KR101531085B1 - Method and apparratus for managing human and material resource of airport - Google Patents

Abstract

A method and an apparatus for operating an airport resource are disclosed. The method for estimating passengers using an airport includes a step of inputting airport usage information, a step of predicting a change in the number of airport users according to time based on the airport usage information, and a step of operating airport resources according to the predicted number of airport users can do. Therefore, it is possible to efficiently use the operating system of the airport, but it is also possible to effectively adjust the schedule of the airport users using the airport.

Description

[0001] METHOD AND APPARATUS FOR MANAGING HUMAN AND MATERIAL RESOURCE OF AIRPORT [0002]

The present invention relates to a resource management method and apparatus, and more particularly, to a method and apparatus for determining a resource management method by calculating a daily predicted amount of resources.

Passenger forecasting is very important for management activities because it links the relationship between external environment and human resource utilization and becomes the basis of management plan. Especially, when the customer service is promoted as the main management philosophy like airport, there is a right and desire to provide high quality service to the users. However, if the passenger forecast is wrong, the passenger will not be provided with appropriate service. There are two cases when the passenger forecast is wrong.

First, if the actual demand is less than the forecast, it causes the inefficiency of the manpower operation due to the overproduction of the workforce. Next, if the actual demand is larger than the forecast, the discomfort due to lack of the workforce and the delay in the procedure There may be a serious situation where you can not get on the reserved airplane. In this case, not only the direct and indirect damages of the users but also the damage of the airport.

If demand forecasts are not made accurately, it will lead to a huge hindrance to the management environment due to the nature of the airport development project, where the investment amount is in trillions.

In 2012, the number of inbound and outbound travelers at Incheon International Airport and Kimpo International Airport is expected to exceed 46 million. If average user growth continues in the last three years, it is predicted that the number of airport passengers will exceed 55 million by 2015. According to the airport industry on March 26, the number of travelers using Incheon International Airport in 2012 was 38.97 million. The number of passengers in Incheon International Airport last year was 3.91 million, which is more than 35.6 million. The number of passengers at Incheon International Airport, which was 1.454 million in 2001, was 202.9 million in 2002, 31.12 million in 2007, 33.48 million in 2010, 35.6 million in 2011, and about 95 million in 2030 .

In the case of transit passengers, the number of transit passengers increased by 790,000 from the previous year to 646,000, and the average annual growth rate reached 14.1%, making it a step closer to the Northeast Asian hub airport of Incheon International Airport. The number of passengers at 14 airports operated by Korea Airports Corporation, including Kimpo International Airport and Jeju International Airport, was estimated at 53.5 million visitors this year. It is estimated that the number of passengers at 14 airports this year is 53.5 million. This is an increase of 3.18 million people (9.4%) compared to last year's 50.32 million passengers. It is the highest since the opening of Incheon International Airport in 2001.

In response to the increasing trend of airport users, there is a need for a method for predicting required airport resources and for efficiently allocating airport resources based on the predicted airport resources.

It is an object of the present invention to provide a method for predicting and effectively operating the physical and human resources of airports.

It is still another object of the present invention to provide an apparatus for performing a method of predicting and effectively operating physical and human resources of an airport.

According to another aspect of the present invention, there is provided an airport use passenger predicting method of an airport use passenger predicting apparatus including an airport use information input unit, an airport user predicting unit and an airport resource calculating unit, The utilization information input unit receives the airport usage information, and the airport user prediction unit predicts a change in the number of airport users according to time based on the airport usage information input through the airport usage information input unit, And calculating the airport resources to be operated according to the information on the number of the airport users generated by the airport user estimating unit, wherein the airport use information includes information on the number of passengers using the airplane, The airplane schedule information and the airplane information, Wherein the step of generating the information on the number of airport users by predicting a change in the number of airport users over time based on the airport usage information based on the statistical model and the mathematical predictive model, Estimating a change with time of the passengers, predicting a change with time of the passengers, predicting a change with time of the passengers according to departure routes, A step of predicting a change with time of the user, a step of predicting a change with time of the user of the departure shuttle train, and a step of predicting a change with time of the entrance shuttle train user, wherein the airport user predicting unit The information including at least one of information, flight schedule information, Based on the probabilistic model of the time distribution of arriving at the arrival place after arriving at the arrival of the arrival airport, the change of the number of airport users according to time is predicted by time, Wherein the airport resource calculation unit calculates the airport resources to be operated in consideration of the number of gates opened for examination in consideration of the number of openings to be operated by the airport resource calculation unit, Wherein the airport resource calculation means calculates an airport resource for operating at least one of an entrance / exit gate manpower, a security manpower, and a public resource manpower adaptively changing according to information on the number of airport users generated through the method When the airport-use passenger prediction device receives the airport usage information May further include the step of providing also the passengers using the airport, the airport using information received through the.

According to another aspect of the present invention, there is provided an airport use passenger predicting apparatus including an airport use information input unit for inputting airport use information, an airport use information inputting unit for inputting through the airport use information input unit, An airport user estimating unit for estimating a change in the number of airport users according to time to generate information on the number of airport users, and an airport resource calculating unit for calculating an airport resource to be operated according to the information on the number of airport users generated Wherein the airport usage information includes airplane use passenger information, aircraft schedule information, and aircraft shelf information, and wherein the airport user predictor is configured to determine a change in the departure hall user over time based on a statistical model and a mathematical prediction model The departure station user predicting unit for predicting the change in the arrival time of the user, A transit station user predicting unit for predicting a change with time of transit passengers, a user predicting unit for each transit route predicting a change with time of the passengers per departure route, A departure shuttle train user predicting unit for predicting a change with time of the departure shuttle train user, and an entry shuttle train user predicting unit for predicting a change with time of the entrance shuttle train user Wherein the airport user predicting unit predicts a change in the number of airport users according to time based on the airport use information including at least one of the airplane use passenger information, the airplane schedule information and the airplane information, Probability of distribution of time to arrive at arrival point after arrival Estimates the number of airport users according to time based on the model and estimates the number of the users in the arrival hall considering the number of gates open for entry examination, Wherein the airport utilization passenger prediction device calculates an airport resource for operating at least one of an entrance gate gate manpower, a security manpower, and a public resource manpower adaptively changing according to information on the number of airport users generated through the airport Information to the users using the airport.

As described above, according to the method and apparatus for operating an airport resource according to the embodiment of the present invention, it is possible to predict the change in the number of airport users over time based on the airport usage information, The airport resources can be operated according to.

Therefore, it is possible to efficiently use the operating system of the airport, but it is also possible to effectively adjust the schedule of the airport users using the airport.

1 is a conceptual diagram showing an airport resource management system according to an embodiment of the present invention.
2 is a conceptual diagram illustrating a method of predicting the number of passengers in a departure hall according to an embodiment of the present invention.
3 is a conceptual diagram illustrating an SLT statistical model for calculating a departure hall visitor by time zone according to an embodiment of the present invention.
FIG. 4 is a statistical data showing the departure location selection according to the check-in counter according to the embodiment of the present invention.
FIG. 5 is a conceptual diagram illustrating that predicted departure passenger information according to an embodiment of the present invention is transmitted to an airport operating system and a homepage.
6 is a flowchart illustrating a method of predicting an arrival floor passenger according to an embodiment of the present invention.
FIG. 7 is a graph showing an arrival time of a visitor at a landing area according to an embodiment of the present invention.
FIG. 8 is a conceptual diagram illustrating a method for transferring the arrival time of the arrival area of a visitor to the airport, according to an embodiment of the present invention, to the airport operating system and the home page.
9 is a flowchart illustrating a method of predicting a transit passenger according to an embodiment of the present invention.
FIG. 10 is a conceptual diagram showing the predicted result of a passenger in a transfer station according to an embodiment of the present invention.
11 is a conceptual diagram showing a result of a passenger prediction for a shuttle train according to an embodiment of the present invention.
12 is a block diagram illustrating an airport user prediction system in accordance with an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the following description of the embodiments of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present disclosure rather unclear.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . In addition, the description of "including" a specific configuration in the present invention does not exclude a configuration other than the configuration, and means that additional configurations can be included in the practice of the present invention or the technical scope of the present invention.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

In addition, the components shown in the embodiments of the present invention are shown independently to represent different characteristic functions, which does not mean that each component is composed of separate hardware or software constituent units. That is, each constituent unit is included in each constituent unit for convenience of explanation, and at least two constituent units of the constituent units may be combined to form one constituent unit, or one constituent unit may be divided into a plurality of constituent units to perform a function. The integrated embodiments and separate embodiments of the components are also included within the scope of the present invention, unless they depart from the essence of the present invention.

In addition, some of the components are not essential components to perform essential functions in the present invention, but may be optional components only to improve performance. The present invention can be implemented only with components essential for realizing the essence of the present invention, except for the components used for the performance improvement, and can be implemented by only including the essential components except the optional components used for performance improvement Are also included in the scope of the present invention.

1 is a conceptual diagram showing an airport resource management system according to an embodiment of the present invention.

FIG. 1 shows an operation method of an airport resource for efficiently operating an airport resource based on a predicted value predicted by a passenger using an airport. Airport resources may include various types and intangible human / material resources to provide services to airport users, such as, for example, personnel at the airport's entry gate and exit gate, other public facility resources, and security search personnel . Hereinafter, an embodiment of the present invention will be described with reference to a method of predicting a passenger using airport resources based on airport utilization information (for example, airplane use passenger information, airplane schedule information, etc.) over time, .

Airport usage information used to predict airport resources is information used to predict passengers using the airport at certain times. Hereinafter, the passenger reservation information, the airplane departure and arrival information, which is the airport utilization information used in the embodiment of the present invention, is exemplary information of the airport usage information, and other information may be used as the airport usage information. Scope of rights.

According to the embodiment of the present invention, it is possible to calculate the passenger information according to the position of the airport for each time slot based on the airport utilization information. It is possible to effectively utilize airport resources by effectively arranging airport resources (entrance and exit gate personnel, security personnel, public resource management personnel, etc.) adaptively changing according to the calculated passenger information. By providing passengers information not only to the airport's resources but also to the passengers who use the airport, it is possible to adjust the time to arrive at the airport adaptively by determining whether there are enough passengers in the time zone they are using, have.

The method of operating the airport resources is as follows: 1) receiving the airport usage information (100), 2) estimating the usage amount of the airport resources based on the inputted airport usage information (120), and 3) Airport resources can be effectively managed (140).

Each of the steps will be described in detail as follows.

(1) receiving the airport use information (step 100)

The airport use information can be, for example, flight schedule information such as aircraft departure information and flight arrival information, reservation information of a passenger using an aircraft, gate allocation information, and the like. As described above, such airport use information may be used as exemplary information, and other information may be used, and these embodiments are also included in the scope of the present invention.

The airport utilization information may be information used for predicting the passengers who use the airport resources at the departure point, the arrival point, the transit gate, and the like of the airports at the time of day.

(2) estimating the number of airport users based on the airport usage information (step 120)

It is possible to calculate the predicted amount of the passenger using the airport resources by using a predetermined procedure based on the airport utilization information. At the airport, the number of airport passengers can be different depending on the location such as the arrival, departure, quarantine, shuttle train, and so on. Therefore, according to the purpose of using the airport, it is necessary to separately estimate an airport user located in the corresponding area. For example, there may be a departure passenger notice, an entry passenger notice, a transit passenger notice, a passenger notice for each departure route, a passenger notice for each entry route, a departure shuttle train passenger notice, and an entry shuttle train passenger notice. The method of predicting the number of passengers according to specific airport locations will be described later.

(3) deploy airport resources based on the estimated number of airport users (140).

The predicted number of airport users may be delivered to the server managing the airport operating system and the home page of the airport. The number of predicted airport passengers delivered to the airport management system is calculated by the departments of the airport operator (eg, Ministry of Justice, customs offices, sales headquarters, mooring station management, security search team) Material resources can be deployed. In addition, the number of estimated airport users can be referenced by commercial facilities or airport users in the airport.

For example, it is necessary to determine the number of airport users by location of airports according to the time of day, as a method of effectively managing the airport resources according to the predicted number of airport users, to arrange the arrival and departure management personnel, Placement of check-in personnel, proper placement of check-in personnel, proper placement of management personnel, and provision of public goods.

In the embodiment of the present invention, a method of predicting an outbound passenger, a method of predicting an arrival passenger, a method of predicting a transit passenger, a method of predicting a passenger on a shuttle train, And a method of predicting and the like will be described in detail.

2 is a conceptual diagram illustrating a method of predicting the number of passengers in a departure hall according to an embodiment of the present invention.

Referring to FIG. 2, the reservation passenger information is provided (step S200).

The reserved passenger information may be information about the passenger boarding the departing airplane. For example, it may be information on the number of passengers boarding an aircraft departing at a specific time.

And receives airline schedule information (step S210).

Airline schedule information can be a factor that can change the number of passengers using the current airport departure area, such as the aircraft information landed at the airport and the aircraft information taken off from the airport.

Based on the airline schedule information and the reservation passenger information, the number of airport users can be grasped according to the purpose for each time slot. The flight schedule information may also include information on aircraft mainframe assignments.

Step S200 and step S210 are examples of the airport use information inputted to predict the passenger using the departure place, and information other than the reserved passenger information and the airline schedule information may be used as the airport use information, .

The departure hall passengers are predicted for each time zone (step S220).

Departure passengers can use the show up time statistical model (SLT), check-in counter departure time (LT), check-in assignment status (x1), passenger departure area selection model (x2) The number of passengers per segment can be predicted.

3 is a conceptual diagram illustrating an SLT statistical model for calculating a departure hall visitor by time zone according to an embodiment of the present invention.

The SLT statistical model can include information on the time when departure passengers enter and leave the airport based on the aircraft departure time when using a specific aircraft.

Referring to FIG. 3 (A), about 24.7% of departure passengers enter the airport 180 minutes before departure time 120 minutes before departure of the aircraft. 68% of the remaining departure passengers will arrive at the airport between 120 and 60 minutes before departure and 7.3% of the remaining departure passengers can arrive 60 minutes before departure. According to these statistical models, departure passengers can, on average, arrive at the airport 105 minutes before departure.

3 (B) is a conceptual diagram showing a SLT time-based model. Referring to FIG. 3 (B), it has a model form similar to FIG. 3 (A).

The SLT statistical model is an exemplary model for predicting arrival times of departure passengers based on departure times of aircraft. It is possible to predict the arrival time of the passenger based on the departure time of the aircraft using a model other than the SLT statistical model, and such an embodiment may also be included in the scope of the present invention.

FIG. 4 is a statistical data showing the departure location selection according to the check-in counter according to the embodiment of the present invention.

Referring to FIG. 4, the usage rate for each departure station can be calculated according to the check-in counters A2 to M2. It is possible to calculate the departure hall information at the check-in counter and calculate the departure hall visitor information.

The prediction models of FIGS. 3 and 4 may use the statistical model as an example and another model may be used to calculate the departure hall utilization rate according to the check-in counter, and such an embodiment may also be included in the scope of the present invention.

These statistical models can update the statistics constantly and use the changed values. For example, if the departure process is fast, there is no reason for departure passengers to arrive quickly. Therefore, the time for the departure passenger to arrive at the departure place before departure of the aircraft may be less than the existing show up time of 105 minutes.

Further, in the present invention, in order to predict departure passengers, the number of users at the time of departure from the main point of the airport at the time of departure is calculated by considering the LT (Lag time) and the check-in assignment status (x1) Prediction and analysis.

(SUT), the departure time (LT), check-in assignment status (x1), passenger departure location selection model (x2), etc. from the check-in counter are used as one statistical model for predicting the departure passenger . Statistical or mathematical models other than these models may be used to predict outbound passengers, and such embodiments may also be included within the scope of the present invention.

The predicted departure passenger through steps S200 to S210 of FIG. 2 may be transmitted to the airport operating system and home page.

FIG. 5 is a conceptual diagram illustrating that predicted departure passenger information according to an embodiment of the present invention is transmitted to an airport operating system and a homepage.

FIG. 5 (A) is a conceptual diagram showing that the departure hall passenger information is transmitted to the airport operating system to calculate the departure passenger per time zone.

Referring to FIG. 5 (A), a value obtained by predicting the number of users using the departure area 1 to the departure area 4 in each time zone is shown. It can be predicted that the number of users using the departure place at 7 o'clock and 17 o'clock is large. In order to perform a more detailed prediction for each time zone, each time may be subdivided into smaller time units such as 10 minute units, so that the departure passenger may be predicted.

5B is a conceptual diagram showing predicted values of departure hall visitors disclosed on the homepage.

Referring to FIG. 5 (B), the predicted value of the departing passenger is disclosed on the homepage, and the passenger using the airport is notified of the number of the passengers of the departure route by time zone so that the passenger who departs the passenger can predict the congestion can do. By using this method, it is possible to utilize the airport resources efficiently because the passengers can get the effect of dispersing the passengers at the departure hall without being attracted to the departure hall only at a specific time.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In the following, embodiments of the present invention will be described with respect to a method for predicting an entering passenger according to an embodiment of the present invention.

6 is a flowchart illustrating a method of predicting an arrival floor passenger according to an embodiment of the present invention.

Referring to FIG. 6, information for predicting the arrival floor passenger is inputted (step S600).

The airport usage information, which is information for predicting the arrival place visitor, may include the aircraft arrival information, the entry reservation passenger information, the aircraft main site assignment information, and the like. These airport utilization information may be added to the airport utilization information as an example, or may not include some of the above information, and these embodiments are also included in the scope of the present invention.

Information on when an aircraft arrives at the port of entry, information on how many passengers are boarding the aircraft, information on the aircraft's layout, etc. can be used to analyze the time for arriving passengers to arrive at the port of entry. have.

The arrival time of the arrival hall user is predicted for each time zone (step S610).

The arrival time of the arrival of passengers at the arrival point may indicate the time when the arriving passenger arrives at the arrival point after landing. Arrival time of the arrival point visitor can be calculated through statistical model or mathematical model. For example, the average time to arrive at boarding school after landing aircraft is 7 minutes 43 seconds, the passenger's flight time is 8 minutes, the arrival time to walk is 03 minutes 59 seconds in the terminal, 13 minutes from the terminal to the terminal It is possible to calculate the arrival time of the arrival area after arrival of the aircraft. These statistical or mathematical models can be continually updated to use statistical values that reflect current airport conditions. For example, if the number of gates performing immigration increases in carrying out the immigration process, the number of arriving passengers can be predicted using statistical and mathematical models that reflect this situation.

FIG. 7 is a graph showing an arrival time of a visitor at a landing area according to an embodiment of the present invention.

Referring to FIG. 7, most landing passengers arrive at the arrival site between 20 and 30 minutes after the aircraft arrives. Based on these statistical data, it is possible to predict the time when the arrival of the passengers to the arrival area after the aircraft arrives at the airport.

The arrival information of the arrival airport visitor predicted through the above procedure can be transmitted to the airport operating system and the homepage.

FIG. 8 is a conceptual diagram illustrating a method for transferring the arrival time of the arrival area of a visitor to the airport, according to an embodiment of the present invention, to the airport operating system and the home page.

Fig. 8 is a conceptual diagram showing how to predict an entry visitor.

Referring to FIG. 8, the number of arriving passengers predicted by arrival point and time zone is shown. Between 5:00 and 7:00, the number of passengers at each port of entry is high, and the number of passengers at the port of entry can be large even between 16:00 and 18:00. It can be used to locate human resources and material resources at the airport by carrying out predictions about the time of arrival. For example, depending on the number of passengers at the port of entry, it is possible to increase or decrease the number of security officers who manage the gate of the port of entry or manage the port of entry.

The predicted arrival hall user information may be displayed on the homepage. By informing the passengers at the arrival point by entry time, it is possible to obtain information about how long the passengers at the entry point take the time to arrive. Those waiting for the arrival of passengers outside the arrival area can predict the time required to wait for the arrival place passenger based on the arrival information of the arrival place on the homepage.

9 is a flowchart illustrating a method of predicting a transit passenger according to an embodiment of the present invention.

Referring to FIG. 9, information for predicting the passengers is provided (step S900).

As the input information for predicting the transit passengers, the aircraft arrival information, the transit reservation passenger information, the aircraft main space assignment information, and the like can be used. Such information is an example, and other information may be added to this information, or information of some of the above information may not be considered, and these embodiments are also included in the scope of the present invention.

Specifically, information on when the aircraft carrying the transfer passenger arrives, information on the time when the transfer passengers depart again, information on the number of transfer passengers who are boarding passengers on board the aircraft, And information on the allocation of the main area, etc., to analyze the time for the transit passenger to arrive at the arrival point.

The transit station use time of the transfer station user is predicted (step S910).

Based on the information input through step S900, it is possible to predict information on the time to arrive at the search station from the aircraft of the transfer station user. The predicted information may be transmitted to the airport operating system to obtain information about the time at which the transit passenger arrives at the search platform.

FIG. 10 is a conceptual diagram showing the predicted result of a passenger in a transfer station according to an embodiment of the present invention.

Referring to FIG. 10, the airport operating system can predict the information about the passengers at each time slot. The airport management system can effectively allocate human and material resources to search for transit passengers based on this information.

The airport resource management system can additionally predict the departure passenger prediction result, the entry passenger prediction result, the transfer passenger prediction result, the shuttle train boarding passenger prediction result, and the route passenger prediction result in the airport resource management system.

11 is a conceptual diagram showing a result of a passenger prediction for a shuttle train according to an embodiment of the present invention.

The departure and arrival information of the aircraft and the departure / entry reservation passenger information can be inputted to predict the passenger on the shuttle train. A shuttle train passenger can be predicted on the basis of a show up time (SLT) statistical model used for predicting an arrival passenger on the basis of the departure and arrival information of the inputted aircraft and the departure / entry reservation passenger information.

The show up time statistical model for predicting the shuttle train passenger can be used as an exemplary model for predicting the shuttle train passenger, and such an embodiment is also included in the scope of the present invention.

Referring to FIG. 11, the predicted number of passengers on a shuttle train can be calculated for each time slot. The number of passengers carrying the shuttle train at 5 ~ 7, 12 and 17 ~ 21 may be higher than other time zones. Therefore, the number of shuttle train operations and the shuttle train operation intervals can be adjusted based on the number of passengers on the shuttle train.

In addition to this, it is also possible to predict various information necessary for operating the airport, such as forecasting passengers by departure and destination, and predicting passengers by route, based on airport utilization information. This information can be provided to the airport operating system on the basis of which it can be utilized in arranging the physical and human resources of the airport.

By using the above method, it is possible to utilize the physical and human resources more systematically and effectively through the predicted value rather than the response method depending on the field experience on the demand of the uncertain airport user. That is, it is possible to improve the services of customs offices, immigration bureaus, quarantine agencies, and check-in counters in airports. In addition, it is possible to improve the ability to respond to airport users due to the flexible allocation of resources for immigration, immigration and transit search, and it is possible to flexibly arrange and reinforce manpower in the Ministry of Justice, customs, and so on. In other words, by accurately predicting the demand for passengers at unspecified times, it is possible to eliminate the uncertainty in utilizing airport resources and to stabilize airport operations.

In addition, in order to mitigate congestion in the passengers security search area and to prevent congestion in certain transit security search areas at certain time zones where transit passengers are expected to converge, it is necessary to adjust the gate using the transit passengers' According to the number of the passengers and the route of the airport, it is possible to prepare the quantity and service according to the demand. In case of using the immigration station, the user can extend the rest time by shortening the waiting time and adjust the departure time.

Although the above-described passenger notification system makes efficient use of the airport's operating system, it can also effectively adjust its own schedule in terms of airport users using the airport.

12 is a block diagram illustrating an airport user prediction system in accordance with an embodiment of the present invention.

12, an airport usage information input unit 1200, an airport user prediction unit 1210, and an airport resource calculation unit 1250 can be included.

The airport use information input unit 1200 can use the airport use information used for predicting the airport resources to indicate information used for predicting the passenger using the airport at a specific time. The airport usage information input unit 1200 receives this information and transmits the information to the airport user predicting unit 1210.

The airport user predicting unit 1210 can calculate the predicted amount of the passenger using the airport resources by using a predetermined procedure based on the airport use information. At the airport, the number of airport passengers can be different depending on the location such as the arrival, departure, quarantine, shuttle train, and so on. Therefore, according to the purpose of using the airport, it is necessary to separately estimate an airport user located in the corresponding area. A statistical model and the mathematical prediction model can be used to calculate the amount of passengers using the airport resources.

The airport user predicting unit 1210 includes a departure hall user predicting unit 1215 for predicting a change with time of a departure hall user, an arrival hall user predicting unit 1220 for predicting a change with time of the arrival hall user, A forecasting unit 1230 for each departure route for predicting a change with time of a user for each departure route, an entry route predicting a change with time of a user for each entry route, An outbound shuttle train user predicting unit 1240 for predicting a change with time of the outbound shuttle train user, an entry shuttle train user predicting unit 1245 for predicting a change with time of the entry shuttle train user, ). ≪ / RTI >

The departure hall user predicting unit 1215 estimates the departure hall arrival time of the departure hall user using the show up time statistical model and predicts the departure hall shift time at the check-in counter of the departure hall user, And predicting the departure airport selection information according to the check-in counter based on the departure airport selection model and estimating the number of airport users according to time for each departure hall.

The landing area user predicting unit 1220 can be implemented to predict a change in the number of airport users with respect to time based on a probability model of time distribution of arriving at the arrival place after arriving at the arrival site of the arrival place visitor.

The statistical model and the mathematical prediction model may be models that receive information on existing values and are periodically updated by reflecting the generated values.

The airport resource calculation unit 1250 may be configured to receive information on the estimated number of airport users and to calculate the numerical values of the human resources and the physical resources of the airports required for each time zone.

It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined in the appended claims. It will be possible.

Claims (14)

An airport-use passenger predicting method of an airport-use passenger predicting apparatus, comprising an airport-use-information input unit, an airport user predicting unit, and an airport resource calculating unit,
Receiving the airport usage information from the airport usage information input unit;
Generating information on the number of airport users by predicting a change in the number of airport users according to time based on the airport use information inputted through the airport use information input unit by the airport user prediction unit; And
Wherein the airport resource calculation unit calculates the airport resource to be operated according to the information on the number of the airport users generated by the airport user prediction unit,
The airport use information
An airplane use passenger information, an airplane schedule information, and an airplane information,
Wherein the step of generating the information on the number of airport users by predicting a change in the number of airport users over time based on the airport use information by the airport user prediction unit comprises:
Based on statistical models and mathematical predictive models,
Predicting a change with time of the departure hall user;
Predicting a change with time of a user of the arrival hall;
Predicting a change with time of a passenger in a transfer station;
Predicting a change with time of a user per departure route;
Predicting a change with time of the passenger according to each entry route;
Estimating a change with time of the departure shuttle train user; And
And estimating a change with time of the entrance shuttle train user,
The airport user predicting unit
Estimating a change in the number of airport users according to time based on the airport usage information including at least one of the airplane use passenger information, the airplane schedule information, and the airplane information,
A change in the number of airport users according to time is predicted on a time basis based on a probability model of a time distribution of arriving at the arrival place after arriving at the arrival point of an aircraft and further considering the number of gates opened for entry examination, And the number of pixels is predicted,
Wherein the step of calculating the airport resource to be operated by the airport resource calculation unit comprises:
The airport resource calculation unit calculates an airport resource for operating at least one of entrance and exit gate personnel, security personnel, and public resource management personnel adaptively changing according to information on the number of airport users generated through the airport user prediction unit With features,
The airport-based passenger prediction method
Further comprising the step of the airport-use passenger predicting device providing the airport-use information input through the airport-use-information inputting section to the users using the airport.
delete delete The method according to claim 1,
Wherein the step of predicting a change in the number of airport users according to time based on the airport use information comprises:
Estimating an arrival time of a departure hall visitor using a show up time statistical model;
Estimating a departure point travel time at a check-in counter of the departure point visitor;
Receiving the check-in counter allocation status information of the departure hall visitor; And
Estimating the number of airport users according to the time for each departure hall through the step of predicting the departure hall selection information according to the check-in counter based on the departure hall selection model.
delete The method according to claim 1,
The statistical model and the mathematical prediction model may be expressed as:
Wherein the model is a model that is periodically updated by reflecting the generated value.
The method according to claim 1,
Wherein the step of calculating the airport resource to be operated by the airport resource calculation unit comprises:
Transmitting information on the number of airport users generated by the airport user predicting unit to the airport operating system; And
And calculating a numerical value of human resources and physical resources of an airport required for the time zone in the airport operating system.
A passenger prediction device for an airport, comprising:
An airport usage information input unit for inputting airport usage information;
An airport user predicting unit for predicting a change in the number of airport users according to time based on the airport usage information input through the airport usage information input unit and generating information on the number of airport users; And
And an airport resource calculating unit for calculating an airport resource to be operated according to the information on the number of the airport users generated,
The airport use information
An airplane use passenger information, an airplane schedule information, and an airplane information,
The airport user predicting unit,
Based on statistical models and mathematical predictive models,
A departure station user predicting unit for predicting a change with time of the departure hall user;
An arrival hall user predicting unit for predicting a change with time of the arrival hall user;
A transfer station user predicting unit for predicting a change with time of the transfer station user;
A user forecasting unit for each departure route, which predicts a change with time of a visitor by departure route;
A user predicting unit for each entry route that predicts a change with time of the passengers per entry route;
An outbound shuttle train user predicting unit for predicting a change with time of an outbound shuttle train user; And
An entrance shuttle train user predicting unit for predicting a change with time of the entrance shuttle train user,
The airport user predicting unit
Estimating a change in the number of airport users according to time based on the airport usage information including at least one of the airplane use passenger information, the airplane schedule information, and the airplane information,
A change in the number of airport users according to time is predicted on a time basis based on a probability model of a time distribution of arriving at the arrival place after arriving at the arrival point of an aircraft and further considering the number of gates opened for entry examination, Predict the number,
The airport resource calculation unit
Calculates airport resources for operating at least one of an entrance / exit gate manpower, a security manpower, and a public resource manpower adaptively changing according to information on the number of airport users generated through the airport user predicting unit,
The airport-use passenger prediction device
And the airport utilization information is also provided to the passengers using the airport.
delete delete 9. The method of claim 8,
The departure hall user predicting unit
Predicts the departure time arrival time of the departure hall visitor using the show up time statistical model, estimates the departure time travel time at the check-in counter of the departure hall user, inputs the check-in counter allocation status information of the departure hall user, And predicts the departure point selection information according to the check-in counter on the basis of the departure point selection information and predicts the number of airport users according to the time for each departure point.
delete 9. The method of claim 8,
The statistical model and the mathematical prediction model
Wherein the model is a model that is periodically updated by reflecting the generated value.
9. The method of claim 8,
The airport resource calculation unit
Wherein the information on the number of the estimated airport users is received and the numerical value of the human resources and the physical resources of the airport required for each time zone is calculated.

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