CN109598459B - Logistics distribution method and device and computer readable storage medium - Google Patents
Logistics distribution method and device and computer readable storage medium Download PDFInfo
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- CN109598459B CN109598459B CN201710912857.4A CN201710912857A CN109598459B CN 109598459 B CN109598459 B CN 109598459B CN 201710912857 A CN201710912857 A CN 201710912857A CN 109598459 B CN109598459 B CN 109598459B
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Abstract
The invention discloses a logistics distribution method and device and a computer readable storage medium, and relates to the technical field of logistics. The logistics distribution method comprises the following steps: extracting address items corresponding to distribution granularity from the delivery addresses of each distribution task of the unmanned distribution trolley; generating a navigation path of an address item passing through each distribution task for the unmanned distribution trolley; and sending the navigation path to the unmanned distribution trolley so that the unmanned distribution trolley executes the distribution task according to the navigation path. The invention can determine the address item according to the distribution granularity and the delivery address of the distribution task of the unmanned distribution trolley, and then automatically determine the navigation path for the unmanned distribution trolley to distribute according to the address item, thereby reducing the human resource cost of the distribution station and improving the distribution efficiency.
Description
Technical Field
The present invention relates to the field of logistics technologies, and in particular, to a method and an apparatus for logistics distribution and a computer readable storage medium.
Background
In the existing logistics distribution process, the transportation of goods is single-thread point-to-point distribution, and the process mainly comprises two sections of distribution. The first-level distribution is a bulk goods transportation section, which is mainly completed by trucks, and the trucks are specially used for distributing goods, such as bulk goods transported from a warehouse to a distribution station. And the secondary distribution is from a distribution station to a user section, and the couriers of all the distribution stations mainly distribute the goods to the hands of the receiving persons.
In the second-level distribution stage, a large number of couriers are needed to carry out manual transportation and delivery, and the cost of human resources is high.
Disclosure of Invention
The embodiment of the invention aims to solve the technical problem that: how to reduce the human resource cost in logistics distribution.
According to a first aspect of the embodiments of the present invention, there is provided a logistics distribution method including: extracting address items corresponding to distribution granularity from the delivery addresses of each distribution task of the unmanned distribution trolley; generating a navigation path of an address item passing through each distribution task for the unmanned distribution trolley; and sending the navigation path to the unmanned distribution trolley so that the unmanned distribution trolley executes the distribution task according to the navigation path.
In one embodiment, the logistics distribution method further comprises: dividing a distribution task of a distribution station into a plurality of distribution areas according to a receiving address; and distributing distribution tasks for the unmanned distribution trolleys according to the distribution capacity of the unmanned distribution trolleys, wherein the distribution tasks of the same unmanned distribution trolley belong to the same distribution area.
In one embodiment, if the extracted address item comprises an indoor address and an outdoor address, a navigation path related to the indoor address is generated according to an indoor map, and a navigation path related to the outdoor address is generated according to an outdoor map.
In one embodiment, when the unmanned distribution vehicle is an unmanned distribution vehicle loaded with goods from a warehouse and transported to the distribution station by an unmanned truck, the logistics distribution method further comprises: calculating the available distribution duration of the unmanned distribution trolley according to the time of the unmanned truck arriving at the distribution station and the predicted return time; and adjusting the navigation path of the unmanned distribution trolley according to the available distribution time length so that the unmanned distribution trolley returns to the distribution station within the available distribution time length.
In one embodiment, adjusting the navigation path of the unmanned delivery vehicle based on the available delivery duration comprises: calculating the task execution time length of the unmanned distribution trolley for executing the distribution tasks according to the navigation path; judging whether the time for executing the task is less than or equal to the available distribution time, if so, not adjusting a navigation path; if not, the distribution tasks are adjusted, so that the time length for the unmanned distribution trolley to execute the adjusted distribution tasks is less than or equal to the available distribution time length, and a navigation path generated according to the adjusted distribution tasks is adopted.
In one embodiment, adjusting the navigation path of the unmanned delivery vehicle based on the available delivery duration comprises: monitoring the current position of the unmanned distribution trolley when the unmanned distribution trolley executes distribution tasks; calculating the estimated return time for directly returning from the current position of the unmanned distribution trolley to the distribution station; and if the difference between the sum of the distributed time length and the predicted return time length of the unmanned distribution trolley and the available distribution time length is smaller than the preset value, generating a navigation path from the current position to the distribution station for the unmanned distribution trolley and indicating the unmanned distribution trolley to return to the distribution station.
In one embodiment, the logistics distribution method further comprises: receiving the current position reported by an unmanned delivery trolley, an emergency and position information related to the emergency; and regenerating a navigation path of the unmanned delivery vehicle according to the receiving address of the unfinished delivery task of the unmanned delivery vehicle and the current position of the unmanned delivery vehicle so as to avoid an emergency.
In one embodiment, the logistics distribution method further comprises: searching an unmanned distribution trolley influenced by the emergency according to the position information related to the emergency; and generating a navigation path for the affected unmanned delivery vehicles again so as to enable the affected unmanned delivery vehicles to avoid the emergency.
According to a second aspect of the embodiments of the present invention, there is provided a logistics distribution apparatus including: the address item extraction module is configured to extract an address item corresponding to the distribution granularity from the receiving address of each distribution task of the unmanned distribution trolley; the navigation path generation module is configured to generate a navigation path of an address item passing through each delivery task for the unmanned delivery vehicle; and the navigation path sending module is configured to send the navigation path to the unmanned distribution trolley so that the unmanned distribution trolley executes the distribution task according to the navigation path.
In one embodiment, the logistics distribution apparatus further comprises: the task distribution module is configured to divide distribution tasks of the distribution stations into a plurality of distribution areas according to the receiving addresses; and distributing distribution tasks for the unmanned distribution trolleys according to the distribution capacity of the unmanned distribution trolleys, wherein the distribution tasks of the same unmanned distribution trolley belong to the same distribution area.
In one embodiment, the navigation path generation module is further configured to generate a navigation path related to the indoor address from an indoor map and a navigation path related to the outdoor address from an outdoor map when the extracted address item includes the indoor address and the outdoor address.
In one embodiment, the logistics distribution apparatus further comprises: the available distribution time length calculation module is configured to calculate the available distribution time length of the unmanned distribution trolley according to the time when the unmanned truck arrives at the distribution station and the predicted return time; and the navigation path adjusting module is configured to adjust the navigation path of the unmanned delivery trolley according to the available delivery time length so that the unmanned delivery trolley returns to the delivery station within the available delivery time length.
In one embodiment, the navigation path adjusting module is further configured to calculate a task execution time length for the unmanned delivery trolley to execute the delivery tasks according to the navigation path; judging whether the time for executing the task is less than or equal to the available distribution time, if so, not adjusting a navigation path; if not, the distribution tasks are adjusted, so that the time length for the unmanned distribution trolley to execute the adjusted distribution tasks is less than or equal to the available distribution time length, and a navigation path generated according to the adjusted distribution tasks is adopted.
In one embodiment, the navigation routing adjustment module is further configured to monitor a current position of the unmanned delivery vehicle while the unmanned delivery vehicle is performing the delivery tasks; calculating the estimated return time for directly returning from the current position of the unmanned distribution trolley to the distribution station; and if the difference between the sum of the distributed time length and the predicted return time length of the unmanned distribution trolley and the available distribution time length is smaller than the preset value, generating a navigation path from the current position to the distribution station for the unmanned distribution trolley and indicating the unmanned distribution trolley to return to the distribution station.
In one embodiment, the logistics distribution apparatus further comprises: the emergency avoiding module is configured to receive the current position reported by the unmanned delivery trolley, the emergency and the position information related to the emergency; and regenerating a navigation path of the unmanned delivery vehicle according to the address item of the unfinished delivery task of the unmanned delivery vehicle and the current position of the unmanned delivery vehicle so as to avoid an emergency.
In one embodiment, the emergency avoidance module is further configured to find unmanned delivery vehicles affected by the emergency according to the position information related to the emergency; and generating a navigation path for the affected unmanned delivery vehicles again so as to enable the affected unmanned delivery vehicles to avoid the emergency.
According to a third aspect of the embodiments of the present invention, there is provided a logistics distribution apparatus including: a memory; and a processor coupled to the memory, the processor configured to execute any of the aforementioned logistics distribution methods based on instructions stored in the memory.
According to a fourth aspect of the embodiments of the present invention, there is provided a computer-readable storage medium on which a computer program is stored, wherein the program is executed by a processor to implement any one of the logistics distribution methods.
One embodiment of the above invention has the following advantages or benefits: the invention can determine the address item according to the distribution granularity and the delivery address of the distribution task of the unmanned distribution trolley, and then automatically determine the navigation path for the unmanned distribution trolley to distribute according to the address item, thereby reducing the human resource cost of the distribution station and improving the distribution efficiency.
Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of an embodiment of the logistics distribution method of the present invention.
Fig. 2 is a flow chart of another embodiment of the distribution method of logistics of the present invention.
Fig. 3 is a flow chart of another embodiment of the logistics distribution method of the invention.
Fig. 4A is a flowchart of an embodiment of the unmanned delivery vehicle scheduling method of the present invention.
Fig. 4B is a flowchart of another embodiment of the unmanned delivery vehicle scheduling method of the present invention.
FIG. 5 is a flowchart illustrating a navigation path adjusting method according to an embodiment of the present invention.
Fig. 6 is a block diagram of one embodiment of the logistics distribution apparatus of the present invention.
Fig. 7 is a block diagram of another embodiment of the logistics distribution apparatus of the present invention.
Fig. 8 is a block diagram of yet another embodiment of the logistics distribution apparatus of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be discussed further in subsequent figures.
FIG. 1 is a flow chart of an embodiment of the logistics distribution method of the present invention. The method of the embodiment of fig. 1 may be performed, for example, by a scheduling device or a control device of a distribution station. Other devices or systems may be employed by those skilled in the art to perform the fig. 1 embodiment as desired. As shown in fig. 1, the logistics distribution method of this embodiment includes steps S102 to S106.
In step S102, an address item corresponding to the delivery granularity is extracted from the delivery address of each delivery task of the unmanned delivery vehicle.
The delivery tasks may be, for example, orders, waybills, goods, etc. to be delivered, and those skilled in the art may set different delivery units as the delivery tasks. The delivery address corresponding to each delivery task may be queried from, for example, an order system, a database, or other equipment or system in which the delivery information of the unmanned delivery vehicle is stored.
The delivery granularity refers to the accuracy of the actual delivery address relative to the delivery address filled by the user when placing an order, and can be determined according to the historical delivery information of the user. The inventor finds that, after analysis, in the existing logistics distribution process, due to reasons of cell control, absence of a user at home and the like, the address of the actual signed-in goods may be different from the receiving address filled by the user when placing an order. Therefore, the invention further determines the address which is more likely to receive goods according to the distribution granularity so as to improve the delivery efficiency of the unmanned distribution trolley.
For example, the address filled by the user is "X province, X city, X district XX district, district No. 1 building 101 room". If the distribution granularity is fine, for example, all the address items "X province X city X district XX district 101 room 1" may be extracted, and if the distribution granularity is coarse, for example, the address item "X province X city X district XX district" may be extracted. One skilled in the art can set multiple levels of delivery granularity as needed and will not be described here.
In step S104, a navigation path for the unmanned delivery vehicles passing through the address item of each delivery task is generated.
The unmanned distribution trolley starts from the distribution station and returns to the distribution station after distribution is finished, so that the starting point and the ending point of the navigation path are both the distribution stations. Thus, the planned navigation path may be a path that starts and ends at the delivery station and passes through all the extracted address items of the unmanned delivery vehicles.
When the navigation path is generated, the shortest path of all distribution tasks executed by the unmanned distribution trolley can be generated according to the principle of the shortest path, so that the distribution efficiency is improved.
And if the extracted address item comprises an indoor address and an outdoor address, generating a navigation path related to the indoor address according to an indoor map and generating a navigation path related to the outdoor address according to an outdoor map. For example, if the extracted part of the information in a certain address item is "X cell 101 room, after the navigation path from the address item of the previous delivery task to the X cell 1 room is planned according to the outdoor map, the path from the entrance of the 1 st building to the 101 room and the path from the entrance of the 1 st building to the entrance of the 1 st building for the unmanned delivery vehicle can be planned according to the indoor map, and then the navigation path from the X cell 1 room to the address item of the next delivery task can be planned according to the outdoor map. Therefore, the unmanned delivery trolley can finish indoor delivery more accurately, and user experience is improved.
In step S106, the navigation path is sent to the unmanned distribution vehicle, so that the unmanned distribution vehicle performs the distribution task according to the navigation path.
By the method of the embodiment, the address item can be determined according to the distribution granularity and the receiving address of the distribution task of the unmanned distribution trolley, and the navigation path for distribution of the unmanned distribution trolley is automatically determined according to the address item, so that the human resource cost of a distribution station can be reduced, and the distribution efficiency is improved.
The unmanned distribution trolley provided by the embodiment of the invention can be an unmanned distribution trolley belonging to a distribution station. For such unmanned delivery vehicles, the delivery stations may generate navigation paths for the vehicles based on the delivery tasks of the current delivery stations. A logistics distribution method according to another embodiment of the present invention is described below with reference to fig. 2.
Fig. 2 is a flow chart of another embodiment of the logistics distribution method of the invention. As shown in fig. 2, the logistics distribution method of this embodiment includes steps S202 to S210.
In step S202, the distribution tasks of the distribution stations are divided into a plurality of distribution areas according to the shipping addresses.
When the distribution tasks are classified, the distribution tasks may be classified according to different geographical areas to which the shipping addresses belong, for example, according to a cell, a street, a block, and the like to which the shipping addresses belong.
In step S204, distribution tasks are allocated to the unmanned distribution vehicles according to the distribution capacities of the unmanned distribution vehicles, wherein the distribution tasks of the same unmanned distribution vehicle belong to the same distribution area.
Distribution tasks of the same distribution area may be distributed to one or more unmanned distribution vehicles, thereby reducing the overlap of distribution paths of different unmanned distribution vehicles.
The dispensing capacity of the unmanned dispensing vehicle may include the dispensed weight and the dispensed volume. When allocating a task, the sum of the weight and the sum of the volume of the cargo corresponding to the allocation task allocated to the unmanned allocation vehicle may be calculated, and the calculation result may be compared with the allocation capacity threshold of the unmanned allocation vehicle to determine whether to continue to increase the allocation task or decrease the allocation task.
In step S206, an address item corresponding to the delivery granularity is extracted from the delivery address of each delivery task of the unmanned delivery vehicle.
In step S208, a navigation path for the unmanned delivery vehicle passing through the address item of each delivery task is generated.
In step S210, the navigation path is sent to the unmanned delivery vehicle, so that the unmanned delivery vehicle performs the delivery task according to the navigation path.
By the method of the embodiment, the overlapping of the distribution routes among different unmanned distribution trolleys can be reduced, and the distribution efficiency can be improved.
The unmanned distribution trolley provided by the embodiment of the invention can be conveyed to a distribution station by an unmanned truck and unfolded for distribution after goods are loaded in a warehouse. Such unmanned delivery vehicles may deploy for delivery immediately upon arrival at the delivery station and departure from the unmanned truck, without the need for the delivery station to sort and load. A logistics distribution method according to still another embodiment of the present invention is described below with reference to fig. 3.
Fig. 3 is a flow chart showing a distribution method of physical distribution according to another embodiment of the present invention. As shown in fig. 3, the logistics distribution method of this embodiment includes steps S302 to S308.
In step S302, a delivery task of an unmanned delivery vehicle delivered to a delivery station by an unmanned truck is acquired, wherein the unmanned delivery vehicle is loaded with goods corresponding to the delivery task.
In one embodiment, after the unmanned delivery vehicle truck finishes loading in the warehouse, the data storage device such as the dispatching system or the order system records the delivery tasks corresponding to the goods on the unmanned delivery vehicle and the relevant task information such as the delivery addresses. When a delivery station to which an unmanned delivery vehicle is to arrive is designated, the data storage device may send the task information to the delivery station.
In one embodiment, after the unmanned truck transports the unmanned delivery vehicle to the delivery station, the delivery station sends a request to the dispatching center according to the identification of the unmanned delivery vehicle so as to obtain information such as a delivery task and a delivery address of the unmanned delivery vehicle. The distribution station can acquire the identification of the unmanned distribution trolley by means of image recognition, bar code scanning and the like.
In step S304, an address item corresponding to the delivery granularity is extracted from the delivery address of each delivery task of the unmanned delivery vehicle.
In step S306, a navigation path for the unmanned delivery vehicle passing through the address item of each delivery task is generated.
In step S308, the navigation path is sent to the unmanned delivery vehicle, so that the unmanned delivery vehicle performs the delivery task according to the navigation path.
By the method of the embodiment, the unmanned distribution trolley can complete loading on the warehouse side and is conveyed to the distribution station by the unmanned truck, so that the unmanned distribution trolley can immediately perform distribution work without additional sorting in the distribution station, distribution efficiency is improved, and labor cost of the distribution station and management and maintenance cost of the unmanned distribution trolley are further reduced.
Of course, for such unmanned distribution vehicles of the embodiment in fig. 3, when the unmanned distribution vehicle is located in the warehouse, the method in the embodiment in fig. 2 may also be referred to allocate distribution tasks, and details thereof are not described here.
The embodiment of fig. 3 provides a vehicle that does not have a fixed delivery station to which it belongs, but rather is loaded directly into the warehouse as needed and carried by the drone truck to the corresponding delivery station. After the unmanned truck arrives at the delivery station, the loaded cargo can be unloaded in addition to releasing the loaded unmanned delivery vehicle for delivery. When unloading of the unmanned truck is finished, or after operations such as energy supplement, inspection and maintenance are finished, the unmanned truck can return to the warehouse. In this case, it is conceivable to return these unmanned delivery vehicles to the warehouse as well.
In the existing courier distribution process, the time limit from the distribution vehicle of the courier to the user is mainly considered, that is, the distribution vehicle needs to deliver the goods to the user within the preset time, and the time for returning the distribution vehicle to the distribution station has no particularly strict requirement. In a scene that the unmanned delivery trolley needs to be transported back to the warehouse by the unmanned truck, the unmanned delivery trolley needs to deliver goods to a user as soon as possible and return to a delivery station within preset time because the unmanned truck has departure time, so that the unmanned truck can bring the unmanned delivery trolley back to the warehouse in time.
In one embodiment, the available delivery time of the unmanned delivery vehicle can be calculated according to the time when the unmanned truck arrives at the delivery station and the predicted return time, and the navigation path of the unmanned delivery vehicle can be adjusted according to the available delivery time. The invention exemplarily provides two specific adjustment modes and corresponding scheduling methods.
The unmanned delivery vehicle scheduling method according to an embodiment of the present invention is described below with reference to fig. 4A.
Fig. 4A is a flowchart of an embodiment of a method for scheduling unmanned delivery vehicles according to the present invention. As shown in fig. 4A, the unmanned delivery vehicle scheduling method of this embodiment includes steps S4102 to S4114.
In step S4102, the address item of the delivery task of the unmanned delivery vehicle is determined.
In step S4104, a navigation path passing through the address entry is generated for the unmanned delivery vehicle based on the address entry of the delivery task of the unmanned delivery vehicle.
In step S4106, an available delivery time period of the unmanned delivery vehicle is calculated from the time when the unmanned truck arrives at the delivery station and the estimated return time.
The time length between the time when the unmanned truck arrives at the delivery station and the predicted return time can be directly used as the available delivery time length, and in addition, a part of reserved time can be deducted from the time length between the time when the unmanned truck arrives at the delivery station and the predicted return time to deal with some emergency situations or eliminate the time consumed by some preparation work when the unmanned truck is sent out.
In step S4108, a task execution time length for the unmanned distribution vehicle to execute the distribution task according to the navigation route is calculated.
For example, the duration of the task can be estimated according to the information such as the vehicle speed, the distance length, the road condition, the historical time, the number of delivered goods and the like of the unmanned delivery vehicle.
In one embodiment, the estimated travel time can be estimated according to the total path length and the average speed of the unmanned delivery vehicles, the estimated waiting time is obtained by multiplying the average time from the arrival of the unmanned delivery vehicles at the address item to the completion of the sign-in of the user in the historical data by the number of the delivery tasks, and the sum of the estimated travel time and the estimated waiting time is used as the estimated task execution time.
In step S4110, it is determined whether the duration of executing the task is less than or equal to the available delivery duration. If yes, go to step S4112; if not, go to step S4114.
In step S4112, the navigation path is used as the actual navigation path of the unmanned delivery vehicle without adjusting the navigation path.
In step S4114, the delivery task is adjusted so that the time length for the unmanned delivery vehicle to execute the adjusted delivery task is less than or equal to the available delivery time length, and the navigation path generated according to the adjusted delivery task is used as the actual navigation path of the unmanned delivery vehicle.
If the unmanned delivery vehicle has completed loading after adjusting the delivery tasks, it is possible to adjust only the delivery tasks of the unmanned delivery vehicle without adjusting the cargo loaded in the unmanned delivery vehicle.
By the method of the embodiment, the navigation path of the unmanned distribution trolley can be adjusted before the unmanned distribution trolley executes the distribution task, so that the time for distribution of the unmanned distribution trolley can be controlled in advance, and the unmanned distribution trolley can return to the distribution station in time.
Under the condition that the unmanned delivery trolley needs to return to the warehouse in time, the embodiment of the invention can monitor the current position of the unmanned delivery trolley in real time and enable the unmanned delivery trolley to return to the delivery station in time when the unmanned truck approaches the return time. A method of unmanned delivery vehicle scheduling according to another embodiment of the present invention is described below with reference to fig. 4B.
Fig. 4B is a flowchart of another embodiment of the unmanned delivery vehicle scheduling method of the present invention. As shown in fig. 4B, the unmanned delivery vehicle scheduling method of the embodiment includes steps S4202 to S4216.
In step S4202, the address item of the delivery task of the unmanned delivery vehicle is determined.
In step S4204, a navigation path passing through the address entry is generated for the unmanned delivery vehicle based on the address entry of the delivery task of the unmanned delivery vehicle.
In step S4206, the navigation path is transmitted to the unmanned delivery vehicle so that the unmanned delivery vehicle performs a delivery task according to the navigation path.
In step S4208, an available delivery time period of the unmanned delivery vehicle is calculated based on the time when the unmanned truck arrives at the delivery station and the estimated return time.
In step S4210, the current position of the unmanned delivery vehicle is monitored while the unmanned delivery vehicle performs the delivery task.
For example, the unmanned delivery vehicle may be caused to report the position every fixed time period, or a request may be sent to the unmanned delivery vehicle to cause the unmanned delivery vehicle to report the position in response to the request.
In step S4212, an estimated return time period for the unmanned distribution vehicle to return directly to the distribution station from the current position is calculated.
If the departure time of the unmanned truck is close after the unmanned delivery trolley directly returns to the delivery station from the current position, the unmanned delivery trolley cannot timely return to the delivery station together with the unmanned truck after all delivery tasks are executed. Thus, in this case, if the drone vehicle needs to be returned to the warehouse along with the drone truck, the drone vehicle cannot perform all of the delivery tasks.
In step S4214, it is determined whether the difference between the sum of the delivered time length and the expected return time length of the unmanned delivery vehicle and the available delivery time length is less than a preset value. If yes, go to step S4216; if not, go back to step S4210.
In step S4216, a navigation path from the current position to the delivery station is generated for the unmanned delivery vehicle and the unmanned delivery vehicle is instructed to return to the delivery station.
If the unmanned delivery trolley still has unfinished tasks currently, the unmanned delivery trolley is still returned, and the remaining unfinished tasks can be delivered to other unmanned delivery trolleys of the delivery station to be finished.
By the method of the embodiment, the time required by the unmanned delivery trolley to return to the delivery station can be predicted in real time in the process of delivery of the unmanned delivery trolley, so that the unmanned delivery trolley can return to the delivery station in time.
In the distribution process of the unmanned distribution trolley, the current road condition can be monitored in real time, and the navigation path of the unmanned distribution trolley is dynamically adjusted according to the road condition. A navigation path adjusting method according to an embodiment of the present invention is described below with reference to fig. 5.
FIG. 5 is a flowchart illustrating a navigation path adjusting method according to an embodiment of the present invention. As shown in fig. 5, the navigation path adjusting method of the embodiment includes steps S502 to S508.
In step S502, the current position, the emergency and the position information related to the emergency reported by the unmanned delivery vehicle are received.
The unmanned delivery vehicle can detect whether an emergency such as a vehicle accident, road maintenance, road section blockage and the like occurs in the front through sensing equipment such as a camera, a radar system, a laser ranging system and the like. When the position of the unmanned delivery vehicle is the position of the emergency, the current position of the unmanned delivery vehicle and the position information related to the emergency may be the same.
The location information related to the emergency event may be single point information such as geographical location coordinates, or may be location information indicating a range such as link information or area information.
In step S504, the navigation path of the unmanned delivery vehicle is regenerated according to the address item of the delivery task that the unmanned delivery vehicle has not completed and the current position of the unmanned delivery vehicle, so as to avoid the emergency.
Therefore, the navigation path of the unmanned distribution trolley can be adjusted in time according to the current road condition, and the distribution efficiency of the unmanned distribution trolley is guaranteed.
In addition, the navigation path adjusting method of this embodiment may further include steps S506 to S508.
In step S506, the unmanned delivery vehicles affected by the emergency are searched according to the location information related to the emergency.
In one embodiment, the dispatch system of the delivery station may look up which unmanned delivery vehicles' navigation paths will pass through the location information involved in the incident.
In one embodiment, the location information related to the emergency event can also be broadcasted to the unmanned delivery vehicle, the unmanned delivery vehicle receiving the broadcast determines whether the unmanned delivery vehicle will pass through the location information related to the emergency event, and if the unmanned delivery vehicle will pass through, the location information is reported to the dispatching system of the delivery station.
In step S508, a navigation path is newly generated for the affected unmanned delivery vehicles, so as to make the affected unmanned delivery vehicles avoid the emergency.
Therefore, the navigation paths of other unmanned distribution trolleys which are possibly influenced can be adjusted according to the emergency reported by the unmanned distribution trolleys, and the overall distribution efficiency of the distribution station is improved.
A logistics distribution apparatus according to one embodiment of the present invention is described below with reference to fig. 6.
Fig. 6 is a block diagram of one embodiment of the logistics distribution apparatus of the present invention. As shown in fig. 6, the logistics distribution apparatus 600 of this embodiment includes: an address item extracting module 610 configured to extract an address item corresponding to a delivery granularity from a shipping address of each delivery task of the unmanned delivery vehicle; a navigation path generation module 620 configured to generate a navigation path for the unmanned delivery vehicle passing through the address item of each delivery task; and a navigation path sending module 630 configured to send the navigation path to the unmanned delivery vehicle so that the unmanned delivery vehicle performs the delivery task according to the navigation path.
In one embodiment, the logistics distribution apparatus 600 may further comprise: a task allocation module 640 configured to divide the distribution tasks of the distribution stations into a plurality of distribution areas according to the shipping addresses; and distributing distribution tasks for the unmanned distribution trolleys according to the distribution capacity of the unmanned distribution trolleys, wherein the distribution tasks of the same unmanned distribution trolley belong to the same distribution area.
In one embodiment, the navigation path generating module 620 is further configured to generate the navigation path related to the indoor address according to an indoor map and the navigation path related to the outdoor address according to an outdoor map when the extracted address item includes the indoor address and the outdoor address.
In one embodiment, the logistics distribution apparatus 600 can further include: an available delivery duration calculation module 650 configured to calculate an available delivery duration of the unmanned delivery vehicle according to a time when the unmanned truck arrives at the delivery station and the estimated return time; a navigation path adjustment module 660 configured to adjust the navigation path of the unmanned delivery vehicle according to the available delivery duration such that the unmanned delivery vehicle returns to the delivery station within the available delivery duration.
In one embodiment, the navigation path adjusting module 660 may be further configured to calculate a task execution duration for the unmanned delivery vehicle to execute the delivery tasks according to the navigation path; judging whether the time for executing the task is less than or equal to the available distribution time, if so, not adjusting a navigation path; if not, the distribution tasks are adjusted, so that the time length for the unmanned distribution trolley to execute the adjusted distribution tasks is less than or equal to the available distribution time length, and a navigation path generated according to the adjusted distribution tasks is adopted.
In one embodiment, the navigation path adjustment module 660 may be further configured to monitor the current position of the unmanned delivery vehicle while the unmanned delivery vehicle is performing the delivery tasks; calculating the estimated return time for directly returning from the current position of the unmanned distribution trolley to the distribution station; and if the difference between the sum of the distributed time length and the predicted return time length of the unmanned distribution trolley and the available distribution time length is smaller than the preset value, generating a navigation path from the current position to the distribution station for the unmanned distribution trolley and indicating the unmanned distribution trolley to return to the distribution station.
In one embodiment, the logistics distribution apparatus 600 may further comprise: the emergency avoiding module 670 is configured to receive the current position reported by the unmanned delivery vehicle, the emergency and the position information related to the emergency; and regenerating a navigation path of the unmanned delivery vehicle according to the address item of the unfinished delivery task of the unmanned delivery vehicle and the current position of the unmanned delivery vehicle so as to avoid the emergency.
In one embodiment, the incident avoidance module 670 may be further configured to find an unmanned delivery vehicle affected by the incident according to the location information related to the incident; and generating a navigation path for the affected unmanned delivery vehicles again so as to enable the affected unmanned delivery vehicles to avoid the emergency.
Fig. 7 is a block diagram of another embodiment of the logistics distribution apparatus of the present invention. As shown in fig. 7, the apparatus 700 of this embodiment includes: a memory 710 and a processor 720 coupled to the memory 710, wherein the processor 720 is configured to execute the logistics distribution method of any of the above embodiments based on instructions stored in the memory 710.
Fig. 8 is a block diagram of yet another embodiment of the logistics distribution apparatus of the present invention. As shown in fig. 8, the apparatus 800 of this embodiment includes: the memory 810 and the processor 820 may further include an input/output interface 830, a network interface 840, a storage interface 850, and the like. These interfaces 830, 840, 850 and the memory 810 and the processor 820 may be connected, for example, by a bus 860. The input/output interface 830 provides a connection interface for input/output devices such as a display, a mouse, a keyboard, and a touch screen. Network interface 840 provides a connection interface for a variety of networking devices. The storage interface 850 provides a connection interface for external storage devices such as an SD card and a usb disk.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, wherein the program, when executed by a processor, implements any one of the aforementioned logistics distribution methods.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (16)
1. A logistics distribution method comprising:
extracting address items corresponding to distribution granularity from the delivery addresses of each distribution task of the unmanned distribution trolley, wherein the distribution granularity refers to the accuracy degree of the actual delivery addresses relative to the delivery addresses filled when the user places orders and is determined according to historical delivery information of the user;
generating a navigation path of an address item passing through each distribution task for the unmanned distribution trolley;
when the unmanned distribution vehicle is an unmanned distribution vehicle which loads goods from the warehouse, is transported to the distribution station by the unmanned truck, and is brought back to the warehouse by the unmanned truck, the logistics distribution method further comprises the following steps: calculating the available distribution time length of the unmanned distribution trolley according to the time of the unmanned truck arriving at the distribution station and the predicted return time, wherein the available distribution time length comprises the following steps: taking the time length between the time when the unmanned truck arrives at the distribution station and the predicted return time as the available distribution time length, or deducting the reserved time from the time length between the time when the unmanned truck arrives at the distribution station and the predicted return time as the available distribution time length; adjusting a navigation path of the unmanned distribution trolley according to the available distribution time length so that the unmanned distribution trolley returns to a distribution station within the available distribution time length, and the unmanned truck can bring the unmanned distribution trolley back to a warehouse in time;
and sending the navigation path to the unmanned distribution trolley so that the unmanned distribution trolley executes the distribution task according to the navigation path.
2. The logistics distribution method of claim 1, further comprising:
dividing a distribution task of a distribution station into a plurality of distribution areas according to the receiving address;
and distributing distribution tasks for the unmanned distribution trolleys according to the distribution capacity of the unmanned distribution trolleys, wherein the distribution tasks of the same unmanned distribution trolley belong to the same distribution area.
3. The logistics distribution method of claim 1, wherein if the extracted address item includes an indoor address and an outdoor address, the navigation path to which the indoor address relates is generated from an indoor map, and the navigation path to which the outdoor address relates is generated from an outdoor map.
4. The logistics distribution method of claim 1, wherein the adjusting the navigation path of the unmanned distribution trolley according to the available distribution time period comprises:
calculating the task execution time length of the unmanned distribution trolley for executing the distribution tasks according to the navigation path;
judging whether the time length for executing the task is less than or equal to the available distribution time length, if so, not adjusting the navigation path; if not, the distribution tasks are adjusted, so that the time length for the unmanned distribution trolley to execute the adjusted distribution tasks is less than or equal to the available distribution time length, and a navigation path generated according to the adjusted distribution tasks is adopted.
5. The logistics distribution method of claim 1, wherein the adjusting the navigation path of the unmanned distribution vehicle according to the available distribution time period comprises:
monitoring the current position of the unmanned delivery trolley when the unmanned delivery trolley executes a delivery task;
calculating the estimated return time for directly returning from the current position of the unmanned distribution trolley to the distribution station;
and if the difference between the sum of the distributed time length and the predicted return time length of the unmanned distribution trolley and the available distribution time length is less than a preset value, generating a navigation path from the current position to the distribution station for the unmanned distribution trolley and indicating the unmanned distribution trolley to return to the distribution station.
6. The logistics distribution method of any one of claims 1 to 5 further comprising:
receiving a current position, an emergency and position information related to the emergency reported by an unmanned delivery trolley;
and regenerating a navigation path of the unmanned delivery vehicle according to the address item of the unfinished delivery task of the unmanned delivery vehicle and the current position of the unmanned delivery vehicle so as to avoid the emergency.
7. The logistics distribution method of claim 6, further comprising:
searching an unmanned distribution trolley influenced by the emergency according to the position information related to the emergency;
and generating a navigation path for the affected unmanned distribution vehicle again so as to enable the affected unmanned distribution vehicle to avoid the emergency.
8. A logistics distribution apparatus comprising:
the address item extraction module is configured to extract address items corresponding to delivery granularity from the delivery addresses of each delivery task of the unmanned delivery trolley, wherein the delivery granularity refers to the accuracy degree of the actual delivery addresses relative to the delivery addresses filled when the user places orders and is determined according to historical delivery information of the user;
the navigation path generation module is configured to generate a navigation path of an address item passing through each delivery task for the unmanned delivery trolley;
an available delivery time length calculation module configured to calculate an available delivery time length of an unmanned delivery vehicle according to the time when the unmanned truck arrives at a delivery station and the predicted return time, the available delivery time length calculation module comprising: taking the time length between the time when the unmanned truck arrives at the distribution station and the predicted return time as the available distribution time length, or deducting the reserved time from the time length between the time when the unmanned truck arrives at the distribution station and the predicted return time as the available distribution time length;
the navigation path adjusting module is configured to adjust the navigation path of the unmanned delivery trolley according to the available delivery time length when the unmanned delivery trolley is the unmanned delivery trolley which loads goods from the warehouse, is conveyed to the delivery station by the unmanned truck and is brought back to the warehouse by the unmanned truck, so that the unmanned delivery trolley returns to the delivery station within the available delivery time length, and the unmanned truck can bring the unmanned delivery trolley back to the warehouse in time;
and the navigation path sending module is configured to send the navigation path to the unmanned distribution trolley so that the unmanned distribution trolley executes the distribution task according to the navigation path.
9. The logistics distribution apparatus of claim 8, further comprising:
the task distribution module is configured to divide distribution tasks of the distribution stations into a plurality of distribution areas according to the receiving addresses; and distributing distribution tasks for the unmanned distribution trolleys according to the distribution capacity of the unmanned distribution trolleys, wherein the distribution tasks of the same unmanned distribution trolley belong to the same distribution area.
10. The logistics distribution apparatus of claim 8, wherein the navigation path generation module is further configured to generate the navigation path related to the indoor address from the indoor map and the navigation path related to the outdoor address from the outdoor map when the extracted address item comprises the indoor address and the outdoor address.
11. The logistics distribution device of claim 8, wherein the navigation path adjustment module is further configured to calculate a task execution duration for the unmanned distribution vehicle to execute the distribution tasks according to the navigation path; judging whether the time length for executing the task is less than or equal to the available distribution time length, if so, not adjusting the navigation path; if not, the distribution tasks are adjusted, so that the time length for the unmanned distribution trolley to execute the adjusted distribution tasks is less than or equal to the available distribution time length, and a navigation path generated according to the adjusted distribution tasks is adopted.
12. The logistics distribution device of claim 8, wherein the navigation path adjustment module is further configured to monitor a current location of the unmanned distribution vehicle while the unmanned distribution vehicle is performing a distribution task; calculating the estimated return time for directly returning from the current position of the unmanned distribution trolley to the distribution station; and if the difference between the sum of the distributed time length and the predicted return time length of the unmanned distribution trolley and the available distribution time length is less than a preset value, generating a navigation path from the current position to the distribution station for the unmanned distribution trolley and indicating the unmanned distribution trolley to return to the distribution station.
13. The logistics distribution device of any one of claims 8 to 12, further comprising:
the emergency avoiding module is configured to receive the current position reported by the unmanned delivery trolley, an emergency and position information related to the emergency; and regenerating a navigation path of the unmanned delivery vehicle according to the receiving address of the unfinished delivery task of the unmanned delivery vehicle and the current position of the unmanned delivery vehicle so as to avoid the emergency.
14. The logistics distribution apparatus of claim 13, wherein the incident avoidance module is further configured to find an unmanned distribution vehicle affected by the incident according to the location information related to the incident; and generating a navigation path for the affected unmanned distribution vehicle again so as to enable the affected unmanned distribution vehicle to avoid the emergency.
15. A logistics distribution apparatus, comprising:
a memory; and
a processor coupled to the memory, the processor configured to execute the logistics distribution method of any of claims 1-7 based on instructions stored in the memory.
16. A computer-readable storage medium on which a computer program is stored, wherein the program when executed by a processor implements the logistics distribution method of any one of claims 1 to 7.
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