Door-to-door delivery dispatching system

Abstract

The invention discloses a door-to-door delivery dispatching system, and relates to the technical field of vehicle dispatching. A data acquisition module; a condition constraint module; a loading estimation module; a vehicle distribution module; an emergency identification module; the abnormity classification module is used for identifying the goods picking abnormal condition and judging whether the goods picking abnormal condition needs to be subjected to emergency processing or not; and the emergency processing module is used for acquiring the real-time distribution condition of the vehicles and forming an emergency adjustment scheme for the abnormal pickup condition needing emergency processing. Through setting a condition constraint module, a loading estimation module, a vehicle distribution module, an emergency identification module and an emergency processing module, multiple factors of door-to-door pickup are taken into consideration, and time delay caused by cargo handling is avoided. Emergency situations caused by abnormal users or vehicles are classified and processed, and the whole scheduling scheme can be adjusted in time.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle scheduling, and specifically relates to a door-to-door pick-up scheduling system. Background Art

[0002] In the field of large-ticket logistics, when picking up goods for the shipper, the pick-up vehicle is communicated with the shipper by the dispatcher for the pick-up time period, and the vehicle is allocated for pick-up based on multiple factors such as the loading of its own vehicles, the available allocation time period, and the logistics center for vehicle diversion, or an external vehicle is rented for pick-up.

[0003] The existing scheduling usually uses the method of regional division for scheduling. Each pick-up operator is responsible for picking up goods in their own area. However, there are various limiting factors for door-to-door pick-up, which may lead to uneven distribution of business volume and poor cost control. In addition, when picking up goods door-to-door, various unexpected situations may occur, resulting in the original scheduling plan being unable to be implemented. However, the existing coping methods usually solve the problem by delaying the pick-up time, and there is still much room for improvement in the rationality of the plan. Summary of the Invention

[0004] To solve the above technical problems, a door-to-door pick-up scheduling system is provided. This technical solution solves the problems in the above background art that the existing scheduling usually uses the method of regional division for scheduling. Each pick-up operator is responsible for picking up goods in their own area. However, there are various limiting factors for door-to-door pick-up, which may lead to uneven distribution of business volume and poor cost control. In addition, when picking up goods door-to-door, various unexpected situations may occur, resulting in the original scheduling plan being unable to be implemented. However, the existing coping methods usually solve the problem by delaying the pick-up time, and there is still much room for improvement in the rationality of the plan.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A door-to-door pick-up scheduling system, comprising:

[0007] A database generation module, which establishes a community database within the scheduling area;

[0008] A data acquisition module, which acquires at least one user who needs to pick up goods on the same day, acquires the pick-up time interval of the user, acquires the location information of the user, and acquires the specifications and quantities of the goods to be picked up by the user. Among them, the pick-up time interval is the time allowable range for the user to have door-to-door pick-up, and the specification of the goods to be picked up is the size and weight of a single good to be picked up;

[0009] A loading estimation module, which estimates the time for transporting the goods to be picked up to the vehicle, and obtains the loading time of the goods to be picked up;

[0010] A vehicle allocation module, which obtains at least one vehicle participating in pick-up on the current day, and forms at least one vehicle pick-up route under the constraints of pick-up cost and the user's pick-up time interval;

[0011] An emergency situation identification module, which identifies the pick-up process and obtains pick-up abnormal situations;

[0012] An abnormal situation classification module, which identifies pick-up abnormal situations and determines whether emergency treatment is required for pick-up abnormal situations;

[0013] An emergency treatment module, which obtains the real-time distribution of vehicles when pick-up abnormal situations occur, and forms an emergency adjustment plan for pick-up abnormal situations that require emergency treatment according to the real-time distribution of vehicles.

[0014] Preferably, the steps for the database generation module to establish a community database within the scheduling area are as follows:

[0015] Obtain at least one community within the scheduling area and obtain the location information of the community;

[0016] Obtain at least one parking location within the community and obtain the building coordinates within the community.

[0017] Preferably, the steps for the loading estimation module to estimate the time for moving the goods to be picked up to the vehicle and obtain the loading time of the goods to be picked up are as follows:

[0018] According to the user's location information and the location information of the community, perform community identification to obtain the community where the user is located as the target community;

[0019] Obtain the building coordinates within the community where the user is located as the target building coordinates;

[0020] Obtain the parking location closest to the target building in the target community as the target parking location;

[0021] Based on big data, obtain the average moving speed of workers carrying goods;

[0022] Obtain the distance from the target parking location to the target building coordinates as the target distance;

[0023] According to the specifications and quantities of the goods to be picked up by the user, calculate the total occupied space and total weight of the goods to be picked up;

[0024] Obtain the weight limit and space limit for a single handling by workers. Divide the total occupied space of the goods to be picked up by the space limit for a single handling by workers to obtain the first number, and divide the total weight of the goods to be picked up by the weight limit for a single handling by workers to obtain the second number;

[0025] Take the larger of the first number and the second number as the handling times of the goods to be picked up.

[0026] Use the time estimation formula to calculate the loading time of the goods to be picked up.

[0027] The time estimation formula is as follows:

[0028]

[0029] Wherein, A is the loading time of the goods to be picked up, B is the target distance, C is the average moving speed of the worker handling the goods, and D is the handling times of the goods to be picked up.

[0030] Preferably, under the constraint conditions of the pick-up cost and the pick-up time interval of the user, forming at least one vehicle pick-up path includes the following steps:

[0031] Obtain the midpoint of the pick-up time interval of the user as the characteristic point.

[0032] Classify the users according to the characteristic points to obtain at least one user classification. The difference between the characteristic points of the users in the same user classification is less than the preset value, and the difference between the characteristic points of the users in different user classifications is not less than the preset value. Wherein, the preset value is the average time for the vehicle to reach the next pick-up location from one pick-up location in the historical data.

[0033] Take the average value of the characteristic points of the users in the user classification to obtain the classification average value.

[0034] Sort the user classifications in ascending order according to the classification average value to obtain the user classification sequence.

[0035] Generate at least one group of preliminary paths. The group of preliminary paths is composed of at least one preliminary path. The preliminary path is composed of at least one preliminary node. The preliminary node is the user in the user classification. The arrangement order of at least one preliminary node in the preliminary path is set according to the order of the preliminary node in the user classification sequence. The preliminary nodes of different preliminary paths in the group of preliminary paths are different from each other. The number of preliminary nodes of all the preliminary paths in a single group of preliminary paths is the same as the number of at least one user who needs to pick up goods on the same day.

[0036] Calculate the difference between the characteristic points corresponding to the adjacent preliminary nodes in the preliminary path as the characteristic time difference.

[0037] Obtain the distance between the communities where the adjacent preliminary nodes in the preliminary path are located as the marked distance, and obtain the average vehicle moving speed based on the historical data. Divide the marked distance by the average vehicle moving speed to obtain the marked time.

[0038] The marked time is superimposed on the loading time of the goods to be picked up at the earlier-prepared node among the adjacent prepared nodes to obtain the time to be verified;

[0039] When the time to be verified corresponding to the adjacent prepared node does not exceed the characteristic time difference corresponding to the adjacent prepared node, then both adjacent prepared nodes are marked as qualified nodes, otherwise no processing is performed;

[0040] Obtain a group of prepared paths in which all the prepared nodes in the prepared path are marked as qualified nodes as the candidate path group;

[0041] When picking up the goods, each of the prepared paths in the candidate path group is assigned a vehicle, and the sum of the distances between the communities where the adjacent prepared nodes in each of the prepared paths in the candidate path group are located is calculated to obtain the total distance;

[0042] Select the candidate path group with the smallest total distance, and assign the prepared path therein to the vehicle as the vehicle goods-picking path.

[0043] Preferably, the emergency situation recognition module recognizes the goods-picking process, and the steps for obtaining the goods-picking abnormal situation include:

[0044] When the goods to be picked up by the user are not picked up at the door within the user's goods-picking time interval, then abnormal recognition is performed to obtain the goods-picking abnormal situation.

[0045] Preferably, the abnormal classification module recognizes the goods-picking abnormal situation, and the steps for judging whether the goods-picking abnormal situation requires emergency treatment include:

[0046] Recognize the goods-picking abnormal situation to judge whether the goods-picking abnormal situation is caused by the vehicle or by the user;

[0047] When the goods-picking abnormal situation is caused by the vehicle, obtain the abnormal repair time of the vehicle. When the abnormal repair time of the vehicle is greater than the preset time, then judge that the goods-picking abnormal situation requires emergency treatment;

[0048] When the goods-picking abnormal situation is caused by the user, obtain the corrected goods-picking time interval after the user adjusts the goods-picking time interval;

[0049] Obtain the users whose goods have not been picked up by the vehicle to obtain at least one remaining user;

[0050] When the difference between the midpoints of the corrected goods-picking time interval and the goods-picking time intervals of the remaining users is not less than the preset value, then judge that the goods-picking abnormal situation requires emergency treatment.

[0051] Preferably, the emergency treatment module obtains the real-time distribution of the vehicles when the goods-picking abnormal situation occurs, and the steps include:

[0052] Obtain the real-time position coordinates of at least one vehicle as the real-time distribution of the vehicles.

[0053] Preferably, the forming of an emergency adjustment plan for the abnormal pick-up situation that needs emergency handling according to the real-time distribution of the vehicles includes the following steps:

[0054] When the abnormal pick-up situation is caused by a vehicle, take the users corresponding to the pick-up time intervals whose time gap between the midpoint and the occurrence time of the abnormal pick-up situation is less than the abnormal repair time of the vehicle as the users to be decomposed;

[0055] Use the exhaustive method to obtain at least one first insertion point in the vehicle pick-up paths of the vehicles without abnormal pick-up. The number of first insertion points is the same as the number of users to be decomposed, and the first insertion point satisfies that when the user to be decomposed is set at the first insertion point, the vehicles without abnormal pick-up will not be delayed;

[0056] When the abnormal pick-up situation is caused by a user, use the exhaustive method to obtain a second insertion point in the vehicle pick-up paths of the vehicles without abnormal pick-up. The second insertion point satisfies that when the user with abnormal pick-up is set at the second insertion point, the vehicles without abnormal pick-up will not be delayed;

[0057] When the first insertion point cannot be obtained, then postpone the pick-up of the user to be decomposed to the next day for scheduling;

[0058] When the second insertion point cannot be obtained, then postpone the pick-up of the user with abnormal pick-up to the next day for scheduling.

[0059] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0060] By setting up a condition constraint module, a loading estimation module, a vehicle allocation module, a sudden situation identification module and an emergency handling module, various factors for door-to-door pick-up are taken into consideration. Considering from the cost and the pick-up time of the users, ensure that the overall cost is within a reasonable range. At the same time, it is more in line with the time of the users, avoiding long waiting times for the users. In addition, the handling time of the goods is also taken into consideration. When there are more or heavier goods, it will inevitably affect the overall time. This solution can avoid the delay of the time caused by the handling of the goods. On the other hand, classify and handle the sudden situations caused by user or vehicle abnormalities, so as to timely adjust the entire scheduling plan, ensure that when there are abnormalities, the pick-up task can be completed on the same day as much as possible, and at the same time, it does not have too much impact on the time requirements of the other users. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic flow chart of the door-to-door pick-up scheduling system of the present invention;

[0062] Figure 2 Schematic diagram of the process for the database generation module of the present invention to establish a cell database within the scheduling area;

[0063] Figure 3 Schematic diagram of the process for the loading estimation module of the present invention to estimate the time for transporting the goods to be picked up to the vehicle and obtain the loading time of the goods to be picked up;

[0064] Figure 4 Schematic diagram of the process for the present invention to form at least one vehicle pick-up path under the constraints of pick-up cost and the pick-up time interval of the user;

[0065] Figure 5 Schematic diagram of the process for the exception classification module of the present invention to identify pick-up exceptions and determine whether emergency treatment is required for the pick-up exceptions;

[0066] Figure 6 Schematic diagram of the process for the present invention to form an emergency adjustment plan for pick-up exceptions that require emergency treatment based on the real-time distribution of vehicles. Detailed implementation manners

[0067] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0068] Refer to Figure 1 As shown, a door-to-door pick-up scheduling system includes:

[0069] A database generation module, which establishes a cell database within the scheduling area;

[0070] A data acquisition module, which acquires at least one user who needs to pick up goods on the same day, acquires the pick-up time interval of the user, acquires the location information of the user, and acquires the specifications and quantities of the goods to be picked up by the user. Among them, the pick-up time interval is the time allowance range during which the user can have door-to-door pick-up, and the specification of the goods to be picked up is the size and weight of a single good to be picked up;

[0071] A loading estimation module, which estimates the time for transporting the goods to be picked up to the vehicle and obtains the loading time of the goods to be picked up;

[0072] A vehicle allocation module, which acquires at least one vehicle participating in pick-up on the same day and forms at least one vehicle pick-up path under the constraints of pick-up cost and the pick-up time interval of the user;

[0073] An emergency situation identification module, which identifies the pick-up process and obtains pick-up exceptions;

[0074] An abnormal classification module, which identifies the abnormal situation of goods pickup and determines whether emergency treatment is required for the abnormal situation of goods pickup;

[0075] An emergency treatment module, which obtains the real-time distribution of vehicles when an abnormal situation of goods pickup occurs, and forms an emergency adjustment plan for the abnormal situation of goods pickup that requires emergency treatment according to the real-time distribution of vehicles.

[0076] In this solution, the loading time of the goods to be picked up is considered. Because when the goods are heavy or there are many goods, the loading time will inevitably increase, resulting in a delay in the time to pick up goods at the next location. Therefore, only estimating the time to the next pick-up point based on the distance is likely to result in an incorrect estimate of the time, leading to a mismatch between the entire scheduling plan and the actual situation. As a result, there will be a situation where many users wait. In addition, at least one vehicle pick-up path is formed under the constraint conditions of pick-up cost and the pick-up time interval of users. When picking up goods according to these vehicle pick-up paths, the overall distance will be restricted, thereby restricting the fuel cost, controlling the cost, and at the same time, it can also ensure that the door-to-door time is within the pick-up time interval of each user as much as possible. Thus, the waiting time of users can be controlled, and the experience of the entire solution can be guaranteed. At the same time, during the actual implementation of the solution, there will inevitably be situations such as vehicle failures or users having urgent matters temporarily. Therefore, these situations need to be scheduled to resolve them as much as possible on the same day and ensure that they do not have a great impact on the pick-up of other users. For the scheduling that cannot be completed on the same day, it will be re-planned according to the scheduling method in this solution the next day.

[0077] Refer to Figure 2 As shown, the steps for the database generation module to establish a community database in the scheduling area are as follows:

[0078] Obtain at least one community in the scheduling area and obtain the location information of the community;

[0079] Obtain at least one parkable location in the community and obtain the building coordinates in the community.

[0080] Roadblocks are set on some roads in the community. Therefore, vehicles cannot drive to certain buildings, but can only drive to the parkable locations near them. After that, the goods are picked up and carried. Therefore, it is necessary to obtain the parkable locations in advance to facilitate obtaining the nearest parkable location to the building where the goods are to be picked up later. Here, it is not necessary to obtain the house number of the user because people go up and down by elevator in the building, so the height of the floor will not have a great difference in the transportation time.

[0081] Refer to Figure 3As shown in the figure, the loading time estimation module estimates the time required to move the goods to be picked up to the vehicle, and the steps for obtaining the loading time of the goods to be picked up are as follows:

[0082] Based on the user's location information and the location information of the community, perform community identification to obtain the community where the user is located as the target community;

[0083] Obtain the building coordinates within the community where the user is located as the target building coordinates;

[0084] Obtain the nearest parkable location to the target building in the target community as the target parkable location;

[0085] Based on big data, obtain the average moving speed of the workers carrying goods;

[0086] Obtain the distance from the target parkable location to the target building coordinates as the target distance;

[0087] According to the specifications and quantity of the goods to be picked up by the user, calculate the total occupied space and total weight of the goods to be picked up;

[0088] Obtain the weight limit and space limit for a single handling by the workers. Divide the total occupied space of the goods to be picked up by the space limit for a single handling by the workers to obtain the first number, and divide the total weight of the goods to be picked up by the weight limit for a single handling by the workers to obtain the second number;

[0089] Take the larger of the first number and the second number as the number of times to handle the goods to be picked up;

[0090] Use the time estimation formula to calculate the loading time of the goods to be picked up;

[0091] The time estimation formula is as follows:

[0092]

[0093] Among them, A is the loading time of the goods to be picked up, B is the target distance, C is the average moving speed of the workers carrying goods, and D is the number of times to handle the goods to be picked up.

[0094] Since the loading time of the goods to be picked up will affect the time to the next point, it is necessary to obtain the loading time of the goods to be picked up. Therefore, according to this time, scheduling planning is carried out to ensure that the time requirements of the users in the planned path can be met and avoid the situation of waiting too long.

[0095] Refer to Figure 4 As shown in the figure, under the constraint conditions of the picking-up cost and the picking-up time interval of the user, forming at least one vehicle picking-up path includes the following steps:

[0096] Obtain the midpoint of the pick-up time interval of the user as the feature point;

[0097] Classify users according to the feature point to obtain at least one user classification. The difference between the feature points of users in the same user classification is less than a preset value, and the difference between the feature points of users in different user classifications is not less than the preset value. Among them, the preset value is the average time for the vehicle to reach the next pick-up location from one pick-up location in historical data;

[0098] Take the mean value of the feature points of the users in the user classification to obtain the classification mean value;

[0099] Sort the user classifications in ascending order according to the classification mean value to obtain the user classification sequence;

[0100] Generate at least one group of preliminary paths. The group of preliminary paths consists of at least one preliminary path. The preliminary path consists of at least one preliminary node. The preliminary node is a user in the user classification. The arrangement order of at least one preliminary node in the preliminary path is set according to the order of the user classification where the preliminary node is located in the user classification sequence. The preliminary nodes of different preliminary paths in the group of preliminary paths are different from each other. The number of preliminary nodes of all the preliminary paths in a single group of preliminary paths is the same as the number of at least one user who needs to pick up goods on the current day;

[0101] Calculate the difference between the feature points corresponding to adjacent preliminary nodes in the preliminary path as the feature time difference;

[0102] Obtain the distance between the communities where adjacent preliminary nodes in the preliminary path are located as the marked distance, and obtain the average vehicle moving speed based on historical data. Divide the marked distance by the average vehicle moving speed to obtain the marked time;

[0103] Superimpose the marked time on the loading time of the goods to be picked up of the preliminary node with a higher ranking among the adjacent preliminary nodes to obtain the time to be verified;

[0104] When the time to be verified corresponding to adjacent preliminary nodes does not exceed the feature time difference corresponding to adjacent preliminary nodes, then mark both adjacent preliminary nodes as qualified nodes, otherwise do nothing;

[0105] Obtain the group of preliminary paths in which all the preliminary nodes in the preliminary path are marked as qualified nodes as the candidate path group;

[0106] When picking up goods, each preliminary path in the candidate path group is assigned a vehicle, and calculate the sum of the distances between the communities where adjacent preliminary nodes in each preliminary path in the candidate path group are located to obtain the total distance;

[0107] Select the candidate path group with the minimum overall distance, and allocate the preliminary path among them to the vehicle as the vehicle's goods pickup path.

[0108] This allocation plan takes into account the cost and the user's time requirements. At the same time, when making the allocation, it is ensured that the number of pickup points for each picker is roughly the same. The cost is mainly the fuel cost, and the fuel cost is determined by the distance. Therefore, the planned path is the shortest path that meets the user's time requirements. When making the plan, since the possibilities are limited, the exhaustive method is used to exhaust each possibility to obtain the required plan.

[0109] The emergency situation recognition module recognizes the pickup process to obtain the pickup abnormal situation, including the following steps:

[0110] When the goods to be picked up by the user are not picked up at the door within the user's pickup time interval, abnormal recognition is performed to obtain the pickup abnormal situation.

[0111] Refer to Figure 5 As shown, the abnormal classification module recognizes the pickup abnormal situation and judges whether the pickup abnormal situation needs to be handled emergently, including the following steps:

[0112] Recognize the pickup abnormal situation and judge whether the pickup abnormal situation is caused by the vehicle or by the user;

[0113] When the pickup abnormal situation is caused by the vehicle, obtain the abnormal repair time of the vehicle. When the abnormal repair time of the vehicle is greater than the preset time, it is judged that the pickup abnormal situation needs to be handled emergently;

[0114] When the pickup abnormal situation is caused by the user, obtain the corrected pickup time interval after the user adjusts the pickup time interval;

[0115] Obtain the users whose goods have not been picked up by the vehicle to get at least one remaining user;

[0116] When the gap between the midpoints of the corrected pickup time interval and the pickup time intervals of the remaining users is not less than the preset value, it is judged that the pickup abnormal situation needs to be handled emergently.

[0117] The reasons for the emergency situation can be classified into two categories, namely, caused by the user and caused by the vehicle. When the vehicle's fault is repaired, its repair time needs to be considered. If the resulting time delay is serious, the users whose pickup time is within the repair time need to be diverted so that these users are picked up by the remaining vehicles. After the vehicle is repaired, it can continue to pick up the users whose pickup time is outside the repair time, thus avoiding the users waiting for too long;

[0118] When the user needs to adjust the time, it is necessary to determine whether the adjusted time interferes with the subsequent pick-up of the vehicle, that is, in the subsequent pick-up process, it is impossible to insert a user who adjusts the pick-up time without affecting other users. Therefore, it is necessary to divert this user and use another vehicle for pick-up.

[0119] When the emergency handling module obtains the abnormal pick-up situation, the real-time distribution of the vehicles includes the following steps:

[0120] Obtain the real-time position coordinates of at least one vehicle as the real-time distribution of the vehicles.

[0121] Refer to Figure 6 As shown, according to the real-time distribution of the vehicles, forming an emergency adjustment plan for the abnormal pick-up situation that needs emergency handling includes the following steps:

[0122] When the abnormal pick-up situation is caused by the vehicle, the users corresponding to the pick-up time intervals where the time difference between the midpoint and the occurrence time of the abnormal pick-up situation is less than the abnormal repair time of the vehicle are used as the users to be decomposed;

[0123] Using the exhaustive method, obtain at least one first insertion point in the vehicle pick-up path of the vehicle without abnormal pick-up. The number of first insertion points is the same as the number of users to be decomposed, and the first insertion point satisfies that when the user to be decomposed is set at the first insertion point, the vehicle without abnormal pick-up will not be delayed;

[0124] When the abnormal pick-up situation is caused by the user, using the exhaustive method, obtain a second insertion point in the vehicle pick-up path of the vehicle without abnormal pick-up. The second insertion point satisfies that when the user with abnormal pick-up is set at the second insertion point, the vehicle without abnormal pick-up will not be delayed;

[0125] When the first insertion point cannot be obtained, the pick-up of the user to be decomposed is postponed to the next day for scheduling;

[0126] When the second insertion point cannot be obtained, the pick-up of the user with abnormal pick-up is postponed to the next day for scheduling.

[0127] In the pick-up adjustment, not all adjustments can be satisfied. Therefore, for the adjustments that cannot be satisfied, they need to be rescheduled the next day to complete.

[0128] Furthermore, this solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned door-to-door pick-up scheduling system runs.

[0129] It can be understood that the storage medium can be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state disk (SSD).

[0130] In summary, the advantages of the present invention are as follows: By setting up a condition constraint module, a loading estimation module, a vehicle allocation module, a sudden situation identification module, and an emergency handling module, various factors for door-to-door pick-up are taken into consideration. Considering the cost and the pick-up time of the user, the overall cost is ensured to be within a reasonable range. At the same time, it is more in line with the user's time, avoiding long waiting times for the user. In addition, the handling time of the goods is also taken into consideration. When there are more or heavier goods, it will inevitably affect the overall time. This solution can avoid delays in time caused by goods handling. On the other hand, sudden situations caused by user or vehicle abnormalities are classified and processed, so that the entire scheduling plan can be adjusted in time to ensure that the pick-up task is completed on the same day as much as possible when there are abnormalities, and at the same time, it does not have an excessive impact on the time requirements of the remaining users.

[0131] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A door-to-door pickup dispatching system, characterized in that: include: A database generation module, wherein the database generation module establishes a cell database in the scheduling area; A data acquisition module, wherein the data acquisition module acquires at least one user who needs to pick up goods on the same day, acquires the user's pick-up time interval, acquires the user's location information, and acquires the specifications and quantity of the goods to be picked up by the user, wherein the pick-up time interval is the time range within which the user can pick up the goods at the door, and the specifications of the goods to be picked up are the size and weight of a single item to be picked up; A loading estimation module, which estimates the time it takes to transport the goods to be picked up to the vehicle, and obtains the loading time of the goods to be picked up; A vehicle allocation module, wherein the vehicle allocation module obtains at least one vehicle participating in the pickup of goods on the day, and forms at least one vehicle pickup route under the constraints of the pickup cost and the user's pickup time interval; An emergency situation identification module, wherein the emergency situation identification module identifies the process of picking up goods and obtains abnormal conditions of picking up goods; An abnormal classification module, which identifies abnormal conditions for picking up goods and determines whether emergency treatment is required for the abnormal conditions for picking up goods; The emergency processing module obtains the real-time distribution of vehicles when an abnormal situation of picking up goods occurs, and forms an emergency adjustment plan for the abnormal situation of picking up goods that requires emergency processing according to the real-time distribution of vehicles.

2. A door-to-door pickup dispatching system according to claim 1, characterized in that: The database generation module establishes a cell database in the scheduling area, including the following steps: Acquire at least one cell in the scheduling area and obtain location information of the cell; Get at least one available parking spot in the community and get the building coordinates in the community.

3. A door-to-door pickup dispatching system according to claim 2, characterized in that: The loading estimation module estimates the time for transporting the goods to be picked up to the vehicle, and obtaining the loading time of the goods to be picked up includes the following steps: According to the location information of the user and the location information of the cell, the cell identification is performed to obtain the cell where the user is located as the target cell; Get the building coordinates in the user's community as the target building coordinates; Obtain the closest available parking spot to the target building in the target community as the target available parking spot; Based on big data, obtain the average moving speed of workers carrying goods; Get the distance from the target parking location to the target building coordinates as the target distance; According to the specifications and quantity of the goods to be picked up by the user, the total occupied space and total weight of the goods to be picked up are calculated; Obtain the weight limit and space limit of a worker's single handling. Divide the total space occupied by the goods to be picked up by the space limit of the worker's single handling to obtain the first number. Divide the total weight of the goods to be picked up by the weight limit of the worker's single handling to obtain the second number. The largest of the first number and the second number is taken as the number of times the goods to be picked up are moved; Use the time estimation formula to calculate the loading time of the goods to be picked up; The time estimation formula is as follows: Among them, A is the loading time of the goods to be picked up, B is the target distance, C is the average moving speed of the workers carrying the goods, and D is the number of times the goods to be picked up are moved.

4. A door-to-door pickup dispatching system according to claim 3, characterized in that: The forming of at least one vehicle pickup route under the constraints of the pickup cost and the user's pickup time interval comprises the following steps: Get the midpoint of the user's pickup time interval as the feature point; Classify users according to feature points to obtain at least one user classification, wherein the difference in feature points of users in the same user classification is less than a preset value, and the difference in feature points of users in different user classifications is not less than a preset value, wherein the preset value is the average time for a vehicle to reach a next pick-up location from one pick-up location in historical data; Take the average of the feature points of users in the user classification to obtain the classification mean; Sort the user categories according to the category mean from small to large to obtain the user category sequence; Generate at least one preparation path group, the preparation path group is composed of at least one preparation path, the preparation path is composed of at least one preparation node, the preparation node is a user in the user classification, the arrangement order of at least one preparation node in the preparation path is set in the user classification sequence according to the user classification where the preparation node is located, the preparation nodes of different preparation paths in the preparation path group are different from each other, and the number of preparation nodes of all preparation paths in a single preparation path group is consistent with the number of at least one user who needs to pick up goods on the day; Calculating the difference between the characteristic points corresponding to the adjacent preparation nodes in the preparation path as the characteristic time difference; Obtaining the distance between the cells adjacent to the preparation node in the preparation path as the marking distance, and obtaining the average vehicle moving speed based on historical data, dividing the marking distance by the average vehicle moving speed to obtain the marking time; The marking time is added to the loading time of the goods to be picked up of the adjacent preparation nodes with the highest ranking, to obtain the verification time; When the verification time corresponding to the adjacent preparation nodes does not exceed the characteristic time difference corresponding to the adjacent preparation nodes, the adjacent preparation nodes are marked as qualified nodes, otherwise no processing is performed; Obtaining a preliminary path group in which the preliminary nodes in the preliminary path are all marked as qualified nodes as a candidate path group; When picking up the goods, each of the preparation paths in the candidate path group is assigned a vehicle, and the sum of the distances of the cells where the adjacent preparation nodes are located in each of the preparation paths in the candidate path group is calculated to obtain the overall distance; Select the candidate path group with the smallest overall distance and assign the backup path to the vehicle as the vehicle pickup path.

5. A door-to-door pickup dispatching system according to claim 4, characterized in that: The emergency situation identification module identifies the delivery process, and obtaining the abnormal delivery situation includes the following steps: When the user's goods to be picked up are not picked up at the door within the user's pick-up time interval, an abnormality identification is performed to obtain the abnormal situation of pick-up.

6. A door-to-door pickup dispatching system according to claim 5, characterized in that: The abnormal classification module identifies the abnormal situation of picking up goods, and determines whether the abnormal situation of picking up goods needs emergency treatment, including the following steps: Identify abnormalities in picking up goods and determine whether they are caused by the vehicle or the user; When the abnormal situation of picking up goods is caused by the vehicle, the abnormal repair time of the vehicle is obtained. When the abnormal repair time of the vehicle is greater than the preset time, it is judged that the abnormal situation of picking up goods needs emergency treatment; When the abnormal situation of picking up goods is caused by the user, the corrected picking up time interval after the user adjusts the picking up time interval is obtained; Get the user whose vehicle has not yet picked up the goods, and get at least one remaining user; When the difference between the midpoint of the revised pickup time interval and the midpoint of the pickup time interval of the remaining users is not less than the preset value, it is determined that the pickup abnormality requires emergency processing.

7. A door-to-door pickup dispatching system according to claim 6, characterized in that: The emergency processing module obtains the real-time distribution of vehicles when an abnormal situation of picking up goods occurs, including the following steps: The real-time position coordinates of at least one vehicle are obtained as the real-time distribution of the vehicles.

8. A door-to-door pickup dispatching system according to claim 7, characterized in that: The method of forming an emergency adjustment plan for abnormal delivery situations that require emergency treatment based on the real-time distribution of vehicles includes the following steps: When the abnormal situation of picking up goods is caused by the vehicle, the users corresponding to the picking up time interval whose time difference between the midpoint and the occurrence of the abnormal situation of picking up goods is less than the abnormal repair time of the vehicle are taken as the users to be decomposed; Using an exhaustive method, at least one first insertion point is obtained in the vehicle pickup path of the vehicle without any pickup anomaly, the number of the first insertion points is consistent with the number of users to be decomposed, and the first insertion point satisfies that when the user to be decomposed is set at the first insertion point, the vehicle without any pickup anomaly will not be delayed; When the abnormal situation of picking up goods is caused by the user, an exhaustive method is used to obtain a second insertion point in the vehicle picking up path of the vehicle without the abnormal situation of picking up goods, and the second insertion point satisfies that when the user with the abnormal situation of picking up goods is set at the second insertion point, the vehicle without the abnormal situation of picking up goods will not be delayed; When the first insertion point cannot be obtained, the pickup of the user to be decomposed will be postponed to the next day for scheduling; When the second insertion point cannot be obtained, the pickup of users with abnormal pickup will be postponed to the next day for scheduling.

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