KR20230007973A - Artificial intelligence-based intelligent drainage apparatus and operating method thereof - Google Patents

Abstract

The present invention relates to a technical idea of performing artificial intelligence-based intelligent dispatch. Proximity is calculated based on a predicted route. At this time, even in the case of delivery vehicles that have already been dispatched and are in operation, the exact confirmed routes of each of the delivery vehicles are considered in real time to provide a more precise and efficient dispatch method.

Description

Artificial intelligence-based intelligent dispatch system and its operation method {ARTIFICIAL INTELLIGENCE-BASED INTELLIGENT DRAINAGE APPARATUS AND OPERATING METHOD THEREOF}

The present invention relates to a technical concept of performing artificial intelligence-based intelligent dispatch, and more specifically, calculates proximity based on a predicted route, and at this time, even in the case of delivery vehicles that have already been dispatched and are being delivered, each delivery It relates to an artificial intelligence-based intelligent dispatching technology that provides a more precise and efficient dispatching method by taking into account the accurate confirmed routes of vehicles in real time.

Most current dispatch technologies use two-dimensional blind dispatch and static dispatch methods based on Spatial Proximity (spatial proximity) using only the location, distance, and reachable time at the time of delivery request.

At the time when a new delivery destination mission is added, it is a form of dispatching to a driver who is in an empty state that can quickly reach that delivery destination, so a method of dispatching without predicting all delivery status according to actual time changes is used.

However, as time elapses, vehicles in an empty state may change and location information of delivery drivers also changes, but it is very difficult to predict or recognize such context changes. For this reason, most current dispatch technologies use a two-dimensional blind dispatch and static dispatch method based on Spatial Proximity (spatial proximity) using only the location, distance, and reachable time at the time of delivery request.

The blind allocation method corresponds to a static allocation method that cannot respond according to dynamically changed situations.

Therefore, at the time when a new delivery destination mission is added, it is a form of dispatching to a driver who is in an empty state that can quickly reach that delivery destination, so there is a disadvantage that dispatching occurs without predicting all delivery status according to actual time changes.

Korean Patent Publication No. 10-2017-0125756, "Dividend Brokerage System and Dividend Brokerage Method" Korean Patent Publication No. 10-2017-0066836, "Distributing method for IoT-based multimodal transportation service and device therefor"

The purpose of the present invention is to realize precise dispatch with maximized delivery efficiency by predicting the existing delivery route for each delivery driver and the expected arrival time for each section, and predicting the expected route, estimated route, and estimated time of arrival for each vehicle at the time of dispatch. to be

The present invention is a Spatial & Temporal Proximity (time, spatial The purpose is to provide a smart dispatch method based on 3D artificial intelligence based on proximity).

The present invention provides an intelligent dispatch dispatch system capable of performing optimal dispatch through predicting all the driving routes of delivery drivers and calculating an accurate cost according to the case of allocating a new delivery address to each delivery driver. aims to

The present invention searches and predicts in real time the driving trajectory of neighboring delivery vehicles that operate in an area adjacent to a new delivery destination in an empty state of empty delivery vehicles that are not assigned a delivery location, predicts the movement path of nearby delivery vehicles in an empty state, and improves delivery efficiency. It aims to realize maximized precision alignment.

According to one embodiment of the present invention, the artificial intelligence-based intelligent dispatch system receives a first delivery route search unit that searches for location information and a first delivery route of a plurality of nearby delivery vehicles, receives an additional delivery request related to a new delivery destination, A delivery vehicle selection unit that selects a plurality of delivery vehicles passing a delivery route close to the starting point of the new delivery destination from among the plurality of nearby delivery vehicles based on the received additional delivery request, the searched location information, and a first delivery route; A delivery order updating unit for updating the delivery order of the selected plurality of delivery vehicles in consideration of remaining delivery addresses and the new delivery location of the selected plurality of delivery vehicles, and a control system of the selected plurality of delivery vehicles based on the updated delivery order. 2 A second delivery route search unit that searches for a delivery route, an arrival time calculator that calculates a plurality of estimated arrival times for the new delivery destination based on the searched second delivery route, and a plurality of estimated arrival times that are calculated A new delivery address allocator for allocating the new delivery address to any one delivery vehicle among the plurality of selected delivery vehicles may be included.

The estimated arrival time calculation unit calculates a first expected arrival time of a first delivery vehicle from among the selected plurality of delivery vehicles as a stopover at the new delivery location, and calculates the first expected arrival time of the second delivery vehicle from among the selected plurality of delivery vehicles. A second estimated time of arrival at the new delivery destination as a stopover may be calculated.

The new delivery address allocator may send any one of the first delivery vehicle and the second delivery vehicle corresponding to any one of the first estimated arrival time and the second estimated arrival time to the new delivery location. can be assigned.

The first delivery route search unit collects location information of the plurality of nearby delivery vehicles according to a delivery request for pre-assigned delivery destinations, and first delivers the plurality of nearby delivery vehicles based on the collected location information. path can be searched.

The first delivery route search unit may determine the departure point and destination of each of the plurality of nearby delivery vehicles according to a delivery request for pre-assigned delivery locations, and search for the determined departure point and destination in pre-stored map data.

The first delivery route search unit collects location information of a plurality of surrounding delivery vehicles in an empty state to which a delivery address is not assigned among the plurality of surrounding delivery vehicles, and based on the collected location information, a plurality of locations in an empty state. A first delivery route of nearby delivery vehicles may be searched.

The first delivery route of the plurality of nearby delivery vehicles in the retrieved empty state may include a travel trajectory in which the plurality of nearby delivery vehicles in the empty state operate in an area adjacent to the new delivery destination in the empty state.

The second delivery route search unit searches for a first route through which the new delivery location of a first delivery vehicle among the selected plurality of delivery vehicles is used as a stopover, and the second delivery vehicle among the selected plurality of delivery vehicles is A second transit route using a new delivery destination as a transit point may be searched.

The estimated time of arrival calculation unit may calculate a first estimated time of arrival for the first via route and a second estimated time of arrival for the second via route.

The estimated time of arrival calculation unit calculates a third estimated time of arrival to a delivery destination passing the new delivery destination among delivery addresses pre-allocated to a first delivery vehicle among the selected plurality of delivery vehicles, and Among the delivery locations pre-assigned to the second delivery vehicle, a fourth expected arrival time to a delivery destination passing the new delivery vehicle is calculated, a fifth estimated arrival time is calculated based on the departure and destination of the new delivery location, and the third The first expected arrival time may be calculated in consideration of the expected arrival time and the fifth expected arrival time, and the second expected arrival time may be calculated in consideration of the fourth expected arrival time and the fifth expected arrival time.

An artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention includes the steps of searching for location information and a first delivery route of a plurality of nearby delivery vehicles in a first delivery route search unit, in a delivery vehicle selection unit, a new delivery destination. Receiving an additional delivery request related to, and based on the received additional delivery request, the retrieved location information, and the first delivery route, a plurality of deliveries passing through a delivery route close to the starting point of the new delivery destination among the plurality of surrounding delivery vehicles Selecting vehicles, in a delivery order update unit, updating the delivery order of the selected plurality of delivery vehicles in consideration of remaining delivery addresses and the new delivery addresses of the selected plurality of delivery vehicles, in a second delivery route search unit , Searching for a second delivery route of the selected plurality of delivery vehicles based on the updated delivery order, in an estimated arrival time calculation unit, based on the searched second delivery route, a plurality of scheduled arrivals for the new delivery destination It may include calculating times and allocating the new delivery address to any one delivery vehicle among the plurality of selected delivery vehicles by comparing the calculated plurality of expected arrival times in a new delivery address allocator.

The step of calculating a plurality of expected arrival times for the new delivery destination based on the searched second delivery route may include a first arrival time of a first delivery vehicle passing through the new delivery destination among the selected plurality of delivery vehicles. and calculating a second expected arrival time at the new delivery destination of a second delivery vehicle among the selected plurality of delivery vehicles as a stopover.

The step of comparing the calculated plurality of estimated arrival times and allocating the new delivery address to one of the selected delivery vehicles includes any one of the first estimated arrival time and the second estimated arrival time. It may include allocating the new delivery location to any one delivery vehicle of the first delivery vehicle and the second delivery vehicle corresponding to the expected arrival time of .

The step of searching for a second delivery route of the plurality of selected delivery vehicles based on the updated delivery order may include a first route through which the new delivery location of a first delivery vehicle among the plurality of selected delivery vehicles is a stopover. The method may include searching for a second transit route using the new delivery destination of a second delivery vehicle among the selected plurality of delivery vehicles as a stopover.

Calculating a plurality of estimated arrival times for the new delivery destination based on the searched second delivery route may include calculating a first estimated arrival time for the first via route, and a second estimated arrival time for the second via route. A step of calculating an estimated time of arrival may be included.

Calculating a plurality of estimated arrival times for the new delivery destination based on the searched second delivery route may include a delivery address passing the new delivery destination among delivery addresses pre-assigned to a first delivery vehicle among the selected plurality of delivery vehicles. Calculating a third expected arrival time to a delivery destination passing the new delivery destination among delivery addresses pre-assigned to a second delivery vehicle among the selected plurality of delivery vehicles; Calculating a fifth expected arrival time based on the departure point and destination of a new shipping destination, calculating a first expected arrival time in consideration of the third expected arrival time and the fifth expected arrival time, and the fourth expected arrival time and calculating a second expected arrival time in consideration of the fifth expected arrival time.

The present invention can realize precise dispatch with maximized delivery efficiency by predicting the existing delivery route for each delivery driver and the expected arrival time for each section, and predicting the expected route, estimated route, and estimated arrival time for each vehicle when dispatching vehicles.

The present invention is a Spatial & Temporal Proximity (time, spatial Proximity) based 3D artificial intelligence based smart dispatch method can be provided.

The present invention provides an intelligent dispatch dispatch system capable of performing optimal dispatch through predicting all the driving routes of delivery drivers and calculating an accurate cost according to the case of allocating a new delivery address to each delivery driver. can

The present invention searches and predicts in real time the driving trajectory of neighboring delivery vehicles that operate in an area adjacent to a new delivery destination in an empty state of empty delivery vehicles that are not assigned a delivery location, predicts the movement path of nearby delivery vehicles in an empty state, and improves delivery efficiency. Maximized precision alignment can be realized.

1 is a diagram illustrating components of an artificial intelligence-based intelligent dispatch system according to an embodiment of the present invention.
2A to 2D are diagrams illustrating an embodiment in which an artificial intelligence-based intelligent vehicle dispatch system allocates a new delivery address according to an embodiment of the present invention.
3 and 4 are diagrams illustrating procedures of an artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention.

Specific structural or functional descriptions of the embodiments according to the concept of the present invention disclosed in this specification are only illustrated for the purpose of explaining the embodiments according to the concept of the present invention, and the embodiments according to the concept of the present invention These may be embodied in various forms and are not limited to the embodiments described herein.

Embodiments according to the concept of the present invention can apply various changes and can have various forms, so the embodiments are illustrated in the drawings and described in detail herein. However, this is not intended to limit the embodiments according to the concept of the present invention to specific disclosures, and includes modifications, equivalents, or substitutes included in the spirit and scope of the present invention.

Terms such as first or second may be used to describe various components, but the components should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another component, for example, without departing from the scope of rights according to the concept of the present invention, a first component may be named a second component, Similarly, the second component may also be referred to as the first component.

It is understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, but other elements may exist in the middle. It should be. On the other hand, when an element is referred to as “directly connected” or “directly connected” to another element, it should be understood that no other element exists in the middle. Expressions describing the relationship between components, such as "between" and "directly between" or "directly adjacent to" should be interpreted similarly.

Terms used in this specification are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as "comprise" or "have" are intended to designate that the described feature, number, step, operation, component, part, or combination thereof exists, but one or more other features or numbers, It should be understood that the presence or addition of steps, operations, components, parts, or combinations thereof is not precluded.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and unless explicitly defined in this specification, it should not be interpreted in an ideal or excessively formal meaning. don't

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, the scope of the patent application is not limited or limited by these examples. Like reference numerals in each figure indicate like elements.

1 is a diagram illustrating components of an artificial intelligence-based intelligent dispatch system according to an embodiment of the present invention.

Referring to FIG. 1 , the artificial intelligence-based intelligent vehicle dispatch system 100 according to an embodiment of the present invention includes a first delivery route search unit 110, a delivery vehicle selection unit 120, and a delivery order update unit 130. , a second delivery route search unit 140, an estimated arrival time calculation unit 150, and a new delivery address allocation unit 160.

The first delivery route search unit 110 according to an embodiment of the present invention may search for location information and a first delivery route of a plurality of nearby delivery vehicles.

For example, the first delivery route search unit 110 collects location information of a plurality of nearby delivery vehicles according to a delivery request for pre-allocated delivery destinations, and determines the plurality of nearby delivery vehicles based on the collected location information. 1 You can search for shipping routes.

The first delivery route search unit 110 according to an embodiment of the present invention determines the departure point and destination of each of a plurality of delivery vehicles in the vicinity according to the delivery request for the pre-assigned delivery locations, and determines the location determined from the map data stored in advance. You can search for origin and destination.

For example, the first delivery route may be determined according to the origin and destination of a delivery destination assigned to each of a plurality of delivery vehicles, and may indicate a route connecting the origin and destination on a map.

For example, the first delivery route may include time information required when nearby delivery vehicles for each section pass in map data stored in advance.

For example, the first delivery route corresponds to a route that consumes the shortest distance or minimum expected arrival time for handling delivery work between a departure point and a destination associated with a specific delivery site among pre-allocated delivery vehicles, respectively. can do.

For example, location information of a plurality of nearby delivery vehicles may be displayed as an item on map data.

For example, an item representing location information may be displayed as a distinguishable and identifiable image such as a motorcycle shape, a truck shape, and a dot.

For example, the first delivery route search unit 110 collects location information of a plurality of delivery vehicles in an empty state to which a delivery destination is not assigned among a plurality of delivery route search units, and based on the collected location information, A first delivery route of a plurality of nearby delivery vehicles may be searched.

For example, the first delivery route of the plurality of neighboring delivery vehicles in the searched empty state includes a driving trajectory in which the plurality of neighboring delivery vehicles in the empty state operate in an area adjacent to a new delivery destination in an empty state, and the driving trajectory is 8 km. to 10 km.

Therefore, the present invention searches and predicts in real time the driving trajectory of neighboring delivery vehicles operating in an area adjacent to a new delivery destination in an empty state of empty delivery vehicles that are not assigned a delivery location, predicts the movement path of nearby delivery vehicles in an empty state, and delivers the delivery. It is possible to implement precision allocation with maximized efficiency.

According to one embodiment of the present invention, the delivery vehicle selection unit 120 receives an additional delivery request related to a new delivery destination, and a plurality of nearby delivery vehicles are sent based on the received additional delivery request, the searched location information, and the first delivery route. Among them, a plurality of delivery vehicles passing through a delivery route close to the starting point of the new delivery location may be selected.

For example, the delivery vehicle selector 120 may select a plurality of delivery vehicles from among a plurality of delivery vehicles passing through the departure point of the new delivery location in consideration of location information on the departure and destination of the new delivery location and the first delivery route. there is.

For example, the delivery vehicle selector 120 may select a plurality of delivery vehicles passing through the departure point of a new delivery destination in the first delivery route from among a plurality of delivery vehicles in the vicinity.

According to an embodiment of the present invention, the delivery order updating unit 130 updates the delivery order of the plurality of delivery vehicles selected by considering the remaining delivery addresses and new delivery addresses of the plurality of delivery vehicles selected by the delivery vehicle selection unit 120. can do.

For example, when the first delivery route searched by the first delivery route search unit 110 is the first delivery route of a plurality of nearby delivery vehicles in an empty state, the delivery order update unit 130 determines that the remaining delivery locations do not exist. Therefore, the delivery order of the selected plurality of delivery vehicles may be updated in consideration of only new delivery.

For example, the delivery order updating unit 130 includes the starting point and destination of the new delivery location in a delivery route related to the new delivery location among the remaining delivery locations of the selected plurality of delivery vehicles, and sets the delivery order considering the delivery processing time for all delivery locations. can be updated

According to one embodiment of the present invention, the second delivery route search unit 140 determines the number of delivery vehicles selected by the delivery vehicle selection unit 120 based on the delivery order updated by the delivery order update unit 130. 2 You can search for shipping routes.

For example, when the second delivery route includes the starting point and destination of the new delivery location in the delivery route related to the new delivery location among the remaining delivery locations of the selected plurality of delivery vehicles, considering the delivery processing time for all delivery locations, delivery processing is performed. The delivery route with the least amount of time may be included.

For example, the second delivery route search unit 140 searches for a first route via a new delivery location of the first delivery vehicle among the selected plurality of delivery vehicles, and searches for a second delivery vehicle among the selected plurality of delivery vehicles. It is possible to search for a second transit route that uses a new delivery destination as a stopover.

For example, the first transit route and the second transit route may include both a departure point and a destination of a new delivery location.

According to one embodiment of the present invention, the estimated time of arrival calculator 150 may calculate a plurality of estimated times of arrival for a new delivery destination based on the second delivery route.

For example, the estimated time of arrival calculation unit 150 calculates a first estimated time of arrival at a new delivery destination of a first delivery vehicle among a plurality of selected delivery vehicles, and a second delivery vehicle among a plurality of selected delivery vehicles. It is possible to calculate the second estimated arrival time of the new delivery destination as a stopover.

According to an embodiment of the present invention, the estimated time of arrival calculation unit 150 may calculate a first estimated time of arrival for a first via route and a second estimated time of arrival for a second via route.

For example, the estimated time of arrival calculation unit 150 calculates a third estimated time of arrival to a delivery destination that passes a new delivery location among delivery addresses pre-assigned to a first delivery vehicle among the selected plurality of delivery vehicles, and calculates a third estimated time of arrival for the selected plurality of delivery vehicles. A fourth expected arrival time to a delivery destination passing a new delivery destination among delivery addresses pre-allocated to a second delivery vehicle among vehicles may be calculated.

In addition, the expected arrival time calculation unit 150 calculates a fifth expected arrival time based on the departure point and destination of the new shipping destination, and calculates a first expected arrival time by considering the third expected arrival time and the fifth expected arrival time, , the second expected arrival time may be calculated in consideration of the fourth expected arrival time and the fifth expected arrival time.

That is, the estimated time of arrival calculation unit 150 calculates the estimated time of arrival related to the delivery destination previously allocated to the selected plurality of delivery vehicles, and analyzes the estimated time of arrival, which is the travel time between the departure point and the destination of the new delivery location, together to determine the first and a second estimated time of arrival may be calculated.

Therefore, the present invention can realize precise dispatch with maximized delivery efficiency by predicting the existing delivery route for each delivery driver and the expected arrival time for each section, and predicting the expected route, estimated route, and estimated arrival time for each vehicle when dispatching vehicles. there is.

According to an embodiment of the present invention, the new delivery address allocator 160 compares a plurality of calculated arrival times and allocates a new delivery address to any one delivery vehicle among a plurality of selected delivery vehicles.

For example, the new delivery address allocator 160 may allocate a new delivery address to a delivery vehicle corresponding to an estimated arrival time that consumes relatively less time between the first estimated arrival time and the second estimated arrival time.

For example, the new delivery address allocator 160 assigns a new delivery destination to any one of the first delivery vehicle and the second delivery vehicle corresponding to any one of the first and second expected arrival times. can be assigned.

For example, when the first expected arrival time is relatively small between the first expected arrival time and the second expected arrival time, the new delivery address allocator 160 sends the first delivery vehicle corresponding to the first expected arrival time to the new delivery location. can be assigned.

Therefore, the present invention predicts the path of all drivers and the accurate Estimated Time Arrival (ETA) for each section, and dynamically recognizes the location and delivery status according to the change in time. . Spatial Proximity) based 3D artificial intelligence based smart dispatch method can be provided.

According to one embodiment of the present invention, the artificial intelligence-based intelligent vehicle dispatch system 100 includes a memory, a display, and a processor.

For example, the memory stores data retrieved by the first delivery route search unit 110, stores data related to a plurality of delivery vehicles selected by the delivery vehicle selection unit 120, and the delivery order update unit 130 It may be controlled by the processor to store data updated by and store data related to the second delivery route searched by the second delivery route search unit 140 .

In addition, the memory stores data on the estimated arrival times calculated by the estimated time of arrival calculator 150 and stores data on delivery vehicles related to the new delivery address allocated by the new delivery address allocator 160. can be controlled by

According to one embodiment of the present invention, the display may be controlled by a processor to display a first delivery route, a second delivery route, an estimated time of arrival, location information of a plurality of delivery vehicles, etc. using data stored in a memory. .

According to one embodiment of the present invention, the processor includes a first delivery route search unit 110, a delivery vehicle selection unit 120, a delivery order update unit 130, a second delivery route search unit 140, and an estimated time of arrival calculation. Operations of the unit 150 and the new delivery address allocating unit 160 may be controlled.

Also, the processor may control an operation of storing data in or retrieving data from the memory and displaying an image related to the data stored in the memory.

In addition, the processor includes a first delivery route search unit 110, a delivery vehicle selection unit 120, a delivery order update unit 130, Operations of the second delivery route search unit 140, the estimated time of arrival calculation unit 150, and the new delivery destination allocation unit 160 may be controlled.

2A to 2D are diagrams illustrating an embodiment in which an artificial intelligence-based intelligent vehicle dispatch system allocates a new delivery address according to an embodiment of the present invention.

2A illustrates a configuration in which an artificial intelligence-based intelligent dispatch system according to an embodiment of the present invention calculates and displays an estimated arrival time according to a first delivery route while searching for a first delivery route of a plurality of nearby delivery vehicles. do.

Referring to FIG. 2A , the map 200 shows the shortest distance for the first delivery vehicle 201 and the second delivery vehicle 202 to handle delivery work to the first destination 203 and the second destination 204. can be displayed

In addition, the map 200 calculates and displays the time for the first delivery vehicle 201 to process delivery to the first destination 203 as 33 minutes, and the second delivery vehicle 202 displays the second destination 204 ), the time to process delivery can be calculated and displayed as 35 minutes.

For example, the time to process delivery may include an estimated time of arrival.

That is, the artificial intelligence-based intelligent dispatch system may control the display to display the map 200 .

2B shows a configuration in which an artificial intelligence-based intelligent dispatch system according to an embodiment of the present invention receives an additional new delivery address, calculates and displays a delivery route and estimated arrival time between the departure point and the destination of the additionally received new delivery address. foreshadow

Referring to FIG. 2B , the map 210 displays current location information of the first delivery vehicle 211 and the second delivery vehicle 212, and moves the shortest distance between the departure point 213 and the destination 214 of the new delivery location. The route is analyzed and displayed, and the estimated arrival time according to the displayed shortest travel route is calculated and displayed.

For example, an artificial intelligence-based intelligent dispatch system searches for the shortest travel path between the origin 213 and destination 214 of a new delivery destination, calculates the required time according to the searched shortest travel path as 15 minutes, and displays the result. can control.

That is, the artificial intelligence-based intelligent dispatch system may control the display to display the map 210 .

2C shows a second delivery route and a second delivery route corresponding to the case where the artificial intelligence-based intelligent dispatch system according to an embodiment of the present invention completes delivery to an existing delivery location by way of a first delivery vehicle via a new delivery location. A configuration for calculating and displaying an estimated time of arrival according to is exemplified.

Referring to FIG. 2C , the map 220 shows that the first delivery vehicle 221 departs from the current location, receives a delivery target product via the starting point 222 of a new delivery location, and transfers the received delivery product to the destination of the new delivery location. After delivery to 223, when delivery to the destination 224 of the previously assigned delivery destination is completed, the searched second delivery route and the calculated expected arrival time are displayed.

For example, the first delivery vehicle 221 may visit the destination 223 of a new delivery destination and the destination 224 of a pre-assigned delivery destination by changing the order of visiting them.

For example, the artificial intelligence-based intelligent dispatch system calculates the time for the first delivery vehicle 221 to arrive at the departure point 222 of the new destination as 16 minutes, and the destination 223 of the new destination The display can be controlled to display on the map 220 by calculating the arrival time by moving to 18 minutes and calculating the arrival time to the destination 224 of the final destination, which is the delivery destination, by 1 hour and 1 minute.

For example, the time at which the first delivery vehicle 221 moves and arrives may correspond to the expected arrival time.

That is, the artificial intelligence-based intelligent dispatch system may control the display to display the map 220 .

2D shows a second delivery route and a second delivery route corresponding to the case where the artificial intelligence-based intelligent dispatch system according to an embodiment of the present invention completes delivery to an existing delivery location by way of a second delivery vehicle via a new delivery location. A configuration for calculating and displaying an estimated time of arrival according to is exemplified.

Referring to FIG. 2D , the map 220 shows that the second delivery vehicle 231 departs from the current location, receives a delivery target product via the starting point 232 of a new delivery location, and transfers the received delivery product to the destination of the new delivery location. After delivery to 233, when delivery to the destination 234 of the previously assigned delivery destination is completed, the searched second delivery route and the calculated estimated arrival time are displayed.

For example, the second delivery vehicle 231 may visit the destination 233 of the new delivery destination and the destination 234 of the pre-assigned delivery destination by changing the order of visiting them.

For example, the artificial intelligence-based intelligent dispatch system calculates the time for the second delivery vehicle 231 to arrive at the new delivery destination 232 as 24 minutes, and the departure point 232 to the new destination 233 The display can be controlled to display on the map 230 by calculating the arrival time by moving to 15 minutes and calculating the arrival time to the destination 234 of the final destination, which is the delivery destination, by 47 minutes.

For example, the time at which the second delivery vehicle 231 moves and arrives may correspond to the expected arrival time.

That is, the artificial intelligence-based intelligent dispatch system may control the display to display the map 230 .

Comparing the estimated arrival time of the first delivery vehicle 221 in FIG. 2C and the second delivery vehicle 231 in FIG. The system may determine the second delivery vehicle 231 as an optimal delivery vehicle for allocating a new delivery location and allocate a new delivery location.

For example, an artificial intelligence-based intelligent dispatch system analyzes and analyzes a delivery route through a new delivery destination of a first delivery vehicle and a second delivery vehicle that perform actual delivery, rather than conventional point or location-based dispatch. A new delivery location may be allocated to the first delivery vehicle or the second delivery vehicle by comparing the estimated arrival time corresponding to the delivery completion time of the first delivery vehicle and the second delivery vehicle according to the determined delivery route.

3 and 4 are diagrams illustrating procedures of an artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention.

Referring to FIG. 3 , in step 301, the artificial intelligence-based intelligent dispatch method searches for a first delivery route.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention provides location information and first delivery of a plurality of nearby delivery vehicles based on departure points and destinations related to delivery destinations pre-assigned to a plurality of nearby delivery vehicles. Searching for a route or collecting location information of a plurality of nearby delivery vehicles in an empty state to which a delivery destination is not assigned among a plurality of nearby delivery vehicles, and first delivering the plurality of surrounding delivery vehicles in an empty state based on the collected location information path can be searched.

In step 302, the artificial intelligence-based intelligent dispatch method selects a plurality of vehicles based on the first delivery route.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention receives an additional delivery request related to a new delivery destination, and a plurality of nearby deliveries based on the received additional delivery request, the searched location information, and the first delivery route. Among the vehicles, a plurality of delivery vehicles passing through a delivery route close to the starting point of the new delivery location may be selected.

In step 303, the artificial intelligence-based intelligent dispatch method updates the delivery order of the selected plurality of vehicles.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention updates the delivery order of the selected plurality of delivery vehicles in consideration of remaining delivery addresses and new delivery addresses of the selected plurality of delivery vehicles.

In step 304, the artificial intelligence-based intelligent dispatch method searches for a second delivery route based on the updated delivery order.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention searches for a second delivery route based on a delivery order in which a plurality of selected delivery vehicles can move in the shortest distance when passing through a new delivery location. do.

In step 305, the artificial intelligence-based intelligent dispatch method calculates a plurality of estimated arrival times based on the second delivery route.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention calculates a first expected arrival time at a new delivery destination of a first delivery vehicle among a plurality of selected delivery vehicles, and calculates a first expected arrival time as a stopover, and Among them, a second expected arrival time for a new delivery destination of the second delivery vehicle as a stopover may be calculated.

In step 306, the artificial intelligence-based intelligent dispatch method compares a plurality of estimated arrival times and allocates a new delivery destination to any one delivery vehicle.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention may allocate a new delivery address to a delivery vehicle corresponding to a relatively small time between the first expected arrival time and the second expected arrival time.

Therefore, the present invention can realize precise dispatch with maximized delivery efficiency by predicting the existing delivery route for each delivery driver and the expected arrival time for each section, and predicting the expected route, estimated route, and estimated arrival time for each vehicle when dispatching vehicles. there is.

Referring to FIG. 4 , in step 401, the artificial intelligence-based intelligent dispatch method adds a new delivery destination.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention receives an additional delivery request for a new destination and adds the new destination to the delivery target list based on the received additional delivery request.

In step 402, the artificial intelligence-based intelligent dispatching method determines the location information of the departure point and destination.

That is, in the artificial intelligence-based intelligent vehicle dispatch method according to an embodiment of the present invention, location information of a departure point and a destination of a new delivery location is retrieved from map data stored in a memory.

In step 403, the artificial intelligence-based intelligent dispatch method searches for location information of nearby delivery vehicles and a first delivery route.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention searches the data of the delivery vehicles stored in the memory, and based on the searched data, the location of the delivery vehicles that handle delivery work around the departure point of the new delivery destination. Information is searched, and a first delivery route is searched according to the locations of nearby delivery vehicles.

For example, location information of nearby delivery vehicles may correspond to current location information of nearby delivery vehicles.

In step 404, the artificial intelligence-based intelligent dispatch method selects delivery vehicles having routes close to the departure point of the new delivery destination.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention selects a plurality of delivery vehicles that pass through the departure point of a new delivery destination or pass to a nearby location.

In step 405, the artificial intelligence-based intelligent dispatch method rearranges the delivery order considering the location information of the remaining delivery destinations and new delivery destinations of the selected delivery vehicles.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention updates the delivery order considering the destination of the delivery destination pre-allocated to the selected plurality of delivery vehicles and the starting point and destination of the new delivery destination.

In step 406, the artificial intelligence-based intelligent dispatch method searches for a second delivery route in the sorted delivery order of the selected delivery vehicles.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention searches for a second delivery route considering the destination of a pre-assigned delivery location and the starting point and destination of a new delivery location.

In step 407, the artificial intelligence-based intelligent dispatch method calculates and compares estimated arrival times according to the searched second delivery route.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention calculates the expected arrival time for a plurality of delivery vehicles when the delivery vehicle moves along the second delivery route, and calculates the plurality of calculated arrival times. to determine the minimum estimated time of arrival.

In step 408, the artificial intelligence-based intelligent dispatch method determines a delivery vehicle that guarantees the minimum expected arrival time and provides it as recommended information.

That is, the artificial intelligence-based intelligent dispatch method according to an embodiment of the present invention selects a delivery vehicle corresponding to the minimum time among a plurality of scheduled arrival times, and displays the selected delivery vehicle as recommendation information on the display. You can control it.

In step 409, the artificial intelligence-based intelligent dispatch method checks whether a new delivery address is assigned.

That is, in an artificial intelligence-based intelligent dispatch method according to another embodiment of the present invention, when recommendation information is adopted and a new delivery destination is allocated to a recommended delivery vehicle, the corresponding procedure is terminated and a new delivery location is allocated to the recommended delivery vehicle. If not, it returns to step 403.

Therefore, the present invention can provide an intelligent dispatch method capable of performing optimal dispatch through predicting all the driving routes of delivery drivers and accurately calculating costs when allocating a new delivery address to each delivery driver. there is.

The devices described above may be implemented as hardware components, software components, and/or a combination of hardware components and software components. For example, devices and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It may be implemented using one or more general purpose or special purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A processing device may run an operating system (OS) and one or more software applications running on the operating system. A processing device may also access, store, manipulate, process, and generate data in response to execution of software. For convenience of understanding, there are cases in which one processing device is used, but those skilled in the art will understand that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that it can include. For example, a processing device may include a plurality of processors or a processor and a controller. Other processing configurations are also possible, such as parallel processors.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. Program commands recorded on the medium may be specially designed and configured for the embodiment or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

Software may include a computer program, code, instructions, or a combination of one or more of the foregoing, which configures a processing device to operate as desired or processes independently or collectively. You can command the device. Software and/or data may be any tangible machine, component, physical device, virtual equipment, computer storage medium or device, intended to be interpreted by or provide instructions or data to a processing device. , or may be permanently or temporarily embodied in a transmitted signal wave. Software may be distributed on networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer readable media.

As described above, although the embodiments have been described with limited drawings, those skilled in the art can make various modifications and variations from the above description. For example, the described techniques may be performed in an order different from the method described, and/or components of the described system, structure, device, circuit, etc. may be combined or combined in a different form than the method described, or other components may be used. Or even if it is replaced or substituted by equivalents, appropriate results can be achieved.

Therefore, other implementations, other embodiments, and equivalents of the claims are within the scope of the following claims.

100: AI-based intelligent dispatch system
110: first delivery route search unit 120: delivery vehicle selection unit
130: delivery order update unit 140: second delivery route search unit
150: Estimated time of arrival calculation unit 160: New delivery address allocation unit

Claims (5)

Location information of a plurality of nearby delivery vehicles and location information of a plurality of nearby delivery vehicles in an empty state to which delivery destinations are not assigned among the plurality of nearby delivery vehicles are collected, and based on the collected location information, the plurality of nearby delivery vehicles are collected. a first delivery route search unit for searching for a first delivery route for the vehicles and the plurality of surrounding delivery vehicles in the empty state;
An additional delivery request related to a new delivery location is received, and based on the received additional delivery request, location information on the departure and destination of the new delivery location, the searched location information and the first delivery route, among the plurality of delivery vehicles in the surrounding area. a delivery vehicle selection unit that selects a plurality of delivery vehicles passing through a delivery route close to the starting point of the new delivery location;
The remaining delivery destinations of the selected plurality of delivery vehicles and the starting point and destination of the new delivery location are considered, and in the case of the first delivery route for the plurality of neighboring delivery vehicles in the empty state, the new delivery location is first considered and the selected a delivery order update unit for updating a delivery order of a plurality of delivery vehicles;
Based on the updated delivery order, a first route through which the new delivery location of the first delivery vehicle among the selected delivery vehicles is searched is searched, and the second delivery vehicle among the selected plurality of delivery vehicles is searched for. a second delivery route search unit for searching for a second delivery route by searching for a second route via a new delivery location;
an estimated arrival time calculation unit calculating a plurality of estimated arrival times for the new destination based on the searched second delivery route; and
And a new delivery address allocator for allocating the new delivery address to any one delivery vehicle among the plurality of selected delivery vehicles by comparing the calculated plurality of estimated arrival times,
The estimated time of arrival calculation unit calculates a first estimated time of arrival for the first via route, and calculates a second estimated time of arrival for the second via route, wherein the first delivery of the selected plurality of delivery vehicles is performed. A third expected arrival time to a delivery destination passing the new delivery destination among delivery addresses pre-allocated to vehicles is calculated, and a delivery address passing the new delivery destination among delivery addresses pre-assigned to a second delivery vehicle among the selected plurality of delivery vehicles. calculates a fourth expected arrival time to, calculates a fifth expected arrival time based on the departure point and destination of the new destination, and considers the third expected arrival time and the fifth expected arrival time; Time is calculated, and the second expected arrival time is calculated in consideration of the fourth expected arrival time and the fifth expected arrival time, and thus the departure point and destination of the new delivery location in the first and second route. The first expected arrival time and the second expected arrival time are calculated by analyzing the travel route and travel time together,
The new delivery destination allocator may send any one of the first delivery vehicle and the second delivery vehicle corresponding to a relatively smaller expected arrival time between the first estimated arrival time and the second estimated arrival time to the new delivery location. to assign
AI-based intelligent dispatch system. According to claim 1,
The first delivery route search unit collects location information of the plurality of nearby delivery vehicles according to a delivery request for pre-assigned delivery destinations, and first delivers the plurality of nearby delivery vehicles based on the collected location information. searching for a route
AI-based intelligent dispatch system. According to claim 1,
The first delivery route search unit determines the departure point and destination of each of the plurality of nearby delivery vehicles according to a delivery request for pre-assigned delivery locations, and searches the determined departure point and destination from pre-stored map data
AI-based intelligent dispatch system. According to claim 1,
The first delivery route of the plurality of nearby delivery vehicles in the empty state includes a travel trajectory in which the plurality of nearby delivery vehicles in the empty state travels in an area adjacent to the new delivery destination in the empty state
AI-based intelligent dispatch system. Location information of a plurality of nearby delivery vehicles and location information of a plurality of nearby delivery vehicles in an empty state to which delivery destinations are not assigned among the plurality of nearby delivery vehicles are collected, and based on the collected location information, the plurality of nearby delivery vehicles are collected. Searching for a first delivery route for vehicles and a plurality of delivery vehicles in the empty state;
The delivery vehicle selection unit receives an additional delivery request related to a new delivery destination, and the plurality of delivery vehicles are configured based on the received additional delivery request, location information about the departure and destination of the new delivery location, the searched location information, and the first delivery route. selecting a plurality of delivery vehicles passing a delivery route close to the departure point of the new delivery destination from among delivery vehicles in the vicinity of the delivery destination;
In the delivery order update unit, the remaining delivery addresses of the selected plurality of delivery vehicles and the starting point and destination of the new delivery location are considered, and in the case of the first delivery route for the plurality of neighboring delivery vehicles in the empty state, the new delivery location Updating the delivery order of the selected plurality of delivery vehicles in consideration of first;
A second delivery route search unit searches for a first route through which the new delivery location of the first delivery vehicle is used as a stopover among the selected plurality of delivery vehicles based on the updated delivery order, and the selected plurality of delivery vehicles Searching for a second delivery route by searching for a second route through which the new delivery location of the second delivery vehicle is used as a stopover;
calculating a plurality of expected arrival times for the new delivery destination based on the searched second delivery route by an estimated time of arrival calculation unit; and
In a new delivery address allocating unit, comparing the calculated plurality of estimated arrival times and allocating the new delivery address to one of the selected delivery vehicles,
Calculating a plurality of estimated arrival times for the new destination based on the searched second delivery route includes:
calculating a third expected arrival time to a delivery destination passing the new delivery address among delivery addresses pre-allocated to a first delivery vehicle among the selected plurality of delivery vehicles;
calculating a fourth expected arrival time to a delivery destination passing the new delivery address among delivery addresses pre-allocated to a second delivery vehicle among the selected plurality of delivery vehicles;
Calculating a fifth estimated time of arrival based on the origin and destination of the new delivery destination;
In consideration of the third estimated time of arrival and the fifth estimated time of arrival, a movement path and travel time between the departure point and the destination of the new delivery location in the first via route are analyzed together, and the first route for the first via route is analyzed. Calculating an estimated time of arrival; and
In consideration of the fourth estimated time of arrival and the fifth estimated time of arrival, a movement route and travel time between the departure point and destination of the new delivery location in the first route are analyzed together, and the second route for the second route is analyzed. Comprising the step of calculating the estimated time of arrival,
The step of comparing the calculated plurality of expected arrival times and allocating the new delivery address to any one delivery vehicle among the selected plurality of delivery vehicles,
Allocating the new delivery location to any one of the first delivery vehicle and the second delivery vehicle corresponding to a relatively smaller expected arrival time between the first estimated arrival time and the second estimated arrival time doing
An artificial intelligence-based intelligent dispatch method.

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