KR102349480B1 - System of allocatio of cars for food delivery rider based on moving lines - Google Patents

Abstract

A dispatching system based on a movement route of a food delivery rider according to the present invention comprises: a rider DB for storing rider information for a plurality of riders delivering food; an order input module for receiving order information including a delivery item, a merchant name, a merchant location, and a delivery location from a merchant; a filtering module for identifying current location information of the rider and identifying the order information in which the merchant location is located within a preset dispatch distance from the current location information; and a delivery execution module which provides the identified order information to the rider, selects at least one of the order information provided from the rider, and executes delivery. The present invention can maximize the efficiency of duplicate delivery.

Description

Dispatching system based on the movement of food delivery riders

The present invention relates to a dispatch system based on the movement line of food delivery riders, and in more detail, by identifying the current location of the rider in progress of delivery, and filtering only delivery calls to restaurants located close to the current location, It relates to a delivery system based on the movement of food delivery riders, which has improved delivery efficiency by providing it.

Recently, as the number of single-person households increases due to the deepening of individualism and aging, a market for delivery agencies that can easily order and order delivery is emerging.

Delivery agencies are developing rapidly in large cities in Korea, and refer to the ‘delivery brokerage service’ business that replaces the delivery service of restaurants and pays the delivery person by charging a monthly membership fee and delivery fee from the seller.

With the development of the food service industry such as small business owners and small franchises, it is necessary to use an agency rather than hiring a delivery person belonging to the restaurant according to the sales and expansion of the sales area for restaurants that did not provide delivery services. It is gaining popularity because it reduces the cost of delivery and frees the delivery man from liability for accidents.

At this time, Korean Patent No. 10-1843099 (title of invention: delivery agent relay operation system using network and delivery agent relay operation method using network network) is registered in relation to delivery agent relay technology.

The prior art is a relay operation system that relays and operates a delivery agency between customers, product sales affiliates, delivery relay agents, delivery drivers, and a remote central server through a network, comprising: a delivery relay operation central server; a POS terminal device provided in each delivery request affiliate store registered in the delivery relay operation central server; a delivery relay agent terminal device provided at the delivery agent agency for each area registered in the delivery relay operation central server and exchanges delivery agent information from the delivery relay operation central server and the POS terminal device; The delivery relay operation is interlocked with the central server, the delivery driver application provided in the delivery driver terminal device; and a customer application interlocked with the delivery relay operation central server and provided in the customer's terminal device, wherein the delivery relay operation central server receives delivery request information along with delivery order information from the POS terminal device. A terminal device information processing unit, an agency information processing unit that receives the processing status of the delivery agency for each area from the delivery relay agency terminal device, and a customer information processing unit that provides affiliate store information and delivery progress information to the customer application, and a delivery machine information processing unit for providing a delivery request and delivery order information of a merchant to the delivery machine application, wherein the POS terminal device information processing unit communicates with the POS terminal device to provide merchant information, customer information, and order products. It is made to receive information, sales information, and whether or not information is collected, and the agency information processing unit allocates and designates unique ID information for each delivery driver and registers it, and communicates with the terminal device of the delivery agency agency for each area to communicate with the delivery driver information and delivery agency information and statistical information are exchanged in real time, and the customer information processing unit receives customer location information including customer location and contact information from the POS terminal device and stores it in a database, and the delivery location from the delivery driver terminal device is provided in real time, and information on the expected delivery arrival time and delivery progress and the unique ID information given to the delivery driver are delivered to the customer's application, and the delivery driver information processing unit receives from the terminal device of the delivery agency for each area. Stored merchant information, order information, customer information, fee information, and delivery completion information in a database, the POS terminal device includes a product processing unit for storing sales information in the database; a reception processing unit for storing order information including delivery location information, customer contact information and product information in a database, and receiving and processing; a delivery agent request unit for processing the delivery agent request information, including the order information and information on whether or not to collect the goods, to the terminal device of the delivery relay agent; Sales purchase processing unit that automatically calculates the purchase amount and sales amount including commission and delivery agent fee according to the customer's payment method upon completion of delivery; and a delivery status check unit configured to receive the delivery status provided from the delivery relay operation central server or the delivery relay agency terminal device in real time. Management; a delivery agent reception unit receiving the delivery request information including affiliate store information, order information, customer information, and product collection information from the delivery agent request unit; A location information extraction unit for extracting and monitoring the location information of the delivery driver in real time; a matching processing unit for matching between an affiliated store and a delivery driver of an optimal distance based on the delivery request information received from the delivery agent reception unit and the location information of the delivery driver extracted from the location information extraction unit; Delivery agency order unit for transmitting the delivery request information to the delivery driver extracted from the matching processing unit to the delivery driver application; a delivery completion processing unit configured to receive delivery completion information from the delivery driver's terminal device, and to settle and manage sales information according to delivery completion; a central server interworking processing unit interlocked so that all information and processes performed in each unit are provided to the delivery relay operation central server; And when a delivery request is received by the delivery agent reception unit, the delivery request information is transmitted to a plurality of delivery driver terminal devices, and selection information indicating that a delivery driver is designated from the delivery driver application for the delivery request information is received. , and a delivery auction execution unit for designating the delivery driver as a delivery person, wherein the matching processing unit is configured to preferentially designate a delivery driver designated by the delivery auction execution unit, and the delivery agency order unit sends the delivery request information to the designated delivery driver terminal is configured to transmit to the device, and when the delivery auction execution unit does not receive the selection information for a preset time, the corresponding delivery request information is processed by the matching processing unit, and the matching processing unit is optimal for the location information of the affiliated store Match the location information of the delivery driver on the street, firstly match the delivery driver for which the delivery completion information is received from the delivery completion processing unit, and if there is no matching delivery driver, secondarily match the delivery driver waiting at the affiliated store If the delivery request information includes collection information, it is calculated whether a predetermined time has elapsed from the time of completion of delivery to the customer, and then the optimal distance between the delivery driver and the customer and the affiliated store is extracted to match the collection delivery driver, and to provide the matching collection delivery driver with collection information including the location of the customer and the location of the recovered goods and merchants, and the delivery driver application receives a delivery request from the terminal device of the delivery relay agency. A status processing unit that registers whether processing is possible, an acceptance processing unit that obtains delivery information from the delivery relay agency terminal device, outputs it on the screen, and accepts and processes delivery service, a completion processing unit that processes whether delivery is completed or not, the current location in real time A location transmitting unit for transmitting, and an interlocking processing unit interlocked to provide all information performed in each unit to the delivery relay operation central server and the delivery relay agency terminal device, wherein the customer application displays product information of each affiliated store A product display unit to say, and a product It includes an order processing unit that orders the product, and a location confirmation unit that receives and confirms the location and expected arrival time of the delivery driver for the ordered product in real time from the delivery relay operation central server, POS terminal device, or delivery relay agency terminal device, Information, product information, price information, order progress, and delivery status are provided, but in conjunction with the GPS system, the location and expected arrival time of the delivery driver are displayed on the map. It is configured to determine whether the unique ID information matches and display the determination result, and the location check unit uses a GPS system to express the location of the delivery driver on the map and provide a delivery agent relay operation system using a network network. is presenting

However, such a delivery agent relay operation system is the same as the conventional delivery agent system that simply receives calls and matches them with delivery drivers, and there is a limitation that a separate configuration to increase delivery efficiency in duplicate delivery is not included or not. .

Therefore, in order to solve the problems described above, in the system for dispatching food delivery agents, considering the movement movement of the food delivery rider, only the order information calls in the vicinity of the movement route are filtered and provided, thereby increasing the efficiency of delivery and providing prompt delivery. The need to develop a dispatch system based on the movement of food delivery riders that made it possible is emerging.

The present invention filters and provides order calls for food delivery based on the rider's movement route, so that only calls in the vicinity can be accepted when the rider accepts an additional call based on the movement route that maximizes delivery efficiency Its main purpose is to provide a single dispatch system.

Another object of the present invention is to further increase the efficiency of delivery by filtering and providing calls near the destination of the rider's current delivery, so that another delivery can be performed immediately following the end of delivery.

Another object of the present invention, based on the delivery route of the rider, the call generated from the rear of the current location based on the rider's progress direction is not provided to the rider by preventing the case of going back the way it came to improve delivery efficiency is to maximize

It is a further object of the present invention to provide an efficient route creation configuration that takes the shortest time for delivery route creation.

In order to achieve the above object, the dispatch system based on the movement line of the food delivery rider according to the present invention, the rider DB for storing rider information for a plurality of riders delivering food; an order input module for receiving order information including delivery items, merchant names, merchant locations, and delivery locations from the merchant; a filtering module for identifying the current location information of the rider and identifying order information in which the affiliated store location is located within a preset dispatch distance from the current location information; A delivery execution module that provides the identified order information to the rider, and selects at least any one of the order information provided from the rider to execute delivery; characterized in that it comprises a.

Furthermore, the filtering module includes a function of identifying a current destination, which is a delivery location of the delivery that the rider is currently performing, and filtering order information in which the affiliated store location is located within a preset dispatch distance from the current destination. do.

In addition, the system, on the basis of the map, for the order information selected from the rider, a route generating module for generating a delivery route from the affiliated store location to the delivery location; includes, the filtering module, the rider Based on the current location information of the current location information of the current location information of the merchant location of the delivery in progress, the merchant location of the merchant is located within a preset blind distance from the travel route. It is characterized in that it includes a function of blind processing the corresponding order information.

In addition, the route generation module, a location identification unit for identifying the location information of the location of the affiliated store and the delivery location based on a map, and a prediction for generating a plurality of predicted routes connecting from the location of the merchant to the delivery location A route generating unit, an expected time calculation unit for calculating the estimated required time for each expected route based on the real-time traffic situation, and a delivery route designation unit for designating the expected route having the lowest expected required time as the delivery route characterized in that

The dispatch system based on the movement line of the food delivery rider according to the present invention,

1) It is possible to maximize the efficiency of duplicate delivery by identifying the current location of the rider in the delivery process, filtering only the delivery call where the affiliate is located within the current location and the preset range, and providing it to the rider,

2) The gap between delivery and delivery can be minimized by filtering calls near the delivery destination of riders in progress and providing them to riders.

3) Creating a delivery route from the merchant location to the delivery location, based on the delivery route and the rider's current location, the call created on the route the rider has already passed is not provided to the rider, thereby increasing the efficiency of flow management. not,

4) It has the effect of enabling the calculation of the optimal delivery route by generating a delivery route by calculating a plurality of expected routes and comparing and processing the required time for each expected route.

1 is a conceptual diagram showing a schematic configuration of a system of the present invention.
Fig. 2 is a block diagram showing the overall configuration of the system of the present invention;
3 is a conceptual diagram illustrating an example of the dispatch distance based on the current location of the present invention.
Figure 4 is a conceptual diagram showing an example of the dispatch distance based on the current destination of the present invention.
5 is a conceptual diagram illustrating an example of a delivery route and a scheduled route.
6 is a conceptual diagram illustrating an example of an expected route and a delivery route.
7 is a conceptual diagram showing the dispatch distance based on the entire delivery route.
8 is a conceptual diagram illustrating an example of a comparison processing between a past delivery route and an actual driving route.
9 is a conceptual diagram illustrating an embodiment of an xy space and coordinate values.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The accompanying drawings are not drawn to scale, and like reference numbers in each drawing refer to like elements.

1 is a conceptual diagram showing a schematic configuration of a system of the present invention.

Referring to Figure 1, the rider automatic dispatch management system for food delivery of the present invention consists of an orderer (1), an affiliated store (2), a rider (3), and a central control server (4).

The orderer (1) is a person who wants to receive and use a delivery item, that is, food delivered through the food delivery of the present invention, and generally enters the delivery item and delivery location on an application or website provided for ordering food delivery to receive information about food. Request delivery. At this time, for food delivery order, the orderer (1) must be equipped with a separate terminal that can install an application for delivery order, such as a smartphone or tablet PC, or must have a desktop PC or laptop computer to access the website. is of course In addition, since an order for food delivery may be made over a wire, a food delivery order may be made by calling the affiliated store 2 through a smartphone.

The affiliated store 2 is a providing entity that cooks and provides food based on the order generated from the orderer 1, and provides food to the orderer 1 who has ordered food through the rider automatic dispatch management system of the present invention. In addition, the affiliated store 2 inputs order information including the delivery item and delivery location input from the orderer 1 to the central control server 4, which will be described later, and the name of the affiliated store and the affiliated store location. At this time, the order information input is preferably may be made through a POS device input to the affiliated store 2 or an application installed on a smartphone or tablet PC owned by the affiliated store owner.

Therefore, the affiliated store 2 of the present invention is most preferably a delivery order from the orderer 1 through a POS (point-of-sale(s)) terminal device provided in the store. , and communicates with the central control server (4) to be able to call the rider (3) to perform delivery.

Rider (3) is a subject that performs food delivery in the present invention, in other words, the rider (3) of the present invention can be said to be an abbreviation of the food delivery rider. The rider 3 serves to deliver food to the orderer 1 by receiving the delivery item from the affiliated store 2 and processing it to be delivered to the delivery location. These riders (3) communicate with the central control server (4) through a rider terminal such as a smartphone in their possession, and receive an assignment for food delivery from the central control server (4) (distribution is made) to perform delivery will do

The central control server 4 of the present invention receives order information from the above-described affiliate store 2, and dispatches the rider 3 to perform delivery for each order information so that the rider 3 executes the delivery. is the subject In addition, it can serve as a management role for order information, and performs a function of providing order information to the rider (3) by filtering only order information near the current location of the rider (3).

This central control server 4 means hardware having a CPU and a storage means in a state where the communication unit and transmission means are provided to communicate with the affiliated store terminals such as the above-described Rider terminal and the POS device provided in the affiliated store 2 . By doing so, a series of modules and specific functions thereof to be described later can be derived by software to be executed in this CPU.

Such a central control server 4 is a central processing unit (CPU) and a program that can be executed in the central processing unit on a hardware basis having a storage means such as a memory and a hard disk, that is, software is installed and the software can be executed. A series of specific configurations of such software will be described later as structural units called 'modules', 'parts', and 'interfaces'.

The central control server 4 temporarily and/or permanently stores the signal (or data) processed therein. RAM (Random Access Memory, not shown) and ROM (ROM: Read-Only Memory, not shown) city), and may include a processor. In addition, the central control server 4 may be implemented in the form of a system on chip (SoC) including at least one of a graphic processing unit, RAM, and ROM.

The processor may include one or more cores (not shown) and a graphic processing unit (not shown) and/or a connection path (eg, a bus, etc.) for transmitting and receiving signals to and from other components.

The memory may store programs (one or more instructions) for executing and controlling a module or a unit to be described later. Programs stored in the memory may be divided into a plurality of modules according to functions.

The steps of a method or algorithm described in relation to an embodiment of the present invention may be implemented directly in hardware, as a software module executed by hardware, or by a combination thereof. A software module may include random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any type of computer-readable recording medium well known in the art to which the present invention pertains.

That is, the components of the present invention may be implemented as a program (or application) to be executed in combination with a computer, which is hardware, and stored in a medium. Components of the present invention may be implemented as software programming or software components, and similarly, embodiments may include various algorithms implemented as data structures, processes, routines, or combinations of other programming constructs, including C, C++ , may be implemented in a programming or scripting language such as Java, assembler, or the like. Functional aspects may be implemented in an algorithm running on one or more processors.

The configuration of these 'modules' or 'parts' or 'interfaces' is installed and stored in the storage means of the main server (force server), and software executed via CPU and memory or hardware such as FPGA or ASIC. it means. In this case, the configuration of 'module', 'unit', and 'interface' is not limited to hardware, and may be configured to be in an addressable storage medium or may be configured to reproduce one or more processors. As an example, 'module' or 'part' or 'interface' refers to components such as software components, object-oriented software components, class components and task components, processes, functions, and properties. , procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables.

Functions provided by these 'modules' or 'units' or 'interfaces' may be combined into a smaller number of components and 'units' or 'modules' or additional components and 'units' or 'modules' can be further separated.

Hereinafter, a detailed configuration and function thereof will be described based on such a macroscopic configuration.

2 is a block diagram showing the overall configuration of the system of the present invention.

Referring to FIG. 2 , the dispatch system based on the movement line of the food delivery rider of the present invention is a rider DB 100 , an order input module 200 , a filtering module 300 , and a delivery execution module 400 . It is characterized in that it includes.

The rider DB 100 performs a function of storing rider information about the rider 3 who performs delivery, where the rider information means the rider 3's name, age, gender, and the rider 3 is delivered. It includes the type of transportation used for the service (types and models of general vehicles, motorcycles, bicycles, etc.), delivery history, available working hours and days, and delivery areas (province/city/gun/gu/eup/myeon). Therefore, it can be said that the information on the individual rider (3) is integrated as rider information and made into a database as the rider DB (100).

The order input module 200 serves to receive order information through the POS terminal provided in the affiliated store 2 , preferably the affiliated store 2 . At this time, the order information refers to the delivery item that is the name of the food to be delivered as described above, the name of the affiliated store that is the name of the affiliated store (2), the position of the affiliated store that is the address of the affiliated store (2), and received input from the orderer (1). The shipping address, which is the shipping address, is included.

In other words, the affiliated store 2 receives an order for food delivery from the orderer 1, generates order information for the received order, and transmits it to the central control server 4, preferably the order input module 200. You will be entering your order information into the system.

3 is a conceptual diagram illustrating an example of the dispatch distance based on the current location of the present invention.

Referring to FIG. 3 together with FIG. 2 described above, the filtering module 300 determines the current location information that is the current location of the rider 3 while driving, and the current location information of the rider 3 among the input order information. It performs the function of filtering and identifying only the location information in the vicinity.

Here, as in the example of FIG. 3 , the filtering means identifying only order information in which the affiliated store location is within the preset dispatch distance range from the current location information of the rider 3 among the input order information.

Here, the dispatch distance may be designated by a system administrator, and for example, may be set to a radius of 100 m, a radius of 200 m, a radius of 500 m, a radius of 1 km, and the like. In addition, the current location information of the rider 3 can be grasped by checking the current location information of the rider terminal through the rider terminal possessed by the rider (3).

Therefore, when the rider (3) is not in delivery, that is, in a waiting state for delivery, all generated order information can be provided to the rider (3), but if the rider (3) is performing delivery That is, when moving to a destination by determining only the order information near the current location information of the rider 3 facing the destination, and providing it to the rider 3 through the delivery execution module 400 to be described later, the rider 3 It is possible to process multiple food delivery at the same time, but it is possible to increase the efficiency of delivery by checking only order information located in a short distance from the current location and performing additional delivery.

The delivery execution module 400 provides only order information that is filtered through the filtering module 300 and identified, that is, order information located within a preset dispatch distance range from the current location information of the rider 3 to the rider 3, At least any one of the provided order information is selected from the rider 3 and performs a function of executing delivery by instructing the rider 3 to deliver the selected order information.

Therefore, in the delivery execution module 400, the filtered order information is provided to the rider 3 through the rider terminal possessed by the rider 3, and the rider 3 is the real person among the provided plurality of order information. You can select the order information you want to perform. After that, the rider 3 is assigned on the system for the selected order information, the rider 3 is notified that the actual delivery has been made, and the delivery is executed by instructing the rider 3 to perform the delivery. Here, the provision of order information, the selection of order information, and the instruction to perform delivery will preferably be made through the rider terminal possessed by the rider (3).

Here, the delivery execution module 400, when the rider 3 is not in progress, that is, in a waiting state that does not deliver any order information, sends the entire order information, not the filtered order information, to the rider 3 Of course, it is also possible to provide. Alternatively, to the rider (3) who is not in the process of delivery, based on the current location information of the rider (3), only order information where the franchise location is located near the rider (3) is provided to increase the delivery convenience of the rider (3) to enable faster delivery. may be

Through the dispatch system based on such a moving line, the current location of the rider 3 who actually performs the delivery is identified, and only the order information that is located near the current location and the merchant location is filtered so that the rider 3 can deliver. By making it possible to do so, it can make delivery more efficient, allowing for faster food delivery.

4 is a conceptual diagram illustrating an example of a dispatch distance based on a current destination of the present invention.

Referring to FIG. 4 together with FIG. 2, the filtering module 300 filters only order information located within the range of the dispatch distance from the current location information based on the current location information of the rider 3 as described above. It was said to perform the function of understanding.

Further, in addition to the order information that the filtering module 300 filters and grasps is the order information located in a short distance from the current location information, the rider 3 is currently delivered to the destination, that is, the affiliate store (2) near the delivery location. Order information located in this location can be provided by further filtering.

For this purpose, the filtering module 300 is an additional function, the rider 3 is currently in progress, that is, the delivery location for the delivery being performed, that is, the destination at the current time of the rider 3, and the merchant location is near the destination. It may further include a function of identifying only the order information by filtering.

Therefore, the location of the affiliated store includes a function to filter and identify only order information located within the preset dispatch distance from the destination. and there is no limit to the scope of its designation.

In addition, the dispatch distance based on the current location information of the rider 3 and the dispatch distance based on the rider 3 destination may be the same, or the dispatch distance based on the rider 3 destination may be set to be farther than the dispatch distance based on the current location information.

In this way, by identifying only order information that is close to the current destination of the rider 3 performing the delivery and the location of the affiliated store, and providing it to the rider 3, the rider 3 can quickly access other order information after completing the delivery in progress. Delivery can be performed so that delivery efficiency can be maximized.

5 is a conceptual diagram illustrating an example of a delivery route and a scheduled route.

Referring to FIG. 5 together with FIG. 2 described above, basically, the rider 3 performs delivery along the delivery path to the location where the merchant picks up the food and the delivery location, which is the location where the orderer 1 has requested delivery. do.

At this time, in providing additional order information, the order information in which the affiliated store 2 is located at the rear (the path that has already passed) based on the path that the rider 3 has already passed, that is, the direction the rider 3 is heading, is processed blindly. In the case of order information, it is also possible not to be provided to the rider (3). To this end, the system of the present invention may further include a path generating module 500 basically.

The route generation module 500 generates a delivery route that is a route from the location of the franchise store as the origin to the delivery location as the destination for the order information selected from the rider 3, that is, the order information dispatched to the rider 3 and delivery is executed. . In this case, when creating a delivery route, it would be preferable to basically create a delivery route based on a map and real-time traffic conditions.

Here, the location of the affiliate store can be generally referred to as the starting point of delivery, and the delivery location can be referred to as the destination point of delivery. At this time, the conventional delivery route generation is basically based on a simple shortest distance, etc., but in the optimal delivery route creation of the present invention, a map is called through a conventional navigation server, etc., and based on the map, the merchant location and delivery location are In the road formed between the franchisee location and the delivery location, the optimal delivery route is created by interconnecting the trunk lines between the branch points based on the road junction (the point at which the road splits or a crosswalk is located), but at this time When connecting the junctions of roads, it is possible to create an optimal delivery route that actually takes the shortest time by reflecting the real-time traffic conditions for the trunk line of the road.

In addition, when a delivery route is created in this way, by providing it based on the rider terminal possessed by the rider (3), it is possible to enable the rider (3) to perform delivery along the optimal delivery route. Therefore, a kind of map or navigation, such as a delivery route, is provided to the rider 3 through the rider terminal.

Therefore, when a delivery route is created as in the above configuration, the rider 3 performs delivery according to the delivery route during delivery. In this case, the rider 3 is a route that has already been passed while driving according to the delivery route The driving route may also be identified. Among the delivery routes, such a running route can be grasped by grasping the current location information, which is the current location of the rider (3) performing delivery from the location of the franchise, which is the origin, among the delivery routes. It will be a driving route.

In the case of such a running route, since it is a route that has already been passed by the rider 3 , it can be said that it is a route behind the rider 3 in consideration of the route progress direction of the rider 3 . Therefore, when order information is filtered, if order information in the range of the driving route is provided, there may be a case where the rider 3 has to return to the way he came and pick up the food.

In order to prevent this, the filtering module may further include a function to determine the rider's driving path and blindly process the corresponding order information when the affiliated store location is located within the blind distance range based on the driving path. have.

In this case, blind processing will not identify the driving route located within the blind distance range among the filtered and identified order information. That is, it means that it will not be provided to the rider 3 by making it blind.

Here, the blind distance may be set as a radius based on the driving route, but preferably, as shown in the drawing, the front and rear distances are 100 m left and right, 200 m left and right, and 500 m left and right based on a point on the driving route. Rather, it is most preferably set based on the left-right distance. This is because the division of the driving route and the delivery route already reflects the forward and rearward progress, so only the left/right directions can be calculated.

In this case, there is no limitation in the setting range of the blind distance, and preferably, the blind distance may be set by a system administrator.

Through such a blind configuration, in enabling the rider 3, who is already performing delivery, to perform additional delivery based on the current location information of the rider 3, the rider 3 moves backward based on their own driving route. Delivery efficiency can be further improved by eliminating the need to go back and pick up the food to perform the delivery.

6 is a conceptual diagram illustrating an example of an expected route and a delivery route.

Referring to FIG. 6 together with FIG. 2 described above, the route generating module 500 is a detailed configuration of the location determining unit 510, the expected route generating unit 520, the expected time calculating unit 530, and the delivery route information. It may be configured to include a government 540 .

As shown in FIG. 6 , the location determining unit 510 performs a function of identifying location information of the affiliate store location and the delivery location based on the map. That is, the map is retrieved by interworking with the navigation server, and the location information of the affiliate store and the delivery location is identified by displaying the location of the affiliated store and the delivery location on the loaded map.

The predicted route generator 520 serves to calculate a plurality of predicted routes by interconnecting trunk lines from the affiliate store location to the delivery location. Here, a plurality of predicted routes are calculated at a junction, especially at a place where the road splits into several branches. If described through the example of FIG. 6 , it can be confirmed that No. 1 predicted route, No. 2 predicted route, and No. 3 predicted route are generated.

Here, the junction is indicated by a red dot in FIG. 6 , and means a point at which a road splits, a direction changes, or diverges into several branches. Accordingly, since routes may vary depending on branch points, the number of generated predicted routes may vary depending on how many branch points exist between the affiliate store location and the delivery location.

First, based on the first junction, the predicted routes ①, ② and ③ are divided, which reflects whether or not the pedestrian crosses the crosswalk. And the predicted routes ① and ② will change depending on whether or not they turn right at the next junction after passing on a straight line. Therefore, the branch points are interconnected in this way, and a plurality of predicted routes from the branch point to the location of the affiliated store and the delivery location are calculated. can

The expected time calculation unit 530 performs a function of calculating an expected required time for each expected route calculated based on real-time traffic conditions. This can be linked with the conventional navigation server to calculate the estimated required time, which is similar in configuration to the estimated required time for each route through navigation, so the detailed description will be omitted with reference to the conventional navigation function.

Delivery route designation unit 540 is to designate any one of the expected routes as the optimal delivery route based on the high and low of the expected required time, most preferably the shortest expected required time (with the shortest expected required time) It performs the function of designating a route as a delivery route.

Therefore, the optimal route that can take delivery in a short time by calculating a plurality of expected routes, calculating the estimated time required for each expected route, comparing them, and designating the route with the shortest expected required time as the delivery route can be calculated.

In addition, when delivery is executed to generate and provide a delivery route from the merchant location to the delivery location to the rider (3), some riders (3) may perform delivery according to the provided delivery route, but some riders ( In case of 3), delivery may be performed according to the preferred route instead of following the provided delivery route.

This can also be referred to as a kind of driving pattern for each rider (3). Is it a rider (3) with a pattern that follows the provided route (delivery route) well, or a rider who does not follow the delivery route by moving according to their preferred route (3) ) to determine whether In addition, if there is a preferred route, if there is a road or zone where the rider 3 frequently travels in a specific area, which zone/road is frequently used for driving may also be identified as a driving pattern.

To this end, the system of the present invention may include a driving pattern generation module 600, the driving pattern generation module 600 is a delivery route that was created in the delivery performed by a specific rider 3 in the past, and the corresponding delivery It performs a function of generating the driving pattern of the rider 3 as described above by comparing and processing the driving routes that have actually been driven.

Here, the driving pattern generation module 600 is basically, in the plurality of deliveries that the rider 3 has previously performed in the past, the past delivery route that is the delivery route that was generated in each delivery, and the past delivery route in which the corresponding past delivery route was actually created. For the order information case, the actual driving route the rider 3 traveled during delivery is compared and processed, and the driving pattern for the rider 3 is generated according to the degree of matching between the past delivery route and the actual driving route.

Therefore, basically, the driving pattern of the rider (3) is to determine the degree of agreement by comparing the past delivery route with the actual driving route. It is determined, and the lower the degree of matching, the more it can be determined as the rider 3 with a pattern that does not travel according to the delivery route.

Further, in the case of the driving pattern, the rider 3 is based on identifying the actual driving route, which is the route on which the delivery was actually performed, and comparing it with the past delivery route, so that a specific rider 3 When delivery is performed, if there is a tendency to use a specific road section a lot among a plurality of actual driving routes, it is also possible to identify this as a driving pattern.

Conversely, when a plurality of actual driving routes and past delivery routes are compared and processed, if there is a road section that is not used by the rider 3, it can also be identified as a driving pattern.

Therefore, in the case of the driving pattern, not only the degree of coincidence between the past delivery route and the actual driving route, but also whether the rider 3 prefers a specific road, which can be identified as the actual driving route, or the general delivery time of the rider 3, or whether the delivery is delayed It may also be included as a driving pattern.

7 is a conceptual diagram showing the dispatch distance based on the entire delivery route.

7, when a delivery route is created, the filtering module 300 has the widest configuration, and the delivery route is created in the delivery that the rider 3 is currently in progress, and the rider 3 proceeds with the delivery. When it is in the middle, based on the points on the map constituting the delivery route, only the order information in which the merchant locations are distributed within the preset dispatch distance range is filtered and provided so that the rider 3 can perform additional delivery. .

Here, the setting range of the dispatch distance may be set to a radius of 100 m, 200 m, 1 km, etc. as described above, or 100 m, 200, 1 km, etc. left and right based on a point included in the delivery route. it is also possible The setting of such a dispatch distance may be made by a system administrator.

Therefore, it is simply the current location of the rider (3) or the delivery that the rider (3) is currently in, that is, the delivery route is created and the delivery location of the rider (3) is the delivery location of the case within the dispatch distance based on the franchise (2). ) is filtered and provided to the rider (3) to enable additional delivery, furthermore, based on all points on the delivery route, that is, all points on the map constituting the delivery route, order information located within the dispatch distance By filtering and understanding, it is possible to provide more diverse order information to the rider (3).

Further, based on the delivery route generated for the delivery in progress, the location of the affiliated store is located within the dispatch distance range by filtering and grasping, and at the same time, the identified order information matches the driving pattern of the rider (3) If not, it is also possible to blindly process the order information.

Here, the order information that does not match the driving pattern means, for example, if a section of the delivery route created when the driving pattern is identified is a section that the rider 3 does not use, the order identified in the vicinity of the section In the case of information, it may be made in a manner that is not provided to the rider 3 by blind processing. In addition, since there is no limitation in the blind processing method for order information that does not match the driving pattern, of course, the blind processing standard can be generated in the blind processing through comparison processing with the driving pattern.

Here, as in the above description, the blind is processed so that even the filtered and identified order information is not provided to the orderer 1 when it belongs to the blind processing target. In other words, it can be said that some of the filtered and identified order information is discarded to be optimized for a specific rider (3), and the blind processed order information is not provided to the corresponding rider (3).

Therefore, through the configuration of setting the dispatch distance based on the delivery route and filtering the order information, and further processing the filtered order information and driving pattern for blind processing, among the order information where the affiliated store 2 is located near the delivery route, , it is possible to provide only those that match the driving pattern of a specific rider 3, thereby further maximizing the efficiency of delivery.

8 is a conceptual diagram illustrating an example of a comparison processing between a past delivery route and an actual driving route.

Referring to FIG. 8 , as a detailed configuration, the driving pattern generating module 600 includes a matching rate calculating unit 610 , a trunk line classifying unit 620 , a driving frequency determining unit 630 , and a driving pattern generating unit 640 . may be included.

The coincidence rate calculator 610 compares the actual driving route for the delivery with the past delivery route generated for each delivery in the plurality of deliveries performed by the specific rider 3 during the analysis period set by the system administrator. By processing, the function of calculating the coincidence rate between the past delivery route and the actual driving route is performed.

Here, the analysis period is set by the system administrator, and can be set as the past 3 days, past 1 week, past 1 month, past 6 months, past 1 year based on the present time, and there is no limit to the setting range. .

In addition, a past delivery route was created for each delivery performed in the past, and there is an actual driving route, which is a route that was actually delivered. is to calculate

Here, there is no limitation on the method of calculating the coincidence rate, but most preferably, the distance where the past delivery route and the actual driving route overlap is calculated, and the ratio of the distance where the actual driving route and the past delivery route overlap with the total distance of the past delivery route is calculated. Therefore, the ratio can be calculated as the coincidence rate.

If the total distance of the past delivery route is 1km and the distance between the actual driving route and the past delivery route is 0.6km (in the case of 400m that does not overlap based on the past delivery route, the distance from the actual driving route is driven) can be 60%.

The trunk classification unit 620 includes a plurality of actual deliveries performed by the rider 3 in each delivery case previously performed by the rider 3 during the analysis period, in the delivery cases in which the same past delivery path is generated. Analyze the driving route. That is, a road included in a plurality of actual driving routes having the same past delivery route is classified and processed into a plurality of trunk lines. Here, the classification criterion for the trunk may be a junction on the map as described above.

In other words, the road included in the actual driving route is identified, the junctions on the road are identified, the trunk lines connecting each junction are created, and the arterial lines are identified by classifying them.

Here, road identification means not only understanding the location of the road itself, but also identifying the junction where the road splits, changes direction, or diverges into several branches like a junction located on the road, and is a line connecting individual junctions. figure out the edges Therefore, the actual driving route is formed by gathering a plurality of trunk lines, connecting two junctions to each other may be a trunk line, and a road is formed by gathering at least one trunk line. Therefore, since the actual driving route is also a set of at least one trunk line, the actual driving route is classified as an trunk line.

The driving frequency determining unit 630 grasps the driving frequency for each of the plurality of trunk lines constituting the actual driving route. For example, assuming that a specific actual driving route has 4 trunks, 4 edges are identified in the corresponding actual driving route. it will be understood

Here, even if it is a different case of delivery, it is of course that delivery may have been performed through the same trunk line, and this tendency may be noticeable when a specific rider 3 has jurisdiction over a specific area or range. However, in general, in the case of riders (3), rather than performing delivery within the range of various regions, it is possible to increase the efficiency of delivery by repeatedly performing delivery within a specific narrow range, so the rider (3) is designated for each specific area and It can be said that the efficiency and validity of edge analysis are high when the edges are identified.

Furthermore, since the present invention compares deliveries generated by the same past delivery route, the analysis utility is very high because it analyzes how the rider 3 actually traveled with respect to the delivery case for which the same delivery route was indicated.

Therefore, for each trunk line, during the analysis period, the rider 3 performs delivery while driving a specific trunk line and grasps the driving frequency passed. Here, if the driving frequency for a specific trunk is low, it can be understood that the rider (3) has a pattern that the rider (3) does not use well in the case of that trunk. to be able to judge that

Here, in judging the running of an arterial line for the driving frequency, the forward and reverse directions are not discriminated (no distinction is made), and if the starting point and starting point of a specific trunk are completely passed (passing the trunk), driving on the relevant trunk is performed regardless of the direction. It is based on counting as the driving frequency by judging that it has been performed.

As an example, during the analysis period, a total of 3 deliveries were made to create 3 past delivery routes, which are called A past delivery route, B past delivery route, and C past delivery route. A past delivery path includes edges a,b,c as an example, B past delivery path includes edges a,i,f,h, and c past delivery path includes edges a,i,f,c When this is done, the driving frequency for each trunk can be grasped as the driving frequency for trunk a is 3, the driving frequency for trunk b is 1, and the driving frequency for trunk c is 2.

Furthermore, if the driving frequency for the trunk line is identified within the delivery area delivered by the corresponding rider 3 for a specific rider 3 as described above, it can also be referred to as a driving pattern of the rider 3 itself.

Accordingly, as described above, the driving pattern generator 640 generates a driving pattern for the rider 3 by reflecting not only the matching rate between the past delivery path and the actual driving path, but also the driving frequency for the trunk line.

Therefore, it is determined as a driving pattern whether the rider 3 performs actual delivery on a route that is consistent with the past delivery route, furthermore, which trunk (section) is mainly used, and which trunk (section) is not used well, It can be used for filtering or blinding of the above-described order information.

9 is a conceptual diagram illustrating an embodiment of an x-y space and coordinate values.

Referring to FIG. 9 together with FIG. 2 described above, further, the driving pattern generating module 600 may further include a target time setting unit 650 . When the target time setting unit 650 compares and processes the match rate during the analysis period, the rider 3 has a high match rate for delivery in a specific time period, or the rider 3 has a low match rate for delivery in a specific time period. , and based on this, it performs the function of determining the target time.

Further, more preferably, the target time is a time when the rider 3 ignores his/her driving pattern and drives according to the provided delivery route, which is generally at his/her own discretion, such as during rush hour. Rather than driving, it can be said that it is a time when it is judged that it is better for the rider 3 to drive along the delivery route reflecting real-time traffic conditions.

Therefore, in this case, the driving pattern of the rider 3 may be different, and preferably, it can be said that the matching rate in the driving pattern of the rider 3 increases. That is, it can be said that it is the time when the rider 3 performs delivery according to the route provided on the system. In this case, there is no need to perform blind processing, so that the amount of information required on the system can be reduced.

Therefore, it can be said that it is also important to determine such a target time point. The target time setting unit 650 has a detailed configuration, including a graph generation part 651 , a basic grasp part 652 , an additional grasp part 653 , and a target A viewpoint setting part 654 may be included.

The graph generation part 651 grasps the coincidence rate calculated for the delivery performed by the rider 3 during the analysis period, and displays the points in the xy space where the x-axis is time and the y-axis is set as the coincidence rate. It acquires coordinates and connects points to create a graph. Here, the unit of time can preferably be compared in units of one hour, and therefore, it can be said that the matching rate for the delivered deliveries is compared and processed for each time zone in which a plurality of deliveries performed in the past are made.

Therefore, by creating such a graph, we can go beyond a simple comparison of the coincidence rate between the past delivery route and the actual driving route in the past delivery, and examine the trend of the coincidence rate for each delivery time in the past delivery. to compare Therefore, with respect to past deliveries made during the analysis period, it is not based on year/month/day, but rather comparing what time the delivery orders were placed.

At this time, for time comparison for each delivery case, the x value of the delivery case, that is, the time value means the value of the time when the order information of the corresponding delivery is input. For example, if a delivery was made on May 26, 2021 at 3:26 PM, the value of x would be 15:26, and if another delivery was made on May 27, 2021 at 9:05 AM, the value of x is 09:05.

That is, in general, the standard of rush hour for delivery is to compare time regardless of year/month/day, so only time (hour/minute) is compared and processed.

The basic grasping part 652 performs a function of grasping the first inclination of the first straight line connecting the current time point and the point immediately before the current time point, that is, the first past time point immediately before the X-axis reference.

At this time, the straight lines connecting the respective coordinate values each have a slope. At this time, the straight line connecting the current time point and the previous time point becomes the first straight line, and the slope of the first straight line becomes the first slope. In this case, the first slope may be changed in real time according to a specific time point and a set time unit. Here, the current time refers to the current time of the analysis time, which also identifies the hours/minutes by limiting the year/month/day.

In other words, the time immediately preceding the current time by a preset time unit becomes the first past time, that is, for example, when the current time is 3:16 pm, the point on the graph corresponding to 15:16 and the It is to determine the slope of the first straight line connecting the points corresponding to the previous point, 14:16.

In addition, if only the time limit for minutes is identified as a unit of time, if the current time is 3:16 pm, the first straight line connecting the point on the graph corresponding to 15:00 and the point corresponding to 14 o'clock immediately before it The first slope is identified by the method of determining the slope of .

The additional grasping part 653 grasps the second slope of the second straight line connecting the point of the first past time, that is, the coordinate value of the first past time and the point of the second past time point immediately before the first past time. As a function to perform the function of performing the function, the time immediately preceding a preset time unit from the current time point is a first past time point, and a time point immediately preceding a preset time unit from the first past time point is the second past time point. In this case, the slope of the second straight line connecting the first past time point and the second past time point becomes the second slope.

The target viewpoint setting part 654 provides a function of determining whether to designate the current viewpoint as the target viewpoint by comparing the first slope and the second slope. Here, the reason for setting the target time point by comparing only the first slope and the second slope is to determine the target time point by identifying the most recent slope, and then generate a driving pattern based on this.

In other words, the target time point may be a time point at which it is determined that the coincidence rate sharply increases or decreases when the slope with the past time points is compared on the graph.

If the first slope suddenly increases compared to the second slope, it is determined that the coincidence rate increases rapidly, so it means that the rider (3) performs delivery according to the route given on the system rather than the route she wants to go in rush hour. , which means that the matching rate is also high in the driving pattern. Therefore, in this case, we focus on increasing the delivery processing speed by reducing the weight of blind processing by driving pattern and focusing on providing order information quickly on the system.

If the first slope suddenly decreases compared to the second slope, the coincidence rate is judged to decrease rapidly, which means that the time has come for the rider 3 to perform delivery according to the path he or she wants to go rather than the given path on the system. . That is, the driving pattern also means that the matching rate is low. Therefore, in this case, by increasing the weight of blind processing according to the driving pattern, it is possible to focus on providing optimized order information by focusing on filtering and providing only optimized order information to the rider 3 on the system.

Accordingly, when the configuration of whether to set the target time is added as described above, the filtering module 300 may reflect whether or not the target time is set in blind processing the order information matching the driving pattern.

That is, in the time zone corresponding to the target time, the blind processing function is turned off so that the affiliated store location grasps all order information located within the preset dispatch distance range from the delivery route of the delivery in progress by the rider 3, and at the target time In the normal time zone that does not apply, it is possible to configure whether or not blind processing is performed in conjunction with whether or not a target time is set by blind processing order information that does not match the driving pattern among the identified order information.

Therefore, in general, the target time means rush hour, so turn off the blind processing function only during rush hour or turn on the blind processing function only during rush hour to efficiently control the data processing volume on the system so that you can order quickly. By enabling information filtering and provisioning, delivery efficiency can be maximized.

Furthermore, the target time setting unit 650 includes a matrix calculation part 655 , a high value calculation part 656 , and a homogeneity value calculation part 657 . can be configured and a comparison process can be performed through it, and based on this, a homogeneity value for the gradient matrix, which is a matrix calculated for each of the first gradient and the second gradient, can be calculated.

The matrix calculation part 655 provides a function of calculating a gradient matrix for each of the first gradient and the second gradient, wherein the gradient matrix is calculated through Equation 1 below.

는 기울기행렬,

은 해당 점에 대한 좌표값,

는 좌표 정보

과 좌표값

의 직전 시점의 점을 연결한 제

직선에 대한 x 방향의 기울기,

는 좌표값

과 좌표값

의 직전 시점의 점을 연결한 제

직선에 대한 y 방향의 기울기,

는 x 방향의 기울기와 y 방향 기울기의 곱을 의미한다.

is the gradient matrix,

is the coordinate value for the point,

is the coordinate information

and coordinates

The first point connecting the points of the previous point in

slope in the x direction with respect to a straight line,

is the coordinate value

and coordinates

The first point connecting the points of the previous point in

slope in the y direction with respect to a straight line,

denotes the product of the gradient in the x-direction and the gradient in the y-direction.

In this way, the x-direction and y-direction inclinations of a line or point are respectively obtained for a specific coordinate value, and the resulting gradients are matrixed to express the product of the x-direction gradient, the y-direction gradient, and the x-direction and y-direction gradients at once.

For example, suppose that there are a total of four coordinate values constituting the graph as shown in FIG. 9, and a first straight line, a second straight line, and a third straight line are configured through the four coordinate values, respectively.

At this time, the x-direction slope of the first straight line is 3, the y-direction slope is 4, the x-direction slope of the second straight line is -5, the y direction slope is 2, and the x-direction slope of the third straight line is 6, the y direction Assume that the slope is -4.

In this case, calculating the gradient matrix

can get the value of

The eigenvalue calculation part 656 performs a function of calculating the maximum eigenvalue and the lowest eigenvalue with respect to the calculated gradient matrix. At this time, the maximum elevation value is calculated through Equation 2 below, and the lowest elevation value is calculated through Equation 3 below.

Equation 2,

Equation 3,

는 최대고윳값,

는 최저고윳값을 의미하고, m, n, l 값은 상술한 수학식 1을 통해 산출된 기울기행렬의 각각의 값을 의미한다. 즉 m값은 좌표 정보

과 좌표값

의 직전 시점의 점을 연결한 제

직선에 대한 x 방향의 기울기의 제곱의 값이며, n은 좌표값

과 좌표값

의 직전 시점의 점을 연결한 제

직선에 대한 y 방향의 기울기의 제곱을 의미하고, l은 x 방향의 기울기와 y 방향 기울기의 곱을 제곱한 값을 의미한다.here,

is the maximum eigenvalue,

denotes the lowest elevation value, and the values of m, n, and l denote respective values of the gradient matrix calculated through Equation 1 above. That is, the m value is coordinate information.

and coordinates

The first point connecting the points of the previous point in

It is the value of the square of the slope of the x-direction with respect to the straight line, and n is the coordinate value

and coordinates

The first point connecting the points of the previous point in

It means the square of the slope of the y-direction with respect to the straight line, and l means the square of the product of the slope of the x-direction and the slope of the y-direction.

That is, based on the coordinate information, the difference between the first slope and the second slope is small, and the gentler the slope change, the smaller the difference between the maximum and the lowest slope, and the larger the difference between the first slope and the second slope, the greater the slope of the slope. The more rapid the change, the wider the difference between the maximum and minimum values.

In the above-described embodiment, if the maximum and minimum values are calculated,

이므로,

Because of,

can yield the same value.

The homogeneity value calculation part 657 calculates the homogeneity value for the gradient matrix calculated on the basis of the calculated maximum and minimum values, and the homogeneity value is preferably through the following Equation 4 can be calculated.

Equation 4,

는 균질도값을 의미하며,

는 수학식 2를 통해 산출된 최대고윳값,

는 수학식 3을 기반으로 산출된 최저고윳값을 의미한다.here,

is the homogeneity value,

is the maximum eigenvalue calculated through Equation 2,

denotes the lowest peak value calculated based on Equation (3).

In this case, the greater the difference between the first slope and the second slope, the closer the homogeneity value is to 1, and the smaller the difference between the first slope and the second slope, the closer the homogeneity value is to 0. That is, the smaller the homogeneity value, the smaller the change in the frequency of game mission achievement with time is.

,

의 값이 얻어졌으므로,In the above example,

,

Since the value of is obtained,

의 값을 얻을 수 있게 된다.

can get the value of

In this way, when the comparison processing of the first gradient and the second gradient through the matrix is enabled, the target time point setting part 654 is the current time point according to the high and low values of the homogeneity values calculated for each of the first and second slopes. You can decide whether or not to set as a milestone.

That is, the greater the homogeneity, the greater the change in inclination between the first straight line and the second straight line, which means that the coincidence rate is rapidly increasing or rapidly decreasing. Therefore, in this case, it is possible to determine whether to determine the target time point, and to compare the on/off processing of the blind function through the above-described driving pattern and order information comparison processing.

As described so far, the configuration and action of the dispatch system based on the movement line of the food delivery rider according to the present invention have been expressed in the above description and drawings, but this is only an example and the spirit of the present invention is not limited to the above description and It is not limited to the drawings, and various changes and modifications are possible without departing from the technical spirit of the present invention.

1: Orderer 2: Merchant
3: Rider 4: Central control server
100: Rider DB 200: Order input module
300: filtering module 400: delivery execution module
500: path generation module 510: location determination unit
520: predicted route generation unit 530: estimated time calculation unit
540: delivery route designation unit 600: driving pattern generation module
610: coincidence rate calculation unit 620: edge classification unit
630: driving frequency determination unit 640: driving pattern generation unit
650: target time setting unit 651: graph generation part
652: basic grasp part 653: additional grasp part
654: target time setting part 655: matrix calculation part
656: high value calculation part 657: homogeneity value calculation part

Claims (9)

As a dispatch system based on the movement of food delivery riders,
Rider DB for storing rider information for a plurality of riders delivering food;
an order input module for receiving order information including delivery items, merchant names, merchant locations, and delivery locations from the merchant;
a route generating module for generating a delivery route from the affiliated store location to the delivery location for the order information selected from the rider based on the map and delivery is executed;
In the delivery performed by the rider, a driving pattern for generating a driving pattern for the rider according to the degree of coincidence between the past delivery route, which is a delivery route created in the past, and the actual driving route, which is a route where the rider actually performed delivery generation module;
Identify the current location information of the rider, and determine the order information in which the affiliated store location is located within a preset dispatch distance range from the delivery route of the delivery in progress by the rider, but order information that does not match the driving pattern is processed blindly a filtering module including a function;
A delivery execution module that provides the identified order information to the rider and selects at least any one of the order information provided from the rider to execute delivery; including,
The driving pattern generation module,
A coincidence rate calculation unit for calculating a coincidence rate between each past delivery route and the actual driving route generated for the delivery performed by the rider during the analysis period;
An arterial classification unit for classifying roads included in a plurality of the actual driving routes generated for the same past delivery route into a plurality of trunks based on a junction on the map; and
During the analysis period, a driving frequency determining unit for figuring out the driving frequency for each trunk identified in the delivery previously performed by the rider;
a driving pattern generator for generating the rider's driving pattern based on the matching rate and the driving frequency for the trunk line;
Determine the matching rate calculated for the delivery performed by the rider during the analysis period, and display the points in the xy space where the x-axis is time and the y-axis is set as the coincidence rate to obtain the coordinate values for the points and connect the points a graph generation part that creates a graph by
A basic grasping part for grasping a first inclination with respect to a first straight line connecting a point at the current time point and a point at a first past time point immediately before the current time point;
An additional grasping part for grasping a second inclination of a second straight line connecting the point of the first past time and the point of a second past time point immediately before the first past time point;
Comprising a target time setting unit having a target time setting part for determining whether to designate the specific time point as a target time point by comparing the first slope with the second slope,
The filtering module,
According to whether the target time is set or not, order information that does not match the driving pattern includes a function of blind processing,
The target time setting unit,
A matrix calculation part for calculating a gradient matrix for each of the first gradient and the second gradient;
an eigenvalue calculation part for calculating the maximum eigenvalue and the lowest eigenvalue for the gradient matrix; and
and a homogeneity value calculation part for calculating the homogeneity value of the gradient matrix based on the maximum eigenvalue and the lowest eigenvalue,
The target time setting part is,
and determining whether to set the current time point as a target time point according to a difference between the values of the homogeneity calculated with respect to the first slope and the second slope. The method of claim 1,
The filtering module,
A dispatch system, characterized in that it includes a function of identifying a destination, which is a delivery location of the delivery being performed by the rider, and identifying order information in which the affiliated store location is located within a preset dispatch distance from the destination. The method of claim 1,
The filtering module,
Based on the origin and the generated delivery route, which is the location of the franchisee of the delivery in progress, the rider's current location information determines the pre-traveling route, which is the path the rider has passed, and the affiliated store location is determined from the pre-running route. Distributing system, characterized in that it includes a function of blind processing the corresponding order information when it is located within the set blind distance. The method of claim 1,
The path generation module,
a location locator to determine the location information of the location of the affiliated store and the delivery location based on a map;
a predicted route generating unit for generating a plurality of predicted routes connecting from the affiliated store location to the delivery location;
An estimated time calculation unit for calculating the estimated required time for each expected route based on real-time traffic conditions;
The delivery system, characterized in that it comprises a delivery route designation unit for designating the expected route with the shortest expected required time as the delivery route. The method of claim 1,
The gradient matrix is
It is calculated through the following Equation 1,
The maximum value is,
It is calculated through Equation 2 below,
The lowest value is,
It is calculated through the following Equation 3,
The homogeneity value is,
A vehicle dispatch system, characterized in that it is calculated through the following Equation (4).
Equation 1,

Equation 2,

Equation 3,

Equation 4,

(here,

is the gradient matrix,

is the coordinate value for the point,

is the coordinate information

and coordinates

The first point connecting the points of the previous point in

slope in the x direction with respect to a straight line,

is the coordinate value

and coordinates

The first point connecting the points of the previous point in

slope in the y direction with respect to a straight line,

is the product of the slope in the x direction and the slope in the y direction,

is the maximum eigenvalue,

is the lowest value,

is the homogeneity value)
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