Route congestion index measuring and calculating method and system based on route sub-route segment space analysis

Abstract

The invention discloses an air route congestion index measuring and calculating method and system based on air route sub-route segment space analysis. The method comprises the steps that S1, three-dimensional route segment calculation airspace corresponding to route segments is divided based on the route segments in an air route GIS space model; s2, counting historical ADS-B data in hours according to a time sequence, collecting the historical ADS-B data in a three-dimensional leg calculation airspace, collecting ADS-B data in N2 days in the past of a research day in hours in the three-dimensional leg calculation airspace, and obtaining leg reference flow; s3, ADS-B data of the research area are collected, the number of aircrafts in a three-dimensional leg calculation airspace is calculated, and then a leg congestion index is obtained through calculation; and S4, taking the proportion of the leg distance of the research aircraft in the whole route distance as the weight of each leg, screening the leg congestion indexes of all the legs of the whole route of the research aircraft, and calculating to obtain the congestion index of the whole route of the research aircraft. According to the invention, the route segment congestion index and the route congestion index can be accurately quantified, and the route congestion condition can be measured and represented.

Description

Technical Field

[0001] The present invention relates to the field of airway congestion measurement, and particularly to a method and system for measuring an airway congestion index based on spatial analysis of airway sub-segments. Background Art

[0002] Civil aircraft also experience congestion in the airspace just like vehicles on the road. With the rapid development of the civil aviation industry, air traffic flow is constantly increasing, and the problem of airway congestion is becoming increasingly prominent. Especially during peak hours, the congestion problem is even more serious. In the existing research on airway congestion index in the civil aviation field, one method is to predict traffic flow based on flight plans. The flight plan of an aircraft is a flight route, and air traffic involves the flights of multiple aircraft. Estimating congestion according to flight plans has a large human factor and lacks flexibility. Another method is with the wide application of ADS-B (Automatic Dependent Surveillance - Broadcast) technology, estimating airway traffic flow through ADS-B data simulation and data statistics, generally using manual calculation methods. This method lacks consideration of factors such as the width and height of flight routes, and has large errors in data statistics, and cannot quantify the congestion conditions of airways and different positions on airways. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for measuring an airway congestion index based on spatial analysis of airway sub-segments, dividing airway segments with each intersection point of the airway as a segmentation point, calculating the airspace corresponding to the three-dimensional airway segment based on the segment division in the airway GIS spatial model, selecting the segment reference flow of each three-dimensional airway segment calculation airspace through the segment flow data set of N1-year historical flight data and N2-day historical flight data, classifying the real-time flight data of ADS-B data into segment congestion indexes, and obtaining the airway congestion index through segment weighting.

[0004] The purpose of the present invention is achieved through the following technical solutions:

[0005] A method for measuring an airway congestion index based on spatial analysis of airway sub-segments, the method comprising:

[0006] S1. Construct an airway GIS spatial model of the research area, divide all flight plan airways into several segments with the intersection points of the flight plan airways projected by all aircraft in the research area as segmentation points, and calculate the airspace i corresponding to the three-dimensional airway segment based on the segment division in the airway GIS spatial model;

[0007] S2. Collect the historical ADS-B data of all aircraft in the research area for N1 years of historical flights. The ADS-B data includes time, longitude and latitude positions, and elevation information. Aggregate the historical ADS-B data into the three-dimensional flight segment calculation airspace by hour count according to the time series to obtain the flight segment flow count set A aggregated by hour for N1 years. Take the ADS-B data of the historical flights in the past N2 days of the research day and aggregate it into the three-dimensional flight segment calculation airspace by hour count to obtain the flight segment flow count set B aggregated by hour for N2 days. Merge the flight segment flow count set A and the flight segment flow count set B and take the median or average of each hour as the flight segment baseline flow R of the three-dimensional flight segment calculation airspace i and hour m. im ;

[0008] S3. Collect the ADS-B data of the research area and calculate the aircraft quantity count Z of the three-dimensional flight segment calculation airspace i in the hour m before the research moment. im , and calculate the flight segment congestion index M of the three-dimensional flight segment calculation airspace i and hour m according to the following formula im ,

[0009] S4. Use the proportion of the flight segment distance of the research aircraft in the whole route distance as the weight W of each flight segment. im , screen the flight segment congestion indices of all flight segments of the whole route of the research aircraft, and calculate the predicted route congestion index C of the whole route of the research aircraft at the research moment according to the following formula im , P is the serial number of the flight segment in the route.

[0010] The present invention provides a second method for calculating the route congestion index. Compared with the first method for calculating the route congestion index, the difference lies in: in method S1, the three-dimensional flight segment calculation airspace i is subdivided into several altitude layers; in method S2, the flight segment baseline flow R of the three-dimensional flight segment calculation airspace i, altitude layer j, and hour m is obtained separately in the three-dimensional flight segment calculation airspace i by altitude layer. i，j，m ; in method S3, the flight segment baseline flow M of the three-dimensional flight segment calculation airspace i, altitude layer j, and hour m is obtained separately in the three-dimensional flight segment calculation airspace i by altitude layer. i，j，m , where Z i，j，m is to collect the ADS-B data of the research area and calculate the aircraft quantity count of the three-dimensional flight segment calculation airspace i, altitude layer j, and in the hour m before the research moment; in method S4, based on the flight plan route of the research aircraft, screen the flight segment congestion indices of the corresponding altitude layers of all flight segments of the whole route, and calculate the predicted route congestion index C of the whole route of the research aircraft at the research moment according to the following formula im ,

[0011] Preferably, the altitude levels of the three-dimensional flight segment calculation airspace i are divided according to the true course angle.

[0012] Preferably, the width of the three-dimensional flight segment calculation airspace i extends N3 kilometers to the left and right with the flight segment as the center.

[0013] Preferably, the method for calculating the route congestion index of the present invention further includes method S5:

[0014] S5. Obtain the route congestion indexes of all aircraft in the research area according to methods S1 to S4, and visually express them in the route GIS spatial model.

[0015] Preferably, the projection plane of the route GIS spatial model is the longitude and latitude plane, and the route congestion indexes of all aircraft are projected onto the projection plane of the route GIS spatial model for visual expression.

[0016] Preferably, the route congestion indexes of all aircraft routes in the research area are visually expressed according to flight segments, and the flight segment congestion indexes are represented by colors from green to red from low to high.

[0017] Preferably, in method S2, the value of N1 year is three years, and the collected historical ADS-B data is subjected to data denoising, cleaning, and removal of invalid data processing. The removal of invalid data includes the removal of outliers and duplicate values.

[0018] A system for calculating the route congestion index based on route sub-flight segment spatial analysis includes an ADS-B data collection module, a route GIS spatial model, a flight segment airspace division module, a flight segment baseline flow calculation module, and a route congestion index calculation module. The ADS-B data collection module is used to collect the historical ADS-B data of all aircraft in the research area for N1 years. The ADS-B data includes time, longitude and latitude position, and elevation information. The flight segment airspace division module divides all flight plan routes into several flight segments based on the intersection points of the projections of the flight plan routes of all aircraft in the research area as segmentation points, and divides the three-dimensional flight segment calculation airspace i corresponding to the flight segments in the route GIS spatial model. The flight segment baseline flow calculation module aggregates the historical ADS-B data by hour according to the time series in the three-dimensional flight segment calculation airspace to obtain the flight segment flow count set A aggregated by hour for N1 years. Take the ADS-B data of the historical flights in the past N2 days of the research day and aggregate it by hour in the three-dimensional flight segment calculation airspace to obtain the flight segment flow count set B aggregated by hour for N2 days. Integrate the flight segment flow count set A and the flight segment flow count set B and take the median or average of each hour as the flight segment baseline flow R of the three-dimensional flight segment calculation airspace i and hour m im; The ADS-B data acquisition module also collects the ADS-B data of the research area and inputs it into the route congestion index calculation module. The route congestion index calculation module is used to calculate the aircraft quantity count Z of the three-dimensional route calculation airspace i in the hour m before the research moment. im The segment congestion index M of the three-dimensional route calculation airspace i and hour m is calculated according to the following formula. im , The route congestion index calculation module uses the proportion of the segment distance of the research aircraft in the entire route distance as the weight W of each segment. im The segment congestion indices of all segments of the entire route of the research aircraft are screened, and the predicted route congestion index C of the entire route of the research aircraft at the research moment is calculated according to the following formula. im ,

[0019] Preferably, the route congestion index measurement system of the present invention further includes a visualization expression module, and the visualization expression module is used for visualization expression in the route GIS space model.

[0020] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0021] (1) In the present invention, each intersection point of the route is used as a segmentation point for segment division, and the corresponding three-dimensional route calculation airspace of the segment is based on the segment division in the route GIS space model. The segment benchmark flow of each three-dimensional route calculation airspace is selected through the segment flow data set of N1-year historical flight data and N2-day historical flight data. The real-time flight data of the collected ADS-B data is classified to calculate the segment congestion index of the three-dimensional route calculation airspace, and the route congestion index is obtained through segment weighting.

[0022] (2) The present invention can obtain the data of the air traffic network congestion index and perform visual display, and can accurately and timely reflect the changes in the air traffic congestion situation in the air traffic network. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a schematic flow chart of the method for measuring the route congestion index of the present invention;

[0024] Figure 2 is a schematic diagram of the altitude layer division shown in the embodiment;

[0025] Figure 3 is a schematic diagram of the vector conversion of the flight plan route data of all aircraft involved in a certain area in the research area and constructed in the route GIS space model;

[0026] Figure 4 is a schematic diagram of a certain planned route after segment division in the embodiment;

[0027] Figure 5 It is a schematic diagram of projecting the route congestion index in the embodiment onto the projection plane of the route GIS spatial model. Specific implementation manners

[0028] The present invention will be further described in detail below in conjunction with embodiments:

[0029] Embodiment 1

[0030] As Figure 1 shown, a method for calculating the route congestion index based on route sub-segment spatial analysis includes:

[0031] S1. Construct a route GIS spatial model of the research area, and divide all flight plan routes into several segments by using the intersection points of the projected flight plan routes of all aircraft in the research area as segmentation points (preferably, construct all flight plan routes of aircraft in the research area in the route GIS spatial model by using vectorized data. After the vectorized conversion of the flight plan route data, as Figure 3 shown). Taking the B208 flight plan route as an example, as Figure 4 shown, it is a schematic diagram of dividing segments by using route intersection points as segmentation points. Calculate the three-dimensional segment corresponding airspace i for the segment based on the segment division in the route GIS spatial model. The research area of this embodiment is selected according to the actual research situation, such as a certain civil aviation control area or several civil aviation control areas, and of course, it can also be a certain national area.

[0032] In some embodiments, the altitude layers of the three-dimensional segment calculation airspace i are divided according to the true course angle. The specific examples are as follows: As Figure 2 shown, the true course angle (in this embodiment, it is divided according to the course angles of the flight plan routes of all aircraft in the research area, and the course angle is measured from the route starting point and turning points) is in the range of 0 degrees to 179 degrees, the altitude ranges from 900 meters to 8100 meters, and each altitude layer is 600 meters apart; the altitude ranges from 8900 meters to 12500 meters, and each altitude layer is 600 meters apart; the altitude is above 12500 meters, and each altitude layer is 1200 meters apart. The true course angle is in the range of 180 degrees to 359 degrees, the altitude ranges from 600 meters to 8400 meters, and each altitude layer is 600 meters apart; the altitude ranges from 9200 meters to 12200 meters, and each altitude layer is 600 meters apart; the altitude is above 13100 meters, and each altitude layer is 1200 meters apart.

[0033] In some embodiments, the width of the three-dimensional segment calculation airspace i is N3 kilometers (for example, N3 kilometers is exemplified as 10 kilometers) extended left and right with the segment as the center.

[0034] S2. Collect the historical ADS-B data of all aircraft in the research area for N1 years of historical flights (in some embodiments, N1 is taken as three years. The collected historical ADS-B data is subjected to data denoising, cleaning, and removal of invalid data. Removing invalid data includes removing outliers and duplicate values to ensure the accuracy and reliability of the data.). The ADS-B data includes time, longitude and latitude position, and elevation information. The historical ADS-B data is counted and aggregated by hour (24 hours a day, aggregated by hour according to 24 hours a day, and calculated together within one hour; the traffic differences in different periods are large. In this embodiment, a detailed segmentation is adopted, and a day is divided into 24 hours, and the traffic value is calculated separately for each hour. In this way, each flight segment has a reference traffic for each hour) in the three-dimensional flight segment calculation airspace to obtain the flight segment traffic count set A aggregated by hour for N1 years. For example: If s is defined as the flight segment data set, y is the year, m is the month, d is the date, h is the hour, H is the altitude layer, and D is the flight segment direction, a flight segment traffic data set is established: Q(s, y, m, d, h, H, D). Q(s, y, m, d, h, H, D) represents the traffic value of flight segment s in the D direction of altitude layer H at hour h on day d of month m in year y. Construct a flight segment traffic function: R(s, h, H, D). R(s, h, H, D) represents the flight segment traffic of flight segment s at hour h. The data correspondence between the flight segment traffic function and the flight segment traffic data set is: R(s, h, H, D) = {Q(s, h, d, m, y, H, D).

[0035] Take the ADS-B data of historical flights in the past N2 days of the research day and count and aggregate it by hour in the three-dimensional flight segment calculation airspace to obtain the flight segment traffic count set B aggregated by hour for N2 days. The flight segment traffic count set A and the flight segment traffic count set B are fused, and the median or average value (the median is selected as an example in this embodiment) of each hour is taken as the flight segment reference traffic R of the three-dimensional flight segment calculation airspace i and hour m. im For example: N1 is taken as three years, N2 is taken as 10 days. Take the traffic data of the same month m, the same date d, and the same hour in the past three years y1, y2, y3 as follows:

[0036] q1 = Q(s, h, d, m, y1, H, D)

[0037] q1 = Q(s, h, d, m, y1, H, D)

[0038] q3 = Q(s, h, d, m, y3, H, D)

[0039] Take the traffic data of the same hour in the past 10 days as follows:

[0040] p n = {Q(s, h, d n , m, y, H, D)},

[0041] Then R(s, h, H, D) = {Q(s, h, d, m, y, H, D)} = [q1, q2, q3, p1, p2, p3... p 10 . In this embodiment, the median is taken as the baseline flow of the flight segment s in the D direction at the H altitude layer at time h:

[0042] Baseline(s, h, H, D) = Median(R(s, h, H, D)).

[0043] S3. Collect ADS-B data of the research area and calculate the aircraft quantity count Z of the three-dimensional flight segment calculation airspace i in the hour m before the research time im , and calculate the flight segment congestion index M of the three-dimensional flight segment calculation airspace i and hour m according to the following formula im , For example: the real-time flight segment flow is the number of aircraft z passing through in the 1-hour period before the current time h in the D direction of the H altitude layer of the flight segment s, A(s, h, H, D) = z. The flight segment congestion index M is the ratio of the real-time flight segment flow to the baseline flow of the flight segment. The congestion index of the flight segment s in the D direction of the H altitude layer is:

[0044] Weighted according to the flow proportion of each altitude layer and direction, calculate the flight segment congestion index as follows:

[0045]

[0046] The congestion index corresponding to the flight segment s is as follows:

[0047]

[0048] S4. Take the proportion of the flight segment distance of the research aircraft in the entire route distance as the weight W of each flight segment im , screen the flight segment congestion indexes of all flight segments of the entire route of the research aircraft, and calculate the predicted route congestion index C of the entire route of the research aircraft at the research time according to the following formula im , P is the serial number of the flight segment in the route.

[0049] S5. Obtain the route congestion indexes of all aircraft in the research area according to methods S1 to S4, and visually express them in the route GIS spatial model. In some embodiments, the projection plane of the route GIS spatial model (the projection plane is the longitude and latitude plane of the route GIS spatial model excluding elevation data) is the longitude and latitude plane, and the route congestion indexes of all aircraft are projected onto the projection plane of the route GIS spatial model for visual expression, such as Figure 5As shown, a schematic diagram of projecting the route congestion index of a study area onto the projection plane of the route GIS spatial model is shown. In some embodiments, all aircraft routes in the study area are visualized by segment congestion index according to the flight segment, and the segment congestion index is represented by colors from green to red from low to high.

[0050] Embodiment 2

[0051] A method for calculating route congestion index based on route segment spatial analysis, the method comprising:

[0052] S1. Construct a route GIS spatial model of the study area. Divide all flight plan routes into several segments based on the intersection of the flight plan route projections of all aircraft in the study area as the segmentation point. In the route GIS spatial model, divide the three-dimensional segment calculation airspace i corresponding to the segment based on the segment. The three-dimensional segment calculation airspace i is subdivided into several altitude layers. For example, the three-dimensional segment calculation airspace i includes J altitude layers, which are arranged in sequence from bottom to top, and altitude layer j is the jth altitude layer.

[0053] S2. Collect historical ADS-B data of N1 years of historical flight of all aircraft in the study area. ADS-B data includes time, latitude and longitude position and altitude information. Count the historical ADS-B data by hour in time series and aggregate them in the corresponding altitude layer of the three-dimensional segment calculation airspace to obtain the segment flow count set A aggregated by hour in N1 years; take the ADS-B data of historical flights of N2 days before the study date and count them by hour in the corresponding altitude layer of the three-dimensional segment calculation airspace to obtain the segment flow count set B aggregated by hour in N2 days, merge the segment flow count set A with the segment flow count set B and take out the median or average of each hour (the median is selected as an example in this embodiment) as the segment reference flow R of the three-dimensional segment calculation airspace i and hour m im In the three-dimensional flight segment calculation airspace i, the flight segment reference flow R of the three-dimensional flight segment calculation airspace i, altitude layer j, and hour m is obtained respectively. i，j，m .

[0054] S3. Collect ADS-B data in the study area and calculate the number of aircraft counts Z in the three-dimensional flight segment calculation airspace i one hour before the study time i，j，m , Z i，j，m To collect ADS-B data in the study area and calculate the number of aircraft in the three-dimensional segment calculation airspace i, altitude level j, and one hour m before the study time. The segment reference flow M of the three-dimensional segment calculation airspace i, altitude level j, and hour m is calculated according to the following formula i，j，m ,

[0055] S4. The proportion of the flight distance of the aircraft to the entire route distance is used as the weight of each flight segment Wim , screen the segment congestion indices of all segments of the entire route of the research aircraft, and calculate the predicted route congestion index C of the entire route of the research aircraft at the research moment according to the following formula im , P is the serial number of the segment in the route.

[0056] S5. Obtain the route congestion indices of all aircraft in the research area according to methods S1 to S5, and visually express them in the route GIS spatial model.

[0057] Embodiment 3

[0058] A route congestion index calculation system based on route segment spatial analysis includes an ADS-B data acquisition module, a route GIS spatial model, a segment airspace division module, a segment baseline flow calculation module, and a route congestion index calculation module. The ADS-B data acquisition module is used to collect the historical ADS-B data of all aircraft in the research area flying in the past N1 years. The ADS-B data includes time, longitude and latitude position, and elevation information. The segment airspace division module divides all flight plan routes into several segments based on the intersection points of the projections of the flight plan routes of all aircraft in the research area as segmentation points, and calculates the three-dimensional segment calculation airspace i corresponding to the segment based on the segment in the route GIS spatial model. The segment baseline flow calculation module aggregates the historical ADS-B data by hour according to the time series in the three-dimensional segment calculation airspace to obtain the segment flow count set A aggregated by hour in N1 years. Take the ADS-B data of the historical flights in the past N2 days of the research day and aggregate them by hour in the three-dimensional segment calculation airspace to obtain the segment flow count set B aggregated by hour in N2 days. Merge the segment flow count set A and the segment flow count set B and take the median or average of each hour as the segment baseline flow R of the three-dimensional segment calculation airspace i and hour m im . The ADS-B data acquisition module also collects the ADS-B data of the research area and inputs it into the route congestion index calculation module. The route congestion index calculation module is used to calculate the aircraft quantity count Z of the three-dimensional segment calculation airspace i in the hour m before the research moment im , and calculate the segment congestion index M of the three-dimensional segment calculation airspace i and hour m according to the following formula im , The route congestion index calculation module uses the ratio of the segment distance of the research aircraft to the entire route distance as the weight W of each segment im , screen the segment congestion indices of all segments of the entire route of the research aircraft, and calculate the predicted route congestion index C of the entire route of the research aircraft at the research moment according to the following formula im ,

[0059] The navigation route congestion index calculation system of the present invention further includes a visualization expression module, which is used for visualizing and expressing in the navigation route GIS spatial model.

[0060] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for calculating the airway congestion index based on the spatial analysis of airway sub-segments, characterized in that: The method includes: S1. Construct a route GIS spatial model of the research area, divide all flight plan routes into several segments with the intersection points of the flight plan route projections of all aircraft in the research area as the segmentation points, and calculate the three-dimensional segment corresponding airspace i based on the segments in the route GIS spatial model; S2. Collect the historical ADS-B data of all aircraft flying in the study area over N1 years. The ADS-B data includes time, longitude and latitude positions, and elevation information. Aggregate the historical ADS-B data by hour count in the three-dimensional flight segment calculation airspace to obtain the flight segment flow count set A aggregated by hour for N1 years. Take the ADS-B data of historical flights in the past N2 days on the study day and aggregate it by hour count in the three-dimensional flight segment calculation airspace to obtain the flight segment flow count set B aggregated by hour for N2 days. Merge the flight segment flow count set A and the flight segment flow count set B, and take the median or average of each hour as the flight segment baseline flow R for the three-dimensional flight segment calculation airspace i and hour m. im ; S3. Collect ADS-B data of the research area and calculate the aircraft quantity count Z of the three-dimensional flight segment calculation airspace i in the previous hour m before the research moment im , and calculate the flight segment congestion index M of the three-dimensional flight segment calculation airspace i and hour m according to the following formula im , S4. Take the proportion of the flight segment distance of the research aircraft in the entire airway distance as the weight W of each flight segment im , screen the flight segment congestion indexes of all flight segments of the entire airway of the research aircraft, and calculate the predicted airway congestion index C of the entire airway of the research aircraft at the research moment according to the following formula im , P is the serial number of the flight segment in the airway.

2. The method for calculating the airway congestion index based on the spatial analysis of airway sub-segments according to claim 1, wherein: In method S1, the three-dimensional flight segment calculation airspace i is subdivided into several altitude layers; in method S2, the flight segment reference flow R of the two-dimensional flight segment calculation airspace i, altitude layer j, and hour m is obtained respectively by altitude layer in the two-dimensional flight segment calculation airspace i i，j，m ; in method S3, the flight segment reference flow M of the three-dimensional flight segment calculation airspace i, altitude layer j, and hour m is obtained respectively by altitude layer in the three-dimensional flight segment calculation airspace i i，j，m , where Z i，j，m is the count of the number of aircraft in the three-dimensional flight segment calculation airspace i, altitude layer j, and the hour m before the research time obtained by collecting ADS-B data in the research area and calculating; in method S4, based on the flight plan route of the research aircraft, the flight segment congestion index of all flight segments corresponding to the altitude layer of the entire route is screened, and the predicted route congestion index C of the entire route of the research aircraft at the research time is calculated according to the following formula im , 3. The method for calculating the route congestion index based on the spatial analysis of route sub-segments according to claim 2, wherein: The altitude levels of the three-dimensional segment calculation airspace i are divided according to the true course angle.

4. The method for calculating the airway congestion index based on the spatial analysis of airway sub-segments according to claim 1 or 2, characterized in that: The width of the three-dimensional segment calculation airspace i is expanded N3 kilometers to the left and right with the segment as the center.

5. The method for calculating the airway congestion index based on the spatial analysis of airway sub-segments according to claim 1, wherein: It also includes method S5: S5. Obtain the route congestion indexes of all aircraft in the research area according to methods S1 to S4, and visually express them in the route GIS spatial model.

6. The method for calculating the airway congestion index based on the spatial analysis of airway sub-segments according to claim 5, characterized in that: The projection plane of the route GIS spatial model is the longitude and latitude plane, and the route congestion indexes of all aircraft are projected onto the projection plane of the route GIS spatial model for visual expression.

7. The method for calculating the airway congestion index based on the spatial analysis of airway sub-segments according to claim 5, wherein: The route congestion indexes of all aircraft routes in the research area are visually expressed according to segments, and the segment congestion indexes are represented by colors from green to red from low to high.

8. The method for calculating the airway congestion index based on the spatial analysis of airway sub-segments according to claim 1, wherein: In method S2, the value of N1 year is three years, and the collected historical ADS-B data is processed for data denoising, cleaning and removing invalid data. Removing invalid data includes removing outliers and duplicate values.

9. A route congestion index calculation system based on spatial analysis of route sub - segments, characterized in that: It includes an ADS-B data acquisition module, a route GIS spatial model, a flight segment airspace division module, a flight segment reference flow calculation module, and a route congestion index calculation module. The ADS-B data acquisition module is used to collect the historical ADS-B data of all aircraft in the research area for N1 years of historical flights. The ADS-B data includes time, longitude and latitude positions, and elevation information. The flight segment airspace division module divides all flight plan routes into several flight segments based on the intersection points of the projections of the flight plan routes of all aircraft in the research area as segmentation points, and calculates the three-dimensional flight segment calculation airspace i corresponding to the flight segment based on the flight segment in the route GIS spatial model. The flight segment reference flow calculation module aggregates the historical ADS-B data by hour count in the time series into the three-dimensional flight segment calculation airspace, and obtains the flight segment flow count set A aggregated by hour for N1 years. Take the ADS-B data of the historical flights in the past N2 days of the research day and aggregate it by hour count into the three-dimensional flight segment calculation airspace, and obtain the flight segment flow count set B aggregated by hour for N2 days. Fuse the flight segment flow count set A and the flight segment flow count set B and take the median or average of each hour as the flight segment reference flow R of the three-dimensional flight segment calculation airspace i and hour m. im The ADS-B data acquisition module also collects the ADS-B data of the research area and inputs it into the route congestion index calculation module. The route congestion index calculation module is used to calculate the aircraft quantity count Z of the three-dimensional flight segment calculation airspace i in the hour m before the research moment. im The route congestion index M of the three-dimensional flight segment calculation airspace i and hour m is calculated according to the following formula. im , The route congestion index calculation module uses the ratio of the flight segment distance of the research aircraft to the entire route distance as the weight W of each flight segment. im Screen the route congestion indexes of all flight segments of the entire route of the research aircraft, and calculate the predicted route congestion index C of the entire route of the research aircraft at the research moment according to the following formula. im , 10. The system for calculating the airway congestion index based on the spatial analysis of airway sub-segments according to claim 9, wherein: It also includes a visual expression module, which is used for visual expression in the route GIS spatial model.

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