CN113038369B

CN113038369B - Geo-fence classification method, vehicle scheduling method and server

Info

Publication number: CN113038369B
Application number: CN202110236490.5A
Authority: CN
Inventors: 韦仕伟; 林剑峰
Original assignee: Mobai Beijing Information Technology Co Ltd
Current assignee: Mobai Beijing Information Technology Co Ltd
Priority date: 2021-03-03
Filing date: 2021-03-03
Publication date: 2023-03-24
Anticipated expiration: 2041-03-03
Also published as: CN113038369A

Abstract

The invention discloses a geo-fence classification method, a vehicle scheduling method and a server. The geo-fence grading method comprises the following steps: obtaining information of a geo-fence network, the information of the geo-fence network including distances between different geo-fences in the geo-fence network; the method comprises the steps of obtaining vehicle riding order data of a geo-fence network, wherein the vehicle riding order data comprise a source geo-fence and a destination geo-fence corresponding to a vehicle riding order; and determining the grade value of the geographic fence in the geographic fence network according to the vehicle riding order data and the information of the geographic fence network. The grading method introduces the connectivity and geographic factors between the geographic fences into the grading process of the geographic fences, so that the grading result can more accurately reflect the importance of the geographic fences in the shared vehicle service.

Description

Geo-fence classification method, vehicle scheduling method and server

Technical Field

The invention relates to the technical field of geographic fences, in particular to a geographic fence grading method, a vehicle scheduling method and a server.

Background

At present, the shared vehicle trip becomes a emerging trip mode in a city, and the trip demand of urban people can be effectively solved. With the increasing scale of shared vehicles, the putting amount of the shared vehicles is increasing, and the problem of random parking of the vehicles occurs, which affects the normal use of users.

In order to solve the problem that the shared vehicle is parked randomly, an operator of the shared vehicle sets a geo-fence in an operating area to guide a user to park regularly, and performs vehicle scheduling and delivery management in units of the geo-fence. The geofence is therefore an important part of the operation and management of the shared vehicles, and in this case, it is necessary to perform importance level division on the geofence to improve the efficiency of the operation and management of the shared vehicles.

Disclosure of Invention

It is an object of embodiments of the present disclosure to provide a new geo-fence classification method, a scheduling method of vehicles, and a server.

According to a first aspect of the present invention, there is provided a geo-fencing method comprising:

obtaining information of a geo-fence network, the information of the geo-fence network including distances between different geo-fences in the geo-fence network;

the method comprises the steps of obtaining vehicle riding order data of a geo-fence network, wherein the vehicle riding order data comprise a source geo-fence and a destination geo-fence corresponding to a vehicle riding order;

determining a rank value of a geofence in the geofence network according to the vehicle ride order data and the information of the geofence network.

Optionally, the determining a rank value of a geofence in the geofence network according to the vehicle ride order data and the information of the geofence network comprises:

determining a set of source geo-fences corresponding to each geo-fence according to the vehicle riding order data;

determining the weight of a source geofence to its destination geofence according to the vehicle ride order data and the information of the geofence network;

obtaining an initial grade value of a geo-fence in the geo-fence network, iterating the grade values of the geo-fences in the geo-fence network according to the following formula, and stopping iteration after the grade values of each geo-fence in the geo-fence network are converged;

wherein, I _a Is the set of source geofences corresponding to geofence a, b is I _a Geofence, RR of _t (a) For the rank value, RR, of geofence a after the t iteration _t-1 (b) Is the rank value, L, of geofence b after the t-1 iteration _RR (b, a) is the weight of geofence b over geofence a, t is an integer and t ≧ 1.

Optionally, the determining, according to the vehicle riding order data and the information of the geo-fence network, a weight of a source geo-fence to its destination geo-fence comprises:

determining the entrance degree of each geo-fence and a set of destination geo-fences corresponding to each geo-fence according to the vehicle riding order data;

determining an attraction value of the destination geofence to its source geofence based on the degree of entry of the destination geofence, the distance between the destination geofence and its source geofence;

determining a weight of a source geofence for its destination geofence according to the following equation:

wherein, O _b Set of destination geofences corresponding to geofence b, c is O _b Geofence of (1), F _RR (b, a) is the attraction value of geofence a to geofence b, F _RR (b, c) is the attraction value of geofence c for geofence b.

Optionally, the determining an attraction value of the destination geofence for its source geofence as a function of the penetration of the destination geofence, the distance between the destination geofence and its source geofence, comprises:

determining an attraction value of the destination geofence for its source geofence according to the following equation:

wherein, F _RR (i, j) is the attraction value of the destination geofence j to its source geofence i, inditree (j) is the entry of the destination geofence j, distance (i, j) is the distance between the destination geofence j and the source geofence i, and γ is a preset distance impact factor.

Optionally, the information of the geo-fence network further comprises an area of a geo-fence;

determining an attraction value of the destination geofence for its source geofence as a function of the penetration of the destination geofence, the distance between the destination geofence and its source geofence, comprising:

wherein, F _RR (i, j) is the attraction value of the destination geofence j to its source geofence i, inditree (j) is the degree of entry of the destination geofence j, area (j) is the area of the destination geofence j, distance (i, j) is the distance between the destination geofence j and the source geofence i, β is a preset area impact factor, and γ is a preset distance impact factor.

Optionally, the information of the geofence network further comprises an area of the geofence and a vehicle turnover rate of the geofence;

wherein, F _RR (i, j) is an attraction value of the destination geofence j to its source geofence i, indegrede (j) is an entrance of the destination geofence j, turnover (j) is a vehicle turnover rate of the destination geofence j, area (j) is an area of the destination geofence j, distance (i, j) is a distance between the destination geofence j and the source geofence i, β is a preset area impact factor, and γ is a preset distance impact factor, wherein the vehicle turnover rate turnover (j) of the destination geofence j is inversely related to an average time the vehicle entering the destination geofence j is ridden.

Optionally, the determining the degree of entry for each geofence according to the vehicle ride order data comprises:

determining a total number of ride-in orders for each geofence from the vehicle ride order data;

determining an occupancy of the geofence based on a total number of orders to ride in the geofence.

The vehicle riding order data comprises the time when the vehicle riding order occurs;

determining the degree of entry of each geofence according to the vehicle ride order data, comprising:

determining an order influence factor of a vehicle riding order according to the time of the vehicle riding order, wherein the order influence factor of the vehicle riding order and the time length of the time of the vehicle riding order from the current time form a negative correlation relationship;

determining a sum of order impact factors for the geofence's ride orders as the geofence's degree of entry.

According to a second aspect of the present invention, there is provided a vehicle scheduling method, comprising:

determining a rank value for a geofence in a geofence network according to the geofence ranking method of the first aspect;

determining a vehicle dispatching strategy corresponding to the geo-fence according to the mapping relation between the grade value of the geo-fence and the vehicle dispatching strategy;

and vehicle scheduling is carried out on the geo-fence according to the vehicle scheduling strategy corresponding to the geo-fence.

According to a third aspect of the present invention, there is provided a server comprising a memory for storing computer instructions and a processor for invoking the computer instructions from the memory to perform the geo-fence classification method of the first aspect or the vehicle scheduling method of the second aspect.

According to the geographic fence grading method provided by the embodiment of the disclosure, the connectivity and geographic factors between the geographic fences are introduced into the grading process of the geographic fences, so that the grading result can more accurately reflect the importance of the geographic fences in the service of shared vehicles, a basis is provided for the operation management of the shared vehicles, and the overall efficiency of the operation management is improved.

In order to make the aforementioned objects, features and advantages of the present disclosure more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the embodiments will be briefly described below. It is appreciated that the following drawings depict only certain embodiments of the invention and are therefore not to be considered limiting of its scope. For a person skilled in the art, it is possible to derive other relevant figures from these figures without inventive effort.

FIG. 1 illustrates a schematic diagram of a shared vehicle operation system provided by embodiments of the present disclosure;

FIG. 2 illustrates a flow chart of a geo-fence ranking method provided by an embodiment of the present disclosure;

FIG. 3 is a flow chart illustrating a vehicle scheduling method provided by an embodiment of the present disclosure;

fig. 4 shows a schematic diagram of a server provided by an embodiment of the present disclosure.

Detailed Description

Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.

Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

< shared vehicle operation System >

As shown in fig. 1, the operation system 100 for sharing vehicles includes a server 1000, a terminal 2000, a vehicle 3000, and a network 4000.

The server 1000 is a service point that provides processing power, databases, and communications facilities. The server 1000 may be a unitary server or a distributed server across multiple computers or computer data centers. In some embodiments, each server may include hardware, software, or embedded logic components or a combination of two or more such components for performing the appropriate functions supported or implemented by the server. For example, the server may be a blade server, a cloud server, or the like, or may be a server group consisting of a plurality of servers.

In one example, the server 1000 may be as shown in fig. 1, including a processor 1100, a memory 1200, an interface device 1300, a communication device 1400, a display device 1500, an input device 1600. Although the server may also include speakers, microphones, etc., these components are not relevant to the present invention and are omitted here. The processor 1100 may be, for example, a central processing unit CPU, a microprocessor MCU, or the like. The memory 1200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 1300 includes, for example, a USB interface, a serial interface, an infrared interface, and the like. Communication device 1400 is capable of wired or wireless communication, for example. The display device 1500 is, for example, a liquid crystal display, an LED display touch panel, or the like. The input device 1600 may include, for example, a touch screen, a keyboard, and the like.

In the present embodiment, the terminal 2000 held by the operator is an electronic device having a communication function and a service processing function. The terminal 2000 may be a mobile terminal held by an operator, such as a mobile phone, a laptop, a tablet computer, a palmtop computer, and the like, and has a corresponding APP, and the operator may receive a vehicle scheduling task, a recovery failure vehicle task, and the like through the APP.

As shown in fig. 1, the terminal 2000 may include a processor 2100, a memory 2200, an interface device 2300, a communication device 2400, a display device 2500, an input device 2600, an output device 2700, a camera device 2800, and the like. The processor 2100 may be a central processing unit CPU, a microprocessor MCU, or the like. The memory 2200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 2300 includes, for example, a USB interface, a headphone interface, and the like. The communication device 2400 is capable of wired or wireless communication, for example, and includes a Wifi communication module, a bluetooth communication module, a 2G/3G/4G communication module, and the like. The display device 2500 is, for example, a liquid crystal display panel, a touch panel, or the like. The input device 2600 may include, for example, a touch screen, a keyboard, or a microphone. The output device 2700 is used for outputting information, and may be a speaker, for example, for outputting voice information to an operator. The camera 2800 is used to capture a faulty vehicle, for example, scan the faulty vehicle to register the faulty vehicle, for example, capture a picture of a fault of the faulty vehicle and upload the picture to a server or the like, and the camera 2800 is a camera or the like, for example. The terminal 2000 may include a positioning device (not shown), for example, a GNSS positioning module such as a GPS positioning module, a beidou positioning module, etc.

The vehicle 3000 is any vehicle that can give the right to share the use by different users in time or separately, for example, a shared bicycle, a shared moped, a shared electric vehicle, a shared vehicle, and the like. The vehicle 3000 may be a bicycle, a tricycle, an electric scooter, a motorcycle, a four-wheeled passenger vehicle, or the like.

As shown in fig. 1, vehicle 3000 may include a processor 3100, a memory 3200, an interface device 3300, a communication device 3400, an output device 3500, an input device 3600, a positioning device 3700, sensors 3800, and so forth. The processor 3100 may be a central processing unit CPU, a microprocessor MCU, or the like. The memory 3200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface 3300 includes, for example, a USB interface, a headphone interface, and the like. The communication device 3400 is capable of wired or wireless communication, for example, and includes a Wifi communication module, a bluetooth communication module, a 2G/3G/4G communication module, and the like, for example. The output device 3500 may be, for example, a device that outputs a signal, may be a display device such as a liquid crystal display panel or a touch panel, or may be a speaker or the like that outputs voice information or the like. The input device 3600 may include, for example, a key, a touch screen, a keyboard, etc., and may also include a microphone for inputting voice information. The positioning device 3700 is used to provide positioning function, and may include a GNSS positioning module such as a GPS positioning module and a beidou positioning module. The sensor 3800 is used for acquiring vehicle attitude information, and may be, for example, an accelerometer, a gyroscope, or a three-axis, six-axis, nine-axis micro-electro-mechanical system (MEMS), or the like.

The network 4000 may be a wireless communication network or a wired communication network, and may be a local area network or a wide area network. In the vehicle system shown in fig. 1, a vehicle 3000 and a server 1000, and a terminal 2000 and the server 1000 can communicate with each other through a network 4000. The vehicle 3000 may be the same as the server 1000, and the network 4000 through which the terminal 2000 communicates with the server 1000 may be different from each other.

It should be understood that although fig. 1 shows only one server 1000, terminal 2000, vehicle 3000, it is not meant to limit the corresponding number, and multiple servers 1000, multiple terminals 2000, multiple vehicles 3000 may be included in the operation system 100.

The operations system 100 shown in fig. 1 is merely illustrative and is in no way intended to limit the present invention, its application, or uses. Although a plurality of devices are shown in fig. 1 for the server 1000, the terminal 2000, and the vehicle 3000, the present invention may relate to only some of the devices.

In an embodiment of the present invention, the memory 1200 of the server 1000 is used for storing instructions for controlling the processor 1100 to operate to execute the geo-fence classification method or the vehicle dispatching method provided by the embodiment of the present disclosure. Those skilled in the art can design instructions in accordance with the teachings of the present invention. How the instructions control the operation of the processor is well known in the art and will not be described in detail herein.

< geofence rating method >

Fig. 2 is a flow diagram of a method of ranking geofences, in accordance with an embodiment of the present disclosure. The method may be implemented by the server 1000 shown in fig. 1.

According to fig. 2, the method of the present embodiment may include steps S202-S206.

S202, acquiring information of the geo-fence network, wherein the information of the geo-fence network comprises distances between different geo-fences in the geo-fence network.

In an embodiment of the disclosure, a geofence network is a network of geofences, a geofence serving as a node in the geofence network. A geofence may be an area defined according to a plan that allows parking. Many geofences may be set up based on the need to manage parking in different territories, which may be streets, grids, and so forth. Wherein the grid may be obtained by dividing the vehicle operation range, for example, into a grid of 100 m x 100 m.

The server stores operation data in advance, for example, data such as geographic positions, areas, shapes, boundaries, vertexes and the like of the geo-fences, distances between different geo-fences, vehicle turnover rates of the geo-fences and the like.

In embodiments of the disclosure, the vehicle turnover rate for a geofence is inversely related to the average time the vehicle entering the geofence is ridden, and the time the vehicle entering the geofence is ridden is the time between the vehicle entering the geofence and the time the user rides out of the geofence. The two variables are in a negative correlation relationship, which means that the change directions of the two variables are opposite, and when one variable changes from large to small or from small to large, the other variable changes from small to large or from large to small. The vehicle turnover rate of a geofence is inversely related to the average time a vehicle entering the geofence is ridden, i.e., the longer the average time a vehicle entering the geofence is ridden, the lower the vehicle turnover rate of the geofence, the shorter the average time a vehicle entering the geofence is ridden, the higher the vehicle turnover rate of the geofence. In one example, the vehicle turnover rate for a geofence is the inverse of the average time that a vehicle entering the geofence is ridden.

S204, vehicle riding order data of the geo-fence network are obtained, wherein the vehicle riding order data comprise a source geo-fence and a destination geo-fence corresponding to the vehicle riding order.

In the embodiment of the present disclosure, the vehicle riding order data refers to order data of a vehicle riding order, and includes a source geo-fence and a destination geo-fence corresponding to the vehicle riding order.

A compliant vehicle ride is one that rides out of one geofence, referred to as a source geofence, and then into another geofence for parking, referred to as a destination geofence. That is, the source geofences and the destination geofences in the embodiments of the present disclosure are relative concepts, and according to the vehicle ride order data, a set of source geofences corresponding to each geofence and a set of destination fences corresponding to each geofence can be determined.

In one embodiment, the vehicle riding order data may further include the time when the vehicle riding order occurs, and the time when the vehicle riding order occurs may be the riding start time when the user starts the riding or the riding end time when the user ends the riding.

S206, determining the grade value of the geo-fence in the geo-fence network according to the vehicle riding order data and the information of the geo-fence network.

In the disclosed embodiments, the rank values of geofences in a geofence network are used to reflect how important the geofences are in the geofence.

The vehicle ride order data may embody connectivity between geofences, the distance between geofences taking into account the geographic factors of the geofences. According to the geographic fence grading method provided by the embodiment of the disclosure, the connectivity and geographic factors between the geographic fences are introduced into the grading process of the geographic fences, so that the grading result can more accurately reflect the importance of the geographic fences in the service of shared vehicles, a basis is provided for the operation management of the shared vehicles, and the overall efficiency of the operation management is improved.

In one embodiment, step S206 includes steps S302-S306.

S302, according to the vehicle riding order data, determining a source geo-fence set corresponding to each geo-fence, and determining a destination fence set corresponding to each geo-fence.

From the order data for a ride order, a set of source geofences-destination geofences can be determined. From the vehicle ride order data for the geofence network, a set of its corresponding destination geofences and a set of its corresponding source geofences can be determined for each geofence in the geofence network, respectively.

S304, determining the weight of the source geo-fence to the destination geo-fence according to the vehicle riding order data and the information of the geo-fence network.

S306, obtaining an initial grade value of the geo-fence in the geo-fence network, iterating the grade values of the geo-fences in the geo-fence network according to the equation 1, and stopping iteration after the grade values of all the geo-fences in the geo-fence network are converged.

I _a For the set of source geofences corresponding to geofence a, b ∈ I _a I.e. geofence b as set I _a The geofence of (1). That is, geofence b is a source geofence of geofence a, which is a destination geofence of geofence b.

RR _t (a) For the rank value, RR, of geofence a after the t iteration _t-1 (b) Is the rank value, L, of geofence b after the t-1 iteration _RR (b, a) is the weight of geofence b over geofence a, t is an integer and t ≧ 1.

RR at t of 1 _t-1 (b) Is RR ₀ (b)，RR ₀ (b) Is the rank value of geofence b after iteration 0, i.e., the initial rank value of geofence b. In the embodiment of the present disclosure, the initial rank value of each geo-fence is preset, and may be set according to engineering experience. In embodiments of the present disclosure, the initial rank value for each geofence in the geofence network is a value that may be the same.

When the geofence network reaches an equilibrium state, that is, when the rank value of each geofence in the geofence network converges, the iteration is stopped, and the rank value of the geofence obtained by the last iteration is used as the rank of the geofence.

In this embodiment, an edge can be created in the geofence network from one vehicle ride order. That is, the geographic fences are taken as nodes, the vehicle riding orders generated between the geographic fences are taken as edges, a directed graph is constructed, and the importance of the nodes is determined by utilizing a node sorting algorithm of the directed graph.

In one embodiment, step S304 may include steps S402-S406:

s402, determining the entrance of each geo-fence according to the vehicle riding order data.

S404, determining an attraction value of the destination geo-fence to the source geo-fence according to the degree of entry of the destination geo-fence and the distance between the destination geo-fence and the source geo-fence.

S406, determining the weight of the source geo-fence to the destination geo-fence according to the formula 2:

O _b for the set of destination geofences corresponding to geofence b, c ∈ O _b I.e. geofence c is set O _b The geofence of (1). That is, geofence b is a source geofence of geofence c, which is a destination geofence of geofence b. As can be seen from the foregoing, a ∈ O _b I.e. geofence a is set O _b The geofence of (1).

In the disclosed embodiment, use F _RR (i, j) represents the attraction value of destination geofence j for its source geofence i. Geofence a is a destination geofence for geofence b, known as F _RR (b, a) attraction value for destination geofence a to its source geofence b. Geofence c is a destination geofence for geofence b, known as F _RR (b, c) attraction value for destination geofence c to its source geofence b.

According to the geo-fence grading method provided by the embodiment of the disclosure, the degree of approach of each geo-fence is determined according to vehicle riding order data, and then the attraction value of the destination geo-fence to the source geo-fence is determined according to the degree of approach of the destination geo-fence, the distance between the destination geo-fence and the source geo-fence, the weight of the source geo-fence to the destination geo-fence is determined according to the attraction value of the destination geo-fence to the source geo-fence, and the connectivity and the geographic factors between the geo-fences are introduced into the grading process of the geo-fences, so that the grading result can more accurately reflect the importance of the geo-fences in shared vehicle service.

In a first example, in step S404, an attraction value of the destination geofence with respect to its source geofence can be determined according to equation 3.

F _RR (i, j) is the attraction value of the destination geofence j to its source geofence i, inditree (j) is the entry of the destination geofence j, distance (i, j) is the distance between the destination geofence j and the source geofence i, and γ is a preset distance impact factor. In the embodiment of the disclosure, γ > 1, and the specific value of γ can be set according to engineering experience.

In a second example, in step S404, an attraction value of the destination geofence with respect to its source geofence can be determined according to equation 4.

F _RR ) i, j) is the attraction value of the destination geofence j to its source geofence i, inditree (j) is the degree of entry of the destination geofence j, area (j) is the area of the destination geofence j, distance (i, j) is the distance between the destination geofence j and the source geofence i, β is a preset area impact factor, and γ is a preset distance impact factor. In the embodiment of the disclosure, β < 1 > is less than 0, γ > 1, and the specific values of β and γ can be set according to engineering experience.

In the embodiment, a larger punishment is given to the geographic fence with a larger area, the outputted fence importance is ensured to be relatively fairer, and the finally determined grade value is prevented from being biased to the fence with a larger area, so that the importance of the geographic fence in the service of the shared vehicle can be more accurately reflected by the grading result, a basis is provided for the operation management of the shared vehicle, and the overall efficiency of the operation management is improved.

In a third example, in step S404, an attraction value of the destination geofence with respect to its source geofence can be determined according to equation 5.

F _RR (i, j) is an attraction value of the destination geofence j to its source geofence i, indetree (j) is an entrance of the destination geofence j, turnover (j) is a vehicle turnover rate of the destination geofence j, area (j) is an area of the destination geofence j, distance (i, j) is a distance between the destination geofence j and the source geofence i, β is a preset area impact factor, and γ is a preset distance impact factor. The vehicle turnover rate turnover (j) for destination geofence j is inversely related to the average time that a vehicle entering destination geofence j is being ridden. In the embodiment of the disclosure, β < 1 > is less than 0, γ > 1, and the specific values of β and γ can be set according to engineering experience.

In the embodiment, the vehicle turnover rate is introduced into the grading process of the geo-fences, and the geo-fences with high vehicle turnover rate are provided with larger influence, so that the grading result can more accurately reflect the importance of the geo-fences in the shared vehicle service, a basis is provided for the operation management of the shared vehicles, and the overall efficiency of the operation management is improved.

In one embodiment, step S402 may include steps S502-S504.

And S502, determining the total number of riding orders of each geo-fence according to the vehicle riding order data.

S504, determining the entrance degree of the geo-fence according to the total number of the riding orders of the geo-fence.

In the disclosed embodiments, an edge can be created in a geofence network from a vehicle ride order. That is, a directed graph is constructed with geofences as nodes and with vehicle ride orders generated between geofences as edges. The edge starts from a source geofence of the vehicle ride order, points to a destination geofence of the vehicle ride order, and the degree of entry into the geofence can be determined based on the edge pointing to the geofence. As seen from steps S502-S504, the degree of entry of a geofence is equal to the number of edges pointing to the geofence, i.e., the number of ride orders for the geofence.

In this embodiment, the degree of entry of the geofence is determined according to the number of ride-in orders for the geofence, and then the weight of the source geofence for its destination geofence is determined, so that the assignment rank value is transferred in an iterative process, thereby reflecting the true importance of the geofence more accurately and obtaining an accurate geofence ranking result.

In one embodiment, the vehicle ride order data includes a time at which the vehicle ride order occurred.

In another embodiment, step S402 may include steps S602-S604.

S602, determining an order influence factor of the vehicle riding order according to the time of the vehicle riding order, wherein the order influence factor of the vehicle riding order and the time length of the time of the vehicle riding order from the current time form a negative correlation relationship.

S604, determining the sum of the order impact factors of the riding orders of the geo-fence as the degree of entry of the geo-fence.

The order influence factor of the vehicle riding order and the time length of the time of the vehicle riding order from the current time are in a negative correlation relationship, that is, the longer the time length of the time of the vehicle riding order from the current time is, the smaller the order influence factor of the vehicle riding order is, the shorter the time length of the time of the vehicle riding order from the current time is, and the larger the order influence factor of the vehicle riding order is. That is to say, the closer the vehicle riding order is to the current date, the higher the timeliness is, the more the current riding requirement can be expressed, and the higher the reference value in the aspect of evaluating the importance degree of the geo-fence is, the larger the influence factor is.

In this further embodiment, a more time-sensitive vehicle ride order is given a greater influence, so that determining the weight of the source geofence for its destination geofence takes into account the time-sensitivity of the vehicle ride order, so as to more accurately shift the assigned rank value in an iterative process, thereby more accurately reflecting the true importance of the geofence and obtaining an accurate geofence ranking result.

The geofence classification methods of the embodiments of the present disclosure are described below in one specific example.

S701, obtaining order data of the vehicle riding orders of the past month of the geo-fence network, and constructing a directed graph by taking the geo-fences as nodes and taking the vehicle riding orders generated among the geo-fences as edges.

S702, assign the same initial rank value to each node in the graph, i.e., each geofence.

And S703, iterating in the directed graph network according to the formula 1 to transfer the distribution grade value.

S704, judging iteration termination conditions: if the currently calculated rank values of all nodes (geo-fences) are the same as or differ little from the last round of calculated rank values, an iteration termination condition is met, the iteration is terminated, and the current rank values are output as final rank values of the nodes (geo-fences). Otherwise, the iteration termination condition is not met, and the next iteration is started according to the formula 1.

The difference between the currently calculated grade value of the node and the grade value calculated in the previous round is not large, that is, the difference between the grade value calculated in the current round of iteration of the node and the grade value calculated in the previous round of iteration is smaller than a preset threshold value, and the threshold value can be determined through engineering tests or test simulation according to actual requirements.

And S705, after the iteration is ended, sorting the geo-fences according to the final grade value. And according to the sequencing result, preferentially scheduling the vehicles for the geo-fences with the top sequence, namely the high rank value. For example, in a situation where scheduling capability is limited, scheduling requirements for geofences with high rank values are preferentially met. For example, where the number of vehicles is limited, priority is given to vehicles to geofences with high rank values.

According to the geographic fence grading method provided by the embodiment of the disclosure, connectivity among geographic fences and geographic factors are introduced into the grading process of the geographic fences, and the spatial concentration degree of riding requirements of a user can be identified, so that the grading result can more accurately reflect the importance of the geographic fences in shared vehicle service, a basis is provided for operation management of shared vehicles, and the overall efficiency of the operation management is improved.

According to the geo-fence grading method provided by the embodiment of the disclosure, when the geo-fence is changed and the user requirement is changed, the importance of the geo-fence can be re-evaluated faster and more accurately in response to the change only by re-performing iterative operation.

The geo-fence grading method provided by the embodiment of the disclosure innovatively utilizes the vehicle riding order to construct the geo-fence into a directed graph, and utilizes the properties of the directed graph to calculate the importance of the geo-fence in the geo-fence network.

< vehicle scheduling method >

The embodiment of the disclosure also provides a vehicle dispatching method, which comprises steps S802-S806.

S802, determining the grade value of the geo-fence in the geo-fence network according to the geo-fence grading method.

In this embodiment, the rank values of the geofences in the geofence network may be determined using the geofence ranking method of any of the preceding embodiments.

S804, determining a vehicle dispatching strategy corresponding to the geo-fence according to the mapping relation between the grade value of the geo-fence and the vehicle dispatching strategy.

For example, the higher the rank value of a geofence, the higher the priority of the corresponding vehicle dispatch strategy, the higher the priority to meet the vehicle dispatch needs of that geofence.

S806, vehicle scheduling is conducted on the geo-fence according to the vehicle scheduling strategy corresponding to the geo-fence.

For example, according to a vehicle scheduling policy corresponding to the geofence, a vehicle scheduling instruction is generated for the geofence, and the vehicle scheduling instruction is issued to a terminal held by an operator, so that the operator performs vehicle scheduling according to the vehicle scheduling instruction.

According to the vehicle dispatching method provided by the embodiment of the disclosure, the geographic fences are classified in advance, and the connectivity and geographic factors between the geographic fences are introduced into the classification process of the geographic fences, so that the classification result can more accurately reflect the importance of the geographic fences in the shared vehicle service, and the classification result of the geographic fences is used as a basis for selecting the vehicle dispatching strategy from the geographic fences, thereby improving the overall efficiency of operation management.

< Server >

In the present embodiment, a server 200 is also provided. As shown in fig. 4, the server 200 includes:

a memory 210 for storing computer instructions.

A processor 220 for invoking computer instructions from the memory 210 to perform any of the geo-fence ranking methods or any of the vehicle dispatching methods provided by the above embodiments.

In this embodiment, the server 200 may be embodied in various forms of entities. For example, the server 200 may be a cloud server. The server 200 may also be the server 1000 as shown in fig. 1.

< computer-readable storage Medium >

In this embodiment, there is also provided a computer readable storage medium having stored thereon computer readable instructions which, when executed by a processor, implement any one of the geo-fence classification methods or any one of the vehicle scheduling methods provided by the above embodiments.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the server embodiment, since it is substantially similar to the method embodiment, the description is simple, and reference may be made to part of the description of the method embodiment for relevant points.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The present invention may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for causing a processor to implement various aspects of the present invention.

The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.

The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.

The computer program instructions for carrying out operations of the present invention may be assembler instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present invention are implemented by personalizing an electronic circuit, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA), with state information of computer-readable program instructions, which can execute the computer-readable program instructions.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, implementation by software, and implementation by a combination of software and hardware are equivalent.

Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the invention is defined by the appended claims.

Claims

1. A geo-fencing method, comprising:

obtaining vehicle riding order data of a geo-fence network, wherein the vehicle riding order data comprises a source geo-fence and a destination geo-fence corresponding to a vehicle riding order;

determining the degree of entrance of each geo-fence and a set of destination geo-fences corresponding to each geo-fence according to the vehicle riding order data; determining an attraction value of the destination geofence to its source geofence based on the degree of entry of the destination geofence, the distance between the destination geofence and its source geofence; determining a weight of a source geofence for its destination geofence according to the following equation:

wherein, O _b Set of destination geofences corresponding to geofence b, c is O _b Geofence of (1), F _RR (b, a) is the attraction value of geofence a to geofence b, F _RR (b, c) is the attraction value of geofence c for geofence b;

obtaining an initial rank value of a geo-fence in the geo-fence network, iterating the rank values of the geo-fences in the geo-fence network according to the following formula, and stopping iteration after the rank values of each geo-fence in the geo-fence network are converged;

wherein, I _a Is the set of source geofences corresponding to geofence a, b is I _a Geofence, RR in _t (a) For the rank value, RR, of geofence a after the t iteration _t-1 (b) Is as followsRank value, L, of geofence b after t-1 iterations _RR (b, a) is the weight of geofence b over geofence a, t is an integer and t ≧ 1;

determining an attraction value of the destination geofence for its source geofence as a function of the penetration of the destination geofence, the distance between the destination geofence and its source geofence, comprising: determining an attraction value of the destination geofence for its source geofence according to any of the following equations: :

2. The method of claim 1, wherein determining the degree of entry for each geofence from the vehicle ride order data comprises:

3. The method of claim 1, wherein the vehicle ride order data comprises a time at which a vehicle ride order occurred;

4. A vehicle scheduling method, comprising:

determining a rank value for a geofence in a geofence network according to the geofence ranking method of any of claims 1-3;

5. A server comprising a memory for storing computer instructions and a processor for invoking the computer instructions from the memory to perform the geofence classification method of any of claims 1-3 or the vehicle dispatch method of claim 4.