controlled within a smaller scope.

[0081] In some embodiments, the information of the abnormal junk event further indicates: the formation factors of the abnormal junk event. Before determining the comprehensive impact coefficient according to the regional correlation coefficient and the workload impact coefficient, it also includes:

[0082] According to the formation factors of abnormal garbage events, the influence coefficients of the formation factors of abnormal garbage events are determined.

[0083] The comprehensive impact coefficients are determined to include:

[0084] The sum of the regional correlation coefficient, workload influence coefficient and formation factor influence coefficient is calculated as the comprehensive influence coefficient.

[0085] The formation factors of abnormal garbage events indicate why there is an abnormal amount of garbage that exceeds the daily work estimate. The impact range of abnormal garbage events will be different for different formation reasons. For example, when a large amount of garbage appears in the area due to the unexpected gathering of people, the amount of garbage in other areas along the road will also be affected due to the movement and evacuation of the crowd. For the appearance of a large amount of garbage without special reasons, that is, ordinary garbage gathering, a large amount of garbage may appear only at a certain point, but it will not affect the surrounding areas.

[0086] Exemplarily, the formation factors of abnormal garbage events include at least one of the following: unexpected crowd gathering, temporary construction, weather disaster impact, and ordinary garbage gathering. Among them, unexpected crowd gathering and temporary construction mainly have an impact on other areas along the road, the impact of weather disasters may affect the surrounding areas to a greater extent, and the impact of ordinary garbage gathering is relatively small. For various formation factors, their impact levels can be preset. In some implementation processes, a range can also be set for the formation factor influence coefficient, allowing sanitation personnel to determine the formation factor influence coefficient within the corresponding range according to actual conditions when reporting the formation factor influence coefficient.

[0087] For better understanding, a specific example is provided below for explanation.

[0088] Assume that the system obtains an abnormal garbage event of event type k. Through the information carried in the abnormal garbage event, the target location p indicated by the abnormal garbage event that requires temporary dispatch of a garbage truck and the amount of garbage to be processed, 50 tons, can be determined.

[0089] The system can locate the target location p in the planning of the first area i. It is assumed that there are several garbage trucks in the first area i, and the remaining garbage that can be processed by these garbage trucks outside of daily work is 100 tons.

[0090] At this time, it is necessary to determine whether other areas around the first area i are included in the route replanning as the second area. Taking a certain area j to be confirmed as an example, assuming that the distance weight W between the first area i and the area to be confirmed j is d is 0.7, and the path connection weight W r is 0.8, and the historical collaborative work weight W h is 0.6, and the influence coefficient β of event type k k is 1.2, and the proportional coefficient of each weight is α d =0.4, α r =0.3, α h =0.3.

[0091] Then calculate the regional correlation coefficient C ij as follows:

[0092] C ij =0.4 0.7+0.3 0.8+0.3 0.6=0.28+0.24+0.18=0.7;

[0093] Workload influence coefficient L i as follows:

[0094] L i =50 / 100=0.5;

[0095] Formation factor influence coefficient T k as follows:

[0096] T k =0.2;

[0097] The comprehensive influence coefficient I can be obtained ij as follows:

[0098] I ij =0.7+0.5+0.2=1.4;

[0099] In summary, the above method can be used to calculate the impact of abnormal garbage events on the surrounding area j to be confirmed, thereby providing support for the dynamic scheduling and route optimization of garbage trucks. In this example, assuming that the threshold is set to 1.2, the above area j to be confirmed will be used as the second area, and will be merged with the first area and other second areas (if any) as the area to be planned. Based on the predetermined route planning algorithm, the working routes of each garbage truck in the area to be planned are recalculated.

[0100] The path planning algorithm includes but is not limited to the dynamic Dijkstra algorithm, the A* algorithm or the machine learning algorithm. In practical applications, the amount of garbage and the balance of workload between garbage stations should also be considered when planning the path. This embodiment does not limit the specific path planning algorithm.

[0101] In a second aspect of the present application, a garbage truck operation system based on route optimization is also provided. Figure 2 It is a schematic block diagram of a garbage truck operation system based on route optimization provided in this embodiment.

[0102] like Figure 2 As shown, the garbage truck operation system 200 based on route optimization includes: an event acquisition module 201, an area demarcation module 202, a path planning module 203 and a notification push module 204.

[0103] Among them, the event acquisition module 201 is used to obtain abnormal garbage events, and the information of the abnormal garbage events indicates the target location where the garbage truck needs to be temporarily dispatched and the amount of garbage to be processed. The area demarcation module 202 is used to determine the first area where the target location is located, and according to the abnormal garbage events and the working conditions of the garbage trucks responsible for the first area, determine a number of second areas around the first area. The path planning module 203 is used to determine the first area and each of the second areas as areas to be planned, and recalculate the working routes of each garbage truck responsible for the area to be planned within the area to be planned based on a predetermined route planning algorithm. The notification push module 204 is used to notify each garbage truck corresponding to the area to be planned of the newly planned working route.

[0104] The specific execution process of the steps executed by each module of the garbage truck operation system 200 based on route optimization can also refer to the steps of the garbage truck operation method based on route optimization provided above in this embodiment, which will not be repeated in this embodiment.

[0105] In addition, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on the present disclosure that are equivalent, modified, omitted, combined (e.g., various embodiments intersecting), adapted or changed. It is not limited to the examples described in this specification or during the implementation of this application, and its examples will be interpreted as non-exclusive.

[0106] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of them) can be used in combination with each other. For example, those of ordinary skill in the art may use other embodiments when reading the above description.

[0107] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the embodiments of the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A garbage truck operation method based on route optimization, characterized in that: include: Acquire an abnormal garbage event, wherein information of the abnormal garbage event indicates a target location where a garbage truck needs to be temporarily dispatched and an amount of garbage to be processed; Determining a first area where the target location is located; Determine a plurality of second areas around the first area according to the abnormal garbage event and the working conditions of the garbage trucks responsible for the first area; The first area and each of the second areas are determined as areas to be planned, and the working routes of each garbage truck responsible for the areas to be planned in the areas to be planned are recalculated based on a predetermined route planning algorithm; Notify each garbage truck corresponding to the area to be planned of the newly planned work route; The determining of a plurality of second areas around the first area according to the abnormal garbage event and the working conditions of the garbage trucks responsible for the first area includes: Obtaining a regional correlation coefficient between the first region and the region to be confirmed; Determining a workload impact coefficient of the abnormal garbage event according to the amount of garbage to be processed and the remaining processing capacity of the garbage truck responsible for the first area; Determine the comprehensive impact coefficient; Determining a second area according to the comprehensive influence coefficient; The regional correlation coefficient is calculated by the following formula: C ij =a d ·W d +a r ·W r +a h ·W h ; Among them C ij represents the regional correlation coefficient between the first region and the region to be confirmed; W d is the distance weight between the first area and the area to be confirmed, and its value is negatively correlated with the distance; W r is the path connection weight between the first area and the area to be confirmed, and its value reflects the path connection status between the first area and the area to be confirmed. The more and smoother the paths between the first area and the area to be confirmed, the larger the value; W h is the historical collaborative work weight, and its value reflects the historical collaborative work of garbage trucks between the first area and the area to be confirmed. The higher the historical collaborative work frequency, the larger the value; α d , α r and α h are proportional coefficients of the distance weight, the path connection weight and the historical collaborative work weight respectively; The workload impact coefficient is calculated by the following formula: L i =G i / M i ; Where L i represents the workload influence coefficient of the first area; G i is the amount of garbage to be processed in the abnormal garbage event in the first area; M i The remaining processing capacity of the garbage trucks responsible for the first area; Determining the comprehensive influence coefficient includes: Calculating the sum of the regional correlation coefficient and the workload influence coefficient as the comprehensive influence coefficient; Determining the second area according to the comprehensive influence coefficient includes: A to-be-confirmed area around the first area where the comprehensive influence coefficient is higher than a set threshold is determined as a second area.

2. The garbage truck operation method based on route optimization according to claim 1, characterized in that: The information of the abnormal junk event also indicates: the formation factors of the abnormal junk event; Before determining the comprehensive influence coefficient according to the regional correlation coefficient and the workload influence coefficient, the method further includes: According to the formation factors of the abnormal junk events, influence coefficients of the formation factors of the abnormal junk events are determined.

3. The garbage truck operation method based on route optimization as claimed in claim 2, characterized in that: Determining the comprehensive influence coefficient includes: Calculating the sum of the regional correlation coefficient, the workload influence coefficient and the formation factor influence coefficient as the comprehensive influence coefficient; Determining the second area according to the comprehensive influence coefficient includes: A to-be-confirmed area around the first area where the comprehensive influence coefficient is higher than a set threshold is determined as a second area.

4. The garbage truck operation method based on route optimization as claimed in claim 2, characterized in that: The factors that cause the abnormal garbage incident include at least one of the following: unexpected crowd gathering, temporary construction, weather disaster impact, and ordinary garbage gathering.

5. The garbage truck operation method based on route optimization according to claim 1, characterized in that: After determining the first area and each of the second areas as areas to be planned, the method further includes: Determining whether the processing capacity of all garbage trucks in the first area and the second area meets the needs of the abnormal garbage event; If not, additional garbage trucks are dispatched during the recalculation of the work route to meet the needs of the abnormal garbage event.

6. A garbage truck operation system based on route optimization, characterized in that: include: An event acquisition module, used to acquire abnormal garbage events, wherein information of the abnormal garbage events indicates a target location where a garbage truck needs to be temporarily dispatched and the amount of garbage to be processed; An area demarcation module is used to determine a first area where the target location is located, and determine a plurality of second areas around the first area according to the abnormal garbage event and the working conditions of the garbage trucks responsible for the first area; A path planning module, used for determining the first area and each of the second areas as areas to be planned, and recalculating the working routes of each garbage truck responsible for the areas to be planned within the areas to be planned based on a predetermined route planning algorithm; A notification push module is used to notify each garbage truck corresponding to the area to be planned of the newly planned work route; The determining of a plurality of second areas around the first area according to the abnormal garbage event and the working conditions of the garbage trucks responsible for the first area includes: Obtaining a regional correlation coefficient between the first region and the region to be confirmed; Determining a workload impact coefficient of the abnormal garbage event according to the amount of garbage to be processed and the remaining processing capacity of the garbage truck responsible for the first area; Determine the comprehensive impact coefficient; Determining a second area according to the comprehensive influence coefficient; The regional correlation coefficient is calculated by the following formula: C ij =a d ·W d +a r ·W r +a h ·W h ; Among them C ij represents the regional correlation coefficient between the first region and the region to be confirmed; W d is the distance weight between the first area and the area to be confirmed, and its value is negatively correlated with the distance; W r is the path connection weight between the first area and the area to be confirmed, and its value reflects the path connection status between the first area and the area to be confirmed. The more and smoother the paths between the first area and the area to be confirmed, the larger the value; W h is the historical collaborative work weight, and its value reflects the historical collaborative work of garbage trucks between the first area and the area to be confirmed. The higher the historical collaborative work frequency, the larger the value; α d , α r and α h are proportional coefficients of the distance weight, the path connection weight and the historical collaborative work weight respectively; The workload impact coefficient is calculated by the following formula: L i =G i / M i ; Where L i represents the workload influence coefficient of the first area; G i is the amount of garbage to be processed in the abnormal garbage event in the first area; M i The remaining processing capacity of the garbage trucks responsible for the first area; Determining the comprehensive influence coefficient includes: Calculating the sum of the regional correlation coefficient and the workload influence coefficient as the comprehensive influence coefficient; Determining the second area according to the comprehensive influence coefficient includes: A to-be-confirmed area around the first area where the comprehensive influence coefficient is higher than a set threshold is determined as a second area.

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