CN116798276A - Method for predicting number of aircrafts in sector - Google Patents

Abstract

The invention provides a method for predicting the number of aircrafts in a sector, and belongs to the field of air traffic management. The technical problem to be solved by the invention is to calculate a set of values of the number of aircraft corresponding to each minute in a future time period in a sector. The technical scheme for solving the problem is that aiming at a control sector consisting of two air segments, firstly, calculating the number value of the aircrafts corresponding to each minute in a certain future time period of each air segment, then arranging the number values of the aircrafts changing with each minute in time on the two air segments according to the time sequence, and then correspondingly accumulating the number values of the aircrafts corresponding to each minute in the time period of the two air segments according to the time sequence to obtain the number value of the aircrafts corresponding to each minute in the certain future time period of one sector. The method for processing the sector formed by the two air sections is also applicable to the control sector with complex air path structure formed by a plurality of air sections.

Description

Method for predicting number of aircrafts in sector

Technical Field

The invention provides a method for predicting the number of aircrafts in a sector, and belongs to the field of air traffic management.

Background

In actual work, the control unit divides the control area into a plurality of control sectors. There is a limit to the number of aircraft that one regulatory sector can simultaneously service. In general, in the case of radar control, the number of aircraft approaching a sector control seat while providing service is at most 8, and the number of aircraft approaching a regional sector control seat while providing radar service is at most 12. If the number of aircraft approaching the control sector exceeds 8 or the number of aircraft approaching the regional control sector exceeds 12, then the traffic management department needs to take some measure (for example, methods of changing the flight segment, increasing the sector, limiting the take-off or landing time, limiting the time to enter the control area or limiting the time to go over a certain navigation device, arranging the aircraft to wait in the air, adjusting the speed of the aircraft, etc.) to ensure that the number of aircraft approaching the control sector and providing radar service is not more than 8, and the number of aircraft approaching the regional control sector and providing radar service is not more than 12. In order for the traffic management department to effectively implement traffic management measures, a key issue is the need to accurately predict the number of aircraft entering the regulatory sector in advance over a period of time in the future. It is therefore very necessary and very useful to solve the problem of predicting the number of aircraft on a sector.

The method for predicting the number of aircrafts in a sector, which is commonly used in the field of air traffic management at present, is as follows: calculating the number of aircraft "occurrences" in a future time period (e.g., 15 minutes, 30 minutes, 60 minutes) (fig. 1); and correspondingly adding the number of the predicted aircrafts which are 'appeared' in the aircrafts in a certain time period (such as 15 minutes) of all aircrafts in the sector to obtain the number of the aircrafts which are predicted to be 'appeared' in the sector (in every 15 minutes), taking the number value as the number of the aircrafts in the predicted sector, and judging whether the number of the aircrafts exceeds the control capacity of the sector according to the number value.

This practice is obviously problematic in practical applications. First, since there may be both aircraft flying into and aircraft flying out of the sector during each minute of a future time period (e.g., 15 minutes), the number of aircraft "occurrences" in the regulatory sector during a time period is a set of dynamic values that vary with each minute, rather than using one value during a time period (15 minutes) to indicate clarity; in addition, the number of aircrafts which one regulatory sector simultaneously provides radar service requires no more than 8 (approach sector) or 12 (area sector), the current approach is simply to obtain the number of aircrafts which appear in the sector every 15 minutes period, and it is not known how this number is distributed over a certain period (15 minutes). Since whether the number of aircraft in a sector exceeds the regulated capacity depends on whether the value of the number of aircraft corresponding to each minute within a certain time period (15 minutes, 30 minutes or 60 minutes) exceeds the regulated capacity, and not on whether the number of aircraft "present" in the sector within a certain time period (such as 15 minutes, 30 minutes, 60 minutes) exceeds the regulated capacity. Therefore, current methods do not provide a substantial benefit in determining whether the number of aircraft exceeds the regulatory capacity of a sector over a period of time in the future.

It is expected that the number of aircraft per minute in a given future time period for an air traffic flow management user will be very necessary and useful for a regulatory sector. At present, the civil aviation air traffic control department always uses an airport collaborative decision-making system (ACDM) developed by China aviation communication network company, an air traffic monitoring and flow management system (ATOM) developed by China civil aviation data company and a national flow management system (NTFM) developed by China electronic Nanjing Lais information company, and no method for predicting the number of aircrafts in each minute of a control sector in a future time period is provided.

Disclosure of Invention

The invention aims to provide a method for predicting the number of aircrafts in a sector, which does not change the hardware resources of an original flow management system, does not increase new data acquisition, and still uses the flight time static data of an aviation segment and the original dynamic data source (AFTN dynamic telegram) of a system in an original database. Only one function is added to calculate the number of aircraft per minute in a future time period in the sector and display it in bar form.

The principle of the invention is as follows: a control sector is constructed which consists of two legs. Firstly, calculating the number value of the aircrafts corresponding to each minute in a future time period of each aircrew, arranging the number values of the aircrafts changing with each minute in time on the two aircrew according to the time sequence, correspondingly accumulating the number values of the aircrafts corresponding to each minute in the time period of the two aircrew in the sector according to the time sequence, thereby obtaining a group of number values of the aircrafts corresponding to each minute in the future time period of the control sector consisting of the two aircrew, and intuitively displaying the group of number values by using a bar graph.

The technical content is as follows:

for ease of explanation, the present invention defines three concepts of leg, sector and distribution, avoiding logic errors occurring during the narrative and counting process.

1 navigation section: the portion of a route between two adjacent waypoints on a route is referred to as a leg.

The two waypoints of a leg are referred to as endpoints.

One route is formed by connecting a limited number of route segments according to the endpoint in sequence.

And the section AB and the section BA represent the same section and are all represented by the section AB.

Each leg has two heading. The navigation section AB has a heading AB and a heading BA.

Heading AB represents that the aircraft flies from waypoint A to waypoint B;

heading BA indicates that the aircraft is flying from waypoint B to waypoint a.

2 sectors: an area consisting of a limited number of legs.

3 distribution: the point in flight where the aircraft position is within the leg is referred to as the aircraft being distributed within the leg, and if the leg is within a sector, the aircraft is referred to as being distributed within the sector; if the number of aircraft on a leg is 3 during a certain time period, the number of aircraft distributed over the leg during this time period is 3.

Description of the problem:

two legs, leg AB and leg CD, form a policing sector S (fig. 2).

The conditions are known:

(1) The aircraft was in flight AB for 23 minutes,

(2) The aircraft had a CD flight time of 17 minutes during the leg,

(3) Current time 08:30, aircraft data on the known legs AB, CD are shown (fig. 3) and (fig. 4).

Problems to be solved: predicted 09:00 to 09: during the period of 20 hours of time,

(1) Every minute, controlling the number value of the aircraft in the sector S;

(2) Generating a bar graph from the set of values obtained in (1), and visually displaying 09:00 to 09: the number of aircraft in the management sector S and its variation are within each 1 minute of time in the 20 time period.

The solving process comprises the following steps:

the leg data processing is illustrated by the aircraft data on leg AB (fig. 3) and the leg data processing flow diagram (fig. 5).

In the first step, a time axis is established.

Step 1.1: drawing a time axis (FIG. 6)

Step 1.2: on the time axis, 1 left-closed right-open section [09000920 ] is taken from 0900 to 0920 and denoted by L (fig. 7).

Step 1.3: on the time axis, from 0900 to 0920, 20 left-closed right-open sections of length 1 are taken:

[0900 0901 ], [0901 0902 ], [0902 0903), … …, [0918 0919 ], and [0919 0920 ] are denoted as S01, S02, S03, …, and S20, respectively (FIG. 8).

And secondly, processing the data of the navigation segment AB.

The leg data AB is processed according to the leg AB data (fig. 3) and the data processing flow chart (fig. 5).

Step 2.1 the moment when the aircraft flies into the end point of the dead band AB in (fig. 3), from the fact that the aircraft is flying in the dead band AB for 23 minutes, the moment when the aircraft flies out of the end point of the dead band AB can be calculated (fig. 9).

Step 2.2 as can be seen from the data in the moment when the aircraft flies out of the end point of leg AB (fig. 9), at the current moment 0830, the predicted aircraft profile over time period [09000920 ] is 3 cases:

(1) Already flown into leg AB at 0900.

(2) But not yet flown into leg AB at 0900, but flown into leg AB during time period [09000920 ].

(3) At 0900, but during the [ 09000920) time period, the aircraft is not distributed in leg AB.

In case (1), the initial time 0907 of the aircraft a03 flying into leg AB in the schedule of the end point of the aircraft flying out of leg AB (fig. 9) is 0930 (=0907+23), which indicates:

(a) Aircraft a03 is distributed within leg AB during the [0900 0920) time period;

(b) During the [0907 0920) period, aircraft a03 is distributed over leg AB, where s07=s08= … =s20=1;

(c) During [0900 0907) the aircraft a03 is not distributed in the leg AB, in which case the score s01=s02= … =s06=0.

In case (2), the initial time 0853 of flight of aircraft a09 into leg AB in the schedule of the end point of flight of aircraft out of leg AB (fig. 9), the time of flight out of leg AB is 0916 (=0853+23), explaining

(a) Aircraft a09 would fly into leg AB during time period [0900 0920);

(b) During the [0916 0920) period, aircraft a09 is not distributed within leg AB, where s16=s17= … =s20=0

(c) During the [0900 0916) period, aircraft a09 is distributed over leg AB, where s01=s02= … =s15=1

In case (3), the initial time 0832 when the aircraft a10 flies into the leg AB in the schedule of the end point of the aircraft flying out of the leg AB (fig. 9) is 0855 (=0832+23) when the aircraft flies out of the leg AB. At 0900, aircraft a10 has flown away from endpoint B of leg AB. Description: the aircraft a10 is not distributed in the leg AB at this time. At this time, the notation s01=s02= … =s20=0.

And 2.3, filling the values of S01, S02, … and S20 obtained from the data of each aircraft on the air segment AB into a table to form a distribution table (figure 10) of the number of the aircraft on the air segment AB in each minute time period. The number of the aircraft on the air section AB is accumulated in the number of 1 contained in each of the columns S01, S02, … and S20 in the distribution table of each minute time period, and the accumulated distribution table (figure 11) of the number of the aircraft on the air section AB in each minute time period is obtained.

Step 2.4 generating a bar graph (fig. 12) of the number of aircraft on the air segment AB over time according to the S01, S02, … and S20 data in the cumulative distribution table (fig. 11) of the number of aircraft on the air segment AB over each minute period.

And thirdly, processing the leg CD data.

According to the leg CD data table (figure 4) and the data processing process flow chart (figure 5),

repeating the steps 2.1 to 2.4, processing the leg CD data,

the endpoint schedule for the aircraft flying out of the leg CD (fig. 13), the distribution table of the number of aircraft on the leg CD for each minute period (fig. 14), and the cumulative distribution table of the number of aircraft on the leg CD for each minute period (fig. 15) are obtained in order. From the data S01, S02, …, S20 in table 8, a bar graph of the number of aircraft on the leg CD over time and distribution is made (fig. 16).

In the fourth step, the third step is that,

step 4.1, correspondingly accumulating the numerical values in each of S01, S02, … and S20 in the accumulated distribution table (fig. 11) of the number of the aircrafts on the aircrafts AB and the accumulated distribution table (fig. 15) of the number of the aircrafts on the aircrafts CD and the aircrafts on the aircrafts AB and the aircrafts CD, so as to obtain the time-varying and accumulated table (fig. 17).

Step 4.2, generating a time-dependent change and distribution map (fig. 18) of the number of aircrafts in the control sector S from a time-dependent change and accumulation table (fig. 17) of the number of aircrafts in the aircrafts AB and the aircrafts CD. The time-dependent bar graph of the number of aircraft in sector S is obtained by superimposing the aircraft bar graph on leg AB and the aircraft bar graph on leg CD.

The bar graph and the superposition thereof are generated by running in an actually used air traffic control computer system, and the program development environment is Linux, apache, PHP and MySQL.

Drawings

The number of aircraft expected to occur in the flight for each 15 minute time period in the future of fig. 1.

Fig. 2 shows a control sector S consisting of a leg AB and a leg CD.

Figure 3 shows a known data table for an aircraft on leg AB.

Figure 4 is a known data table for an aircraft on leg CD.

FIG. 5 is a flow chart of the leg data processing.

Fig. 6 time axis.

Fig. 7 shows 1 left-right open section [09000920 ] on the time axis.

Fig. 8 shows 20 left-closed and right-open sections of length 1 in section [09000920 ].

Fig. 9 is a schedule of aircraft flight from the end point of leg AB.

Figure 10 is a table of the number of aircraft on leg AB for each minute period.

Figure 11 is a cumulative distribution of aircraft numbers on leg AB over each minute period.

Fig. 12 shows the number of aircraft over time and the profile of the aircraft on leg AB.

Fig. 13 endpoint schedule for aircraft flight away from leg CD.

Figure 14 is a table of the number of aircraft on the leg CD for each minute period.

Figure 15 is a cumulative distribution table of aircraft numbers on leg CD for each minute period.

Fig. 16 shows the number of aircraft on a leg CD over time and the profile.

FIG. 17 shows a chart of the number of aircraft on segment AB versus segment CD over time.

Fig. 18 controls the number of aircraft in sector S over time and the distribution diagram.

FIG. 19 is a control sector with a complex airway structure.

Detailed Description

In practice, a policing sector is not composed of only two legs, but rather of a plurality of legs of unequal length. In theory, any one of the control sectors with complex route structure can be regarded as a control sector consisting of a limited number of segments (fig. 19). For the control sector with a complex road structure formed by a limited number of air sections, the method for processing the data of the two air sections is still adopted to process each air section one by one, and then the number of the air vehicles in each minute time section on all the air sections is correspondingly accumulated to obtain a group of numerical values of the number of the air vehicles of the sector formed by all the air sections along with the time change of each minute. According to the set of numerical values, a bar chart is generated, and the situation that the number of aircrafts in a complex sector of the airway structure changes with time can be intuitively displayed through the bar chart.

By implementing the invention, a set of air flow management system does not need to be redeveloped, and only one function of the invention needs to be newly added in the original flow management system. According to the invention, new data are not required to be acquired, and the static data of the flight time of the navigation segment in the original flow management system database are still used; the original dynamic telegram data source of the AFTN (Aeronautical Fixed Telemunication Network aviation fixed telecommunication network) system of the flow management system is still used, the aircraft flight dynamic data are directly obtained, and the calculation method provided by the invention indirectly obtains the data of the aircraft flight entering section endpoint moment and the aircraft flight exiting section endpoint moment according to the static data of the original aircraft in the flight time of the aircraft section and the aircraft flight dynamic data (AFTN dynamic telegram).

Claims (1)

1. A method of predicting the number of aircraft in a sector, comprising:

the first step: constructing a control sector S consisting of an air section AB and an air section CD and containing two air sections;

and a second step of:

step 2.1: determining the flight time of the aircraft in the flight segment AB;

step 2.2: determining the flight time of the aircraft in the leg CD;

and a third step of:

step 3.1: on a time number axis, determining the current moment;

step 3.2: on a time number axis, determining an initial moment of a certain time period in the future;

step 3.3: on the time axis, determining the length of a certain time period (20 minutes) in the future;

fourth step:

step 4.1.1: calculating the number value of the aircrafts corresponding to each minute of the aircrew AB in the given time period (20 minutes);

step 4.1.2: arranging the number values of the aircrafts on the aviation section AB, which change with time every minute, according to the time sequence;

step 4.2.1: calculating the number value of the aircrafts corresponding to each minute of the air segment CD in the given time period;

step 4.2.2: arranging the number values of the aircrafts on the air section CD, which change with time every minute, according to the time sequence;

fifth step:

respectively and correspondingly accumulating the aircraft quantity values corresponding to each minute in the time period determined in the step 3.3 in the navigation section AB and the navigation section CD in the sector S according to the time sequence order to obtain a group of data;

sixth step: based on the set of data obtained in the fifth step, a bar graph is generated showing the number of aircraft expected in sector S and the variation over time for each minute.