CN115423406A

CN115423406A - Unmanned aerial vehicle-bus combined area cooperative distribution system and method

Info

Publication number: CN115423406A
Application number: CN202211085149.5A
Authority: CN
Inventors: 彭勇; 张雅丽; 任志; 高舒晗; 刘松
Original assignee: Chongqing Jiaotong University
Current assignee: Chongqing Jiaotong University
Priority date: 2022-09-06
Filing date: 2022-09-06
Publication date: 2022-12-02

Abstract

The invention belongs to the technical field of logistics distribution, and discloses an unmanned aerial vehicle and bus combined regional collaborative distribution system and a method, wherein the system comprises the following steps: the unmanned aerial vehicle subsystem executes distribution tasks and stores user articles; the bus carrying subsystem provides long-distance transportation and midway charging for the unmanned aerial vehicle on the way of distribution by using an unmanned aerial vehicle wireless charging carrying platform arranged on the top of the bus; the intelligent terminal APP provides an online ordering interface and displays distribution information in real time. The bus and unmanned aerial vehicle coordinated distribution mode realized by the invention not only solves the problems of low cargo vehicle distribution efficiency and insufficient transportation capacity in the same city distribution, but also solves the problems of short endurance and limited flight distance of the unmanned aerial vehicle. The goods storage cabinets arranged at the bus station and the bus station of the target customer district are the best choices obtained by carrying out preference analysis by means of big data and reasonably screening, so that the construction cost is reduced, and meanwhile, better planning arrangement is provided for the navigation path of the unmanned aerial vehicle.

Description

Unmanned aerial vehicle-bus combined area cooperative distribution system and method

Technical Field

The invention belongs to the technical field of logistics distribution, and particularly relates to an unmanned aerial vehicle and bus combined regional collaborative distribution system.

Background

At present, domestic express delivery business volume increases rapidly, relies on unmanned aerial vehicle can promote goods delivery efficiency and can effectively solve the higher problem of traditional delivery mode cost. With the mature development of the logistics industry market in China and the continuous innovation of the Internet of things and the sensor technology, the application of the logistics unmanned aerial vehicle is supported by a certain technology, and the application of the unmanned aerial vehicle (vehicle) to improve the distribution efficiency becomes an industry consensus. In the existing unmanned aerial vehicle distribution stage, a plurality of problems in the aspects of technology, cost, safety and the like still exist, but in China or abroad, the unmanned aerial vehicle has started to exert force on the track in recent years, and a new distribution mode mainly based on the unmanned aerial vehicle gradually enters the visual field of people.

The pilotless plane is an unmanned plane for short, is a manned plane operated by a radio remote control device and a self-contained program control device, is provided with corresponding systems such as avionics, sensors, communication, flight control and the like, and has the functions of autonomous flight and independent completion of a certain task. With the development of technology, it is not a contention fact that drones have become intelligent robots that can fly. The field of unmanned aerial vehicles is in a brisk development stage. Around unmanned aerial vehicles, various technical innovations emerge endlessly, and with the comprehensive opening of the low-altitude field in China, the high-tech achievements of unmanned aerial vehicles once sealed in the military field are now revealing mysterious veil, entering the civil fields and showing huge potential. At present, express logistics enterprises start unmanned aerial vehicle express research and development and carry out unmanned aerial vehicle express tests. However, because the unmanned aerial vehicle has the limitation of load and flying distance, the unmanned aerial vehicle can only deliver goods with specific specifications to customers within a certain range, and therefore the use of the pure unmanned aerial vehicle for delivery still has great limitation.

Urban public transport is an important infrastructure closely related to the productive life of the people. The urban public transport is preferentially developed, a public transport system which is adaptive to the urban scale, population and economic development is built, the total number of vehicles in the urban central area is reduced, the urban public transport system is an important measure for improving the urban transport resource utilization efficiency and relieving traffic congestion, and the urban public transport system is a pragmatic measure for improving the urban air quality and accelerating the construction of an environment-friendly society. The public transport construction promotes the fusion development of new technologies such as internet, big data and artificial intelligence and urban public transport, promotes the concept of 'service as trip', promotes the system construction such as intelligent operation supervision of urban public transport, intelligent enterprise scheduling, trip information service and big data decision support, provides urban public transport real-time trip information service for passengers, improves the real-time forecast rate of the incoming information of urban public transport vehicles, and improves the non-cash payment rate.

Unmanned aerial vehicles and urban public transport have wide development prospects, but have the defect that the unmanned aerial vehicles and the urban public transport are difficult to overcome. The unmanned aerial vehicle cannot bear heavier objects, has limited cruising ability and cannot work for a long time; urban public transport needs to accurately follow a specified route, and the related range is limited, so that the information of nearby ground conditions is difficult to acquire quickly. If the unmanned aerial vehicle is combined with urban public transport, the integration development of a new technology and the public transport is embodied, the advantage complementation is formed, the defects between the unmanned aerial vehicle and the public transport are probably made up, but the current cooperative distribution technology of the unmanned aerial vehicle and the public transport is not applied.

Due to remote positions, order dispersion, difficult distribution and sudden accidents of the urban end logistics, logistics order distribution is basically completed manually, distribution efficiency is low, and distribution cost is high. In the prior art, goods are sent from a warehousing station to a distribution station, and a distributor arrives one by one according to addresses, or a buyer arrives at a distribution point to pick up the goods. In addition, due to ground traffic jam and high distribution demand, the logistics distribution time is long at present, the distribution cost is high, the logistics distribution is influenced by the geographical environment, the district of an individual region does not support delivery service, and buyers need to pick up the goods from the distribution station, so that the user experience and consumption will are reduced, and huge consumption potential cannot be released. Along with the development of unmanned aerial vehicle technique, the mode of vehicle and unmanned aerial vehicle collaborative distribution receives extensive concern, and a plurality of commodity circulation enterprises have accomplished with scientific and technological company and have utilized unmanned aerial vehicle to carry out the preliminary experiment of terminal delivery. At present unmanned aerial vehicle mostly starts from the warehouse and returns the warehouse after delivering, and in actual conditions, the warehouse can't provide the delivery service for the customer that surpasss unmanned aerial vehicle delivery range, and unmanned aerial vehicle must obtain the balance between load restriction and continuation of the journey mileage, consequently establishes a plurality of unmanned aerial vehicle websites and provides the delivery service of long distance for unmanned aerial vehicle, becomes the important mode that improves the unmanned aerial vehicle utilization ratio and further exert the car machine and deliver in coordination.

Through the above analysis, the problems and defects of the prior art are as follows:

(1) The existing unmanned aerial vehicle distribution has the limitations of endurance, load and sensing technology. The power battery can not support long-time operation, and the flight distance is limited; only the distribution of goods with specific specifications can be carried out on customers within a certain range, the load capacity is limited, and the goods of all categories cannot be comprehensively covered; the distribution application scenes are limited, and the distribution tasks cannot be accurately executed under various complex and variable scenes; the method cannot cope with sudden scenes, and has the hidden trouble of safe distribution.

(2) The existing distribution method has low distribution efficiency, high distribution cost and low user experience. The method for self-picking, appointing delivery time and setting community self-picking cabinet in the community convenience store solves the problems of cargo safety and service quality to a certain extent, but only meets the requirements of a consumer end, and increases the distribution cost for a supply end.

(3) The acquisition cost and the operating cost of the existing unmanned aerial vehicle are high, and the manufacturing industry chain is not perfect for the moment and the cost can not be reduced through systematic production.

(4) The prior art does not have a method or a system for cooperatively distributing unmanned aerial vehicles and public transport at present.

(5) Legal policies related to unmanned aerial vehicle distribution are imperfect, uncontrollable performance of flight safety problems of the unmanned aerial vehicle is large, responsibility confirmation problems are not clearly specified when traffic accidents occur in the distribution process, and public safety and privacy problems can be greatly disputed in the flight process.

Disclosure of Invention

Aiming at the problems in the prior art, the invention provides an unmanned aerial vehicle and bus combined regional collaborative distribution system.

The invention is realized in this way, an unmanned aerial vehicle combines the regional cooperative delivery system of bus to include:

the unmanned aerial vehicle subsystem comprises an unmanned aerial vehicle and unmanned aerial vehicle stations arranged in a bus station and a user cell; the unmanned aerial vehicle is used for executing distribution tasks and storing user articles, when the articles are sent to a bus stop, the articles are grabbed by the unmanned aerial vehicle and placed on a bus carrying platform (meanwhile, the unmanned aerial vehicle is charged on the bus), the unmanned aerial vehicle moves along with the bus until a background program determines a flying point according to an optimal path, the unmanned aerial vehicle takes off again to deliver the articles to a customer and sends the articles to a customer receiving point, a goods storage cabinet of the customer stop at the bus stop receives packages when the goods are sent to the customer receiving point, and the background detects the package state and sends goods taking information to the customer;

the bus carries on subsystem for the wireless platform of carrying of charging of unmanned aerial vehicle that utilizes setting and bus roof provides the long distance on the way and transports and charge midway for unmanned aerial vehicle provides the delivery route, the bus is whole to be gone according to normal route, each bus has unmanned aerial vehicle to carry on the system, when arriving a certain website, there may be unmanned aerial vehicle to carry on this system, also may not have unmanned aerial vehicle to carry on this system, backstage program can calculate which route and customer's terminal distance are more close, thereby select the route bus.

Intelligent terminal APP, this subsystem is the exclusive APP of product of development, can realize the organic connection of the delivery under the bill and the line of going down on the line, can make the user operation more convenient, form good product ecological environment, also can be used to provide the interface of making an order under the line, and show the delivery information in real time, this APP service has the tripartite, the trade company is posted, customer point addressee, post, most importantly, the backstage calculates the optimal route, can calculate in which website to post in the short time, get goods by which unmanned aerial vehicle, unmanned aerial vehicle takes which bus, unmanned aerial vehicle sends goods at which point, and provide to the user both sides simultaneously and post a sign indicating number, get the goods sign indicating number.

Another objective of the present invention is to provide a method for cooperative distribution in an unmanned aerial vehicle-bus area, which is applied to a system for cooperative distribution in an unmanned aerial vehicle-bus area, wherein the method for cooperative distribution in an unmanned aerial vehicle-bus area comprises:

step one, a user registers and logs in an account; the user sends a purchase demand; after receiving the order, the merchant generates a delivery code containing the bus stop and the route related decision;

secondly, the merchant transports the commodities to the matched public transportation station, and scans the codes of the commodities to enter a warehouse; the unmanned aerial vehicle grabs the goods which are put in a warehouse and places the goods on the bus-building platform to move along with the bus;

determining a flying point of the unmanned aerial vehicle according to the optimal path, and transporting the commodity to a delivery point appointed by a user; the user takes the goods by using the receiving code.

Further, the unmanned aerial vehicle and bus area combined collaborative distribution method further comprises the following steps:

(1) A login user sends a distribution demand containing the information of a designated receiving point and a receiver and generates a delivery code containing a bus stop and a route related decision;

(2) The user transports the goods to be delivered to the matched bus station; the unmanned aerial vehicle grabs the goods which are put in the warehouse and is placed on the bus lapping platform to move along with the bus;

(3) Determining the flying point of the unmanned aerial vehicle according to the optimal path, and transporting goods to be delivered to a delivery point appointed by a user; the user takes the goods by using the goods receiving code.

Further, before generating a delivery code containing bus stops and route related decisions, clustering analysis of users is required;

the user cluster analysis method comprises the following steps:

clustering customers by adopting a genetic algorithm of K-means clustering, and clustering and dividing according to the limitation conditions of the flight endurance mileage and the maximum load of the unmanned aerial vehicle, wherein the steps are as follows:

(1) Determining cluster number

Indicating the number of servings of all orders; q represents the maximum load of the drone, [ x ]]Represents rounding up on x;

(2) The spatiotemporal distance between customer points is calculated using the following equation:

wherein k represents a cluster number, the cluster number being the number of drones, z _i Representing all user points in the ith cluster;

(3) Initializing a population: carrying out decimal coding on individuals in the population by adopting natural integers, wherein the length of each individual is K, each digit of each individual represents a clustering center, and classifying all users according to a principle of proximity when the centers of the clusters are determined according to a K-means algorithm;

(4) Calculating objective function values of individuals in the population, and taking the objective function values as fitness values of the individuals; optimizing the population by selecting, crossing and varying individuals;

(5) Judging whether a termination condition is met; if yes, outputting a clustering analysis result; otherwise, returning to the step (1).

Further, the bus stop matching method comprises

1) The center of gravity of each cluster divided by the user nodes in the region is calculated by the following formula:

wherein (X) _(I) ,Y _(I) ) Representing the center of gravity of the ith cluster, i representing the ith customer in the ith cluster, and nI representing the number of users in the ith cluster, (x) _i ,y _i ) Two-dimensional coordinates representing the ith user;

2) Calculating the gravity center distance between a plurality of candidate stations and each cluster by using the following formula, and taking the candidate station with the minimum gravity center distance to each cluster as a screened bus station:

wherein j = 1.. N; w is a _j RepresentCost of use of the jth candidate station, (x) _j ,y _j ) Coordinates representing the jth candidate station, (a) _i ,b _i ) Expressing the barycentric coordinates of the ith cluster, and respectively expressing the number of the clusters and the number of candidate stations by m and n;

3) And judging whether the screened bus stops meet the user requirements, and if so, outputting corresponding arch springing stops.

Further, the optimal path determining method includes:

(1) Inputting node information of a flying point, a landing point and an obstacle area, judging whether straight line flight from the flying point to the landing point passes through an obstacle or not, if so, storing the flying point information into an OPEN LIST, turning to the step (2), and if not, directly ending the step;

(2) Traversing the current OPEN LIST, selecting a node corresponding to the minimum value of f (n), and unfolding: determining a first obstacle passing through from the node to a landing point, and putting available node information of the obstacle into OPENLIST, and simultaneously putting the expanded node in OPENLIST into CLOSE LIST;

wherein, f (n) is calculated as follows:

f(n)＝g(n)+h(n)；

in the formula, f (n) is expressed as an evaluation function of a node to be expanded and represents the estimated cost of reaching a target point from a starting point through a node n; g (n) represents the actual cost from the starting point to the current node n, h (n) represents the cost estimate from the current node n to the target point,

x _n ，x _G ，y _n ，y _G respectively representing the horizontal and vertical coordinates of the current node n and the falling point G;

(3) And (3) repeating the step (2), and ending the circulation when no obstacle exists between the expansion point and the drop point in the OPENLIST (namely the node information of the obstacle is empty) or the OPENLIST is empty, and outputting the optimal path.

Further, the objective function and constraint conditions of the unmanned aerial vehicle combined bus area collaborative distribution method are as follows:

wherein the content of the first and second substances,

constraint conditions are as follows:

secret；

wherein n is _p Which represents a node of a user's,

representing a user node n _p The package demand of (a); p is a radical of _i Representing a bus stop;

means at willBus stop p _i Open fixed costs;

representing user node n _p And site D _j The distance between them; t is _clu (i) Representing the time consumed by the drone to service customers within the cluster; t is t _p Representing departure time periods for each station; tau. _a (p _p S) unmanned aerial vehicle arrives at bus stop p in representation path s _p The time of day; tau is _d (p _p And s) represents the time when the unmanned aerial vehicle on the path s gets on the public transportation after waiting at the station;

representing the waiting time of the unmanned aerial vehicle at the bus station;

indicating the waiting time of the customer site.

Another object of the present invention is to provide a computer device, characterized in that the computer device includes a memory and a processor, the memory stores a computer program, and the computer program, when executed by the processor, causes the processor to execute the steps of the unmanned aerial vehicle cooperative distribution method in conjunction with a bus area.

Another object of the present invention is to provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the processor executes the steps of the method for cooperative distribution of unmanned aerial vehicles in conjunction with bus areas.

The invention also aims to provide an information data processing terminal which is used for realizing the unmanned aerial vehicle and bus area combined cooperative distribution system.

In combination with the technical solutions and the technical problems to be solved, please analyze the advantages and positive effects of the technical solutions to be protected in the present invention from the following aspects:

first, aiming at the technical problems existing in the prior art and the difficulty in solving the problems, the technical problems to be solved by the technical scheme of the present invention are closely combined with results, data and the like in the research and development process, and some creative technical effects are brought after the problems are solved. The specific description is as follows:

the bus and unmanned aerial vehicle coordinated distribution mode realized by the invention not only solves the problems of low cargo vehicle distribution efficiency and insufficient transportation capacity in the same city distribution, but also solves the problems of short endurance and limited flight distance of the unmanned aerial vehicle. The goods storage cabinets arranged at the bus station and the bus station of the target customer district are the best choices obtained by carrying out preference analysis by means of big data and reasonably screening, so that the construction cost is reduced, and meanwhile, better planning arrangement is provided for the navigation path of the unmanned aerial vehicle.

The bus and unmanned aerial vehicle cooperative distribution system provided by the invention can complete long-distance routes in distribution without flying from a distribution center to a customer door, and only needs to complete the distribution part of the last kilometer, so that the unmanned aerial vehicle driven by the battery can save electric quantity, improve endurance and reduce noise. For the bus, the invention can improve the utilization rate of the bus, increase the income of the bus and the like.

Secondly, considering the technical scheme as a whole or from the perspective of products, the technical effect and advantages of the technical scheme to be protected by the invention are specifically described as follows:

the invention provides a method for realizing urban logistics distribution by combining buses and unmanned planes, which can well solve the problems of endurance and load of the unmanned planes in the prior art, and on the other hand, the low-carbon and environment-friendly concept of public transportation is more and more accepted by the public, so that the development prospect is wide.

The invention provides safe professional distribution service for local consumers, and provides diversified services such as buying, delivering, taking, handling and the like; the system creates four products of brand, timeliness, economy and customization for all merchants, and aims to solve the distribution problem for various merchants in a one-stop way by using high-quality, high-efficiency and full-scene services.

Third, as an inventive supplementary proof of the claims of the present invention, there are also presented several important aspects:

(1) The expected income and commercial value after the technical scheme of the invention is converted are as follows:

the product is formulated to cooperate with a merchant with goods distribution demand at the initial stage, and meanwhile, the product is sent by receiving the APP which is independently downloaded by a personal consumer to the same area of small articles, and the optimization service of the consumer is performed. Meanwhile, the existing social platform is reasonably utilized to promote and recruit products, and the online sale and the promotion are synchronously carried out, so that the multi-channel sale is realized. After the product is further mature, the product cooperates with more small-sized enterprises and individual household and business companies, and the profit mode can be continued.

The invention creates a rapid, efficient and green distribution mode of the unmanned aerial vehicle and the bus, and has high commercial value. The unmanned aerial vehicle delivery number is called as 'air express delivery', which takes technical change and innovation service as the core, does not depend on ground traffic and the inherent advantages of terrain and topography, creates high-quality delivery service for users of high-value-added commodities, and enables the users to feel the leap of logistics service capability. Unmanned aerial vehicle has expanded the availability factor in space (from the plane to the solid), does not have the traffic congestion risk, therefore no aircraft will promote delivery efficiency by a wide margin. In the last three years, the cost of unmanned distribution of the whole vehicle is gradually reduced to be within 10 ten thousand yuan from 20 ten thousand yuan to 50 ten thousand yuan, and unmanned distribution of the race tracks is the first to come out. Carry on the bus and can accomplish long distance road in the distribution, need not to fly to client's door from the distribution center, only need accomplish the distribution part of "last kilometer", therefore can save the electric quantity, promote continuation of the journey, noise reduction by battery drive's unmanned aerial vehicle. For the bus, the product can improve the utilization rate of the bus, increase the income of the bus and the like.

(2) The technical scheme of the invention fills the technical blank in the industry at home and abroad:

at present, no unmanned aerial vehicle and bus distribution technology exists at home and abroad, and the technology provided by the invention fills the technical blank in the field at first. The application of unmanned aerial vehicles (vehicles) to improve distribution efficiency is a common consensus in the industry. At present, express logistics enterprises all start unmanned aerial vehicle express development and carry out unmanned aerial vehicle express test. However, the unmanned aerial vehicle has the limitation of load and flying distance, and can only deliver goods with specific specifications to customers within a certain range, so that the use of pure unmanned aerial vehicle for delivery is still limited. The problem of endurance and load of the unmanned aerial vehicle can be well solved by combining the bus and the unmanned aerial vehicle to realize urban logistics distribution, and on the other hand, the low-carbon environment-friendly concept of public transportation is more and more accepted by the public, so that the development prospect is wide. Unmanned aerial vehicle and bus are in coordination with the delivery both can solve the problem of unmanned aerial vehicle continuation of the journey and load, can realize green delivery again, is a big innovative achievement in the commodity circulation field.

(3) The technical scheme of the invention solves the technical problem that people are eager to solve but can not succeed all the time:

end delivery problems: in the face of multiple pressures that the end distribution demand is increased day by day, distribution pain points continuously exist and labor population is reduced continuously, a plurality of solutions are provided for the market, such as co-distribution, self-lifting cabinets, self-lifting convenience stores and the like, and the problems are relieved to a certain extent. However, the problem of logistics distribution of the last kilometer cannot be completely solved by only depending on manual distribution. The unmanned aerial vehicle is incorporated into a logistics distribution system at the tail end of a city, and the distribution problem of the last kilometer can be greatly solved. In certain environments and conditions, efficient delivery can only be achieved with drone traffic, which is not otherwise available. For example, when people or life bodies are trapped in a certain high-rise building or a certain place of a mountain, a lake and a sea and urgently need life and rescue goods and materials, the unmanned aerial vehicle can realize extremely efficient and accurate delivery. Compare in general air transportation and navigation transport mode, the unmanned aerial vehicle transportation has advantages such as with low costs, the dispatch is nimble to can fill current air traffic capacity blank. Meanwhile, the restriction of human factors such as pilots and aircrafts is reduced in capacity scheduling. In addition, in some remote mountain areas and river sea dangerous areas, land transportation and water transportation are extremely inconvenient, and the unmanned aerial vehicle is suitable for transportation.

The cost problem is as follows: the cost of the logistics industry is always high, and compared with air transportation, the technical scheme greatly reduces the logistics labor cost. In the long term, the purchase cost of the unmanned aerial vehicle is lower than the labor cost; unmanned aerial vehicle can improve long distance logistics distribution efficiency in the same region, reduces logistics distribution time, alleviates trade company's delivery burden.

Drawings

Fig. 1 is an architecture diagram of a cooperative distribution system for unmanned aerial vehicles and bus areas provided by an embodiment of the present invention;

fig. 2 is a schematic diagram of picking and placing goods by an unmanned aerial vehicle according to an embodiment of the present invention; wherein, fig. 2 (a) open states of the drone and the pick-up facility; fig. 2 (b) drone and pick-up facility off state;

fig. 3 is a diagram of a bus carrying subsystem provided by an embodiment of the present invention, and fig. 3 (a) is a front view of a bus carrying unmanned aerial vehicle; fig. 3 (b) top view of the unmanned aerial vehicle carrying platform;

FIG. 4 is a schematic view of a cargo storage cabinet for a bus station according to an embodiment of the present invention; wherein, fig. 4 (a) the bus station goods storage cabinet (closed state); fig. 4 (b) the bus station cargo holder (open state);

fig. 5 is a functional schematic diagram of an unmanned aerial vehicle system provided by an embodiment of the present invention;

FIG. 6 is a schematic diagram of a bus-mounted subsystem provided by an embodiment of the invention;

fig. 7 is a flowchart of an implementation of the unmanned aerial vehicle combined with the bus area collaborative distribution system according to the embodiment of the present invention;

fig. 8 is a flow chart of a method for area collaborative distribution of an unmanned aerial vehicle and a bus according to an embodiment of the present invention;

fig. 9 is a schematic diagram of coordinated delivery of public transport unmanned aerial vehicles according to an embodiment of the present invention;

FIG. 10 is a flow chart of a method for sending a purchase request from a consumer according to an embodiment of the present invention;

fig. 11 is a flowchart of a method for sending a distribution demand by a consumer according to an embodiment of the present invention.

Fig. 12 is a schematic diagram of a cooperative distribution system combining an unmanned aerial vehicle and a bus area according to another embodiment of the present invention;

FIG. 13 is a comparison of various delivery distances provided by embodiments of the present invention;

FIG. 14 is a comparison of various distribution costs provided by embodiments of the present invention;

in the figure: 1. an unmanned aerial vehicle system; 2. a bus carrying subsystem; 3. intelligent terminal APP.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.

1. Illustrative embodiments are explained. This section is an illustrative example developed to explain the claims in order to enable those skilled in the art to fully understand how to implement the present invention.

Example 1

As shown in fig. 1, the unmanned aerial vehicle and bus area cooperative distribution system provided in the embodiment of the present invention includes:

the unmanned aerial vehicle system 1 comprises an unmanned aerial vehicle and unmanned aerial vehicle stations arranged in a bus station and a user community; the unmanned aerial vehicle is used for executing distribution tasks and storing user articles, when the articles are sent to a bus stop, the articles are grabbed by the unmanned aerial vehicle and placed on a bus carrying platform (meanwhile, the unmanned aerial vehicle is charged on the bus), the unmanned aerial vehicle moves along with the bus until a background program determines a flying point according to an optimal path, the unmanned aerial vehicle takes off again to deliver the articles to a customer and sends the articles to a customer receiving point, a goods storage cabinet of the customer stop at the bus stop receives packages when the goods are sent to the customer receiving point, and the background detects the package state and sends goods taking information to the customer; as shown in fig. 2, the schematic diagram of the unmanned aerial vehicle pick and place goods, wherein fig. 2 (a) shows the open states of the unmanned aerial vehicle and the goods pick-up facility; fig. 2 (b) drone and pick-up facility off state;

subsystem 2 is carried on to the bus for the wireless platform of carrying that charges of unmanned aerial vehicle that utilizes setting and bus roof provides the long distance on the way and transports and charge midway for unmanned aerial vehicle delivery route, the bus is whole to be gone according to normal route, each bus has unmanned aerial vehicle to carry on the system, when arriving a certain website, there may be unmanned aerial vehicle to carry on this system, also may not have unmanned aerial vehicle to carry on this system, backstage program can calculate which route and customer's terminal distance are more close, thereby select the route bus. As shown in fig. 3, the bus carrying subsystem, fig. 3 (a) is a front view of the bus carrying the unmanned aerial vehicle; fig. 3 (b) top view of the unmanned aerial vehicle carrying platform;

the goods storing compartment of the bus station can be in high automatic cooperation with an unmanned aerial vehicle and can be seamlessly connected, automatic take-off and landing of the unmanned aerial vehicle can be achieved, automatic loading and unloading of goods are carried, and automatic classification of express mails and a series of intelligent functions such as express mail access based on identity comparison and real-name authentication are achieved. When the unmanned aerial vehicle falls to the top of the goods storage cabinet, the infrared scanner at the top end of the cabinet body scans the bar code of the unmanned aerial vehicle, the parking apron at the top end of the storage cabinet is opened after successful recognition, the unmanned aerial vehicle picks or unloads corresponding goods and flies away from the goods storage cabinet, and the top of the cabinet is closed. In addition, the storage cabinet can scan the bar code on the goods express bill, and the goods that will lift off are sent to the customer simultaneously and get goods information in corresponding express check automatically sorted. Fig. 4 (a) shows a goods storage cabinet (closed state) of a bus station; fig. 4 (b) the bus station cargo holder (open state).

The intelligent terminal APP 3 is a developed product exclusive APP, can realize organic connection of online ordering and offline distribution, can enable user operation to be more convenient and faster, forms a good product ecological environment, can also be used for providing an online ordering interface and displaying distribution information in real time;

this APP service has the tripartite, and the trade company is posted, customer point addressee, is posted, and the most important backstage calculates optimal route, can calculate in the short time and post at which website, by which unmanned aerial vehicle get goods, unmanned aerial vehicle take which bus, unmanned aerial vehicle send goods at which point to send goods to provide to the user both sides simultaneously and post the sign indicating number, get the goods sign indicating number.

Example 2

As shown in fig. 5, the unmanned aerial vehicle provided by the embodiment of the present invention is combined with a bus area cooperative distribution system, and further, the unmanned aerial vehicle system is divided into two parts, namely a hardware facility and a software facility, wherein the hardware facility includes an unmanned aerial vehicle and an unmanned aerial vehicle delivery operation cabinet; the software facility comprises three subsystems of an information collection system, an information processing system and a safety early warning system. The information collection system is responsible for collecting data such as customer order data, goods receiving and dispatching places and the like; the information processing system is responsible for planning a route for the unmanned aerial vehicle according to the current bus running state and the cargo receiving and dispatching points; the safety early warning system is responsible for feeding back important information such as the electric quantity, the position and the flight state of the unmanned aerial vehicle.

Example 3

As shown in fig. 6, based on the unmanned aerial vehicle provided by the embodiment of the present invention and the bus regional collaborative distribution system, further, the bus carrying subsystem is divided into two parts, namely a hardware facility and a software facility, wherein the hardware facility includes an unmanned aerial vehicle carrying charging station and a bus goods storage cabinet; the software facility comprises an information feedback system and an unmanned aerial vehicle charging system. The information feedback system feeds the current bus running state information such as GPS (global positioning system), driving time and the like back to the unmanned aerial vehicle system, so that the unmanned aerial vehicle system can calculate an optimal line; the unmanned aerial vehicle charging system can display the electric quantity state of the charging facility above the bus in real time.

Example 4

As shown in fig. 7, an implementation process of the unmanned aerial vehicle and the bus area collaborative distribution system provided by the embodiment of the present invention includes: unmanned aerial vehicle sets out from the warehouse, carries on the public transit and moves according to fixed line, fixed timetable, when apart from the optimal position of customer point distance, unmanned aerial vehicle takes off and flies to the customer point and deliver, and after the delivery task was accomplished, unmanned aerial vehicle need go to near station and carry on the public transit forward to next delivery area or return warehouse.

Example 5

As shown in fig. 8, the method for cooperative distribution by combining an unmanned aerial vehicle and a bus area provided by the embodiment of the present invention includes:

s101, a user registers and logs in an account; the user sends a purchase demand; after receiving the order, the merchant generates a delivery code containing the bus stop and the route related decision;

s102, a merchant transports the commodities to the matched bus station, and scans the codes of the commodities to be put into a warehouse; the unmanned aerial vehicle grabs the goods which are put in a warehouse and places the goods on the bus-building platform to move along with the bus;

s103, determining a flying point of the unmanned aerial vehicle according to the optimal path, and transporting the commodity to a delivery point appointed by a user; the user takes the goods by using the receiving code.

Example 6

As shown in fig. 9, the method for cooperatively delivering by a bus and an unmanned aerial vehicle provided by the embodiment of the present invention includes:

the cooperative distribution of the public transport unmanned aerial vehicle is carried out through three scenes: scene A is that a businessman receives an order at a certain moment, and places delivered articles to an automatic goods taking platform of a nearby bus station, and an unmanned aerial vehicle brings the articles above the bus; scene B is that the unmanned aerial vehicle runs along with the bus according to the bus route, and meanwhile, the unmanned aerial vehicle is charged; and the scene C is that the unmanned aerial vehicle takes off according to the preset planned optimal path, avoids obstacles such as terrain and the like, and delivers the delivered articles to a customer goods taking point.

The method specifically comprises the following steps:

different commercial tenants and possible customer demand points are scattered near a certain bus route in a city, customers send demands through an intelligent terminal APP, according to various factors such as customer position points, merchant position points and the current running situation of the bus route, the system automatically calculates a bus and unmanned aerial vehicle service route with the optimal time cost, a scene A shows that an unmanned aerial vehicle system receives an order, captures goods at a bus goods cabinet and waits for taking an upcoming bus; when the bus arrives at a designated station, the unmanned aerial vehicle carries the goods to carry the bus, and then the unmanned aerial vehicle runs on a fixed line along with the bus, as shown in a scene B; in the process of the unmanned aerial vehicle accompanying the bus, the unmanned aerial vehicle system selects a better accompanying route (such as a transfer bus, a switching route and the like) in real time by combining the current road condition (namely the running condition of the bus), and when the bus runs to the position closest to a customer demand point, the unmanned aerial vehicle takes off immediately and carries goods to fly to a customer goods storage cabinet, such as a scene C; and the unmanned aerial vehicle which finishes the service returns to the nearest stop station to charge and wait for the next flight task.

Example 7

As shown in fig. 10, the method for sending a purchase request by a consumer according to an embodiment of the present invention includes:

(1) The consumer in need orders the goods to be purchased on the platform.

(2) After receiving the order, the merchant generates a delivery code containing the bus stop and the route related decision; then, the commodities are sent to a designated bus stop, and the commodities are put in a warehouse through code scanning.

(3) After receiving the instruction, the unmanned aerial vehicle reaches the goods storage cabinet of the bus station to grab goods and places the goods on the bus-building platform to move along with the bus.

(4) Determining a flying point of the unmanned aerial vehicle according to the optimal path, and transporting goods to be delivered to a delivery point appointed by a user; the user takes the goods by using the receiving code.

Example 8

As shown in fig. 11, the method for cooperative distribution by combining an unmanned aerial vehicle and a bus area provided by the embodiment of the present invention further includes:

(1) A login user sends a delivery demand containing the information of a designated receiving point and a receiver, and generates a delivery code containing a bus stop and a route related decision;

(2) The user transports the goods to be delivered to the matched bus station; the unmanned aerial vehicle grabs the goods which are put in a warehouse and places the goods on the bus-building platform to move along with the bus;

(3) Determining a flying point of the unmanned aerial vehicle according to the optimal path, and transporting goods to be delivered to a delivery point appointed by a user; the user takes the goods by using the receiving code.

Example 9

Based on the unmanned aerial vehicle and bus regional collaborative distribution method provided by the embodiment 8 of the invention, further, before generating the delivery code including bus stop and route related decision provided by the step (1) of the embodiment of the invention, user clustering analysis is required.

The user cluster analysis method provided by the embodiment of the invention comprises the following steps:

(1) Determining cluster number

Number of food items representing all orders; q represents the maximum load of the drone, [ x [ ]]Presentation pairRounding the x direction;

wherein k represents the number of clusters, which is the number of drones, z _i Representing all user points in the ith cluster;

Example 10

Based on the unmanned aerial vehicle and bus area collaborative distribution method provided by the embodiment 8 of the invention, further, in the step (2) of the embodiment of the invention, the provided bus stop matching method comprises the following steps:

wherein (X) _(I) ,Y _(I) ) Represents the center of gravity of the ith cluster, i represents the ith customer in the ith cluster, and nI represents the number of users in the ith cluster, (x) _i ,y _i ) Two-dimensional coordinates representing the ith user;

wherein j = 1.. N; w is a _j Represents the use cost of the jth candidate station, (x) _j ,y _j ) Coordinates representing the jth candidate station, (a) _i ,b _i ) Expressing the barycentric coordinates of the ith cluster, and respectively expressing the number of clusters and the number of candidate stations by m and n;

The optimal path determining method provided by the embodiment of the invention comprises the following steps:

wherein, f (n) has the following calculation formula:

f(n)＝g(n)+h(n)；

x _n ，x _G ，y _n ，y _G respectively representing the horizontal and vertical coordinates of the current node n and the drop point G;

Example 11

Based on the cooperative distribution method of the unmanned aerial vehicle and the bus area provided by the embodiment 9 of the present invention, further, in the step (4), the objective function and the constraint condition of the cooperative distribution method of the unmanned aerial vehicle and the bus area provided by the embodiment are as follows:

wherein the content of the first and second substances,

constraint conditions are as follows:

secret；

wherein n is _p A representation of a node of a user is shown,

representing any bus stop p _i Open fixed costs;

representing user node n _p And site D _j The distance therebetween; t is _clu (i) Representing the time consumed by the drone to service customers within the cluster; t is t _p Representing departure time periods for each station; tau is _a (p _p S) indicates that the drone arrives at the bus stop p in the path s _p The time of day; tau is _d (p _p And s) represents the time when the unmanned aerial vehicle on the path s gets on the public transportation after waiting at the station;

indicating the waiting time of the customer site.

Example 12

As shown in fig. 12, the embodiment of the present invention provides an unmanned aerial vehicle and bus area cooperative distribution system, which is formed by three subsystems. The first is an unmanned aerial vehicle subsystem, including unmanned aerial vehicle and set up the unmanned aerial vehicle website in bus station and customer's district, this subsystem mainly undertakes the function of delivery task and storage customer's article. The second is bus carries on the subsystem, places the wireless platform of carrying that charges of unmanned aerial vehicle at the bus roof mainly, and the function of this subsystem is for the unmanned aerial vehicle provides long distance transport on the way and midway to charge of delivery route. The third is "flying the crust" APP subsystem, and this subsystem is the exclusive APP of product of development, can realize about the line list and the organic connection of distribution under the line, can make the user operation more convenient, forms good product ecological environment.

2. Application examples. In order to prove the creativity and the technical value of the technical scheme of the invention, the part is the application example of the technical scheme of the claims on specific products or related technologies

Application examples

Based on the unmanned aerial vehicle and bus area cooperative distribution system provided by the embodiment, the combined system provided by the embodiment of the invention can solve several problems, for example, a bus is carried to complete a long-distance route in distribution, the bus does not need to fly to a customer door from a distribution center, and only a last kilometer distribution part needs to be completed, so that the unmanned aerial vehicle driven by a battery can save electric quantity, improve endurance and reduce noise. For the bus, the product can improve the utilization rate of the bus, increase the bus income and the like.

The algorithm model of the unmanned aerial vehicle and bus area cooperative distribution system provided by the embodiment of the invention is as follows:

scene A is that a merchant receives an order at a certain moment, and places delivered articles to an automatic goods taking platform of a nearby bus station, and an unmanned aerial vehicle brings the articles to the upper part of the bus; scene B is that the unmanned aerial vehicle runs along with the bus according to the bus route, and meanwhile, the unmanned aerial vehicle is charged; and the scene C is that the unmanned aerial vehicle takes off according to the preset planned optimal path, avoids obstacles such as terrain and the like, and delivers the delivered articles to a customer goods taking point.

The following assumptions are made in combination with the bus characteristics of the unmanned aerial vehicle:

(1) The bus departure intervals are dense, and the departure punctuality rate can be ensured to a certain extent, so that the endurance problem of the bus does not need to be considered;

(2) The cruising mileage of the unmanned aerial vehicle is 20km, the charging process on the bus can be realized, and the two round-trip flight tasks of goods taking and delivery can be sufficiently realized, so that the cruising problem of the unmanned aerial vehicle is not considered;

(3) The unmanned aerial vehicle speed is constant, and the running speed of the bus is set to be a congestion coefficient a (0.2-0.8);

(4) Standardizing the mass and volume of each delivered article, namely, the delivery demand sent by a client can only be integral multiples of a unit fixed value lower than the load requirement of the unmanned aerial vehicle;

(5) The unmanned aerial vehicle has capacity limitation, and each bus carries 2 unmanned aerial vehicles at most;

(6) Weather conditions, traffic conditions and other accidents encountered by the unmanned aerial vehicle in flight are not considered;

stage one: customer clustering

Clustering customers by adopting a genetic algorithm of K-means clustering, and clustering and dividing according to the limitation conditions of flight endurance mileage and maximum load of the unmanned aerial vehicle, wherein an objective function is as shown in formula (1), and the objective function is to minimize the space-time distances from all clustering clusters, other customer points to a clustering center. Where k is the number of clusters, i.e. the number of drones, z _i For all customer points in the ith cluster.

(1) Determining cluster number

Representing the number of food items of all orders, Q being the maximum load of the drone, [ x [ ]]Represents rounding up x;

(2) Calculating the space-time distance between the customer points according to the formula;

(3) And initializing the population. The method comprises the steps of adopting decimal coding of natural integers for individuals in a population, setting the length of the individuals as K, enabling each digit of the individuals to represent a clustering center, and classifying all customers according to the principle of proximity when the centers of clusters are determined according to the thought of a K-means algorithm;

(4) Calculating objective function values of individuals in the population, and taking the objective function values as fitness values of the individuals;

(5) And (5) population evolution. Optimizing the population by selecting, crossing and varying individuals;

(6) And judging whether the termination condition is met. If yes, ending; NO, return to (1)

And a second stage: bus stop selection and customer allocation

Dividing customer nodes in the region into a plurality of clusters clu through a clustering algorithm of a previous stage _i ＝{clu ₁ ,clu ₂ ,...,clu _k And calculating the gravity center of each cluster according to a formula, wherein the gravity center calculated by the formula (2) is taken as a representative of each cluster, so that a proper station can be selected from different candidate station sets:

in the formula (X) _(I) ,Y _(I) ) Is the center of gravity of the ith cluster, i represents the ith customer in the ith cluster, and nI represents the number of customers in the ith cluster, (x) _i ,y _i ) Representing the two-dimensional coordinates of the ith customer. By defining the gravity center of each cluster, the invention can start to select a proper station as an unmanned aerial vehicle getting-off point between candidate stations. A classical single facility siting problem solution is used to select the appropriate station. In the classical facility siting problem, a station with the smallest distance to the center of gravity is selected, where the distance is calculated as the euclidean distance as equation (3).

Candidate station coordinates (x) ^* ,y ^* ) Is represented as follows:

wherein j = 1.. N; w is a _j Cost of use for jth candidate station, (x) _j ,y _j ) Coordinates of jth candidate station, (a) _i ,b _i ) The barycentric coordinates of the ith cluster, m and n, respectively represent the number of clusters and the number of candidate stations. If the selected stop can meet the customer's demand, 0 public transportation stop selection will stop. The siting phase is stopped when all stations selected can cover the customer's needs within the area.

And a third stage: unmanned aerial vehicle obstacle avoidance track planning

The algorithm A searches the adjacent nodes at the current position, selects the node with the minimum cost value as an expansion node to be added into a search space, generates a new expansion node until the target point is selected as the expansion node, and then carries out reverse tracing from the target node to find a path with the minimum cost from a starting point to the target point. The cost function of the node n in the A-algorithm is as follows:

f(n)＝g(n)+h(n) (4)

where f (n) is an evaluation function of the node to be expanded and represents an estimated cost for reaching the target point from the starting point via the node n, g (n) is an actual cost from the starting point to the current node n, and h (n) represents an estimate of the cost from the current node n to the target point. And when the next node is expanded by the A-algorithm, selecting the node with the minimum estimated cost value f (n) from the nodes to be selected and inserting the node into the path linked list.

Aiming at the problem of planning the obstacle avoidance flight path of the two-dimensional plane unmanned aerial vehicle, the invention designs an A-star algorithm as follows. Setting a take-off station S and a landing station G of the unmanned aerial vehicle and node information of each obstacle area, and establishing an OPEN LIST and a CLOSE LIST of two pieces of storage node information. Since the objective is to minimize the flight distance of the drone, the cost considered in equation (4) is the range of the drone, G (n) represents the flown range from the takeoff station S to the node n to avoid the obstacle, h (n) represents the straight-line distance from the current node n to the landing point G without considering the obstacle area,

x _n ，x _G ，y _n ，y _G respectively are the horizontal and vertical coordinates of the current node n and the falling point G,

the algorithm comprises the following specific steps:

(1) Inputting node information of a flying point, a landing point and an obstacle area, judging whether straight line flying from the flying point to the landing point passes through an obstacle or not, if so, storing the flying point information into an OPEN LIST, and turning to (2); if not, the process is finished directly.

(2) And traversing the current OPEN LIST, finding a node corresponding to the minimum value of f (n) and expanding, namely finding a first obstacle passing from the node to the drop point, putting available node information of the obstacle into the OPEN LIST, and simultaneously putting the expanded node in the OPEN LIST into the CLOSE LIST.

(3) And (2) repeating, and ending the cycle when no obstacle exists between the expansion point and the drop point in the OPEN LIST (namely the node information of the obstacle is empty) or the OPEN LIST is empty.

TABLE 3 variable definitions

Objective function and constraint:

customer node n _p The package demand is

The unmanned aerial vehicle selects a proper bus station as a take-off point and a landing point of each customer cluster distribution task, the unmanned aerial vehicle returns to the station to take the bus after distribution is completed, and the set p represents a bus station set. For any bus stop p _i With an open fixed cost of

Customer node n _p And site D _j Is a distance of

T _clu (i) Time consumed by drone to service customers within a cluster:

assuming that departure time of each station is consistent and is according to a period t _p Departure, starting the first bus at a time every day, and the stations are [ a + kt ] _p ,b+kt _p ,k＝0,1,2,,]Can supply unmanned aerial vehicle to take in the time quantum. Suppose that the drone is at b + kt _p When the station arrives at the moment, the bus can not take the bus, and the bus can only wait for the next shift. Let τ be _a (p _p ,s) Indicating that the unmanned aerial vehicle arrives at the bus stop p in the path s _p Time of (c), τ _d (p _p And s) represents that the time when the unmanned aerial vehicle gets on the public transportation after waiting at the station in the route s is as follows:

waiting time of unmanned aerial vehicle at bus station

Waiting time of client site

The calculation formula is as follows:

in summary, the following steps: the objective function of the model problem involved in the present invention is simplified as follows:

constraint conditions are as follows:

secret (13)

formula (9) ensures that the total amount of customer demands in the clustered cluster is not greater than the maximum load of the unmanned aerial vehicle, and formula (10) ensures that the unmanned aerial vehicle can reach each node in the customer cluster. Equation (11) ensures that customer nodes are matched to only one site, and equation (12) ensures that each customer cluster is accessed in only one global path.

The page of the unmanned aerial vehicle and bus area cooperative distribution system provided by the embodiment of the invention comprises the following steps:

the new user interface: the user who uses the Feiba express for the first time enters the interface, the resident merchant selects the merchant edition, and the common user selects the personal edition.

Trade edition:

"merchant version" interface:

the merchant is resident in the interface and uploads shop information including business license, contact phone and the like.

Store interface (O bao pet store for example):

merchants can manage stores through the page, and the functions comprise income statistics, asset management, order management, asset management, store introduction and store evaluation;

a service information interface:

the interface is used for the functions of selection of distribution service by merchants, selection of adaptive bus stops, service time, service cost and the like.

"delivery service": the merchant can select a self-distribution or femto distribution service mode;

"selection to adapt to bus stops": a merchant selects a proper bus line and a proper bus stop according to the self requirement;

"service time": the merchant selects the work of the shop, namely the order receiving time;

product management, store order interface:

the interface relates to functions of putting products on shelves, putting products off shelves, storing orders and the like of stores, supports merchants to check details of the stores at any time, and is simple and rapid to operate.

Personal edition:

personal version interface:

the interface comprises 'I buy goods', 'I send goods', 'merchant deposit', and relates to different functions and different application scenes.

The purchase interface:

the customer inputs keywords in the search bar, and the background automatically screens out the required articles closest to the customer.

An order confirmation interface:

the customer selects the item to place an order, inputs the receiving address, the system calculates the amount of the order, and after placing the order, the payment is displayed to be successful and the goods taking code is generated.

A logistics detail interface:

after the customer successfully places an order, clicking the logistics details to see the delivery details and the delivery time of the current article.

"I want to send goods" interface:

the function is used by customers with goods sending requirements, the sending information, the receiving address and the like are input, and the information such as the logistics direction, the delivery time and the like can be checked at any time after the order is generated.

The process provided by the embodiment of the invention comprises the following steps: the method comprises two processes of the consumer sending a purchase demand and the consumer sending a distribution demand.

The 'flying bar' regional distribution system provided by the embodiment of the invention is composed of a distribution unmanned aerial vehicle, an unmanned aerial vehicle station depending on a bus station, a bus carrying platform and a flying bar APP.

1. Hardware device preparation: the main vehicles (drones) required by the distribution system can be purchased from the drone manufacturer and loaded with the system code provided by the invention.

2. Software APP development: the good product ecological chain is formed and the exclusive matched APP of the flying bar is necessarily required to be developed, users with different requirements can order the APP, and the APP can realize the functions of ordering in real-time shopping, ordering in real-time distribution, order state tracking and the like.

3. Cooperating with a public transportation group: because the system needs to be carried with the bus, negotiation and cooperation with a bus group are needed, partial buses in a trial run area are modified, and the unmanned aerial vehicle carrying platform capable of being charged wirelessly is arranged on the top of the bus.

The application method of the unmanned aerial vehicle and bus area combined collaborative distribution system provided by the embodiment of the invention comprises the following steps:

(1) User registration

A user A is a certain resident of a community in front of a sky and a rain mountain in the southern coast region and is a take-away software enthusiast, all take-away software in the industry is basically used by the user A, and on a certain day, the user A sees a brand-new APP on a mobile phone and is named 'flying bar', so that the user A is said to play a new mode of 'unmanned aerial vehicle + bus delivery', play a curious role in exploring the competition, click downloaded software and register an account number.

(2) User receiving and sending article

On a certain day, the user A suddenly wants to eat fresh fruits at home, but a large fruit store is far away in the neighborhood of the community, so that the user A opens the newly downloaded software, orders the fruits delivered in the same city up and down on the 'flying bar' software, only needs to wait for a while, and clicks the 'I need to pick up the goods', and the fruits delivered in the same city can be received at the goods pick-up point in the neighborhood of the community.

On the day, the user A is on vacation at home, but the company urgently needs a document, so the user A opens the software of 'flying bus', clicks 'express mail' on the home page, inputs the contact way of a sender and a receiver, clicks an article letter, clicks an order after inputting article information, and can check the specific delivery condition of the article in the period.

(3) Merchant registration

The merchant B is an offline pet store, the loss of the physical store is large in recent years, but the market of pet supplies is really in demand, so that the merchant B intends to open an online network to serve customers in the same city, and in a certain day, the customers see the advertisement of the 'flying bar' when taking a bus, and think that the advertisement meets the demand of the customers, so the customers open a mobile phone, download software and register accounts.

(4) Posting article for merchant

The store B owner who just opens is welcomed by the majority of users as soon as opening, though the operation is slow before the system is not familiar in the early stage, but the store B owner is skillful in the later stage, only needs to put on the shelf and set the stock every day, and regularly participates in a lot of promotion, so that the customer can wait for ordering, and after ordering, the customer only needs to send the product to the unmanned aerial vehicle station, check and sell the two-dimensional code, and then can automatically start distribution.

The unmanned aerial vehicle and bus combined regional collaborative distribution method provided by the embodiment of the invention is applied to computer equipment, the computer equipment comprises a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor, so that the processor executes the steps of the unmanned aerial vehicle and bus combined regional collaborative distribution method.

The unmanned aerial vehicle and bus combined regional collaborative distribution method provided by the embodiment of the invention is applied to a computer readable storage medium, a computer program is stored, and when the computer program is executed by a processor, the processor executes the steps of the unmanned aerial vehicle and bus combined regional collaborative distribution method.

The unmanned aerial vehicle and bus combined regional collaborative distribution method provided by the embodiment of the invention is applied to an information data processing terminal, and the information data processing terminal is used for realizing the unmanned aerial vehicle and bus combined regional collaborative distribution system.

3. Evidence of the relevant effects of the examples. The embodiment of the invention achieves some positive effects in the process of research and development or use, and has great advantages compared with the prior art, and the following contents are described by combining data, diagrams and the like in the test process.

Example (c): taking Chongqing 303 bus route as an example, 5 nearby customer points and 1 nearby warehouse point are selected, and longitude and latitude coordinates of each point are picked up through a Baidu map and are shown in a table 4;

TABLE 4

Node point	Longitude (longitude)	Latitude
			0	106.544984	29.387409
1	106.55368	29.391248
			2	106.55332	29.384765
3	106.552278	29.390083
			4	106.553967	29.406321
5	106.547068	29.408334

303 a transit route part station longitude and latitude meter 5;

TABLE 5

Number of	Site name	Longitude (G)	Latitude
				S1	Longzhou bay junction station	106.546896	29.383308
S2	Fish lake crossing	106.543857	29.382096
				S3	Intersection of major roads of Longzhou	106.540904	29.383054
S4	Minghua Longzhou province	106.541837	29.385887
				S5	Yanlongshan water	106.542945	29.391205
S6	Future of city	106.544275	29.395264
				S7	Longzhou park	106.544874	29.3989
S8	Longzhou dao	106.544587	29.405777
				S9	Middle section of Longzhou avenue	106.544543	29.40834
S10	New Longwan	106.544563	29.413347

The running speed of the vehicle on a general urban road is 40 km.h ^-1 The unit distance driving cost of the truck is 1.5 yuan/km and the no-load speed of the unmanned aerial vehicle is 50 km.h ^-1 The maximum straight-line distance of the unmanned plane is 20km, the load limit of the unmanned plane is 5kg, and the flight speed and load influence factor of the unmanned plane is 2km (h.kg) ^-1 The unit distance transportation cost of the unmanned aerial vehicle is 0.3 yuan/km, the demand of each customer is 2kg, the customers adopt independent delivery of trucks and unmanned aerial vehicles or delivery of buses and unmanned aerial vehicles, and the comparison results of time, average driving paths and delivery cost are as follows:

truck distribution: the method is characterized in that the load limit of a truck is not considered, the speed time change caused by urban road congestion is analyzed, the problem is simplified into that the TSP is solved to obtain the optimal path distance as follows: 3.61km, service time: 0.67775h.

Unmanned aerial vehicle delivery: considering unmanned aerial vehicle load limit, converting the problem into a vehicle path problem with capacity limit, and solving to obtain an optimal path distance: 5.41km, service time: 0.3082h.

Unmanned aerial vehicle + public transit delivery: analyzing the load of the unmanned aerial vehicle, inputting data points into the system according to the idea of the invention, and obtaining the optimal flight distance: 3.41km, which takes 0.7532h. As in table 6.

TABLE 6

The distribution distance comparison is shown in fig. 13, and the distribution cost comparison is shown in fig. 14.

In conclusion, the bus and unmanned aerial vehicle delivery mode has obvious advantages in delivery distance and delivery cost compared with the mode that a truck and an unmanned aerial vehicle are delivered independently in example demonstration, but has certain defects in delivery time due to the limitation of the bus shift interval; compared with independent delivery of trucks and unmanned planes, the invention has great advantages in the aspects of green, low carbon and sustainability.

It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portions may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus of the present invention and its modules may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, or software executed by various types of processors, or a combination of hardware circuits and software, e.g., firmware.

The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.

Claims

1. The utility model provides an unmanned aerial vehicle combines regional delivery system in coordination of bus which characterized in that, unmanned aerial vehicle combines regional delivery system in coordination of bus includes:

the unmanned aerial vehicle system is used for executing distribution tasks, storing user articles, detecting the received packages and sending goods taking information to the customers;

the bus carrying subsystem is used for providing long-distance transportation and midway charging on a distribution road for the unmanned aerial vehicle by utilizing the unmanned aerial vehicle wireless charging carrying platform arranged on the top of the bus;

and the intelligent terminal APP is used for organically connecting the online ordering and offline distribution and displaying distribution information in real time through the online ordering interface.

2. Unmanned aerial vehicle and bus area cooperative distribution system as claimed in claim 1, wherein the unmanned aerial vehicle and bus area cooperative distribution system

The unmanned aerial vehicle system comprises an unmanned aerial vehicle and unmanned aerial vehicle stations arranged in a bus station and a user community; when goods are sent to a bus station, the unmanned aerial vehicle grabs the goods and places the goods on a bus carrying platform, the unmanned aerial vehicle moves along with the bus until a background program determines a flying point according to an optimal path, the unmanned aerial vehicle takes off again to deliver the goods to a customer and sends the goods to a customer receiving point, the customer receives the packages when the customer orders a goods storage cabinet of the bus station, and the background detects the package state and sends goods taking information to the customer;

the buses of the bus carrying subsystem run according to normal routes in the whole process, each bus is provided with an unmanned aerial vehicle carrying system, when a certain station is reached, a background program calculates which route is closer to a client terminal point, and a route bus is selected;

the intelligent terminal APP includes that a merchant sends a mail, a customer point receives a mail, sends a service function, the background calculates an optimal path, a station where the mail is sent is calculated in a short time, goods are taken by an unmanned aerial vehicle, the unmanned aerial vehicle takes a bus and the unmanned aerial vehicle sends goods at the point, and meanwhile, a mail code and a goods code are sent to both sides of a user.

3. An unmanned aerial vehicle and bus area cooperative distribution method applied to the unmanned aerial vehicle and bus area cooperative distribution system according to claim 1, wherein the unmanned aerial vehicle and bus area cooperative distribution method comprises the following steps:

4. The regional collaborative distribution method of unmanned aerial vehicles in combination with buses as claimed in claim 3, wherein the regional collaborative distribution method of unmanned aerial vehicles in combination with buses further comprises:

(3) Determining a flying point of the unmanned aerial vehicle according to the optimal path, and transporting goods to be delivered to a delivery point appointed by a user; the user takes the goods by using the goods receiving code;

before generating delivery codes containing bus stops and route related decisions, user clustering analysis is required;

the user cluster analysis method comprises the following steps:

(1) Determining a cluster number

Number of food items representing all orders; q represents the maximum load of the drone, [ x [ ]]Represents rounding up x;

5. The unmanned aerial vehicle and bus area cooperative distribution method as claimed in claim 3, wherein the bus stop matching method comprises:

1) The center of gravity of each cluster divided by the user nodes in the area is calculated by the following formula:

wherein j = 1.. N; w is a _j Represents the use cost of the jth candidate station, (x) _j ,y _j ) Coordinates representing the jth candidate station, (a) _i ,b _i ) Expressing the barycentric coordinates of the ith cluster, and respectively expressing the number of the clusters and the number of candidate stations by m and n;

6. The unmanned aerial vehicle-bus area collaborative distribution method as claimed in claim 3, wherein the optimal path determination method comprises:

(2) Traversing the current OPEN LIST, selecting a node corresponding to the minimum value of f (n), and unfolding: determining a first obstacle passing through from the node to a landing point, putting available node information of the obstacle into an OPENLIST, and putting a node expanded in the OPENLIST into a CLOSE LIST;

wherein, f (n) is calculated as follows:

f(n)＝g(n)+h(n)；

(3) And (3) repeating the step (2), and ending the circulation when no obstacle exists between the expansion point and the falling point in the OPENLIST (namely the node information of the obstacle is empty) or the OPENLIST is empty, and outputting the optimal path.

7. The area cooperative distribution method combining unmanned aerial vehicles and buses as claimed in claim 3, wherein the objective function and constraint conditions of the area cooperative distribution method combining unmanned aerial vehicles and buses are as follows:

wherein, the first and the second end of the pipe are connected with each other,

constraint conditions are as follows:

secret；

wherein n is _p A representation of a node of a user is shown,

representing a user node n _p The package demand of (a); p is a radical of formula _i Representing a bus stop;

to represent any bus stop p _i Open fixed costs;

representing a user node n _p And site D _j The distance therebetween; t is _clu (i) Representing the time consumed by the drone to service customers within the cluster; t is t _p Representing departure time periods of the stations; tau. _a (p _p S) unmanned aerial vehicle arrives at bus stop p in representation path s _p The time of day; tau is _d (p _p And s) represents the time when the unmanned aerial vehicle on the path s gets on the public transportation after waiting at the station;

indicating the waiting time of the customer site.

8. A computer arrangement, characterized in that the computer arrangement comprises a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the steps of the method for coordinated distribution of drones in combination with bus zones as claimed in any one of claims 3 to 7.

9. A computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method for coordinated distribution of drones in conjunction with a bus area as claimed in any one of claims 3 to 7.

10. An information data processing terminal, characterized in that, the information data processing terminal is used to realize the unmanned aerial vehicle of any one of claims 1-2 in combination with a bus area cooperative distribution system.