CN114444985B

CN114444985B - Unmanned vehicle-based dynamic adjustment method and device for mobile selling route

Info

Publication number: CN114444985B
Application number: CN202210371022.3A
Authority: CN
Inventors: 李俊宁
Original assignee: Neolix Technologies Co Ltd
Current assignee: Neolix Technologies Co Ltd
Priority date: 2022-04-11
Filing date: 2022-04-11
Publication date: 2022-06-28
Anticipated expiration: 2042-04-11
Also published as: CN114444985A

Abstract

The disclosure relates to the technical field of unmanned selling, and provides a method and a device for dynamically adjusting a mobile selling route based on an unmanned vehicle. The method comprises the following steps: acquiring historical transaction geographic position information of a plurality of targeted intention users associated with the targeted unmanned vehicle; generating a purchasing intention heat distribution map according to historical transaction geographic position information; generating an initial mobile selling path according to the purchase intention heat distribution map; controlling the target unmanned vehicle to move to sell the commodity according to the initial moving selling path; if new transaction geographic position information is detected, updating the purchasing intention heat distribution map by using the new transaction geographic position information to obtain an updated purchasing intention heat distribution map; and dynamically adjusting the initial mobile selling path according to the updated purchase intention heat distribution map to obtain an updated mobile selling path. The method and the system have the advantages that the driving path flexibility of the commodity sold by the unmanned vehicle is good, the high-intention purchasing customers can be effectively locked, and the commodity selling transaction success rate is improved.

Description

Unmanned vehicle-based dynamic adjustment method and device for mobile selling route

Technical Field

The disclosure relates to the technical field of unmanned selling, in particular to a method and a device for dynamically adjusting a mobile selling path based on an unmanned vehicle.

Background

With the continuous development of internet technology, people pursue higher and higher quality of life. The unattended sales mode is one of the most attractive and favored sales modes in recent years. For example, series of high-tech products sold by nobody such as nobody vending cabinets, nobody supermarkets, nobody cars, etc. have come to the end, and the commodity purchasing channels and shopping experience of people are greatly enriched.

In the prior art, the unmanned vehicles basically sell the commodities loaded on the vehicles along the way according to the preset driving route, but the driving route of the mode is unchanged, the flexibility is poor, high-intention purchasing customers cannot be effectively locked, and the commodity selling transaction success rate is low.

Disclosure of Invention

In view of this, the embodiments of the present disclosure provide a method and an apparatus for dynamically adjusting a mobile vending path based on an unmanned vehicle, an electronic device, and a computer-readable storage medium, so as to solve the problems in the prior art that a driving path of a commodity sold by the unmanned vehicle is fixed, the flexibility is poor, a high-intention purchasing client cannot be effectively locked, and a transaction success rate of the commodity vending is low.

In a first aspect of the embodiments of the present disclosure, a method for dynamically adjusting a mobile vending path based on an unmanned vehicle is provided, including:

acquiring a plurality of target intention users associated with the target unmanned vehicle and historical transaction geographic position information of each target intention user;

generating a purchasing intention heat distribution map according to historical transaction geographic position information of a plurality of target intention users;

generating an initial mobile selling path according to the purchasing intention heat distribution map;

controlling the target unmanned vehicle to move according to the planned moving direction of the initial moving selling path so as to enable the target unmanned vehicle to move along the way to sell the commodities to be sold;

in the process that the target unmanned vehicle moves in the planned moving direction, whether newly added transaction geographic position information exists in a transaction database of the target unmanned vehicle is detected according to a preset detection step length;

if the new transaction geographic position information exists, updating the purchasing intention heat distribution map by using the new transaction geographic position information to obtain an updated purchasing intention heat distribution map;

dynamically adjusting the initial mobile selling path according to the updated purchase intention heat distribution map to obtain an updated mobile selling path;

And controlling the target unmanned vehicle to move according to the planned path direction of the updated moving selling path so as to enable the target unmanned vehicle to sell the goods to be sold along the way.

In a second aspect of the embodiments of the present disclosure, there is provided an unmanned vehicle-based mobile vending path dynamic adjustment device, including:

the information acquisition module is configured to acquire a plurality of target intention users associated with the target unmanned vehicle and historical transaction geographic position information of each target intention user;

the map generation module is configured to generate a purchasing intention heat distribution map according to historical transaction geographic position information of a plurality of target intention users;

the path generation module is configured to generate an initial mobile selling path according to the purchase intention heat distribution map;

the first control module is configured to control the target unmanned vehicle to move according to the planned moving direction of the initial moving selling path so that the target unmanned vehicle moves along the way to sell goods to be sold;

the detection module is configured to detect whether newly added transaction geographic position information exists in a transaction database of the target unmanned vehicle according to a preset detection step length in the process that the target unmanned vehicle moves and moves in the planned moving direction;

The updating module is configured to update the purchasing intention heat distribution map by using the newly added transaction geographic position information if the newly added transaction geographic position information exists, so that the updated purchasing intention heat distribution map is obtained;

the path adjusting module is configured to dynamically adjust the initial mobile selling path according to the updated purchase intention heat distribution map to obtain an updated mobile selling path;

and the second control module is configured to control the target unmanned vehicle to move according to the planned path direction of the updated moving selling path so that the target unmanned vehicle sells the goods to be sold along the way.

In a third aspect of the embodiments of the present disclosure, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program.

In a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, which stores a computer program, which when executed by a processor, implements the steps of the above-mentioned method.

Compared with the prior art, the beneficial effects of the embodiment of the disclosure at least comprise: the method comprises the steps that a plurality of target intention users related to a target unmanned vehicle and historical transaction geographic position information of each target intention user are obtained; generating a purchasing intention heat distribution map according to historical transaction geographic position information of a plurality of target intention users; generating an initial mobile selling path according to the purchasing intention heat distribution map; controlling the target unmanned vehicle to move according to the planned moving direction of the initial moving selling path so as to enable the target unmanned vehicle to move along the way to sell the commodities to be sold; in the process that the target unmanned vehicle moves according to the planned moving direction, whether newly added transaction geographic position information exists in a transaction database of the target unmanned vehicle is detected according to a preset detection step length; if the new transaction geographic position information exists, updating the purchasing intention thermal distribution map by using the new transaction geographic position information to obtain an updated purchasing intention thermal distribution map; dynamically adjusting the initial mobile selling path according to the updated purchase intention heat distribution map to obtain an updated mobile selling path; the target unmanned vehicle is controlled to move according to the planned path direction of the updated moving selling path, so that the target unmanned vehicle can sell commodities to be sold along the way, the driving path of the commodities sold by the unmanned vehicle is good in flexibility, high-intention purchasing customers can be effectively locked, and the commodity selling transaction success rate is improved.

Drawings

To more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without inventive efforts.

FIG. 1 is a scenario diagram of an application scenario in accordance with an embodiment of the present disclosure;

fig. 2 is a schematic flowchart of a method for dynamically adjusting a mobile vending path based on an unmanned vehicle according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of an unmanned vehicle-based mobile vending path dynamic adjustment device according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the disclosed embodiments. However, it will be apparent to one skilled in the art that the present disclosure may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail.

A method and an apparatus for dynamically adjusting a mobile vending path based on an unmanned vehicle according to an embodiment of the present disclosure will be described in detail with reference to the accompanying drawings.

Fig. 1 is a scene schematic diagram of an application scenario according to an embodiment of the present disclosure. The application scenario may include a target unmanned vehicle 101, a remote control 102, a plurality of target intended users 103, and a network 104.

The target unmanned vehicle 101 may be a mobile vehicle integrated with a camera (e.g., a camera), a communication device, a positioning device (e.g., a GPS, etc.), and the like. An unmanned vehicle can be configured to correspond to a commodity patrol selling work in an area (such as an XX park, an XX cell, an XX community and the like).

The remote control terminal 102 may be a server providing various services, for example, a backend server receiving data sent by the unmanned vehicle with which a communication connection is established, and the backend server may receive, analyze, and the like the data sent by the unmanned vehicle and generate a processing result. The server may be one server, or a server cluster composed of a plurality of servers, or may also be one cloud computing service center, which is not limited in this disclosure.

The server may be hardware or software. When the server is hardware, it may be various electronic devices that provide various services to the unmanned vehicle. When the server is software, it may be a plurality of software or software modules for providing various services for the unmanned vehicle 101, or may be a single software or software module for providing various services for the unmanned vehicle 101, which is not limited by the embodiment of the present disclosure.

The target intention user 103 generally refers to a customer who has purchase intention (purchase demand) for a product sold in a target unmanned vehicle. In one embodiment, the targeted intended user 103 may purchase goods on the unmanned vehicle by way of human-computer interaction with the targeted unmanned vehicle 101. For example, when the target unmanned vehicle travels to a certain location (e.g., the location of the target intended user), the target intended user may purchase a certain item on the vending interface of the target unmanned vehicle by clicking on and paying for the item. In another embodiment, the targeted intent user 103 page may establish a communication connection with the targeted unmanned vehicle 101 using a terminal device on which an unmanned vehicle shopping APP (cell phone software), an unmanned vehicle shopping applet, or the like may be installed. The target intention user 103 can enter a commodity shopping page of the unmanned vehicle by opening the unmanned vehicle shopping APP, the unmanned vehicle shopping applet and the like on the terminal device, and can browse and order commodities displayed on the commodity shopping page.

The terminal device may be hardware or software. When the terminal device is hardware, it may be various electronic devices having a display screen and supporting communication with the unmanned vehicle, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like; when the terminal device is software, it may be installed in an electronic device as above. The terminal device may be implemented as multiple pieces of software or software modules, or may be implemented as a single piece of software or software module, which is not limited in this disclosure. Further, various applications, such as a data processing application, an instant messaging tool, social platform software, a search application, a shopping application, and the like, may be installed on the terminal device.

The network 104 may be a wired network connected by a coaxial cable, a twisted pair cable, and an optical fiber, or may be a wireless network that can interconnect various Communication devices without wiring, for example, Bluetooth (Bluetooth), Near Field Communication (NFC), Infrared (Infrared), and the like, which is not limited in the embodiment of the present disclosure.

The remote control 102 may establish a communication connection with the target unmanned vehicle 101 via the network 104 to receive or transmit information or the like. Specifically, the remote control 102 may first obtain a plurality of intended target users associated with the target unmanned vehicle and historical transaction geographic location information of each intended target user; generating a purchasing intention heat distribution map according to historical transaction geographic position information of a plurality of target intention users; generating an initial mobile selling path according to the purchasing intention heat distribution map; then, the target unmanned vehicle is controlled to move according to the planned moving direction of the initial moving selling path, so that the target unmanned vehicle moves along the way to sell the commodities to be sold; in the process that the target unmanned vehicle moves in the planned moving direction, whether newly added transaction geographic position information exists in a transaction database of the target unmanned vehicle or not can be detected according to a preset detection step length; if the new transaction geographic position information exists, updating the purchasing intention heat distribution map by using the new transaction geographic position information to obtain an updated purchasing intention heat distribution map; dynamically adjusting the initial mobile selling path according to the updated purchase intention heat distribution map to obtain an updated mobile selling path; and controlling the target unmanned vehicle to move according to the planned path direction of the updated moving selling path so as to enable the target unmanned vehicle to sell the commodities to be sold along the way. Therefore, when the newly added transaction geographical position information is detected, the purchase intention thermal distribution map is updated by using the newly added transaction geographical position information, the initial mobile selling path is dynamically adjusted by using the updated purchase intention thermal distribution map, the driving path sold by the unmanned vehicle is not invariable during the whole patrol selling period, but can be dynamically adjusted according to the updated purchase intention thermal distribution map, and therefore the driving path has good flexibility; meanwhile, the (updated) purchase intention thermal distribution map is generated according to (newly added) historical transaction geographic position information of the target intention user, so that the high intention purchasing client can be accurately and effectively locked, and the transaction success rate of commodity selling can be effectively improved.

It should be noted that specific types, numbers, and combinations of the target unmanned vehicle 101, the remote control terminal 102, the plurality of target users 103, and the network 104 may be adjusted according to actual requirements of an application scenario, which is not limited in the embodiment of the present disclosure.

Fig. 2 is a schematic flow chart of a method for dynamically adjusting a mobile vending path based on an unmanned vehicle according to an embodiment of the present disclosure. The method for dynamically adjusting the unmanned vehicle-based mobile vending path of fig. 2 may be performed by the remote control 102 of fig. 1. As shown in fig. 2, the method for dynamically adjusting the mobile vending path based on the unmanned vehicle comprises the following steps:

step S201, a plurality of intended target users associated with the target unmanned vehicle and historical transaction geographic location information of each intended target user are obtained.

When a user uses a terminal device (such as a mobile phone) to access channels such as an unmanned vehicle shopping APP (mobile phone software) or a small program (an application which can be used without downloading and installing) to use an unmanned vehicle service (such as a commodity selling service), after the user authorization, the unmanned vehicle can acquire GPS information of the terminal device of the user. That is, after the user uses the unmanned vehicle APP or applet installed on the terminal device and authorizes the unmanned vehicle APP or applet, the terminal device may send the acquired GPS information to the unmanned vehicle, and at this time, the unmanned vehicle may obtain geographic location information of a location where the user places an order on line or browses a commodity page.

The historical transaction geographic position information may be historical geographic position information (such as GPS information) acquired by the terminal device when the user accesses an unmanned vehicle shopping APP or applet by using the terminal device to browse or place an order for subscription or pay for purchasing a certain commodity sold by the unmanned vehicle; the method can also be used for directly purchasing or browsing the commodities on the target unmanned vehicle in a man-machine interaction mode when the user is on a patrol selling site of the target unmanned vehicle, and the target unmanned vehicle acquires and records the site GPS information through a positioning device (such as a GPS sensor) of the target unmanned vehicle when detecting that the user pays for the purchased or browsed commodities loaded on the vehicle.

Step S202, a purchasing intention heat distribution map is generated according to historical transaction geographic position information of a plurality of users with target intentions.

In the embodiment of the present disclosure, the purchase intention thermal distribution map may be understood as a geographic location distribution where the user appears at a certain location on the map and uses an unmanned vehicle service (for example, purchases a commodity from an unmanned vehicle) at the certain location. The distribution situation can also visually show the main gathering places where the user uses the unmanned vehicle service and the purchase intention degree of the commodities purchased at the places. Specifically, by collecting historical transaction geographic position information of the target intended user, it can be analyzed and obtained which place(s) where the target intended user will usually use the unmanned vehicle service (such as purchasing goods from the unmanned vehicle), so that places where the target intended user may appear or stay frequently can be accurately locked, and the possibility that the target intended user will use the unmanned vehicle service at the places can be accurately locked.

As an example, it is assumed that there are 10 intended users, namely, intended users 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, which have appeared in one or more places of the area a (c), g, or (c) and used the unmanned car service to purchase goods sold on the intended unmanned car (responsible for patrol sales service of the area a). The users who have bought and bought the goods sold by the target unmanned vehicles at the place (r) comprise target intention users 01, 02, 05, 06, 07 and 10, the users who have bought and bought the goods sold by the target unmanned vehicles at the place (r) comprise target intention users 01, 03, 06, 08 and 09, and the users who have bought and bought the goods sold by the target unmanned vehicles at the place (r) comprise target intention users 02, 05, 04, 09 and 10. Then, the locations where the user may appear or frequently stay with the intention of the target may be locked are locations (r), (c) and (c) of the area a. Also, the likelihood (i.e., probability) that a user will use the unmanned vehicle service at each location may be determined by calculating the number of targeted users for each location. For example, in site (r), there are 6 users with the intention of destination, the probability that the user will use the unmanned vehicle service in site (r) is 6/10= 0.6.

According to the steps, the places of the area A can be highlighted (such as different colors or highlighting) on the map to generate a purchasing intention heat distribution map.

And step S203, generating an initial mobile selling path according to the heat distribution map of the purchasing intention.

With reference to the example listed in step S202, it can be calculated that the probabilities of the users in the locations (i), (ii), and (iii) of the area a using the unmanned vehicle service (purchasing goods from the target unmanned vehicle) are 0.6, 0.5, and 0.5, respectively, so that the geographical position of the transaction in which the target intended user in the location (i) realizes the commodity transaction with the target unmanned vehicle can be highlighted in red, and the geographical position of the transaction in which the target intended user in the location (ii) and (iii) realizes the commodity transaction with the target unmanned vehicle can be highlighted in orange on the map of the area a. On the map, a point may be used to indicate that a target intended user uses the unmanned vehicle service (purchases goods from the target unmanned vehicle) at that location.

As can be seen from the above, the locations (i), (ii) and (iii) of the area a have 6, 5 and 5 target users using the unmanned vehicle service, and then the locations (i), (ii) and (iii) can be respectively determined as a path node, such as nodes 01, 02 and 03, and then connected in a certain connection order to form an initial mobile vending path.

And S204, controlling the target unmanned vehicle to move according to the planned moving direction of the initial moving selling path so as to enable the target unmanned vehicle to move along the way to sell the commodities to be sold.

If the planned moving direction of the initial moving selling path in the area a is the node 02 → the node 01 → the node 03, the remote control terminal can issue a moving control instruction to the target unmanned vehicle so as to control the target unmanned vehicle to move according to the planned moving direction of the node 02 → the node 01 → the node 03, and sell the goods to be sold loaded on the vehicle along the way. Wherein, the goods to be sold can be food, daily necessities, stationery and the like. The commodity to be sold may be one kind or multiple kinds, and may be determined according to actual conditions, and is not limited specifically herein. For example, when the target unmanned vehicle cooperates with a merchant and plans to promote a new product (e.g., chicken snack) in 20XX year 1 month 1 day to 20XX year 2 month 1 day, the target unmanned vehicle may be loaded with only the new chicken snack and then sold along the way according to the planned moving direction of the initial moving selling path.

And S205, detecting whether newly added transaction geographic position information exists in a transaction database of the target unmanned vehicle according to a preset detection step length in the process that the target unmanned vehicle moves and moves according to the planned moving direction.

The preset detection step length refers to a preset detection time interval. The detection time interval can be flexibly set according to actual conditions, and can be set to 10 minutes, 20 minutes and 30 minutes, for example.

And the newly added transaction geographic position information means that some newly added intention users use the unmanned vehicle service to purchase the goods to be sold loaded on the target unmanned vehicle in the process that the target unmanned vehicle moves according to the planned moving direction of the initial moving selling path. Alternatively, the original intended user uses the unmanned vehicle service to purchase the commodity to be sold loaded on the target unmanned vehicle at another location.

In the process of selling commodities to be sold through the mobile selling mode, the target unmanned vehicle can store the acquired newly-added transaction geographic position information into a transaction database (which can be a cloud database).

And step S206, if the new transaction geographic position information exists, updating the purchasing intention thermal distribution map by using the new transaction geographic position information to obtain an updated purchasing intention thermal distribution map.

In combination with the above-mentioned examples of step S202 and step S203, if the target unmanned vehicle moves on the way of selling the chicken snack on the vehicle in the planned moving direction of node 02 → node 01 → node 03 in the area a, receiving new users to purchase chicken fast food on orders by using the unmanned vehicle service, obtaining the newly added transaction geographic position information authorized by the new users, or one or more of the targeted intended users 01, 02, 03, 04, 05, 06, 07, 08, 09, 10 places an order for the targeted unmanned vehicle to purchase chicken snacks at the new location using the unmanned vehicle service, or the chicken fast food is purchased on site, and the target unmanned vehicle acquires the newly added transaction geographical position information of the original user, so that the heat points corresponding to the newly added transaction geographical position information can be added in the updated purchase intention heat distribution map to obtain the updated purchase intention heat distribution map.

And step S207, dynamically adjusting the initial mobile selling path according to the updated purchase intention heat distribution map to obtain an updated mobile selling path.

As an example, referring to the method for generating the initial mobile selling route in step S203, a new mobile selling route may be generated according to the updated purchase intention distribution map. And comparing the new mobile selling path with the initial mobile selling path, and determining whether the planning moving direction of the initial mobile selling path needs to be changed and/or new path nodes need to be added, namely dynamically adjusting the initial mobile selling path to obtain an updated mobile selling path.

And S208, controlling the target unmanned vehicle to move according to the planned path direction of the updated moving selling path so as to enable the target unmanned vehicle to sell the goods to be sold along the way.

And then, the remote control end can issue a new movement control instruction to the target unmanned vehicle so as to control the target unmanned vehicle to move according to the planned path direction of the updated movement selling path and carry out commodity selling operation along the way.

According to the technical scheme provided by the embodiment of the disclosure, the driving route sold by the unmanned vehicle is not invariable during the whole patrol selling period, but can be dynamically adjusted according to the heat distribution map of the updated purchasing intention, so that the driving route has good flexibility; meanwhile, the (updated) purchase intention thermal distribution map is generated according to (newly added) historical transaction geographic position information of the target intention user, so that the high intention purchasing client can be accurately and effectively locked, and the transaction success rate of commodity selling can be effectively improved.

In some embodiments, the step S201 includes:

acquiring a mobile selling task, wherein the mobile selling task comprises a commodity to be sold and a selling area;

calling a target unmanned vehicle corresponding to a selling region and a user data set corresponding to the target unmanned vehicle, wherein the user data set comprises a plurality of users and user data of each user, and the user data at least comprises historical webpage browsing data and historical commodity order data;

determining a plurality of target intention users according to historical webpage browsing data and/or historical commodity order data;

and calling historical transaction geographic position information of each target intention user.

The selling area can be a plurality of districts, communities, parks and the like. The selling area can be determined by means of negotiation and the like when the unmanned vehicle operator and the commodity provider (or a distributor and the like) make a selling cooperation plan, and can also be determined by a supply place and a promotion area of the commodity provider. For example, a certain commodity provider wants to promote and sell a new marketed product m under the south China, and the supply locations are respectively three locations a, b and c in south China, so that the unmanned vehicle operator can determine which areas in the south China are divided into the selling areas according to the supply locations of the commodity provider, the target sales groups, the sales volume and the like and the distribution locations of unmanned vehicles.

In order to facilitate management, save traffic costs and better offer unmanned vehicle services to users in general, the area of a vending area is preferably sized so that an unmanned vehicle can be responsible for the vending services in that area, i.e., one unmanned vehicle corresponds to one vending area.

At the remote control end, the corresponding relation between the unmanned vehicle and the selling area can be established in advance, and a corresponding relation table is formed and stored at a preset position. When the mobile selling task is obtained, the target unmanned vehicle corresponding to the selling area can be called according to the corresponding relation table.

In the process of patrolling and selling the commodities, each unmanned vehicle collects some user data which are subjected to man-machine interaction with the unmanned vehicle or browse the commodities loaded on the unmanned vehicle or purchase the commodities loaded on the unmanned vehicle by using the service of the unmanned vehicle to obtain a user data set, and stores the user data set into a preset user data pool (or a user database, or a cloud database) of the unmanned vehicle.

Historical webpage browsing data including, but not limited to, historical browsing record information (including browsing time, browsing times, browsed pages, browsed commodities and the like) of a user browsing commodities sold by a target unmanned vehicle by using the unmanned vehicle APP or the applet.

Historical merchandise order data including, but not limited to, historical order data (including the name of the merchandise placed, the time of placing an order, the quantity of the merchandise, the payment method, the amount of the transaction, etc.) of the merchandise that the user places an order to purchase or subscribe to the target unmanned vehicle for sale using the unmanned vehicle APP or applet.

In some embodiments, determining a plurality of intended users based on historical web browsing data and/or historical merchandise order data includes:

historical webpage browsing data and/or historical commodity order data of each user are extracted, wherein the historical webpage browsing data and/or the historical commodity order data comprise historical record information of commodities to be sold and/or similar commodities to be sold;

determining a purchase intention value of each user for purchasing the commodity to be sold according to the historical record information;

and determining the users with the purchase intention value exceeding a preset threshold value as target intention users.

The similar products to the products to be sold refer to similar products (or substitute products) belonging to the same category as the products to be sold. For example, the commodity to be sold is chicken fast food, and the commodity similar to the chicken fast food can be beef fast food, pork fast food, duck fast food and the like.

As an example, assuming that the goods to be sold are chicken snacks, historical information (e.g., historical browsing goods record information, historical ordering goods record information, etc.) containing "chicken snacks" and/or the like may be first extracted from historical web browsing data and/or historical goods order data of each user. Then, according to the history information, the purchase intention value of each user for purchasing the commodity to be sold is determined. Specifically, the browsing time, the browsing times, the ordering purchase frequency, the purchase quantity and the like of the "chicken fast food" and/or the similar products to the "chicken fast food" in the history information of each user can be counted to predict the purchase intention value (purchase probability value) of the user for purchasing the chicken fast food (for sale).

In one embodiment, a correspondence relationship between a purchase intention value (purchase probability value, which may be a range value or a point value) and a statistical result of each item of record data in the history information may be set in advance. For example, the history information includes a web browsing record or an order record of the commodity to be sold and/or the similar commodity to be sold, and the corresponding purchase intention value is X1; two web browsing records or order records containing commodities to be sold and/or similar commodities to be sold are arranged in the history record information, and the purchase intention value is X2; the history information includes two or more web browsing records or order records including the commodity to be sold and/or the similar commodity to be sold, and the purchase intention value is X3.

In another embodiment, the web browsing duration, the number of orders placed and purchased, etc. may also be included in the statistics as a basis for setting the corresponding relationship between the purchase intention value (the purchase probability value, which may be a range value or a point value) and the statistical result of each item of record data in the history information. For example, if the history information of a certain user a includes 3 browsing records of a commodity including "chicken fast food", each browsing time exceeds 30 seconds, and there are 2 order records for purchasing "chicken fast food" and 1 order record for purchasing "pork fast food", the purchase intention value of the user a is determined to be 80% -100% according to the record information.

The preset threshold may be flexibly set according to actual situations, and for example, may be set to be greater than 50%, 60%, or 70%, which is not limited herein.

In some embodiments, generating a purchasing intent heat distribution map based on historical transactional geolocation information for a plurality of targeted intent users includes:

acquiring an electronic map of a selling area;

according to the historical transaction geographic position information of the target intention user, point tracing is carried out on an electronic map, and a point position corresponding to each historical transaction geographic position information is obtained;

determining a purchase intention value of a target intention user corresponding to each point and a purchase thermodynamic grade corresponding to the purchase intention value;

and determining the display color of each point on the electronic map according to the purchasing heat power grade to generate a purchasing intention heat distribution map, wherein different purchasing heat power grades correspond to different display colors, and different display colors correspond to different purchasing intention values.

As an example, assuming that the selling area is region B, the goods to be sold are chicken snacks, and the target intended users are users who have an intention value of purchase of 50% or more. Firstly, the remote control end can call an electronic map of the area B from a preset map database, then points are drawn on the electronic map of the area B according to the historical transaction geographic position information of the target users, and one point corresponds to one historical transaction geographic position. And then, determining the purchasing heat level corresponding to each purchasing intention value according to a pre-established corresponding relation table of the purchasing intention values and the purchasing heat levels. For example, the correspondence between the preset purchase intention value and the purchase thermodynamic level is shown in table 1 below.

TABLE 1 corresponding relationship table of purchase intention values and purchase thermodynamic grades

Purchase intention value	Purchasing thermal ratings
		50% (containing 50%) -60% (containing no 60%)	Grade one
60% (containing 60%) -70% (containing no 70%)	Two grade
		70% (containing 70%) -80% (containing no 80%)	Three levels
80% (80% contained) to 90% (90% not contained)	Four grades
		90% (containing 90%) -100% (containing 100%)	Five grades

In combination with the above table 1, the corresponding relationship between each point on the electronic map and the purchase intention value and the purchase thermodynamic grade can be determined.

If there are 10 point locations on the electronic map, namely point locations (first, second, third, fourth, fifth, sixth, seventh, eight, 65%, 70%, 60%, 85%, 100%, 90%, 75%, 65%) corresponding to the purchase intention value, and the purchase thermodynamic level (first, fourth, second, third, fourth, fifth, third, second). And then, determining the display color corresponding to each point according to the purchasing heat power grade. In practical application, the corresponding relation between the purchasing heat power grade and the display color can be preset. For example, one level corresponds to purple, two levels correspond to blue, three levels correspond to yellow, four levels correspond to orange, and five levels correspond to red. And after the display color of each point location is determined, a purchase intention heat distribution map can be obtained. The purchase heat level and the purchase intention value of each point can be visually seen through the purchase intention heat distribution map, and the purchase intention values of the points in the area B are visually seen, and the concentrated target intention users are the most.

In some embodiments, the step S203 includes:

extracting road condition information and purchasing intention heat distribution characteristic information of a purchasing intention heat distribution map;

and generating an initial mobile selling path according to the road condition information and the heat distribution characteristic information of the purchase intention.

The road condition information includes information such as road traffic conditions of the selling area corresponding to the purchase intention heat distribution map, and a monitoring management policy of the road (such as a monitoring requirement of a road gate).

The purchasing intention heat distribution characteristic information mainly refers to the purchasing intention value and the purchasing heat grade distribution condition of each point on the map.

In some embodiments, generating the initial mobile selling path according to the road condition information and the purchasing intention thermodynamic distribution characteristic information includes:

determining a plurality of parking selling places according to the road condition information;

each parking lot selling place is taken as a center, and a corresponding parking lot selling circle is defined;

counting the number of the points scattered in each parking selling circle, wherein the purchase intention value meets the preset range value;

screening at least two selling points which can be parked from a plurality of selling places as selling path nodes according to the number of the points;

And connecting at least two selling path nodes to obtain an initial mobile selling path.

As an example, a plurality of places allowing parking and selling (for example, a place having a temporary parking position, or some places facilitating sale, etc.) may be determined according to road condition information of a selling area corresponding to a purchase intention heat distribution map. Each parking selling place is used as a center, and a parking selling circle with a preset radius is drawn. Then, the number of the point locations scattered in each parking selling circle and having the purchase intention value meeting the preset range value is counted. The preset range value may be flexibly set according to actual situations, for example, may be greater than or equal to 60%, 70%, and the like, which is not limited herein. And then, selecting target parkable selling points with the point location number exceeding a preset point number (which can be flexibly set according to actual conditions, such as 10 or 20 different points) from the multiple parkable selling points, wherein the target parkable selling points are the selling path nodes of the initial mobile selling path. And finally, connecting the selling path nodes according to a certain connecting sequence to obtain an initial mobile selling path.

In some embodiments, dynamically adjusting the initial mobile selling path according to the updated purchase intention heat distribution map to obtain an updated mobile selling path includes:

determining the distribution point of a newly added heat point corresponding to the newly added transaction geographic position information in the updated purchase intention heat distribution map;

screening target distribution points which do not fall into a stoppable selling circle corresponding to any selling path node from the distribution points, and counting the number of the target distribution points;

if the number of the target distribution point locations exceeds the preset number and the distance value between the target distribution point locations does not exceed the preset distance value, clustering the target distribution point locations to obtain a clustering center;

determining the clustering center as a newly added path node;

and dynamically adjusting the node connection sequence of the initial mobile selling path according to the node position relation between the newly added path node and at least two selling path nodes to obtain an updated mobile selling path.

The preset distance threshold may be flexibly set according to actual conditions, and is not limited specifically herein.

As an example, if there are 20 new transaction geographic location information and 5 selling route nodes, the distribution points of the new heat points corresponding to the 20 new transaction geographic location information in the updated purchase intention heat distribution map, that is, the specific positions of the new heat points in the updated purchase intention heat distribution map, may be determined first. Then, the distance value between each distribution point and the 5 selling path nodes is calculated to obtain 5 distance values. If all the 5 distance values exceed the preset distance threshold value, it can be determined that the distribution point does not fall into the stoppable selling circle corresponding to any selling path node, and the distribution point can be determined as the target distribution point.

According to the mode, all target distribution points which do not fall into the parking sale circle corresponding to any one sale path node can be screened out from the 20 distribution points, and the number of the target distribution points is counted. If the counted number exceeds the preset number (which may be flexibly set according to actual conditions, for example, may be set to 10), and the distance value between every two point locations of the 10 target distribution points does not exceed the preset distance value, it may be determined that the target distribution points are relatively concentrated. Further, clustering is performed on the target distribution point locations to obtain a clustering center (distance average value), and the clustering center is determined as a newly added path node. And finally, according to the node position relation between the newly added path node and a plurality of selling path nodes in the initial mobile selling path. For example, the initial mobile vending path has three vending path nodes of nodes 01, 02 and 03, and the planned moving direction is node 02 → node 01 → node 03. And the node 04 of the newly added path is between the nodes 01 and 02, then the node connection sequence of the initial mobile selling path can be dynamically adjusted to: node 02 → node 04 → node 01 → node 03, i.e. the updated mobile vending route.

All the above optional technical solutions may be combined arbitrarily to form optional embodiments of the present application, and are not described in detail herein.

The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods. For details not disclosed in the embodiments of the apparatus of the present disclosure, refer to the embodiments of the method of the present disclosure.

Fig. 3 is a schematic diagram of a mobile vending path dynamic adjustment device based on an unmanned vehicle according to an embodiment of the present disclosure. As shown in fig. 3, the unmanned vehicle-based mobile vending path dynamic adjustment device includes:

an information acquisition module 301 configured to acquire a plurality of intended target users associated with the target unmanned vehicle and historical transaction geographic location information of each intended target user;

a map generation module 302 configured to generate a purchasing intent thermodynamic distribution map according to historical transaction geographic location information of a plurality of targeted intent users;

a path generation module 303 configured to generate an initial mobile selling path according to the map of the distribution of heat according to the buying intention;

a first control module 304, configured to control the target unmanned vehicle to move according to the planned moving direction of the initial moving selling path, so that the target unmanned vehicle moves along the way to sell the goods to be sold;

The detection module 305 is configured to detect whether new transaction geographic position information exists in a transaction database of the target unmanned vehicle according to a preset detection step length in the process that the target unmanned vehicle moves and moves according to the planned moving direction;

the updating module 306 is configured to update the purchasing intention heat distribution map by using the newly added transaction geographic position information if the newly added transaction geographic position information exists, so as to obtain an updated purchasing intention heat distribution map;

a path adjusting module 307 configured to dynamically adjust the initial mobile selling path according to the updated purchase intention thermal distribution map, so as to obtain an updated mobile selling path;

and the second control module 308 is configured to control the target unmanned vehicle to move according to the planned path direction of the updated moving selling path, so that the target unmanned vehicle sells the goods to be sold along the way.

According to the technical scheme provided by the embodiment of the disclosure, the selling route of the unmanned vehicle is not invariable during the whole patrol selling period, but can be dynamically adjusted according to the updated purchasing intention heat distribution map, so that the flexibility of the selling route is good; meanwhile, the (updated) purchase intention heat distribution map is generated according to (newly added) historical transaction geographic position information of the target intention users, high intention purchase customers can be accurately and effectively locked, and the transaction success rate of commodity selling can be effectively improved.

In some embodiments, the information obtaining module 301 includes:

the mobile selling system comprises a task obtaining unit, a selling unit and a selling unit, wherein the task obtaining unit is configured to obtain a mobile selling task which comprises commodities to be sold and selling areas;

the system comprises a data calling unit and a data receiving unit, wherein the data calling unit is configured to call a target unmanned vehicle corresponding to a selling area and a user data set corresponding to the target unmanned vehicle, the user data set comprises a plurality of users and user data of each user, and the user data at least comprises historical webpage browsing data and historical commodity order data;

a determining unit configured to determine a plurality of intended users according to historical web browsing data and/or historical commodity order data;

and the information retrieval unit is configured to retrieve the historical transaction geographic position information of each targeted intention user.

In some embodiments, the determining unit may be specifically configured to:

acquiring an electronic map of a selling area;

In some embodiments, the path generating module includes:

the information extraction unit is configured to extract road condition information and purchasing intention thermal distribution characteristic information of the purchasing intention thermal distribution map;

and the path generating unit is configured to generate an initial mobile selling path according to the road condition information and the purchasing intention thermodynamic distribution characteristic information.

In some embodiments, the path generating unit may be specifically configured to:

In some embodiments, dynamically adjusting the initial mobile vending path according to the updated buying intention heat distribution map to obtain an updated mobile vending path includes:

determining the distribution point position of a newly added heat point corresponding to the newly added transaction geographic position information in the updated purchase intention heat distribution map;

screening target distribution points which do not fall into a parking selling circle corresponding to any selling path node from the distribution points, and counting the number of the target distribution points;

if the number of the target distribution point locations exceeds the preset number and the distance value between the target distribution point locations does not exceed the preset distance value, clustering the target distribution point locations to obtain a clustering center, and determining the clustering center as a newly added path node;

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by functions and internal logic of the process, and should not constitute any limitation to the implementation process of the embodiments of the present disclosure.

Fig. 4 is a schematic diagram of an electronic device 4 provided by the embodiment of the present disclosure. As shown in fig. 4, the electronic apparatus 4 of this embodiment includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and operable on the processor 401. The steps in the various method embodiments described above are implemented when the processor 401 executes the computer program 403. Alternatively, the processor 401 implements the functions of the respective modules/units in the above-described respective apparatus embodiments when executing the computer program 403.

The electronic device 4 may be a desktop computer, a notebook, a palm computer, a cloud server, or other electronic devices. The electronic device 4 may include, but is not limited to, a processor 401 and a memory 402. Those skilled in the art will appreciate that fig. 4 is merely an example of electronic device 4 and does not constitute a limitation of electronic device 4 and may include more or fewer components than shown, or different components.

The Processor 401 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc.

The storage 402 may be an internal storage unit of the electronic device 4, for example, a hard disk or a memory of the electronic device 4. The memory 402 may also be an external storage device of the electronic device 4, for example, a plug-in hard disk provided on the electronic device 4, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. The memory 402 may also include both internal storage units and external storage devices of the electronic device 4. The memory 402 is used for storing computer programs and other programs and data required by the electronic device.

It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules, so as to perform all or part of the above described functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit.

The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the above embodiments may be realized by the present disclosure, and the computer program may be stored in a computer readable storage medium to instruct related hardware, and when the computer program is executed by a processor, the steps of the above method embodiments may be realized. The computer program may comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain suitable additions or additions that may be required in accordance with legislative and patent practices within the jurisdiction, for example, in some jurisdictions, computer readable media may not include electrical carrier signals or telecommunications signals in accordance with legislative and patent practices.

The above examples are only intended to illustrate the technical solution of the present disclosure, not to limit it; although the present disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present disclosure, and are intended to be included within the scope of the present disclosure.

Claims

1. A mobile vending path dynamic adjustment method based on unmanned vehicles is characterized by comprising the following steps:

acquiring a plurality of target intention users associated with a target unmanned vehicle and historical transaction geographic position information of each target intention user;

generating an initial mobile selling path according to the purchase intention heat distribution map;

Detecting whether newly added transaction geographic position information exists in a transaction database of the target unmanned vehicle according to a preset detection step length in the process that the target unmanned vehicle moves according to the planned moving direction;

if the new transaction geographic position information exists, updating the purchasing intention thermal distribution map by using the new transaction geographic position information to obtain an updated purchasing intention thermal distribution map;

controlling the target unmanned vehicle to move according to the planned path direction of the updated moving selling path so as to enable the target unmanned vehicle to sell goods to be sold along the way;

wherein, according to the distribution map of heat of the intention of purchase, generate the initial and move the selling route, including:

extracting road condition information and purchasing intention heat distribution characteristic information of the purchasing intention heat distribution map;

defining a corresponding parking lot circle by taking each parking selling place as a center;

counting the number of the point positions scattered in each parking selling circle and having a purchasing intention value meeting a preset range value;

Screening at least two selling path nodes from the plurality of parking selling places according to the number of the points;

connecting at least two selling path nodes to obtain an initial mobile selling path;

wherein, according to the purchase intention heat distribution map of update, dynamic adjustment the initial mobile selling route obtains the update mobile selling route, include:

determining distribution points of newly added heat points corresponding to the newly added transaction geographic position information in the updated purchase intention heat distribution map;

if the number of the target distribution point locations exceeds a preset number and the distance value between the target distribution point locations does not exceed a preset distance value, clustering the target distribution point locations to obtain a clustering center, and determining the clustering center as a newly added path node;

2. The method of claim 1, wherein obtaining a plurality of intended target users associated with a target unmanned vehicle and historical transactional geographic location information for each of the intended target users comprises:

calling a target unmanned vehicle corresponding to the selling region and a user data set corresponding to the target unmanned vehicle, wherein the user data set comprises a plurality of users and user data of each user, and the user data at least comprises historical webpage browsing data and historical commodity order data;

determining a plurality of target intention users according to the historical webpage browsing data and/or the historical commodity order data;

and calling historical transaction geographic position information of each targeted intention user.

3. The method of claim 2, wherein determining a plurality of intended users based on the historical web browsing data and/or historical merchandise order data comprises:

extracting historical webpage browsing data and/or historical commodity order data of each user, wherein the historical webpage browsing data and/or the historical commodity order data comprise historical record information of the commodities to be sold and/or the similar commodities to be sold;

Determining a purchase intention value of each user for purchasing the commodities to be sold according to the historical record information;

4. The method of claim 3, wherein generating a purchasing intent thermodynamic distribution map based on historical transactional geographic location information for a plurality of the targeted intended users comprises:

acquiring an electronic map of the selling area;

according to the historical transaction geographic position information of the target intention user, point drawing is carried out on the electronic map, and a point position corresponding to each piece of historical transaction geographic position information is obtained;

determining a purchase intention value of a target intention user corresponding to each point position and a purchase heat level corresponding to the purchase intention value;

5. The utility model provides a remove and sell route dynamic adjustment device based on unmanned car which characterized in that includes:

The system comprises an information acquisition module, a transaction processing module and a transaction processing module, wherein the information acquisition module is configured to acquire a plurality of target intention users related to a target unmanned vehicle and historical transaction geographic position information of each target intention user;

a path generation module configured to generate an initial mobile selling path according to the purchase intention heat distribution map;

the detection module is configured to detect whether newly added transaction geographic position information exists in a transaction database of the target unmanned vehicle according to a preset detection step length in the process that the target unmanned vehicle moves according to the planned moving direction;

the updating module is configured to update the purchasing intention heat distribution map by using the newly-added transaction geographic position information if the newly-added transaction geographic position information exists, so as to obtain an updated purchasing intention heat distribution map;

the second control module is configured to control the target unmanned vehicle to move according to the planned path direction of the updated moving selling path, so that the target unmanned vehicle can sell goods to be sold along the way;

wherein, according to purchase intention heating power distribution map, generate initial removal selling route, include:

screening out at least two selling path nodes from the plurality of parking selling places according to the number of the points;

screening target distribution points which do not fall into a stoppable selling ring corresponding to any selling path node from the distribution points, and counting the number of the target distribution points;

and dynamically adjusting the node connection sequence of the initial mobile selling path according to the node position relation between the newly added path nodes and at least two selling path nodes to obtain an updated mobile selling path.

6. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor realizes the steps of the method according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of a method according to any one of claims 1 to 4.