Method and device for analyzing the impact of airport dual-area traffic status

Abstract

The present invention provides a method and device for analyzing the impact of dual-area traffic status at an airport, relating to the technical field of airport traffic analysis. The method comprises obtaining historical operating data of the airport; calculating analysis parameters based on the historical operating data, and constructing a macro basic map of the entire airport area using the analysis parameters; performing polynomial function fitting on the macro basic map of the entire airport area to obtain a polynomial expression of the macro basic map of the entire airport area; obtaining the regional arrival rate of a single area of ​​the airport, and constructing a macro basic map of the dual-area airport based on the polynomial expression of the macro basic map of the entire airport area and the regional arrival rate; and analyzing the impact of the regional arrival rate on weighted flow and weighted density using the macro basic map of the dual-area airport. The present invention addresses the problem that research on airport traffic status currently focuses primarily on single-area traffic, lacking research on dual-area traffic dynamics.

Description

Technical Field

[0001] The present invention relates to the technical field of airport traffic analysis, and in particular to a method and device for analyzing the impact of airport dual-area traffic status. Background Art

[0002] As a pillar of the global economy, the civil aviation industry is experiencing increasing demand for air travel driven by growing international trade and resident travel needs. With the continuous increase in air traffic, airports, as key nodes affecting the efficiency of the aviation network, are particularly prone to severe congestion during peak hours at large airports. These issues include prolonged taxiing times, long runway queues, and stop-and-go aircraft. These issues not only increase taxiing times, fuel consumption and exhaust emissions, and reduce passenger satisfaction, but also reduce the efficiency of the entire aviation network. The severe congestion faced by airport flights has become a major challenge for airport optimization.

[0003] In order to alleviate airport congestion, a large amount of research work is devoted to improving the airport operation support capabilities. One of the important tasks is to study the dynamic changes of airport traffic flow and its impact. The current focus of research on traffic flow dynamics is to capture traffic flow characteristics and the mechanisms of congestion formation, propagation and dissipation in an effective way.

[0004] Currently, there are methods that use airport arrival rate, taxi number and departure rate as traffic characteristics to construct airport macro basic map, but the research on the dynamic changes and impacts of airport regional traffic flow is limited to the single area of ​​the airport. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and device for analyzing the impact of airport dual-zone traffic status to improve the above-mentioned problem. To achieve the above-mentioned purpose, the technical solution adopted by the present invention is as follows:

[0006] In a first aspect, the present application provides a method for analyzing the impact of dual-area traffic conditions at an airport, comprising:

[0007] Obtain historical operation data of the airport;

[0008] Calculating analysis parameters based on the historical operation data, and constructing a macro basic map of the entire airport area using the analysis parameters, wherein the analysis parameters include arrival rate, weighted density, and weighted flow;

[0009] Performing polynomial function fitting on the macro basic graph of the entire airport area to obtain a polynomial expression of the macro basic graph of the entire airport area, wherein the polynomial expression is a nonlinear equation of weighted flow and weighted density at different arrival rates;

[0010] Obtaining a regional arrival rate for a single area of ​​an airport, and constructing a macro basic map of two areas of the airport based on a multinomial expression of a macro basic map of the entire airport area and the regional arrival rate;

[0011] Through the macro basic diagram of the dual areas of the airport, the impact of the regional arrival rate on the weighted flow and weighted density is analyzed.

[0012] In a second aspect, the present application further provides an airport dual-area traffic status impact analysis device, comprising:

[0013] Acquisition module, used to obtain historical operation data of the airport;

[0014] A first construction module is configured to calculate analysis parameters based on the historical operation data and construct a macro basic map of the entire airport area using the analysis parameters, wherein the analysis parameters include arrival rate, weighted density, and weighted flow;

[0015] a fitting module, configured to perform polynomial function fitting on the macro basic graph of the entire airport area to obtain a polynomial expression of the macro basic graph of the entire airport area, wherein the polynomial expression is a nonlinear equation of weighted flow and weighted density at different arrival rates;

[0016] The second construction module is used to obtain the regional arrival rate of a single area of ​​the airport, and construct a macro basic map of the two areas of the airport based on the multinomial expression of the macro basic map of the entire airport area and the regional arrival rate;

[0017] The analysis module is used to analyze the impact of the regional arrival rate on the weighted flow and weighted density through the macro basic map of the dual areas of the airport.

[0018] The beneficial effects of the present invention are as follows: the present invention constructs a macro basic map of the airport through arrival rate, weighted density and weighted flow, and uses the macro basic map to study the mutual influence between the traffic status of different areas of the airport, and designs a macro basic map of the airport's dual areas that is suitable for any scene topology and operation scenario, taking into account the characteristics of the airport's traffic flow distribution. Compared with macro basic maps constructed by other methods, the present invention has better prediction effects, can more accurately capture the traffic status of the airport scene, and provides technical support for achieving airport operation optimization. The macro basic map of the airport's dual areas not only has the ability to describe the dynamic changes in traffic in a single area, but also has the ability to quantitatively evaluate the mutual influence of regional traffic.

[0019] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the embodiments of the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 Schematic diagram of the flow of the airport dual-area traffic status impact analysis method according to an embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram of the airport taxiway segmentation in an embodiment of the present invention;

[0023] Figure 3 Schematic diagram of the nonlinear relationship between weighted flow and weighted density in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0025] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are used only to distinguish the description and should not be understood as indicating or implying relative importance.

[0026] Example 1:

[0027] This embodiment provides a method for analyzing the impact of dual-area traffic status in an airport.

[0028] See also Figure 1 , the figure shows that the method includes step S100, step S200, step S300, step S400 and step S500.

[0029] Step S100: Acquire historical operation data of the airport;

[0030] In this embodiment, historical operation data of the airport is collected through different relevant management and operation departments, specifically including:

[0031] Step S101: The airport surface network structure and operation rule information is obtained from the airport operation command department or other relevant departments. The airport surface network structure and operation rule information includes historical flight operation data, network topology, and aircraft stand and runway information. The aircraft stand and runway information includes information on applicable aircraft models, operation rules, restrictions, and preferences.

[0032] Step S102: Extract key data based on the airport surface network structure and operation rule information, where the key data includes flight date, flight number, aircraft model, flight departure point, flight type, planned arrival and departure times, actual arrival and departure times, used parking spaces, used runways, and actual block time.

[0033] Step S103: Input key data into the ACA platform for simulation, and output the trajectory data of all flights during the airport operation period, that is, obtain the historical operation data of the airport.

[0034] Step S200: Calculating analysis parameters based on the historical operation data, and constructing a macro basic map of the entire airport area using the analysis parameters, wherein the analysis parameters include arrival rate, weighted density, and weighted flow;

[0035] The step S200 includes:

[0036] Step S201: Based on the historical operation data, the number of arriving flights in the entire area of ​​the airport within a time interval, the total number of equivalent medium-sized flights on each taxiway within the time interval, the length of each taxiway, and the number of flights passing each taxiway within the time interval are obtained;

[0037] Step S202: taking the number of flights arriving in the time interval as the arrival rate of the entire airport area;

[0038] Step S203: Calculating the weighted density of the entire airport area by using the total number of medium-sized flights on each taxiway within the time interval and the length of each taxiway;

[0039] In this embodiment, the calculation formula of the weighted density is:

[0040]

[0041]

[0042] Where d(t) represents the weighted density in time interval t, n(t,i′) represents the total number of equal medium-sized flights on taxiway i′ in time interval t, L(i′) represents the length of taxiway i′, N represents the number of taxiways, RF represents the first reinforcement factor, l(k′,i′) represents the fuselage length of the k′th flight on taxiway i′, P(t,i′) represents the number of flights on taxiway i′ in time interval t, Indicates the average fuselage length of medium-sized aircraft.

[0043] Due to the different types of flights at the airport, they are divided into heavy, medium and light flights according to the length of the fuselage and the passenger capacity, as shown in Table 1. Considering that the space occupied by the fuselage is inconsistent, the flow impact of different types of flights on the airport surface is inconsistent. Therefore, different types of flights are converted into equal medium-sized flights.

[0044] Table 1 Flight type classification

[0045]

[0046]

[0047] The taxiways are divided based on the intersections and turning nodes on the airport, such as Figure 2 As shown in , the intersections and turns of the airport taxiways are used as nodes for dividing the taxiways, such as Figure 2 Node1, Node2, Node3 and Node4 in , and the taxiway between two adjacent nodes is an independent taxiway, such as Figure 2 L i nk1 and L i nk2 in , where Node represents a node and L i nk represents an independent taxiway.

[0048] In this embodiment, if the first reinforcement coefficient RF is taken as 200, d(t) is used to describe the average weighted density of every 200 meters of the taxiway.

[0049] Step S204: Calculating the weighted traffic flow of the entire airport area based on the number of flights passing through each taxiway within the time interval and the length of each taxiway;

[0050] In this embodiment, the calculation formula of the weighted flow is:

[0051]

[0052] Where f(t) represents the weighted flow rate in time interval t, g(t,i′) represents the number of flights passing through taxiway i′ in time interval t, L(i′) represents the length of taxiway i′, N represents the number of taxiways, and RL represents the second reinforcement factor.

[0053] Step S205: Mapping the arrival rate, the weighted density, and the weighted flow corresponding to different time intervals into three-dimensional coordinates to obtain a macro basic map of the entire airport area that reflects the supply and demand relationship of the airport surface.

[0054] In this embodiment, different arrival rates, weighted densities and weighted flows are mapped to the x-axis of the three-dimensional coordinate system, the weighted density is mapped to the y-axis, and the weighted flow is mapped to the z-axis. This allows us to obtain a macroscopic basic diagram of the three airport traffic states, namely, arrival rate, weighted density and weighted flow, which reflects the supply and demand relationship of the airport surface.

[0055] Step S300: performing polynomial function fitting on the macro basic graph of the entire airport area to obtain a polynomial expression of the macro basic graph of the entire airport area, wherein the polynomial expression is a nonlinear equation of weighted flow and weighted density at different arrival rates;

[0056] In this embodiment, for different arrival rates, a two-dimensional basic graph of weighted density and weighted flow can be obtained. This two-dimensional graph shows a nonlinear relationship between weighted density and weighted flow. By fitting a polynomial to this two-dimensional data, a polynomial relationship can be obtained for different arrival rates. In this embodiment, a second-order polynomial is selected for fitting, and the following formula can be obtained:

[0057] A·(d(t)) 2 +B·d(t)+C(4)

[0058] Where A, B, and C are fitting parameters, d(t) represents the weighted density within time interval t, and a(t) represents the arrival rate within time interval t.

[0059] The macro basic map of the entire airport area in formula (4) is defined as follows:

[0060] G′(a(t),d(t))(5)

[0061] where d(t) represents the weighted density within time interval t, a(t) represents the arrival rate within time interval t, and G′(·) represents the mathematical form of the macro basic graph.

[0062] Formula (5) is a family of functions related to Formula (4), which indicates that when the arrival rate is different, the weighted flow and weighted density present different nonlinear relationships. Therefore, Formula (5) can be used to solve the weighted flow when the arrival rate and weighted density are known.

[0063] Step S400: obtaining the regional arrival rate of a single area of ​​an airport, and constructing a macro basic map of two areas of the airport based on the multinomial expression of the macro basic map of the entire airport area and the regional arrival rate;

[0064] In this embodiment, under the premise that the airport adheres to the runway priority policy for arriving aircraft over departing aircraft, a higher regional arrival rate at the airport means that the runway resources available to departing flights will be smaller. When the runway resources available to departing flights change, it can be regarded as a change in the airport's topological structure. Therefore, under different arrival rate conditions, the airport presents different traffic conditions, and the weighted density and weighted flow will also show different nonlinear relationships. Therefore, the airport surface arrival rate plays an important role in influencing the airport traffic status, and it is necessary to explore the mechanism by which the arrival rate affects the surface traffic status.

[0065] Specifically, with the help of the shock wave concept in the field of traffic flow, the different nonlinear relationships between weighted density and weighted flow when the arrival rate changes are explained, and a macro basic diagram of the airport dual area is constructed. Among them, this concept refers to the fact that when changing from one traffic state to another, a continuously propagating fluctuation will be generated in the region, and the fluctuation will affect the traffic state in the time and space range.

[0066] The step S400 includes:

[0067] Step S401: Divide the entire airport area into two single airport areas using the shared runway as a dividing boundary;

[0068] In this embodiment, for an airport, it is relatively difficult to divide the airport into relatively uniform areas due to the relatively sparse airport topology and traffic flow. Therefore, in this step, the shared runway is used as the segmentation basis to divide the airport into two different areas.

[0069] Step S403: Calculating the regional arrival rate of each single area of ​​the airport by using the runway arrival rate, where the runway arrival rate is the number of flights arriving at the runway within an interval;

[0070] In this embodiment, the regional arrival rate and the runway arrival rate can be expressed in terms of each other, and the conversion relationship is as follows:

[0071]

[0072]

[0073] Where az(k,t) represents the arrival rate of region k within time interval t, S represents the shared runway between two regions, R(k) represents the set of runways in region k, ar(e,t) represents the number of flights arriving at runway e within time interval t, and w e,k represents the proportion of flights to area k in the number of flights arriving at runway e, v k,e represents the proportion of flights arriving from runway e in zone k, Indicates the number of areas in the scene.

[0074] It can be seen from formula (6) that when the runway arrival rate of the shared runway changes, it will affect the traffic status of the two areas at the same time.

[0075] Step S404: Calculating the weighted density of each single area of ​​the airport;

[0076] The step S404 includes:

[0077] Step A100: Calculate the maximum departure capacity of the runway;

[0078] In this embodiment, the calculation formula for the maximum departure capacity of the runway is:

[0079]

[0080] Where M(e) represents the maximum departure capacity of runway e, Δt represents the time interval window used for statistical data on the surface, k(·) represents the empirical maximum throughput of the runway published by the airport, and t land (·) represents the minimum time interval between the departure flight and the arrival aircraft landing on the runway, t off (·) represents the minimum time interval between two consecutive departing flights from the runway, and min{·} indicates the minimum value.

[0081] Step A200: Calculate the maximum departure capacity of each single area of ​​the airport by taking into account the proportion of flights bound for a single area of ​​the airport in the number of arriving flights on the runway, the proportion of flights bound for the runway in the number of arriving flights on the runway, and the maximum departure capacity of the runway.

[0082] The calculation formula for the maximum departure capacity of a single area of ​​the airport is:

[0083]

[0084]

[0085] Where D(i,j,k) represents the maximum departure capacity of zone k when the arrival rate of zone 1 is i and the arrival rate of zone 2 is j, M(2) represents the maximum departure capacity of runway 2, and v 1,2 represents the proportion of flights arriving from runway 2 in the region 1, v 2,2 represents the proportion of flights arriving from runway 2 in area 2, i and j both represent the specific value of the arrival rate, and w 2,k represents the proportion of flights bound for region k in the number of arrivals on runway 2, M(e) represents the maximum departure capacity of runway e, R(k) represents the set of runways in region k, and v k,2 represents the proportion of flights from runway 2 among the arriving flights in area k, and arr(k) represents the intermediate function.

[0086] Among them, runway 2 represents a shared runway.

[0087] Step A300: Calculating the weighted density of each airport single area;

[0088] Step A400: Calculating a weighted density change of each single area of ​​the airport based on the weighted density of the single area of ​​the airport and the maximum departure capacity of the single area of ​​the airport;

[0089] In this embodiment, the calculation formula for the weighted density change of a single area of ​​an airport is:

[0090]

[0091] Where Δad(a1,i,k) represents the weighted density change when the arrival rate of area k changes from a1 to i, D(a1,a2,k) represents the maximum departure capacity of area k when the arrival rate of area 1 is a1 and the arrival rate of area 2 is a2, D(i,a2,k) represents the maximum departure capacity of area k when the arrival rate of area 1 is i and the arrival rate of area 2 is a2, ad(k,a1) represents the weighted density when the arrival rate of area k is a1, ad(k,i) represents the weighted density when the arrival rate of area k is i, and Δt represents the time interval window used for statistical data on the scene.

[0092] Step A500: Inputting the weighted density change of the single airport area into a preset weighted density dynamic equation to update the weighted density of each single airport area.

[0093] In this embodiment, the preset weighted density dynamic equation is:

[0094] ad(k,j)=ad(k,i)+Δad(i,j,k) (12)

[0095] Where ad(k,j) represents the weighted density when the arrival rate of region k is j, ad(k,i) represents the weighted density when the arrival rate of region k is i, and Δad(i,j,k) represents the change in weighted density when the arrival rate of region k changes from i to j.

[0096] The calculation formula for the weighted density of a single airport area is:

[0097]

[0098] where ad(k,i) represents the weighted density of region k when the arrival rate is i, D(i,a2,k) represents the maximum departure capacity of region k when the arrival rate of region 1 is i and the arrival rate of region 2 is a2, D(a1,a2,k) represents the maximum departure capacity of region k when the arrival rate of region 1 is a1 and the arrival rate of region 2 is a2, ad(k,a1) represents the weighted density of region k when the arrival rate of region k is a1, and O(·) represents the error estimate.

[0099] Step S405: obtaining a continuous macro basic graph of each single airport area based on the weighted density of the single airport area and the multinomial expression of the macro basic graph of the entire airport area;

[0100] The step S405 includes:

[0101] Step B100: inputting the weighted density of the single airport area into the multinomial expression of the macro basic graph of the entire airport area to obtain a discrete macro basic graph of each single airport area;

[0102] Step B200: calculating the average weighted density change rate of each single area of ​​the airport when the regional arrival rate of the single area of ​​the airport changes;

[0103] Step B300: Correcting the discrete macro basic map of the corresponding single airport area by the average weighted density change rate of the single airport area to obtain a continuous macro basic map of each single airport area.

[0104] In this embodiment, the expression of the continuous macro basic graph of a single area of ​​the airport is:

[0105] G k (i,ad(k,i))=β(a1,i,a2,a2,k)·G′ k (a1,ad(k,i)) (14)

[0106] Where G k (i,ad(k,i)) represents the continuous macroscopic basic graph of region k under ad(k,i), ad(k,i) represents the weighted density when the arrival rate of region k is i, G′ k (a1,ad(k,i)) represents the discrete macroscopic basic graph of region k under ad(k,i), and β(a1,i,a2,a2,k) represents the average weighted density change rate of region k when the arrival rate of region 1 changes from a1 to i and the arrival rate of region 2 remains at a2.

[0107] In formula (14), the calculation formula for the average weighted density change rate is:

[0108]

[0109] Where β(i,j,p,q,k) represents the average weighted density change rate of region k when the arrival rate of region 1 changes from i to j and the arrival rate of region 2 changes from p to q. D(i,p,k) represents the maximum departure capacity of region k when the arrival rate of region 1 is i and the arrival rate of region 2 is p. D(j,q,k) represents the maximum departure capacity of region k when the arrival rate of region 1 is j and the arrival rate of region 2 is q.

[0110] Step S405: Based on the regional arrival rate of the single airport area, the continuous macro basic graphs of the two airport single areas are jointly represented to obtain the macro basic graph of the dual airport areas.

[0111] In this embodiment, for the full-area arrival rate, Area 1 and Area 2 will correspond to different combinations. Therefore, the full airport area is subdivided into the following macro basic diagram of the airport dual area, as shown in the following formula:

[0112]

[0113] where G(·) represents the macro basic graph of the airport dual area, az(k,t) represents the arrival rate of area k in time interval t, d(k,t) represents the weighted density of area k in time interval t, k = 1, 2, G1(az(1,t),d(1,t)) represents the continuous macro basic graph of area 1 under az(1,t) and d(1,t), and G2(az(2,t),d(2,t)) represents the continuous macro basic graph of area 2 under az(2,t) and d(2,t).

[0114] Step S500: Analyze the impact of the regional arrival rate on the weighted flow and weighted density through the macro basic map of the dual-area of ​​the airport.

[0115] The step S500 includes:

[0116] Step S501: performing polynomial function fitting on the macro basic graph of the dual-area airport to obtain a polynomial expression of the macro basic graph of the dual-area airport;

[0117] In this embodiment, the nonlinear relationship between weighted density and weighted flow under different arrival rates is regarded as a quadratic function, as shown in formula (1). Therefore, the polynomial expression of the macro basic graph of the airport dual area is:

[0118] G(a,d)=β 3 ·A·d 2 +β 2 ·B·d+β·C (17)

[0119] where G(·) represents the macro basic map of the airport dual area, d represents the weighted density, a represents the arrival rate, β represents the average weighted density change rate, and A, B, and C represent fitting parameters.

[0120] Step S502: Derivative calculation is performed on the polynomial expression of the macro basic graph of the dual-area airport to obtain a weighted flow change rate, where the weighted flow change rate includes the weighted flow change rate of the two single-area airports and the weighted flow change rate of the entire airport area.

[0121] In this embodiment, the expression of the weighted flow rate change rate is:

[0122]

[0123]

[0124]

[0125] Where, It represents the weighted traffic change rate of area 2 when the arrival rate of area 1 changes and the arrival rate of area 2 remains unchanged. It represents the weighted traffic change rate of area 1 when the arrival rate of area 2 changes and the arrival rate of area 1 remains unchanged. represents the weighted traffic change rate of the entire airport area when the arrival rates of area 1 and area 2 change, w 2,k represents the proportion of flights to area k in the number of arrival flights on runway 2, v k,2 represents the proportion of flights from runway 2 among the arrival flights in area k, k = 1, 2, d represents the weighted density, β represents the average weighted density change rate, A, B and C represent fitting parameters, D(a1, a2, k) represents the maximum departure capacity of area k when the arrival rate of area 1 is a1 and the arrival rate of area 2 is a2, represents the number of zones in the scene, az(k,t) represents the arrival rate of zone k in time interval t, G1 represents the continuous macro basic graph of zone 1, G2 represents the continuous macro basic graph of zone 2, G(·) represents the macro basic graph of the dual zones of the airport, and a represents the arrival rate.

[0126] Step S503: Obtaining a weighted density change rate through a polynomial expression of the macro basic graph of the dual-area airport, wherein the weighted density change rate includes the corresponding weighted density change rates of the two single-areas of the airport and the weighted density change rate of the entire airport area under different changes in the regional arrival rate;

[0127] In this embodiment, when the arrival rate changes in two areas are different, the formulas for the weighted density change rates of area 1, area 2 and the entire airport area are different. The weighted density change rate of area 1 includes the first weighted density change rate and the second weighted density change rate, the weighted density change rate of area 2 includes the third weighted density change rate and the fourth weighted density change rate, and the weighted density change rate of the entire airport area includes the fifth weighted density change rate and the sixth weighted density change rate.

[0128] Specifically, when the arrival rate of region 1 changes from i to j and the arrival rate of region 2 remains at p, the weighted density change rate of region 2 is:

[0129] Δad1(i,j,2)=β(i,j,p,p,2) (21)

[0130] where Δad1(i,j,2) represents the third weighted density change rate, and β(i,j,p,p,2) represents the average weighted density change rate of region 2 when the arrival rate of region 1 changes from i to j and the arrival rate of region 2 remains at p.

[0131] When the arrival rate of region 1 remains at p and the arrival rate of region 2 changes from i to j, the rate of change of the weighted density of region 1 is:

[0132] Δad1(i,j,1)=β(p,p,i,j,1) (22)

[0133] where Δad1(i,j,1) represents the first weighted density change rate, and β(p,p,i,j,1) represents the average weighted density change rate of region 1 when the arrival rate of region 1 remains at p and the arrival rate of region 2 changes from i to j.

[0134] When the arrival rate of region 1 changes from i to j and the arrival rate of region 2 remains at p, the weighted density change rate of region 1 is:

[0135] Δad2(i,j,1)=β(i,j,p,p,1) (23)

[0136] where Δad2(i,j,1) represents the second weighted density change rate, and β(i,j,p,p,1) represents the average weighted density change rate of region 1 when the arrival rate of region 1 changes from i to j and the arrival rate of region 2 remains at p.

[0137] When the arrival rate of region 1 remains at p and the arrival rate of region 2 changes from i to j, the rate of change of the weighted density of region 2 is:

[0138] Δad2(i,j,2)=β(p,p,i,j,2) (24)

[0139] where Δad2(i,j,2) represents the fourth weighted density change rate, and β(p,p,i,j,2) represents the average weighted density change rate of region 2 when the arrival rate of region 1 remains p and the arrival rate of region 2 changes from i to j.

[0140] When the arrival rate in area 1 changes from i to j, and the arrival rate in area 2 remains at p, the weighted density change rate for the entire airport area is:

[0141]

[0142] Where Δad1(i+p,j+p) represents the fifth weighted density change rate, D(j,p,k) represents the maximum departure capacity of region k when the arrival rate of region 1 is j and the arrival rate of region 2 is p, and D(i,p,k) represents the maximum departure capacity of region k when the arrival rate of region 1 is i and the arrival rate of region 2 is p, where k = 1, 2.

[0143] When the arrival rate in area 2 changes from i to j, and the arrival rate in area 1 remains at p, the weighted density change rate for the entire airport area is:

[0144]

[0145] Wherein, Δad2(i+p,j+p) represents the sixth weighted density change rate, D(p,j,k) represents the maximum departure capacity of region k when the arrival rate of region 1 is p and the arrival rate of region 2 is j, and D(p,i,k) represents the maximum departure capacity of region k when the arrival rate of region 1 is p and the arrival rate of region 2 is i, where k = 1, 2.

[0146] Step S504: analyzing the influence of the regional arrival rate on the weighted traffic through the weighted traffic change rate, and analyzing the influence of the regional arrival rate on the weighted density through the weighted density change rate.

[0147] In this embodiment, in addition to analyzing the impact of regional arrival rate on weighted flow and weighted density through the macro basic diagram of the dual-region airport, an optimal weighted density can also be obtained.

[0148] Specifically, the macro basic diagram of the airport dual area is a functional combination of the nonlinear relationship between weighted flow and weighted density under different arrival rates. The schematic diagram of this nonlinear relationship is shown in Figure 3 shown.

[0149] Figure 3 The weighted flow rate first increases with the weighted density, then reaches its maximum value and continues to decrease as the weighted density increases. Therefore, for different arrival rates, there exists an optimal weighted density that maximizes the weighted flow rate.

[0150] The optimal weighted density can be obtained by taking the partial derivatives of the arrival rates for Regions 1 and 2, respectively, and summing the weighted densities corresponding to the minimum of these two partial derivatives. When the arrival rate of a scene changes, continuously adjusting the scene's weighted density through control and management to maintain the optimal weighted density and ensure that the scene's flow rate remains at the maximum level is one strategy for improving scene operational efficiency using a macro-basic map.

[0151] In summary, the present invention constructs a macro basic map of the airport through arrival rate, weighted density, and weighted flow, and uses the macro basic map to study the mutual influence between the traffic conditions of different areas of the airport, thereby obtaining a macro basic map of the airport's dual areas. This not only takes into account the distribution characteristics of airport surface traffic, but also has better prediction effects than macro basic maps constructed by other methods. It can more accurately capture the traffic conditions of the airport surface, providing technical support for achieving airport operation optimization. The present invention also conducts a quantitative analysis of the mutual influence of the traffic conditions of the dual areas of the airport, which helps to achieve more refined control of the traffic conditions of the airport surface.

[0152] Example 2:

[0153] This embodiment provides a device for analyzing the impact of dual-area traffic conditions in an airport, the device comprising:

[0154] Acquisition module, used to obtain historical operation data of the airport;

[0155] A first construction module is configured to calculate analysis parameters based on the historical operation data and construct a macro basic map of the entire airport area using the analysis parameters, wherein the analysis parameters include arrival rate, weighted density, and weighted flow;

[0156] a fitting module, configured to perform polynomial function fitting on the macro basic graph of the entire airport area to obtain a polynomial expression of the macro basic graph of the entire airport area, wherein the polynomial expression is a nonlinear equation of weighted flow and weighted density at different arrival rates;

[0157] The second construction module is used to obtain the regional arrival rate of a single area of ​​the airport, and construct a macro basic map of the two areas of the airport based on the multinomial expression of the macro basic map of the entire airport area and the regional arrival rate;

[0158] The analysis module is used to analyze the impact of the regional arrival rate on the weighted flow and weighted density through the macro basic map of the dual areas of the airport.

[0159] The first building block includes:

[0160] a first acquiring unit configured to acquire, based on the historical operation data, the number of arriving flights in the entire area of ​​the airport within a time interval, the total number of equivalent medium-sized flights on each taxiway within the time interval, the length of each taxiway, and the number of flights passing each taxiway within the time interval;

[0161] defining a unit for using the number of arriving flights in the time interval as the arrival rate for the entire area of ​​the airport;

[0162] A first calculation unit is configured to calculate a weighted density of the entire airport area according to the total number of equal medium-sized flights on each taxiway within the time interval and the length of each taxiway;

[0163] a second calculating unit, configured to calculate the weighted traffic flow of the entire airport area according to the number of flights passing through each taxiway within the time interval and the length of each taxiway;

[0164] A mapping unit is used to map the arrival rate, the weighted density and the weighted flow corresponding to different time intervals into three-dimensional coordinates to obtain a macro basic map of the entire airport area that reflects the supply and demand relationship of the airport surface.

[0165] The second building block includes:

[0166] a division unit, configured to divide the entire airport area into two single airport areas using the shared runway as a dividing boundary;

[0167] a third calculation unit, configured to calculate an area arrival rate for each single area of ​​the airport by using a runway arrival rate, wherein the runway arrival rate is the number of flights arriving at the runway within an interval;

[0168] a fourth calculation unit, configured to calculate the weighted density of each single area of ​​the airport;

[0169] A second acquisition unit is configured to acquire a continuous macro basic map of each of the single airport areas based on the weighted density of the single airport area and a multinomial expression of the macro basic map of the entire airport area;

[0170] The joint representation unit is used to jointly represent the two continuous macro basic graphs of the single airport area based on the regional arrival rate of the single airport area to obtain the macro basic graph of the dual airport area.

[0171] The analysis module includes:

[0172] A fitting unit, configured to perform polynomial function fitting on the macro basic graph of the dual-area airport to obtain a polynomial expression of the macro basic graph of the dual-area airport;

[0173] a fifth calculation unit, configured to perform derivative calculations on a polynomial expression of the macro basic graph of the dual-area airport to obtain a weighted flow rate change rate, wherein the weighted flow rate change rate includes the weighted flow rate change rates of the two single-area airports and the weighted flow rate change rate of the entire airport area;

[0174] a sixth calculation unit, configured to obtain a weighted density change rate through a polynomial expression of the macro basic graph of the dual-area airport, the weighted density change rate comprising the weighted density change rates of the two single-area airports and the weighted density change rate of the entire airport area corresponding to different changes in the regional arrival rate;

[0175] An analyzing unit is used to analyze the influence of the regional arrival rate on the weighted traffic through the weighted traffic change rate, and to analyze the influence of the regional arrival rate on the weighted density through the weighted density change rate.

[0176] It should be noted that, regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here.

[0177] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

[0178] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for analyzing the impact of dual-area traffic conditions at an airport, characterized in that: include: Obtain historical operation data of the airport; Calculating analysis parameters based on the historical operation data, and constructing a macro basic map of the entire airport area using the analysis parameters, wherein the analysis parameters include arrival rate, weighted density, and weighted flow; Performing polynomial function fitting on the macro basic graph of the entire airport area to obtain a polynomial expression of the macro basic graph of the entire airport area, wherein the polynomial expression is a nonlinear equation of weighted flow and weighted density at different arrival rates; Obtaining a regional arrival rate for a single area of ​​an airport, and constructing a macro basic map of two areas of the airport based on a multinomial expression of a macro basic map of the entire airport area and the regional arrival rate; By using the macro basic diagram of the dual areas of the airport, the influence of the arrival rate of the area on the weighted flow and weighted density is analyzed; The calculating of analysis parameters based on the historical operation data and constructing a macro basic map of the entire airport area using the analysis parameters include: Based on the historical operation data, obtaining the number of arriving flights in the entire area of ​​the airport within the time interval, the total number of equivalent medium-sized flights on each taxiway within the time interval, the length of each taxiway, and the number of flights passing each taxiway within the time interval; The number of flights arriving during the time interval is taken as the arrival rate for the entire area of ​​the airport; Calculating a weighted density for the entire area of ​​the airport based on the total number of equivalent medium-sized flights on each taxiway during the time interval and the length of each taxiway; Calculating the weighted traffic flow of the entire airport area according to the number of flights passing each taxiway within the time interval and the length of each taxiway; Mapping the arrival rate, the weighted density, and the weighted flow corresponding to different time intervals into three-dimensional coordinates to obtain a macroscopic basic map of the entire airport area reflecting the supply and demand relationship of the airport surface; The method of obtaining the regional arrival rate of a single area of ​​an airport and constructing a macro basic map of two areas of an airport based on a multinomial expression of a macro basic map of the entire area of ​​the airport and the regional arrival rate includes: The entire airport area is divided into two single airport areas using the shared runway as a dividing boundary; Calculating the regional arrival rate of each single area of ​​the airport by using the runway arrival rate, where the runway arrival rate is the number of flights arriving at the runway during the interval; Calculating the weighted density of each single area of ​​the airport; Obtaining a continuous macro basic map of each of the single airport areas based on the weighted density of the single airport area and a multinomial expression of the macro basic map of the entire airport area; The continuous macro basic graphs of the two airport single areas are jointly represented based on the regional arrival rate of the airport single area to obtain the macro basic graph of the airport dual area.

2. The airport dual-area traffic status impact analysis method according to claim 1 is characterized in that , the calculation of the weighted density of each single area of ​​the airport includes: Calculate the maximum departure capacity of a runway; Calculate the maximum departure capacity of each single area of ​​the airport by using the proportion of flights destined for a single area of ​​the airport to the number of arrival flights on the runway, the proportion of flights destined for the runway to the number of arrival flights on the single area of ​​the airport, and the maximum departure capacity of the runway; Calculating the weighted density of each single area of ​​the airport; Calculating a weighted density change of each of the single areas of the airport based on the weighted density of the single area of ​​the airport and the maximum departure capacity of the single area of ​​the airport; The weighted density change of the single area of ​​the airport is input into a preset weighted density dynamic equation to update the weighted density of each single area of ​​the airport.

3. The airport dual-area traffic status impact analysis method according to claim 1 is characterized in that The method of obtaining a continuous macro basic map of each single airport area based on the weighted density of the single airport area and the multinomial expression of the macro basic map of the entire airport area includes: Inputting the weighted density of the single airport area into the multinomial expression of the macro basic map of the entire airport area to obtain a discrete macro basic map of each single airport area; When calculating the change in regional arrival rate of the single airport area, the average weighted density change rate of each single airport area; The discrete macro basic map of the corresponding single airport area is corrected by the average weighted density change rate of the single airport area to obtain a continuous macro basic map of each single airport area.

4. The airport dual-area traffic status impact analysis method according to claim 1 is characterized in that ,The macro basic diagram of the dual areas of the airport is used to analyze the ,impact of the regional arrival rate on the weighted flow and weighted density, including: Performing polynomial function fitting on the macro basic graph of the dual-area airport to obtain a polynomial expression of the macro basic graph of the dual-area airport; Derivative calculation is performed on the polynomial expression of the macro basic graph of the dual-area airport to obtain a weighted flow change rate, wherein the weighted flow change rate includes the weighted flow change rates of the two single-area airports and the weighted flow change rate of the entire airport area; Obtaining a weighted density change rate through a polynomial expression of the macro basic graph of the dual-area airport, the weighted density change rate including the corresponding weighted density change rates of the two single-areas of the airport and the weighted density change rate of the entire airport area under different changes in the regional arrival rate; The influence of the regional arrival rate on the weighted traffic is analyzed by the weighted traffic change rate, and the influence of the regional arrival rate on the weighted density is analyzed by the weighted density change rate.

5. An airport dual-area traffic status impact analysis device, characterized in that: include: Acquisition module, used to obtain historical operation data of the airport; A first construction module is configured to calculate analysis parameters based on the historical operation data and construct a macro basic map of the entire airport area using the analysis parameters, wherein the analysis parameters include arrival rate, weighted density, and weighted flow; a fitting module, configured to perform polynomial function fitting on the macro basic graph of the entire airport area to obtain a polynomial expression of the macro basic graph of the entire airport area, wherein the polynomial expression is a nonlinear equation of weighted flow and weighted density at different arrival rates; The second construction module is used to obtain the regional arrival rate of a single area of ​​the airport, and construct a macro basic map of the two areas of the airport based on the multinomial expression of the macro basic map of the entire airport area and the regional arrival rate; An analysis module, configured to analyze the impact of the regional arrival rate on the weighted flow and weighted density using a macro basic map of the dual-region airport; The first building block includes: a first acquiring unit configured to acquire, based on the historical operation data, the number of arriving flights in the entire area of ​​the airport within a time interval, the total number of equivalent medium-sized flights on each taxiway within the time interval, the length of each taxiway, and the number of flights passing each taxiway within the time interval; defining a unit for using the number of arriving flights in the time interval as the arrival rate for the entire area of ​​the airport; A first calculation unit is configured to calculate a weighted density of the entire airport area according to the total number of equal medium-sized flights on each taxiway within the time interval and the length of each taxiway; a second calculating unit, configured to calculate the weighted traffic flow of the entire airport area according to the number of flights passing through each taxiway within the time interval and the length of each taxiway; a mapping unit, configured to map the arrival rate, the weighted density, and the weighted flow corresponding to different time intervals into three-dimensional coordinates to obtain a macro basic map of the entire airport area reflecting the supply and demand relationship of the airport surface; The second building block includes: a division unit, configured to divide the entire airport area into two single airport areas using the shared runway as a dividing boundary; a third calculation unit, configured to calculate an area arrival rate for each single area of ​​the airport by using a runway arrival rate, wherein the runway arrival rate is the number of flights arriving at the runway within an interval; a fourth calculation unit, configured to calculate the weighted density of each single area of ​​the airport; A second acquisition unit is configured to acquire a continuous macro basic map of each of the single airport areas based on the weighted density of the single airport area and a multinomial expression of the macro basic map of the entire airport area; The joint representation unit is used to jointly represent the two continuous macro basic graphs of the single airport area based on the regional arrival rate of the single airport area to obtain the macro basic graph of the dual airport area.

6. The airport dual-area traffic status impact analysis device according to claim 5, characterized in that: The analysis module includes: A fitting unit, configured to perform polynomial function fitting on the macro basic graph of the dual-area airport to obtain a polynomial expression of the macro basic graph of the dual-area airport; a fifth calculation unit, configured to perform derivative calculations on a polynomial expression of the macro basic graph of the dual-area airport to obtain a weighted flow rate change rate, wherein the weighted flow rate change rate includes the weighted flow rate change rates of the two single-area airports and the weighted flow rate change rate of the entire airport area; a sixth calculation unit, configured to obtain a weighted density change rate through a polynomial expression of the macro basic graph of the dual-area airport, the weighted density change rate comprising the weighted density change rates of the two single-area airports and the weighted density change rate of the entire airport area corresponding to different changes in the regional arrival rate; An analyzing unit is used to analyze the influence of the regional arrival rate on the weighted traffic through the weighted traffic change rate, and to analyze the influence of the regional arrival rate on the weighted density through the weighted density change rate.

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