CN108074421B - Time-based terminal area approach efficiency measurement method - Google Patents

Time-based terminal area approach efficiency measurement method Download PDF

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CN108074421B
CN108074421B CN201810083741.9A CN201810083741A CN108074421B CN 108074421 B CN108074421 B CN 108074421B CN 201810083741 A CN201810083741 A CN 201810083741A CN 108074421 B CN108074421 B CN 108074421B
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任新刚
赵嶷飞
张云翔
郭毅
陈聪
丁百卉
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Flightnet (Shanghai) Technology Co.,Ltd.
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Abstract

The invention discloses a time-based terminal area approach efficiency measuring method, which comprises the following steps: establishing a terminal area model: and taking the airport reference point as the center of a circle and taking an airspace range with the radius of 100 nautical miles as an airport terminal area, collecting and processing flight ADS-B data, and estimating the unblocked approach time and the approach efficiency evaluation of the terminal area. Compared with the prior art, the time-based terminal area approach efficiency measuring method provided by the technical scheme is an objective quantitative method for evaluating the terminal area approach efficiency, and a new method for estimating the unblocked approach time is provided from the perspective of economic metrology, so that the defects of the current research are overcome, a powerful reference is provided for the terminal area efficiency evaluation, a foundation is laid for the comparison of approach efficiencies of different airports and the comparison of different approach optimization methods, the evaluation method is simple and easy to use, and the evaluation result is clear at a glance.

Description

Time-based terminal area approach efficiency measurement method
Technical Field
The invention belongs to the technical field of air traffic management and management, and particularly relates to a terminal area approach efficiency measuring method based on time.
Background
With the vigorous development of the civil aviation industry, the contradiction between the limited service resources and the increasing flight traffic becomes more prominent. The phenomena of congestion and sequencing are frequently generated when a busy airport in China is over the air, and the method is particularly remarkable in the aspect of aircraft approach. However, at present, no standardized key evaluation index exists for the approach efficiency of the terminal area in China. Although some operation data statistics are presented in various operation reports, the evaluation of the approach efficiency of the terminal area is mainly based on qualitative analysis due to the lack of data analysis. How to evaluate the approach efficiency of the terminal area and how to quantify the approach efficiency of the terminal area are urgent, because the quantification of the approach efficiency of the terminal area can embody the approach efficiency of the terminal area more intuitively and clearly compared with qualitative analysis, and can also provide reference for comparison of the approach efficiency of each terminal area and comparison of different approach optimization methods. The terminal area approach efficiency is quantized, influence factors of the approach efficiency are identified, so that the low-efficiency root is found, a starting point can be locked for the optimization research of the approach flights, and further, the drugs are issued according to the symptoms.
Disclosure of Invention
The invention aims to provide a terminal area approach efficiency measuring method based on time, which is used for evaluating the approach efficiency of a terminal area according to actual flight operation data aiming at the current situation that China lacks of evaluation indexes for measuring the approach efficiency of the terminal area.
The invention is realized by the following technical scheme in order to achieve the purpose:
a terminal area approach efficiency measurement method based on time comprises the following steps:
s1, establishing a terminal area model: taking an airport reference point as a circle center, and taking an airspace range with 100 nautical miles as a radius as an airport terminal area;
s2, collecting and processing flight ADS-B data: downloading ADS-B data of incoming flights of a terminal area of a target airport from a flightradar24 website, screening the ADS-B data, and respectively calculating the position coordinates of each flight from 100 nautical places of airport reference points and the corresponding time t by taking each flight as a unit100And landing time t0；
S3, estimating the clear approach time: according to the ADS-B data processed in the step S2, calculating the actual approach time t of each approach flightactualAccording to the number of the incoming queues and the actual incoming time tactualData of (2) establishing the number of incoming queues and the average incoming time ttransitA univariate linear regression model of (c); aiming at the flight i, when the number of the incoming queues is 0, namely no incoming flight influences the incoming time of the flight i, and the constant item at the moment is the smooth incoming time tunimpededThe number of the inbound queues is the total number of all queued landing flights in the process from the inbound to the landing of the flight i;
s4, terminal area approach efficiency assessment: using the actual approach time t obtained in step S3actualAnd time t of smooth approachunimpededAnd calculating the airport terminal area entrance efficiency index based on time:
Figure BDA0001561782350000021
t hereactualRepresenting the actual approach time, tunimpededAnd (4) representing the smooth approach time, and finally carrying out efficiency evaluation on the whole flight by using the approach efficiency index of the terminal area.
Further, in step S2, in step S2, the specific steps of processing the flight ADS-B data are as follows:
s2.1, determining an approach position and an approach time, namely intercepting two track points which are closest to an airport reference point 100 nautical miles in ADS-B data of each flight: p1＝min(Pi|0＜|PiParp|-100＜1)、P2＝min(Pj|-1＜|PjParpI-100 < 0) and corresponding time, calculating the time and other parameters at 100 nautical miles by a cubic spline interpolation method to respectively obtain the longitude and latitude coordinates of the approach point and the corresponding approach time t100；
S2.2, calculating the landing time: let flight landing time be t0Selecting the corresponding time t of two tracks before the flight landing1And t2(t1＞t2) And corresponding heights are respectively h1And hx (h)1＜h2) The descent rate before the flight lands is:
RD2-1＝(h2-h1)/(t1-t2)，
estimating the landing time t from the descent rate0：
t0＝t1+(h1-0)/RD2-1
Further, in step S2, the screening ADS-B data includes flight data with cancellation, no record, and no landing information removed; the ADS-B data contains flight number, time, latitude, longitude, altitude, speed, and heading information.
Further, in step S3, the specific steps of estimating the clear approach time are as follows:
s3.1, calculating the actual approach time: calculating the actual approach time t according to the ADS-B data processed in the step S2actualTime t from the approach of an approach flight from 100 nautical miles to landingactual＝t0-t100；
S3.2, calculating the number of incoming queues: the number of inbound queues, N, represents the total number of flights j for flight i that land later than the arrival of flight i and earlier than the arrival of flight i:
Figure BDA0001561782350000031
wherein ETiFor the approach time of flight i, LTiLanding time for flight i;
s3.3, establishing an approach time prediction model: according to the number of the incoming queues and the actual incoming time tactualThe data of (2) constructing the number of incoming queues and the average incoming time ttransitThe unary linear regression model of (1):
ttransit＝α*N+β
where α, β represent correlation coefficients, and when N is equal to 0, ttransitThe value beta of is the clear approach time tunimpededThe value of (c).
Compared with the prior art, the time-based terminal area approach efficiency measuring method is an objective quantitative method for evaluating the approach efficiency of the terminal area, and provides a new method for estimating the unblocked approach time from the perspective of economic metrology, so that the defects of the current research are overcome, a powerful reference is provided for the terminal area efficiency evaluation, a foundation is laid for the comparison of approach efficiencies of different airports and the comparison of different approach optimization methods, the evaluation method is simple and easy to use, and the evaluation result is clear at a glance.
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FIG. 1 is a block flow diagram of the present invention;
FIG. 2 is a regression line graph of the number of lines of incoming flights and the time of approach measured over time according to one embodiment.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
As shown in fig. 1, a time-based terminal region approach efficiency measurement method of the present invention includes the following steps:
step S1, establishing a terminal area model: an airspace range taking an airport reference point as a circle center and 100 nautical miles as a radius is drawn as an airport terminal area.
Step S2, flight ADS-B data is collected and processed: downloading ADS-B data of incoming flights of a terminal area of a target airport from a flightradar24 website, screening the ADS-B data, and respectively calculating the position coordinates of each flight from 100 nautical places of airport reference points and the corresponding time t by taking each flight as a unit100And landing time t0. The ADS-B data screening comprises removing flight data with cancellation, no record and no landing information; ADS-B data contains flight number, time, latitude, longitude, altitude, speed, and heading information.
Preferably, in step S2, the specific steps of processing the flight ADS-B data are as follows:
s2.1, determining an approach position and an approach time, namely intercepting two track points which are closest to 100 nautical miles of the airport reference point in ADS-B data of each flight: p1＝min(Pi|0＜|PiParp|-100＜1)、P2＝min(Pj|-1＜|PjParpI-100 < 0) and corresponding time, calculating the time and other parameters at 100 nautical miles by a cubic spline interpolation method to respectively obtain the longitude and latitude coordinates of the approach point and the corresponding time t100(ii) a Track point P is a space point on a flight track, i, j refers to flights in the range of the airport terminal area; the point Pi is the airport reference point, and PiParp is the distance from the point Pi to the airport reference point.
Step S2.2, calculating the landing time: let flight landing time be t0Selecting the corresponding time t of two tracks before the flight landing1And t2(t1＞t2) And corresponding heights are respectively h1And h2(h1＜h2) The descent rate before the flight lands is:
RD2-1＝(h2-h1)/(t1-t2)，
estimating the landing time t from the descent rate0：
t0＝t1+(h1-0)/RD2-1。
Step S3, estimating the clear approach time: according to the ADS-B data processed in the step S2, calculating the actual approach time t of each approach flightactualAccording to the number of the incoming queues and the actual incoming time tactualData of (2) establishing the number of incoming queues and the average incoming time ttransitA univariate linear regression model of (c); aiming at the flight i, when the number of the incoming queues is 0, namely no incoming flight influences the incoming time of the flight i, and the constant item at the moment is the smooth incoming time tunimpededAnd the number of the inbound queues is the total number of all queued landing flights in the process from the inbound to the landing of the flight i.
Preferably, in step S3, the specific steps of estimating the clear approach time are as follows:
step S3.1, calculating the actual approach time: calculating the actual approach time t according to the ADS-B data processed in the step S2actualTime t from the approach of an approach flight from 100 nautical miles to landingactual＝t0-t100；
Step S3.2, calculating the number of incoming queues: the number of inbound queues, N, represents the total number of flights j for flight i that land later than the arrival of flight i and earlier than the arrival of flight i:
Figure BDA0001561782350000061
wherein ETiFor the approach time of flight i, LTiLanding time for flight i;
s3.3, establishing an approach time prediction model: according to the number of the incoming queues and the actual incoming time tactualThe data of (2) constructing the number of incoming queues and the average incoming time ttransitThe unary linear regression model of (1):
ttransit＝α*N+β
where α, β represent correlation coefficients, and when N is equal to 0, ttransitThe value of beta is just rightTime t of passing through fieldunimpededThe value of (c). Mean approach time ttransitThe average approach time for various queuing number cases.
Step S4, terminal area approach efficiency assessment: using the actual approach time t obtained in step S3actual and clear approach time tunimpededAnd calculating the airport terminal area entrance efficiency index based on time:
Figure BDA0001561782350000062
t hereactualRepresenting the actual approach time, tunimpededAnd (4) representing the smooth approach time, and finally carrying out efficiency evaluation on the whole flight by using the approach efficiency index of the terminal area.
In the first embodiment, the terminal area approach efficiency of 19-day approach flights in 2017 of Beijing capital airport is measured as an example
Step S1, establishing a terminal area model: an airspace range taking the airport reference point as the center of a circle and 100 nautical miles as the radius is drawn as the airport terminal area related to the method.
Step S2, flight ADS-B data is collected and processed: and downloading incoming flight ADS-B data of 19 days 4 and 7 years of the Beijing capital airport in 2017 from a flightradar24 website, wherein the ADS-B data information comprises flight number, time, latitude, longitude, altitude, speed and course. 730 ADS-B data are downloaded totally, 46 cancelled flights are removed, 122 recorded flights are not provided, 10 landing information is not provided, and 522 effective ABS-B data are provided. The position coordinates and time of each flight from the airport reference point 100 at sea and the precise landing time t0 are then calculated separately in flight number units.
S2.1, determining an approach position and an approach time, namely intercepting two track points which are closest to an airport reference point 100 nautical miles in ADS-B data of each flight: p1＝min(Pi|0＜|PiParp|-100＜1)，P2＝min(Pj|-1＜|PjParpI-100 < 0) and corresponding time, and using cubic spline interpolation method to correct the time at 100 nautical milesAnd calculating other parameters to respectively obtain longitude and latitude coordinates of the approach point and the corresponding approach time t100。
Step S2.2, calculating the landing time: set flight landing time t0Selecting the corresponding time t of two tracks before the flight landing1And t2(t1＞t2) And corresponding heights are respectively h1And h2(h1＜h2). The descent rate before the flight lands is: RD2-1＝(h2-h1)/(t1-t2) Estimating the landing time according to the descent rate: t is t0＝t1+(h1-0)/RD2-1. The result of processing flight data is shown in table 1.
TABLE 1 flight ADS-B data processing result sample
Figure BDA0001561782350000071
Wherein, the time t of 100 nautical miles100And landing time t0The time it takes for the flight aircraft to start from the departure.
Step S3, estimating the clear approach time: and obtaining the approach time of each flight according to the data processed in the step S2, and establishing a unary linear regression model of the approach queuing number and the approach time. For the flight i, when the number of the incoming queues is 0, namely the flight without the incoming landing influences the incoming time of the flight i, the constant term at this time is the smooth incoming time tunimpeded(ii) a The number of inbound queues in the model is the total number of all queued landing flights for that flight from inbound to landing.
Step S3.1, calculating the actual approach time: calculating the actual approach time t of the flight according to the ADS-B data processed in the step S2actualI.e. the time for an incoming flight to approach from 100 nautical miles to land: t is tactual＝t0-t100；
Step S3.2, calculating the number of incoming queues: the number of inbound queues, N, represents the total number of flights j for flight i that land later than the arrival of flight i and earlier than the arrival of flight i:
Figure BDA0001561782350000081
wherein ETiFor the approach time of flight i, LTiLanding time for flight i;
step S3.3, establishing an approach time prediction model: according to the number of the incoming queues and the actual incoming time tactualConstructing the number of incoming queues and the average incoming time ttransitOne-dimensional linear regression model (in minutes):
ttransit＝α*N+β
in this example, the correlation coefficient α is 0.4814, β is 22.8838, i.e., the unary linear regression equation is ttransitThe regression line plot of the number of lines in approach and the time of approach is shown in fig. 2 at 0.4814 × N +22.8838, where when N is equal to 0, t istransitValue of 22.8838 is the clear approach time tunimpededThe value of (1), i.e. in this example, the clear approach time tunimpeded22.8838 minutes.
Step S4, terminal area approach efficiency assessment: calculating a time-based efficiency index using the estimated clear approach time:
Figure BDA0001561782350000082
t hereactualRepresenting actual airport time, tunimpededIndicating a clear approach time.
Finally, the average value of the actual approach time of all flights in the day of the terminal area of the Beijing capital airport of 19 th in 4 th and 19 th in 2017 is obtained through calculation, and the calculated approach efficiency is 83.47%.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.

Claims (2)

1. A terminal area approach efficiency measurement method based on time is characterized by comprising the following steps:
s1, establishing a terminal area model: taking an airport reference point as a circle center, and taking an airspace range with 100 nautical miles as a radius as an airport terminal area;
s2, collecting and processing flight ADS-B data: downloading ADS-B data of incoming flights of a terminal area of a target airport from a flightradar24 website, screening the ADS-B data, and respectively calculating the position coordinates of each flight from 100 nautical miles of the airport reference point and the corresponding time by taking each flight as a unitt 100And landing timet 0；
S2.1, determining an approach position and an approach time, namely intercepting two track points which are closest to an airport reference point 100 nautical miles in ADS-B data of each approach flight:P 1 =min(P i |0<|P i P arp |-100<1)、P 2 =min(P j |-1<|P j P arp |-100<0) the longitude and latitude coordinates and the corresponding time are calculated by a cubic spline interpolation method for the time of 100 nautical miles, and the longitude and latitude coordinates of the approach point and the corresponding approach time are respectively obtainedt 100(ii) a Track point P is a spatial point on the flight track,i，jrefers to flights within the terminal area of an airport;Parpit is the airport reference point that is,PiParprefers to the track pointPiPoint to airport reference pointParpThe distance of (d);
s2.2, calculating the landing time: set the flight landing time ast 0Selecting corresponding time of two tracks before the flight landingt 1Andt 2and corresponding heights are respectivelyh 1Andh 2wherein, in the step (A),t 1> t 2、h 1< h 2the descent rate before the flight lands is:
RD 2-1=( h 2- h 1)/( t 1- t 2)，
estimating landing time from descent ratet 0：
t 0=t 1 +( h 1-0)/RD 2-1；
S3, estimating the clear approach time: according to the ADS-B data processed in the step S2, the actual approach time of each approach flight is calculatedt actual According to the number of incoming queues and the actual incoming timet actual Data of (2) establishing the number of incoming queues and the average incoming timet transit A univariate linear regression model of (c); for flightiWhen the number of incoming queues is 0, i.e. there are no incoming flights to flightiThe constant term is the unblocked approach timet unimpeded The number of the incoming queues is the number of the flightsiThe total number of all queued landing flights in the process from approach to landing; the specific steps of estimating the clear approach time are as follows:
s3.1, calculating the actual approach time: calculating the actual approach time of the flight according to the ADS-B data processed in the step S2t actual I.e. the time for an incoming flight to approach from 100 nautical miles to land:t actual = t 0 - t 100 ；
s3.2, calculating the number of incoming queues:number of queues in approachNRepresenting for flightiThe landing time of the flight is greater than that of the flightiIs late and is more than the flightiFlight with early landing timejThe total amount of (A):
N(i)=∑count(j)ij(ET i <LT j <LT i )，
whereinET i For flightsiThe time of approach of the vehicle,LT i for flightsiThe landing time of (c);
s3.3, establishing an approach time prediction model: according to the number of the incoming queues and the actual incoming timet actual The data of (2), constructing the number of incoming queues and the average incoming timet transit The unary linear regression model of (1):
t transit =α*N+β
whereinα，βRepresenting the correlation coefficient, when N is equal to 0,t transit value of (A)βNamely the unblocked approach timet unimpeded A value of (d);
s4, terminal area approach efficiency assessment: using the actual approach time obtained in step S3t actual And smooth approach timet unimpeded And calculating the airport terminal area entrance efficiency index based on time:
efficiency=1- (t actual -t unimpeded )/ t unimpeded ｘ100%，
herein, thet actual The actual time of approach is represented by,t unimpeded and (4) representing the smooth approach time, and finally carrying out efficiency evaluation on the whole flight by using the approach efficiency index of the terminal area.
2. The time-based terminal region approach efficiency measurement method according to claim 1, wherein in step S2, the screening ADS-B data includes removing flight data of cancellation, no record and no landing information; the ADS-B data contains flight number, time, latitude, longitude, altitude, speed, and heading information.
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