CN114529034B - Scenic spot pleasure boat intelligent scheduling method based on real-time passenger flow - Google Patents
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Abstract
The invention discloses an intelligent scenic spot pleasure boat scheduling method based on real-time passenger flow, which comprises the following steps: data collection is carried out firstly; determining the instant bearing capacity of the station; then calculating future passenger flow trend; finally determining a dispatching station; distributing according to the degree that each station exceeds different instant bearing capacity, and calculating the optimal distance of all dispatching pleasure boats and dispatching stations to obtain an optimal running scheme; the problem that people flow is not evacuated timely and tourist waiting time is long because the number of tourists exceeds the site bearing pressure and then scheduling is arranged in the past is solved.
Description
Technical Field
The invention relates to the field of cruise ship management and control, in particular to an intelligent scenic spot cruise ship scheduling method based on real-time passenger flow.
Background
With the rapid development of Chinese economy in recent years, the tourist industry is continuously heated, the number of scenic spots and tourist numbers developed nationwide are continuously increased, higher requirements are made on the bearing and balancing capacity of the scenic spots, and particularly the problems of ticket purchasing queuing, vehicle and ship scheduling failure, overlong waiting time and the like caused by the rapid increase of the number of tourist spots can occur in the scenic spots during holidays. The reason for the problems is mainly that tourists in scenic spots are numerous and the environment is complex, so that an administrator cannot acquire and master the conditions and information of the tourists in scenic spots in real time, and the situation that vehicles and ships are dispatched to the scene cannot be timely guaranteed. The intelligent scheduling method for the scenic spot pleasure boats based on the real-time passenger flow volume improves the operation efficiency of the scenic spot pleasure boats, reduces the cost and improves the playing experience of tourists.
The existing scenic spot pleasure boat scheduling scheme is mainly that management staff views information of scenic spot sites through a monitoring system and then initiates scheduling tasks to the management staff through interphones according to experience, the scheme has high requirements on the management staff, the situation of the pleasure boat and the sites needs to be focused in real time, and real-time scheduling cannot be achieved.
In the prior art, a supervision system is mainly adopted, an administrator can see real-time running conditions of the pleasure boats and real-time passenger flow information of stations, but effective analysis is carried out on real-time passenger flow in future time, so that the problem of delayed scheduling of the pleasure boats is caused.
For example, chinese patent application No.: CN202010525181.5, a platform and a method for dispatching and managing the number of pleasure boats, the platform comprises: the quantity analysis equipment is used for receiving the first collection quantity and the second collection quantity, and sending a pleasure boat conveying instruction when the quotient value obtained by dividing the second collection quantity by the first collection quantity is smaller than or equal to a preset quotient value; the wireless dispatching interface is connected with the quantity analysis equipment and is used for wirelessly transmitting pleasure boat conveying instructions or pleasure boat conveying instructions to a server of a remote pleasure boat dispatching center; the wireless mobilizing interface is also used for synchronously transmitting the number of the transported pleasure boats to a server of a remote pleasure boat dispatching center when the pleasure boat transporting instruction is transmitted; the invention has complex process and slow dispatching of the pleasure boat.
Disclosure of Invention
The invention mainly solves the problem of slow scheduling of the pleasure boats in the prior art, and provides a method for intelligently scheduling the pleasure boats in advance according to a station passenger flow pressure threshold.
The technical scheme adopted for solving the technical problems is as follows:
the invention provides an intelligent scenic spot pleasure boat scheduling method based on real-time passenger flow, which comprises the following steps:
s1: collecting data;
s2: determining the instant bearing capacity of a station; defining i as the number of pleasure boat stations in the scenic spot according to the berthing sequence, wherein the number of pleasure boats at the station i is n, defining j as the number of pleasure boats in the station, and the passenger carrying capacity of each pleasure boat is c j The area of the station is A i The most number of serviceable people per unit area
And if the large density is gamma, the maximum number of serviceable persons of the instant pleasure boat at the station i is as follows:
site i service area maximum number of waitable people: w (W) i ＝γA i ；
Station instantaneous bearing capacity z according to different pleasure boat states i Is divided into two parts:
a. when the station has a free pleasure boat, the instant bearing capacity of the station i is defined as the maximum number of people which can be served by the free pleasure boat;
b. when the station pleasure boats are running, the instantaneous bearing capacity of the station i defines that the waiting number of people in the service area of the station i is multiplied by a coefficient alpha; the data collected in step S1 can be used to determine the instantaneous load capacity of the station, which is a major determinant for determining the scheduling of the pleasure craft.
S3: calculating future passenger flow trend;
s4: a scheduling site is determined.
And distributing according to the degree that each station exceeds different instantaneous bearing capacity, and calculating the optimal distance of all dispatching pleasure boats and dispatching stations to obtain an optimal running scheme.
Preferably, the step S1 further includes the steps of:
a: collecting the position of a berthing station of a pleasure boat and the size of a station service area;
b: collecting the number of pleasure boats at each site and the passenger carrying capacity of the pleasure boats;
c: a feasibility network between the sites is determined.
Setting a stop station and determining the actual situation of a service area, and fully considering the riding requirement of tourists; the number of pleasure boats at the sites should be reasonably distributed at each site according to historical experience; after the cruise ships receive the schedule, a travel route may be selected among these feasibility networks.
Preferably, the step S3 further includes generating a set of tourist number data varying with time sequence according to the tourist flow data returned in real time, and calculating the number of tourists in future time by using linear regression.
Setting a geofence as a service area of a pleasure boat station within a certain distance, and setting the number of people m of the station in real time i And the sum of the number of tourists returned according to the site camera interface data in the effective service area of the site i.
Preferably, the linear regression formula is:
y＝bx+α+ε，∈～N(0，，σ 2 )，
wherein the method comprises the steps ofRepresents the sum of squares of y; r isCorrelation coefficient representing the ratio of variance interpreted by regression line; s is S yy (1-r 2 ) That is, variations that cannot be explained between regressions, SSEs; />Wherein y is i Is the actual value, Y i Is a predicted value calculated according to a linear equation.
Preferably, the step S4 further includes determining a scheduling site: calculating and obtaining the tourist flow v of each station at a certain moment in the future according to the prediction model i The site pressure value at this time is noted as:when mu i When the number is more than 1, the station is required to schedule pleasure boats; when the pressure value of a plurality of stations is greater than 1, the pressure value is expressed as mu i And sorting the values, preferentially scheduling the stations with larger pressure values, and then recalculating the station pressure values.
Preferably, the step S4 further includes determining to dispatch the pleasure boat: obtaining the time distance t from the current time of the station needing to be scheduled according to the tourist flow prediction model i Analyzing the distance of each dispatching pleasure boat reaching the site needing to be dispatched, and recording the combined set S= {1,2, 3..n } of the sites needing to be dispatched, wherein the combined set of the positions of the dispatching pleasure boats is {1,2, 3..m }, n }<The scheme of m, sharing pleasure boat dispatch is as follows:
preferably, the pleasure boat scheduling scheme further comprises the following scheme: b (B) v For the travel matrix of cruise ship V, if the cruise ship will travel from station i to station j (i and j being any two cruise ship service stations in the scenic spot), thenL ij An optimal path distance matrix from the station i to the station j; the sum of the distances of this scheme is:
preferably, the step S4 obtains an optimal path of the pleasure boat dispatch after calculating the path sum of each scheme; when the pleasure boat scheduling scheme is selected, the optimal distance calculation is carried out on all the scheduled pleasure boats and the scheduled stations according to the fact that the stations exceed different instantaneous bearing capacity degrees, and the optimal running scheme is obtained. And continuing to execute the step S1 after the dispatching is completed until the passenger flow positive pressure of each station is 1, and ending the dispatching.
The invention has the advantages that:
(1) By using a linear regression method, the real-time flow data of scenic spots in a period of time in the future can be predicted is displayed, and the problem that people can only evacuate in time when the number of tourists exceeds the bearing pressure of the spots and then scheduling is arranged in the past, so that the waiting time of the tourists is long is solved.
(2) When the pleasure boat scheduling scheme is selected, the optimal distance calculation is carried out on all the scheduled pleasure boats and the scheduled stations according to the fact that the stations exceed different instantaneous bearing capacity degrees, and the optimal running scheme is obtained.
Drawings
FIG. 1 is a flow chart of the scheduling method of the present invention;
FIG. 2 is a calculated base map of the operation of the pleasure boat of the present invention.
Detailed Description
The technical solution of the present invention will be further described by way of examples with reference to the accompanying drawings, and it should be understood that the preferred embodiments described herein are merely for illustrating and explaining the present invention, and are not limited thereto.
Examples: the invention provides an intelligent scenic spot pleasure boat scheduling method based on real-time passenger flow, which is shown in fig. 1 and comprises the following steps:
s1: collecting data; collecting the position of a berthing station of a pleasure boat and the size of a station service area; setting a stop station and determining the actual situation of a service area, fully considering the riding requirement of tourists, enabling the stop station to be as close to a position with more people in a scenic spot as possible, and enabling colleagues to consider other factors such as safety, convenience, comfort and the like; collecting the number of pleasure boats at each site and the passenger carrying capacity of the pleasure boats; the number of pleasure boats at the stations is reasonably distributed at each station according to historical experience, so that the dispatching cost is reduced as much as possible; determining a feasibility network among stations; after the cruise ships receive the schedule, a travel route may be selected among these feasibility networks.
S2: determining the instant bearing capacity of a station; defining i as the number of pleasure boat stations in the scenic spot according to the berthing sequence, wherein the number of pleasure boats at the station i is n, defining j as the number of pleasure boats in the station, and the passenger carrying capacity of each pleasure boat is c j The area of the station is A i The most number of serviceable people per unit area
And if the large density is gamma, the maximum number of serviceable persons of the instant pleasure boat at the station i is as follows:
site i service area maximum number of waitable people: w (W) i ＝γA i ；
Station instantaneous bearing capacity z according to different pleasure boat states i Is divided into two parts:
a. when the station has a free pleasure boat, the instant bearing capacity of the station i is defined as the maximum number of people which can be served by the free pleasure boat;
b. when the station pleasure boats are running, the instantaneous bearing capacity of the station i defines that the waiting number of people in the service area of the station i is multiplied by a coefficient alpha; the data collected in step S1 can be used to determine the instantaneous load capacity of the station, which is a major determinant for determining the scheduling of the pleasure craft.
S3: calculating future passenger flow trend; setting a geofence as a service area of a pleasure boat station within a certain distance, and setting the number of people m of the station in real time i The sum of the number of tourists returned according to the site camera interface data in the effective service area of the site i; including according to the realityAnd (3) returning the tourist flow data, generating a group of tourist number data changing with time sequence, as shown in figure 2, and calculating the number of the tourists in the future time by using linear regression.
The linear regression formula is:
y＝bx+α+ε，∈～N(0，，σ 2 )，
wherein the method comprises the steps ofRepresents the sum of squares of y; r is a correlation coefficient representing the ratio of variance interpreted by the regression line; s is S yy (1-r 2 ) That is, variations that cannot be explained between regressions, SSEs; />Wherein y is i Is the actual value, Y i Is a predicted value calculated according to a linear equation. By using a linear regression method, the real-time flow data of scenic spots in a period of time in the future can be predicted is displayed, and the problem that people can only evacuate in time when the number of tourists exceeds the bearing pressure of the spots and then scheduling is arranged in the past, so that the waiting time of the tourists is long is solved.
S4: determining a scheduling site; further comprising determining a scheduling site: calculating and obtaining the tourist flow v of each station at a certain moment in the future according to the prediction model i The site pressure value at this time is noted as:when mu i When the number is more than 1, the station is required to schedule pleasure boats; when the pressure value of a plurality of stations is greater than 1, the pressure value is expressed as mu i And sorting the values, preferentially scheduling the stations with larger pressure values, and then recalculating the station pressure values.
Step S4 further comprises determining to dispatch the cruise ship: obtaining the time distance current when the station to be scheduled needs to be scheduled according to the tourist flow prediction modelTime t i Analyzing the distance of each dispatching pleasure boat reaching the site needing to be dispatched, and recording the combined set S= {1,2, 3..n } of the sites needing to be dispatched, wherein the combined set of the positions of the dispatching pleasure boats is {1,2, 3..m }, n }<The scheme of m, sharing pleasure boat dispatch is as follows:
the pleasure boat scheduling scheme also comprises the following schemes: b (B) v For the travel matrix of cruise ship V, if the cruise ship will travel from station i to station j (i and j being any two cruise ship service stations in the scenic spot), thenL ij An optimal path distance matrix from the station i to the station j; the sum of the distances of this scheme is:
step S4, after calculating the path sum of each scheme, obtaining the optimal path of pleasure boat dispatching; and continuing to execute the step S1 after the dispatching is completed until the passenger flow positive pressure of each station is 1, and ending the dispatching. When the pleasure boat scheduling scheme is selected, the optimal distance calculation is carried out on all the scheduled pleasure boats and the scheduled stations according to the fact that the stations exceed different instantaneous bearing capacity degrees, and the optimal running scheme is obtained.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. The intelligent scenic spot pleasure boat scheduling method based on the real-time passenger flow is characterized by comprising the following steps of:
s1: collecting data;
s2: determining the instant bearing capacity of a station; defining i as the number of pleasure boat stations in the scenic spot according to the berthing sequence, wherein the number of pleasure boats at the station i is n, defining j as the number of pleasure boats in the station, the passenger carrying capacity of each pleasure boat is cj, the area of the station is Ai, and the number of serviceable persons in unit area is the greatest
And if the large density is gamma, the maximum number of serviceable persons of the instant pleasure boat at the station i is as follows:
site i service area maximum number of waitable people: w (W) i ＝γA i ；
The instantaneous bearing capacity zi of the station is divided into two parts according to the different states of the pleasure boat:
a. when the station has a free pleasure boat, the instant bearing capacity of the station i is defined as the maximum number of people which can be served by the free pleasure boat;
b. when the station pleasure boats are running, the instantaneous bearing capacity of the station i defines that the waiting number of people in the service area of the station i is multiplied by a coefficient alpha;
s3: calculating future passenger flow trend;
s4: determining a scheduling site;
the step S1 includes the steps of:
a: collecting the position of a berthing station of a pleasure boat and the size of a station service area;
b: collecting the number of pleasure boats at each site and the passenger carrying capacity of the pleasure boats;
c: determining a feasibility network among stations;
step S3, generating a group of tourist quantity data changing along with a time sequence according to the tourist flow data returned in real time, and calculating the number of tourists in future time by utilizing linear regression;
the linear regression formula is:
y＝bx+α+ε，∈～N(0，σ 2 )，wherein->Represents the sum of squares of y; r is a correlation coefficient representing the ratio of variance interpreted by the regression line; s is S yy (1-r 2 ) That is, variations that cannot be explained between regressions, SSEs; />Wherein y is i Is the actual value, Y i Is a predicted value calculated according to a linear equation;
the step S4 further includes determining a scheduling site: calculating and obtaining the tourist flow v of each station at a certain moment in the future according to the prediction model i The site pressure value at this time is noted as:when mu i When the number is more than 1, the station is required to schedule pleasure boats; when the pressure value of a plurality of stations is greater than 1, the pressure value is expressed as mu i Sequencing the values, preferentially scheduling the sites with larger pressure values, and then recalculating the site pressure values;
the step S4 further comprises determining to dispatch the pleasure boat: obtaining the time distance t from the current time of the station needing to be scheduled according to the tourist flow prediction model i Analyzing the distance of each dispatching pleasure boat reaching the site needing to be dispatched, and recording the combined set S= {1,2, 3..n } of the sites needing to be dispatched, wherein the combined set of the positions of the dispatching pleasure boats is {1,2, 3..m }, n }<The scheme of m, sharing pleasure boat dispatch is as follows:
the pleasure boat scheduling scheme also comprises the following steps ofThe scheme is as follows: b (B) v For the travel matrix of cruise ships V, if the cruise ships travel from station i to station j (i and j being any two cruise ship service stations in the scenic spot),then L is ij An optimal path distance matrix from the station i to the station j; the sum of the distances of the scheme is:
step S4, after calculating the path sum of each scheme, obtaining the optimal path of pleasure boat dispatching; and continuing to execute the step S1 after the dispatching is completed until the passenger flow positive pressure of each station is 1, and ending the dispatching.
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Denomination of invention: A real-time passenger flow based intelligent scheduling method for scenic spot cruise ships Granted publication date: 20231124 Pledgee: Zhejiang Deqing rural commercial bank Limited by Share Ltd. Pledgor: Zhejiang Zhongce Spacetime Technology Co.,Ltd. Registration number: Y2024980016347 |