CN109146150B - Method, system, storage medium and mobile terminal for intelligently selecting logistics collection points - Google Patents

Method, system, storage medium and mobile terminal for intelligently selecting logistics collection points Download PDF

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CN109146150B
CN109146150B CN201810853392.4A CN201810853392A CN109146150B CN 109146150 B CN109146150 B CN 109146150B CN 201810853392 A CN201810853392 A CN 201810853392A CN 109146150 B CN109146150 B CN 109146150B
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邹亮
张洪斌
冯如玉
杨乐南
尹慧
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Shenzhen University
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Abstract

The invention discloses a method, a system, a storage medium and a mobile terminal for intelligently selecting a logistics collection point, wherein the method comprises the following steps: the method comprises the steps that a mobile terminal of a first user collects travel data information of the first user, and a travel rule of the first user is analyzed based on the thermal distribution of the first user on a map; analyzing the times of the first user appearing in a preset distance range of each logistics collection point in a preset time range according to the travel rule of the first user; and setting the logistics collection point with the largest number of times as a target collection point, and sending the position information of the target collection point to the mobile terminal of the second user so as to enable the mobile terminal of the second user to carry out path planning. According to the invention, the travel rule of the first user is acquired and analyzed based on the thermal distribution, and the optimal logistics collection point is selected according to the travel rule of the first user, so that the distribution path of the second user to the logistics is improved, the distribution space-time mismatch rate is effectively reduced, and the distribution efficiency is improved.

Description

Method, system, storage medium and mobile terminal for intelligently selecting logistics collection point
Technical Field
The invention relates to the technical field of logistics distribution, in particular to a method, a system, a storage medium and a mobile terminal for intelligently selecting a logistics collection point.
Background
The logistics end distribution cost is always a key factor for restricting the logistics industry to improve efficiency and reduce cost. With the rapid development of the electricity business in China in recent years, the express quantity is increased dramatically. The quantity of express packages is increased sharply, so that the pressure at the tail end of logistics is huge. In the face of terminal pressure, a new distribution mode is introduced for terminal distribution in cities, and users are self-promoted to be a mainstream mode. The intelligent express cabinet is continuously popularized in cities by virtue of the characteristics of safety, high flexibility and low cost. The mode of 'terminal + community O2O' expands the service range of the original commercial point, and is suitable for the development of terminal distribution under the conditions of shortage of land used in cities and high rent, which is a mode widely applied at present.
Although the proportion of the delivery to the door can be reduced to a certain extent by adopting a user self-picking mode for tail-end delivery, the time of couriers is saved, and meanwhile, the self-picking cabinet runs continuously for 24 hours, so that convenience is brought to the user for selecting time to take out the express. However, this method is not much improved in solving the time-space difference between the courier and the user, and only gives the user the freedom to choose the time for receiving the courier. When the express delivery sharply increases, the terminal self-picking point also faces insufficient storage space, and the problem of overstocked user express delivery influences the delivery efficiency of express delivery.
Accordingly, there is a need for improvements and developments in the art.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method, a system, a storage medium and a mobile terminal for intelligently selecting a physical delivery collection point, aiming at solving the problems in the prior art that the time-space difference between a courier and a user is not greatly improved, the delivery efficiency of express delivery is low, and the like.
The technical scheme adopted by the invention for solving the technical problem is as follows:
a method of intelligently selecting a logistics collection point, wherein the method comprises:
the method comprises the steps that a mobile terminal of a first user collects travel data information of the first user, and a travel rule of the first user is analyzed based on the thermal distribution of the first user on a map;
analyzing the times of the first user appearing in a preset distance range of each logistics collection point in a preset time range according to the travel rule of the first user;
and setting the logistics collection point with the largest number of times as a target collection point, and sending the position information of the target collection point to a preset mobile terminal of a second user so as to enable the mobile terminal of the second user to carry out path planning.
The method for intelligently selecting logistics collection points comprises the steps that the first user is a user receiving logistics, and the second user is a user distributing logistics.
The method for intelligently selecting logistics collection points includes that a mobile terminal of a first user collects travel space information of the first user, and the step of analyzing a travel rule of the first user based on thermal distribution of the first user on a map specifically includes:
the method comprises the following steps that a mobile terminal of a first user collects and records travel data information of the first user through a GPS module of the mobile terminal;
mapping a position point of a first user in the collected travel data information on a map, and presenting the position point in a heat distribution mode;
and analyzing the travel rule of the first user according to the heat distribution of the first user on the map.
The method for intelligently selecting logistics collection points comprises the following steps: the longitude and latitude of the location of the first user, and the current time.
The method for intelligently selecting logistics collection points comprises the following steps:
presetting a time range and a distance range;
and the time range and the distance range are used for screening out the travel position points meeting the conditions from the travel rule of the first user and eliminating the travel position points not meeting the conditions.
The method for intelligently selecting logistics collection points, wherein the analyzing, according to the travel rule of the first user, the number of times that the first user appears in a preset distance range of each logistics collection point within a preset time range specifically includes:
calculating the distance from the travel position point of the first user to each known logistics collection point, and comparing the distance with a preset distance range;
and when the calculated distance meets the distance range, calculating the times of the first user appearing at each logistics collection point in a preset time range.
The method for intelligently selecting the logistics collection point comprises the following steps of setting the logistics collection point with the largest number of times as a target collection point, and sending the position information of the target collection point to a preset mobile terminal of a second user so as to enable the mobile terminal of the second user to carry out path planning, wherein the step of setting the logistics collection point with the largest number of times as the target collection point specifically comprises the following steps:
the mobile terminal of the first user sets the logistics collection point with the maximum calculated times as a target collection point;
acquiring the position information of the target collection point, and sending the position information of the target collection point to a mobile terminal of a second user;
and after receiving the position information of the target collection point, the mobile terminal of the second user acquires the current position information of the second user and carries out path planning.
A system for intelligently selecting logistics collection points, wherein the system comprises: the method comprises the steps that a mobile terminal of a first user and a mobile terminal of a second user connected with the mobile terminal of the first user are connected;
the mobile terminal of the first user comprises:
the data acquisition module is used for collecting travel data information of a first user and analyzing a travel rule of the first user based on the thermal distribution of the first user on a map;
the data analysis module is used for analyzing the times of the first user appearing in the preset distance range of each logistics collection point in the preset time range according to the travel rule of the first user;
the target selection module is used for setting the logistics collection point with the maximum times as a target collection point and sending the position information of the target collection point to a preset mobile terminal of a second user;
the mobile terminal user of the second user receives the position information of the target collection point sent by the mobile terminal of the first user, and carries out path planning according to the position information;
the first user is a user for receiving logistics, and the second user is a user for distributing logistics.
A storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to perform the steps of a method of intelligently selecting logistics collection points of any of the above.
A mobile terminal, comprising: a processor, a storage medium communicatively coupled to the processor, the storage medium adapted to store a plurality of instructions; the processor is adapted to invoke instructions in the storage medium to perform the steps of a method of intelligently selecting a logistics collection point of any of the above.
The invention has the beneficial effects that: according to the invention, the travel rule of the first user is acquired and analyzed based on the thermal distribution, and the optimal logistics collection point is selected according to the travel rule of the first user, so that the distribution path of the second user to the logistics is improved, the distribution space-time mismatch rate is effectively reduced, and the distribution efficiency is improved.
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FIG. 1 is a flow chart of a preferred embodiment of the method for intelligently selecting logistics collection points of the present invention.
Fig. 2 is a diagram of the thermodynamic distribution of a user on a map in the method for intelligently selecting logistics collection points according to the invention.
Fig. 3 is a functional schematic diagram of the mobile terminal of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
In recent years, the rapid development of China's electric business leads to the rapid increase of the number of express deliveries. In 2017, the express delivery volume of China breaks through 400 hundred million pieces, and the express delivery volume is expected to increase at a speed of 100 hundred million pieces every year. According to the data published by the official network of the state post and government offices, in 2018, 1-5 months, the service income of the postal industry (excluding the direct business income of a postal savings bank) is accumulated to be 3071.7 yen, and the business income is increased by 22.9 percent on year-on-year basis. In the aspect of express service, in 1-5 months, the business volume of national express service enterprises is accumulated and is 178.5 hundred million, and the business volume is increased by 28.3 percent on year-on-year basis; wherein, the traffic in the same city is accumulated by 41.1 hundred million pieces, and the traffic is increased by 27.1 percent on the same scale; the traffic of different places is accumulated to complete 133 hundred million pieces, and the traffic is increased by 28.1 percent on a par with the accumulated traffic. In 5 months, the business volume of nationwide express service enterprises is 41.8 hundred million, and the business volume is increased by 25.1 percent on year-by-year basis.
The quantity of express packages is increased sharply, so that the pressure at the tail end of logistics is huge. The express delivery quantity is increased, pressure is increased for a delivery center at the tail end, and when the express delivery quantity is increased rapidly, a tail end delivery point is prone to risks of bin explosion. Secondly, a large amount of express packages are backlogged at the tail end, so that a large amount of logistics distribution is delayed, and the user experience is reduced. The cost of the final end delivery point is increased, the cost of the end delivery in China is higher than 30%, and the cost is more obvious in cities due to factors of rent, traffic, delivery environment and employment cost.
In the face of terminal pressure, a new distribution mode is introduced for terminal distribution in cities, and users are self-promoted to be a mainstream mode. The efficiency is improved in a user self-picking mode, and meanwhile, the delivery time mismatch is not greatly improved. Although the proportion of the distribution to the door can be reduced to a certain extent by adopting a user self-service mode in the end distribution, the time of couriers is saved. Meanwhile, the self-service cabinet runs continuously for 24 hours, and convenience is brought to users for collecting express at selected time. However, this approach does not greatly improve on resolving the time-space difference between the courier and the user, but gives the user the freedom to choose the time to receive the courier. When express delivery sharply increases, the terminal self-picking-up point also faces the problem of insufficient storage space and overstocked express delivery of users.
In order to solve the above problem, the present invention provides a method for intelligently selecting a logistics collection point, as shown in fig. 1, the method comprising:
step S100, a mobile terminal of a first user collects travel data information of the first user, and analyzes a travel rule of the first user based on the thermal distribution of the first user on a map;
step S200, analyzing the times of the first user appearing in a preset distance range of each logistics collection point in a preset time range according to the travel rule of the first user;
and step S300, setting the logistics collection point with the largest number of times as a target collection point, and sending the position information of the target collection point to a preset mobile terminal of a second user so as to enable the mobile terminal of the second user to carry out path planning.
The method and the system have the advantages that the travel rule of the first user is acquired and analyzed based on the thermal distribution, the optimal logistics collection point is selected according to the travel rule of the first user, and after the second user receives the address of the optimal logistics collection point, the path planning is carried out, so that the distribution path of the second user for the logistics is improved, the distribution space-time mismatching rate is effectively reduced, and the distribution efficiency is improved.
With the development of mobile terminals, mobile phone APP and geographic information technology, it becomes possible to find the optimal point of logistics end distribution by sensing user spatial information and combining the existing logistics technology based on the user spatial information. The invention integrates the spatial aggregation of user travel in the geographic information, presents a hot point distribution rule and is combined with the vehicle path problem, thereby realizing the intelligent selection and path optimization of the logistics collection points in the logistics distribution process at the tail end of the city.
In specific implementation, the invention predefines two mobile terminals, namely a mobile terminal of a first user and a mobile terminal of a second user, wherein the first user is a user for receiving logistics, and the second user is a user (courier) for delivering logistics. The mobile terminal of a first user collects and records travel data information of the first user through a self-contained GPS module, wherein the travel data comprises: the longitude and latitude of the location of the first user, and the current time. After the travel data is collected, the position point where the first user appears in the collected travel data information is mapped on a map and presented in a heat distribution manner, as shown in fig. 3. And analyzing the travel rule of the first user according to the heat distribution on the map.
As can be seen from fig. 3, when the first user appears at a certain location, a corresponding shadow trace is correspondingly left on the map, and the higher the frequency of the first user appearing at the same location, the deeper the shadow left on the map, so that the location where the first user appears most frequently can be known through the position and the color depth of the shadow trace on the map, and in addition, the mobile terminal of the present invention can record the time when the first user travels to different locations, so that the time period in which the locations where the first user travels most frequently are approximately distributed can be quickly obtained, that is, the travel rule of the first user can be obtained. Therefore, the collected position points are mapped on the map, the travel position data of the user are gathered in space and presented in hot spot distribution, and the travel rule of the first user can be more obviously reflected through time constraint.
Preferably, the trip position points of the first user can be screened based on the trip data of the first user, and the position points with the frequency obviously lower than a certain value are deleted and are not displayed on a map, so that the trip rule of the first user can be better analyzed. For example, when the average number of times that the first user appears in the same place every week is less than 3 times, the place is considered to be not a place where the first user frequently goes, the place has no great significance for the analysis of the travel law of the first user, data of the place can be deleted in sequence, the thermal distribution is not displayed on a map, and the accuracy of the travel law analysis is improved.
Further, after the travel data of the first user are obtained, the mobile terminal of the first user calculates distances from the travel position point of the first user to each known logistics collection point, and compares the distances with a preset distance range; and when the calculated distance meets the distance range, calculating the times of the first user appearing at each logistics collection point in a preset time range.
According to the method, the time of a first user at a certain travel position point is compared with the time range, so that the travel position points which do not meet the time range are screened, the distance between the screened travel position points and the logistics collection point is calculated and compared with the distance range, and the travel position points which meet the distance range are further screened. Therefore, the travel position points finally screened need to satisfy both the time range and the distance range. Preferably, since the trip data of the first user includes longitude and latitude data of each location point, the method for calculating the distance in the present invention may adopt a method for calculating a location distance between two points on a spherical surface.
Preferably, the present invention presets a time range and a distance range; and the time range and the distance range are used for further screening out the travel position points meeting the conditions from the travel rule of the first user and eliminating the travel position points not meeting the conditions. Since the invention mainly aims at the logistics distribution industry, the time (from 9 am to 18 pm) when the first user conveniently receives the accessories can be set to be the time range, and the distance from the travel position point to the known logistics collection point can be further calculated only by the travel position point meeting the time range, so that the travel position point can be further screened. In addition, the distance range in the present invention is a distance of the self-lifting express item optimal for the first user, for example, 0 to 500 meters. And further screening whether the positions from the travel position point of the first user to the known logistic collection point meet the condition or not according to the distance range, and if the position from the travel position point of the first user to the logistic collection point is more than 500 meters, indicating that the logistic collection point is not the optimal logistic collection point, and directly excluding the logistic collection point.
And after the screening of the time range and the distance range is completed for the travel position point of the first user, calculating the times of the first user appearing at each logistics collection point meeting the conditions. Because the times of the first user appearing at different logistics collection points are different, the logistics collection point with the largest appearing times is the optimal target collection point.
Specifically, the following algorithm may be adopted in this embodiment to calculate the number of times that the first user appears at each logistics collection point. For example, the first user needs to be analyzed within a preset time range [ t', t ″ ]]The times of the internal appearance in the preset distance range L of each logistics collection point, and the recorded times formula
Figure GDA0003827915630000101
Wherein Q represents a set of logistic collection points, P represents a set of first users, i represents a user, j represents a logistic collection point, and Q j Represents a set of logistic collection points, P i Representing a set of users, k representing a location point of user i,
Figure GDA0003827915630000102
the sum of the number of the position points which satisfy the preset time and the preset distance in the preset range is shown, I shows whether the position point of a certain record satisfies the preset time [ t', t]And a variable of 0-1 for the predetermined distance L. I =1 when it simultaneously satisfies the condition, otherwise I =0.
Figure GDA0003827915630000103
In the formula, D represents a distance function between two points, i represents a user, j represents a logistics collection point, k represents a position point of the user i, and x ik Denotes the longitude, y, of user i at the kth location point ik Indicates the latitude of user i at the kth location point, a j Longitude position information indicating jth physical distribution collection point, b j Latitude position information, t, representing the jth logistics collection point ik Representing the time at which user i is at the kth location point.
Will satisfy the preset time t', t for the first user "]And presetting the distance L, and setting the logistics collection point with the maximum recorded position data frequency as a target collection point. The model is expressed as
Figure GDA0003827915630000111
Wherein M represents the number of collection points, t j Represents the opening time of a logistic collection point j, t max Represents the maximum open time of the logistic collection point.
Further, the mobile terminal of the first user sets the calculated logistics collection point with the largest number of times as a target collection point; and acquiring the position information of the target collection point, and sending the position information of the target collection point to a mobile terminal of a second user. And after receiving the position information of the target collection point, the mobile terminal of the second user acquires the current position information of the second user and carries out path planning. Preferably, the path planning method of the invention is different from the traditional path planning, and the path planning of the invention is carried out by combining the travel rule of the first user, namely, the delivery receiving time range of the first user is taken into an optimization link, and the path planning is not carried out by only considering the shortest distance or the lowest cost of the second user, namely, the courier in the traditional method. For example, after the second user receives the location information of the target collection point set by the first user, the mobile terminal of the second user automatically performs path planning, and considers the time when the first user conveniently receives the logistics (for example, the time when the first user conveniently receives the logistics only at 9-11 am) while performing the path planning, so as to perform logistics distribution more accurately.
Preferably, in the present invention, the mobile terminal of the first user and the mobile terminal of the second user need to establish a communication connection in advance, and the communication connection may be in various manners, which is not limited in this embodiment. For example, the communication method may adopt the existing communication technology, and an application program is designed, and the mobile terminal of the first user and the mobile terminal of the second user can log in through respective ports, and real-time communication can be performed on the application program. In addition, the first user can select and update the target collection point on the application program, and the second user can check the target collection point selected by the first user on the application program, so that path planning is facilitated. Preferably, the route planning of the target collection point for the mobile terminal of the second user can be carried out by the method, so that the conventional navigation application can be carried, more convenient and faster navigation service can be provided for the second user (courier), and the logistics distribution efficiency is improved.
Therefore, the selection of the target collection point is based on the condition that the travel position point of the first user needs to meet the time range and the distance range and the condition that the total times of the first user appearing at each logistics collection point are the maximum, so that the selected logistics collection point is the optimal collection point, and a second user (courier) can carry out logistics distribution according to the selected optimal collection point, so that the express mail can be distributed to the optimal collection point of the receiver, the distribution time-space mismatching rate is reduced, the logistics distribution efficiency is effectively improved, and the risk that all the express mails are distributed at the same collection point to cause a collection point warehouse is avoided.
Based on the above embodiment, the present invention further provides a system for intelligently selecting a logistics collection point, where the system includes: the mobile terminal of the first user and the mobile terminal of the second user connected with the mobile terminal of the first user. The first user is a user for receiving logistics, and the second user is a user for distributing logistics.
The mobile terminal of the first user comprises:
the data acquisition module is used for collecting travel data information of a first user and analyzing a travel rule of the first user based on the thermal distribution of the first user on a map;
the data analysis module is used for analyzing the times of the first user appearing in the preset distance range of each logistics collection point in the preset time range according to the travel rule of the first user;
and the target selection module is used for setting the logistics collection point with the maximum times as a target collection point and sending the position information of the target collection point to a preset mobile terminal of a second user.
And the mobile terminal user of the second user receives the position information of the target collection point sent by the mobile terminal of the first user and carries out path planning according to the position information.
Further, the data acquisition module comprises:
the system comprises a data collection unit, a data processing unit and a data processing unit, wherein the data collection unit is used for collecting and recording trip data information of a first user by a mobile terminal of the first user through a self-contained GPS module;
the data presentation unit is used for mapping the position point where the first user appears in the collected travel data information on a map and presenting the position point in a heat distribution mode;
and the rule analysis unit is used for analyzing the travel rule of the first user according to the heat distribution of the first user on the map.
The data analysis module includes:
the first calculating unit is used for calculating the distance from the travel position point of the first user to each known logistics collection point and comparing the distance with a preset distance range;
and the second calculating unit is used for calculating the times of the first user appearing at each logistics collection point in a preset time range when the calculated distance meets the distance range.
The target selection module comprises:
a target setting unit, configured to set, by the mobile terminal of the first user, the logistics collection point with the largest calculated number of times as a target collection point;
and the information sending unit is used for acquiring the position information of the target collection point and sending the position information of the target collection point to a mobile terminal of a second user so as to enable the mobile terminal of the second user to carry out path planning.
Based on the above embodiment, the present invention also discloses a mobile terminal, as shown in fig. 3, including: a processor (processor) 10, a storage medium (memory) 20 connected to the processor 10; wherein, the processor 10 is configured to call the program instructions in the storage medium 20 to execute the method provided by the foregoing embodiment, for example, to execute:
the method comprises the steps that a mobile terminal of a first user collects travel data information of the first user, and a travel rule of the first user is analyzed based on the thermal distribution of the first user on a map;
analyzing the times of the first user appearing in a preset distance range of each logistics collection point in a preset time range according to the travel rule of the first user;
and setting the logistics collection point with the largest number of times as a target collection point, and sending the position information of the target collection point to a preset mobile terminal of a second user so as to enable the mobile terminal of the second user to carry out path planning.
It should be noted that the mobile terminal in this embodiment includes a mobile terminal of a first user and a mobile terminal of a second user, and the mobile terminal of the first user and the mobile terminal of the second user may be interchanged.
Embodiments of the present invention further provide a storage medium, where a computer instruction is stored on the storage medium, and the computer instruction causes a computer to execute the method provided in each of the above embodiments.
In summary, the present invention provides a method, a system, a storage medium and a mobile terminal for intelligently selecting a logistics collection point, wherein the method comprises: the method comprises the steps that a mobile terminal of a first user collects travel data information of the first user, and a travel rule of the first user is analyzed based on the thermal distribution of the first user on a map; analyzing the times of the first user appearing in a preset distance range of each logistics collection point in a preset time range according to the travel rule of the first user; and setting the logistics collection point with the largest number of times as a target collection point, and sending the position information of the target collection point to the mobile terminal of the second user so as to enable the mobile terminal of the second user to carry out path planning. According to the invention, the travel rule of the first user is acquired and analyzed based on the thermal distribution, and the optimal logistics collection point is selected according to the travel rule of the first user, so that the distribution path of the second user to the logistics is improved, the distribution time-space mismatching rate is effectively reduced, and the distribution efficiency is improved.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.

Claims (7)

1. A method for intelligently selecting logistics collection points, the method comprising:
the method comprises the steps that a mobile terminal of a first user collects travel data information of the first user, and a travel rule of the first user is analyzed based on the thermal distribution of the first user on a map;
analyzing the times of the first user appearing in a preset distance range of each logistics collection point in a preset time range according to the travel rule of the first user;
setting the logistics collection point with the largest number of times as a target collection point, and sending the position information of the target collection point to a preset mobile terminal of a second user so as to enable the mobile terminal of the second user to carry out path planning;
the first user is a user for receiving logistics, and the second user is a user for distributing logistics;
the analyzing, according to the travel rule of the first user, the number of times that the first user appears in a preset distance range of each logistic collection point within a preset time range specifically includes:
calculating the distance from the travel position point of the first user to each known logistics collection point, and comparing the distance with a preset distance range;
when the calculated distance meets the distance range, calculating the times of the first user appearing at each logistics collection point in a preset time range;
the method further comprises the following steps: the mobile terminal of the first user updates the target collection point and sends the updated target collection point to the mobile terminal of the second user;
the method further comprises the following steps:
presetting a time range and a distance range;
the time range and the distance range are used for screening out travel position points meeting the conditions from the travel rule of the first user and eliminating the travel position points not meeting the conditions;
when the calculated distance satisfies the distance range, calculating the number of times that the first user appears at each logistics collection point within a preset time range, including:
the first user needs to be analyzed within a preset time range [ t', t]The times of the internal appearance in the preset distance range L of each logistics collection point, and the recorded times formula
Figure FDA0003827915620000021
Wherein Q represents a set of logistic collection points, P represents a set of first users, i represents a user, j represents a logistic collection point, and Q j Represents a collection of logistics collection points, P i Representing a set of users, k representing the location point of user i,
Figure FDA0003827915620000022
the sum of the number of the position points meeting the preset time and the preset distance in the preset range is represented, I represents whether the position point of a record meets the preset time [ t', t]And a variable of 0-1 of the preset distance L, I =1 when it satisfies the condition at the same time or I =0 otherwise,
Figure FDA0003827915620000023
in the formula, D represents a distance function of two points, i represents a user, j represents a logistics collection point, k represents a position point of the user i, and x ik Represents the longitude, y of user i at the kth location point ik Indicates the latitude, a, of user i at the kth location point j Longitude position information indicating jth physical distribution collection point, b j Latitude position information, t, representing the jth logistics collection point ik Represents the time of user i at the kth location point;
will satisfy the preset time t', t for the first user "]And setting the logistics collection point with the maximum recorded position data times at a preset distance L as a target collection point, wherein the model is expressed as
Figure FDA0003827915620000024
Wherein M represents the number of collection points, t j Represents the opening time of a logistics collection point j, t max Represents the maximum open time of the logistic collection point.
2. The method of claim 1, wherein the collecting, by the mobile terminal of the first user, the travel space information of the first user, and analyzing the travel rule of the first user based on the thermal distribution of the first user on the map specifically comprises:
the method comprises the following steps that a mobile terminal of a first user collects and records travel data information of the first user through a GPS module of the mobile terminal;
mapping a position point of a first user in the collected travel data information on a map, and presenting the position point in a heat distribution mode;
and analyzing the travel rule of the first user according to the heat distribution of the first user on the map.
3. The method of intelligently selecting logistics collection points of claim 2, wherein the travel data comprises: the longitude and latitude of the location of the first user, and the current time.
4. The method according to claim 1, wherein the setting of the logistics collection point with the largest number of times as a target collection point and the sending of the location information of the target collection point to a preset mobile terminal of a second user, so that the path planning of the mobile terminal of the second user specifically includes:
the mobile terminal of the first user sets the logistics collection point with the maximum calculated times as a target collection point;
acquiring the position information of the target collection point, and sending the position information of the target collection point to a mobile terminal of a second user;
and after receiving the position information of the target collection point, the mobile terminal of the second user acquires the current position information of the second user and carries out path planning.
5. A system for intelligently selecting logistics collection points, the system comprising: the method comprises the steps that a mobile terminal of a first user and a mobile terminal of a second user connected with the mobile terminal of the first user are connected;
the mobile terminal of the first user comprises:
the data acquisition module is used for collecting travel data information of a first user and analyzing a travel rule of the first user based on the thermal distribution of the first user on a map;
the data analysis module is used for analyzing the times of the first user appearing in the preset distance range of each logistics collection point in the preset time range according to the travel rule of the first user;
the target selection module is used for setting the logistics collection point with the maximum times as a target collection point and sending the position information of the target collection point to a preset mobile terminal of a second user;
the mobile terminal user of the second user receives the position information of the target collection point sent by the mobile terminal of the first user and carries out path planning according to the position information;
the first user is a user for receiving logistics, and the second user is a user for distributing logistics;
the analyzing, according to the travel rule of the first user, the number of times that the first user appears in a preset distance range of each logistic collection point within a preset time range specifically includes:
calculating the distance from the travel position point of the first user to each known logistics collection point, and comparing the distance with a preset distance range;
when the calculated distance meets the distance range, calculating the times of the first user appearing at each logistics collection point in a preset time range;
presetting a time range and a distance range;
the time range and the distance range are used for screening out the travel position points meeting the conditions from the travel rule of the first user and eliminating the travel position points not meeting the conditions;
when the calculated distance satisfies the distance range, calculating the number of times that the first user appears at each logistics collection point within a preset time range, including:
the first user needs to be analyzed within a preset time range [ t', t ″ ]]The times of the internal appearance in the preset distance range L of each logistics collection point, and the recorded times formula
Figure FDA0003827915620000051
Wherein Q represents a set of logistic collection points, P represents a set of first users, i represents a user, j represents a logistic collection point, and Q j Represents a set of logistic collection points, P i Representing a set of users, k representing a location point of user i,
Figure FDA0003827915620000052
the sum of the number of the position points which satisfy the preset time and the preset distance in the preset range is shown, I shows whether the position point of a certain record satisfies the preset time [ t', t]And a variable of 0-1 for a preset distance L, I =1 when it satisfies the condition at the same time or I =0 otherwise,
Figure FDA0003827915620000053
in the formula, D represents a distance function between two points, i represents a user, j represents a logistics collection point, k represents a position point of the user i, and x ik Denotes the longitude, y, of user i at the kth location point ik Indicates the latitude of user i at the kth location point, a j Longitude and latitude information indicating the jth physical distribution collection point, b j Latitude position information representing the jth logistics collection point, t ik Represents the time of user i at the kth location point;
will satisfy the preset time t', t for the first user "]And setting the logistics collection point with the maximum number of times of the recorded position data at a preset distance L as a target collection point, wherein the model is expressed as
Figure FDA0003827915620000061
Wherein M represents the number of collection points, t j The open time of the logistics collection point j is shown,t max represents the maximum open time of the logistic collection point.
6. A storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to perform the steps of a method for intelligently selecting logistics collection points according to any of claims 1-4.
7. A mobile terminal, comprising: a processor, a storage medium communicatively coupled to the processor, the storage medium adapted to store a plurality of instructions; the processor is adapted to invoke instructions in the storage medium to perform the steps of a method of implementing the intelligent selection logistics collection point of any one of the above claims 1-4.
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