CN112362060A

CN112362060A - Civil aviation flight route planning method

Info

Publication number: CN112362060A
Application number: CN202010889879.5A
Authority: CN
Inventors: 陈创希; 常先英; 赵明宇; 周兴; 吴东岳; 曾力舜; 张苗苗
Original assignee: China Southern Airlines Co Ltd
Current assignee: China Southern Airlines Co Ltd
Priority date: 2020-08-28
Filing date: 2020-08-28
Publication date: 2021-02-12
Anticipated expiration: 2040-08-28
Also published as: CN112362060B

Abstract

The invention discloses a civil aviation flight route planning method, which comprises the following steps: 1) loading waypoint and waypoint data on a horizontal plane, and filtering nodes and edges which do not meet navigation rules; 2) according to the optimization target, calculating the edge weight of each height layer at each navigation side; 3) selecting the minimum value of the weight values in all the height layers as the weight value of the route edge; 4) generating K horizontal shortest paths by using a KSP algorithm; 5) calculating the flight height of each navigation side on the K paths and the initial oil carrying quantity of the airplane, and finally selecting the optimal result from the K results as a final result according to an optimization target; and if the optimization target is the shortest distance, taking K as 1. The civil aviation flight route planning method based on the operational research optimization algorithm theory is constructed by taking the shortest distance, the most time-saving or the minimum oil consumption as the optimization target, and the civil aviation flight route planning method designed by the invention achieves the optimization target through verification, is reasonable in algorithm and can be used for planning the civil aviation flight route.

Description

Civil aviation flight route planning method

Technical Field

The invention relates to the technical field of civil aviation operation command and dispatch release.

Background

Route planning is one of the core technologies of a flight planning system. The flight planning system is a set of system adopted by an airline company for making computer flight plans, dispatching, releasing and the like of each flight, and aims to standardize operation management, improve working efficiency, control flight operation risks, save flight operation cost and increase operation benefits. The core functional modules of the flight plan system are the flight plan making, the air route planning and the like. The technical principle and the core algorithm of route planning are currently mainly handled by hansa systems in germany, sepbo in usa, jackson in usa, Navblue in france, and the like.

The Lido/Flight system of Hansa is an international advanced Flight planning system at present. Lido/Flight was developed in the early stage of the signing system within the Hansa airlines, and there are currently over 120 users in the world, including Dutch airlines, France airlines, British airlines, Canadian airlines, emilian headings (aircrafts), Singapore aircrafts, Hanyao aircrafts, UPS (United Package service), China aircrafts, Changrong aircrafts, and China south aviation. The main characteristics are that: the system has high integration and automation degree of functions and provides a real-time and reliable route optimization function, and the system can calculate the most oil-saving route, the most cost-saving route, the most time-saving route and the closest distance route according to relevant data such as operating conditions, airplane performance, weather and the like.

The Saybolt air Flight Plan Manager system was developed on the basis of the internal system (named Dispatch Manager) of American aviation (American aircines). The system has the main functions of realizing the calculation of the flight plan through computer statistics, cannot automatically calculate and optimize the legal available air route, and has relatively poor integration of system functions and data. In the Flight planning system of austria, FWZ, purchased in sabo in 2010, the systems of the two original companies were gradually integrated in sabo in recent years and renamed as air centre Flight Plan Manager. The new version system of Saibo purchased by the eastern China aviation is in the upgrading stage at present and is not formally on line. Currently, users of the Saybook system also include twenty more households, such as International aviation in China, JetBlue, United Airlines (United aircines), Indian aviation, Japan aviation, and dimensional aviation (Virgin Atlantic/Virgin Australia).

Jeppson's JetPlanner system can calculate the least costly route and, in combination with factors such as weather, calculate the available route. Small and medium-sized airlines such as marine navigation, deep navigation, Sichuan navigation and Shandong navigation in China all use Jetplanner to make flight plans.

The N-Flight Planning system of Navblue corporation was originally owned by Navtech, Canada, and Navblue was purchased from Navtech in 2016 and was gradually upgraded based on the product of its original Flight Planning system. At present, buildings use the system to make flight plans for intercontinental flights, and the optimized air route is supposed to be generated.

At home, at present, the aircraft is in the starting stage of the research and development of a flight planning system, and no company releases molded products. The aircraft performance calculation algorithm with independent intellectual property rights has professional global meteorological data, complete AIP and NAIP data and domestic airliner data, can be seamlessly accessed into an open external data interface of airborne navigation data, is convenient for the system to integrate the flight plan, and can carry out customized output, but has no airway optimization function module. In addition, medium air material navigation technology (beijing) ltd currently develops a function of calculating the closest distance air path, but cannot combine with a flight plan.

The above flight planning systems are available to airlines, but even if they are purchased, their routing algorithms remain confidential. As a result, airlines lack their own control over core technology and core services, and they incur expensive system maintenance costs each year. The research of the algorithms is helpful for the air company to control the core technology and the core business and break monopoly on one hand, and is helpful for optimizing the flight plan of the flight and reducing the operation cost on the other hand.

Disclosure of Invention

The invention aims to provide a civil aviation flight route planning method.

The invention aims to be realized by the following technical scheme: a civil aviation flight route planning method comprises the following steps:

1) loading waypoint and waypoint data on a horizontal plane, and filtering nodes and edges which do not meet navigation rules;

2) according to the optimization target, calculating the edge weight of each height layer at each navigation side;

3) selecting the minimum value of the weight values in all the height layers as the weight value of the route edge;

4) generating K horizontal shortest paths by using a KSP algorithm;

5) calculating the flight height of each navigation side on the K paths and the initial oil carrying quantity of the airplane, and finally selecting the optimal result from the K results as a final result according to an optimization target; and if the optimization target is the shortest distance, taking K as 1.

In the step 2), the optimization target is the shortest distance, the most time-saving or the least oil consumption; the step 2) is realized by the following specific steps:

height layer information of the edge is obtained through the airway data, and the weight of the edge is calculated layer by layer:

(1) if the optimization target is the shortest distance, the length of the edge to the ground is the weight of the edge; if the optimization target is the time saving or the oil consumption minimum, turning to the step (2);

(2) acquiring wind temperature, wind speed and course angle according to information on a navigation side;

(3) estimating the current weight of the airplane, wherein the estimated value of the weight of the airplane is the distance between the current edge and a landing airport and the average oil consumption of unit distance plus the landing weight;

(4) acquiring a corresponding Mach number in a performance table according to the estimated weight of the airplane, the current altitude and the wind temperature;

(5) then calculating the vacuum speed according to the Mach number and the air temperature;

(6) synthesizing the ground speed based on the vacuum speed, the wind speed and the course angle;

(7) if the optimization target is the most time-saving, the flight time weight of the airway edge is the airway edge distance/ground speed; if the optimization target is the minimum oil consumption, turning to (8);

(8) calculating oil consumption in unit time according to the current height layer, the wind temperature and the estimated weight of the airplane;

(9) and calculating the fuel consumption of the current height layer at the side of the navigation road, namely the fuel consumption weight value at the side of the navigation road is the flight time and the unit time fuel consumption.

Calculating the flying height of each navigation side on the K paths and the initial oil carrying amount of the airplane in the step 5), wherein the calculation comprises the calculation of the flying height and the oil consumption in the vertical direction, and the specific steps are as follows:

A1) estimating a takeoff weight, and initializing the takeoff weight into a known standard landing weight;

A2) determining TOC according to the takeoff weight, and calculating the flight time, horizontal distance, oil consumption and the like of the takeoff and climbing stages; determining TOD according to the standard floor weight;

A3) taking the next waypoint A of the TOC point as a starting point of cruise optimization, taking the previous waypoint E of the TOD as an end point of the cruise optimization, forming an optimization stage by two waypoints adjacent to each other in the cruise process, and performing cruise optimization from the point A one by one in sequence until the point E is finished;

A4) calculating the flight time, horizontal displacement, oil consumption and the like of the descending, approaching and landing stages according to the weight, the height and the like of the plane when the TOD descends;

A5) calculating the flight range oil, namely the flight range oil is the takeoff oil consumption, the climbing oil consumption, the cruising oil consumption, the descending oil consumption, the approach and landing oil consumption;

A6) calculating the weight of the airplane when landing, namely landing weight is the weight of the airplane which is the weight of the airplane during the landing process, namely the weight of the airplane during the landing process is the weight of the airplane during the landing process; comparing the calculated falling weight with the standard falling weight, and stopping iteration if the difference is not more than 20 kg; otherwise, iteration is repeated with another initial fly-by, turning to step A1.

The specific implementation process of the step A3) is as follows:

assuming that the next waypoint of the point A is B and the next waypoint of the point B is C, then:

(A31) constructing outgoing edges of the A-B stage, and calculating the weight of each outgoing edge A-Bi;

(A32) calculating the path with the minimum side weight value in the A-Bi stage;

(A33) constructing the outgoing edges of the B-C stage, and calculating the weight of each outgoing edge Bi-Cj;

(A34) calculating the minimum path of the side weight values of the A-Cj stages;

(A35) sequentially extending forwards until the cruise optimization end point E;

different values of i in the Bi represent a plurality of points which have the same horizontal coordinate as B and are positioned in different height layers;

different values of j in Cj represent points with horizontal coordinates C at different height levels.

The Bi is set as follows:

assume that the weight of the aircraft arriving at point A is m_AAccording to the mathematical relationship between the maximum flying height and the weight of the aircraft:

h_max＝f(m_A)

the flyable height h of the aircraft from the point a to the point B satisfies the following relationship:

h∈{h|h≤h_max}

and determining the height value of Bi by combining the height layer division of the air route.

The method comprises the following steps of (1) carrying out iterative calculation on the initial oil carrying amount of an airplane, namely flight oil + emergency oil + standby oil + waiting oil + extra oil, wherein the emergency oil is 10% of the flight oil, the waiting oil is calculated according to the weight and the waiting time of the airplane, the extra oil is a constant, and the initial oil carrying amount of the airplane is calculated according to the following steps:

(B1) making the voyage oil be 0, and then making the emergency oil be 10% and the voyage oil be 0;

(B2) calculating the flying height and the standby oil of the standby landing route based on the vertical direction flying height and oil consumption calculating step by taking the landing weight of the standby landing airport as the standard of the oil-free weight of the plane, the extra oil, the emergency oil and the standby oil to obtain the landing weight of the target airport as the landing weight of the standby landing airport and the standby oil;

(B3) judging whether the oil-free weight is within 20kg of the standard oil-free weight, if so, returning the result, otherwise, turning to (4);

(B4) calculating flight distance oil by taking the landing weight of the target airport as a reference through the step of calculating the flight height and the oil consumption in the vertical direction;

(B5) and (5) updating the emergency oil to 10% by flight oil, and returning to the iteration of the step (2).

Has the advantages that:

the civil aviation flight route planning method based on the operational research optimization algorithm theory is established, the shortest distance, the most time-saving or the least oil consumption are used as optimization targets, and verification proves that the civil aviation flight route planning method designed by the invention achieves the optimization target, is reasonable in algorithm and can be used for planning civil aviation flight routes.

Drawings

FIG. 1 is a schematic view of a drawn ellipse;

FIG. 2 is a diagram of the effect of the airway;

FIG. 3 is a schematic illustration of a current weight calculation for an aircraft;

FIG. 4 is a schematic illustration of aircraft cruise origin calculation;

FIG. 5 is a schematic diagram of a civil aviation flight process;

FIG. 6 is a schematic diagram of calculation of fly height and fuel consumption in the vertical direction 1;

FIG. 7 is a schematic diagram of calculation of altitude and fuel consumption in the vertical direction 2;

FIG. 8 is a flow chart of a civil aviation flight route planning algorithm.

Detailed Description

The embodiment provides a civil aviation flight route planning method realized through computer software, which can automatically adjust an optimization flow according to a selected optimization target (including shortest distance, most time saving and minimum oil consumption), and comprises the following specific steps:

step1: loading and processing data

And loading waypoint and waypoint edge data (which can be acquired from a waypoint map), and filtering nodes and edges which do not meet navigation rules. The navigation rules generally include no-fly, flight-restricted announcements, and the like.

In order to reduce the calculation scale, the ellipse is made by focusing on the departure and landing airports (when the aircraft makes a flight plan, not only the departure airport and the target airport need to be determined, but also a landing airport needs to be provided, as shown in fig. 5, so the departure and landing airports can be the departure airport and the target airport or the target airport and the landing airport), and only the route and the route side inside the ellipse are obtained. As shown in fig. 1, F1 (takeoff airport longitude and latitude coordinates) and F2 (landing airport longitude and latitude coordinates) are respectively two focuses of an ellipse, and the major axis AB of the ellipse is 2a, so as to avoid that the ellipse range is too small due to too short distance between the takeoff and landing airports (which often occurs from the target airport to the standby airport), and the minimum value of a is 250 nautical miles, that is: when the distance | F1F2| >250 nautical miles between two foci, a ═ F1-F2|, otherwise a ═ 250 nautical miles; if the starting point or the ending point of one route side falls within the ellipse, the route side is loaded, otherwise, the route side is not loaded, and the final effect is shown in fig. 2, route sides such as b1, b2, c1 and c2 are reserved, and c1-c5 are directly abandoned.

Step2: respectively calculating the edge weight of each height layer aiming at each navigation side

Height layer information of the edge is obtained through the airway data, and weight values of the edge (horizontal edges of different height layers) are calculated layer by layer:

(1) if the optimization target is the shortest distance, the length of the edge to the ground is the weight value of the edge. And (3) if the optimization target is the time saving or the oil consumption minimum, performing relevant calculation, and turning to the step (2).

(2) And acquiring the wind temperature, the wind speed and the course angle according to the information of the navigation side, such as longitude, latitude, altitude and the like. Specifically, an integral method is recommended to divide one edge into n small edges, the wind temperature and the wind speed of each small edge are obtained by a linear interpolation method according to weather data, and the course angle is an included angle between a connecting line of starting points and end points of the airway edges and the true north direction.

(3) The current weight of the aircraft is estimated, the estimated aircraft weight being the distance of the current edge from the landing airport (landing airport means target or alternate landing airport, where distance means horizontal distance, ignoring altitude) unit distance average fuel consumption (which may be an average calculated from aircraft performance data) + landing weight (input parameters, typically determined from airport runway constraints and empty weight versus traffic).

As shown in fig. 3, the weight of the aircraft at point M | MB |. unit distance average fuel consumption + weight to ground. | MB | represents the horizontal distance of the M position from the B position.

(4) And acquiring the corresponding Mach number in the performance table according to the estimated weight of the airplane, the current altitude and the wind temperature.

(5) And then calculating the vacuum speed according to the Mach number and the air temperature.

(6) And synthesizing the ground speed based on the vacuum speed, the wind speed and the course angle.

(7) If the optimization target is the most time-saving, the flight time weight of the airway edge is equal to the length of the airway edge/the ground speed. If the optimization target is the minimum oil consumption, the calculation is continued, and the operation is turned to (8).

(8) And (4) calculating the oil consumption per unit time (obtained from the airplane performance data by using a linear interpolation method) according to the current height layer, the wind temperature and the estimated weight of the airplane.

(9) And (4) calculating the fuel consumption of the current height layer at the navigation side, namely the fuel consumption weight at the navigation side is the flight time (namely the flight time weight at the navigation side in the step (7)) and the fuel consumption per unit time.

And step3: and selecting the minimum value of the weights in all the height layers as the weight of the route edge.

And 4, step4: generation of K horizontal shortest paths using KSP algorithm

And (3) outputting K shortest paths from the take-off airport to the target airport and from the target airport to the reserve airport based on a KSP algorithm according to the airway nodes and the edges loaded in the step (1) and the airway edge weights calculated in the step (1) and the corresponding nodes of the take-off airport, the target airport and the reserve airport in the airway graph.

And 5: and calculating the flight altitude of each navigation side on the K paths and the initial oil carrying capacity of the airplane, and finally selecting the optimal result from the K results as a final result according to the optimization target. The calculated initial oil pick-up is used for aircraft oil pick-up recommendations. And if the optimization target is the shortest distance, taking K as 1. The specific process of step 5 is as follows:

initial oil loading is voyage oil + emergency oil + slack oil + waiting oil + extra oil, emergency oil is 10% voyage oil, waiting oil is calculated according to the weight of the aircraft and the waiting time, extra oil is a constant and is input by a user and is generally determined according to company and local regulations. The weight of the airplane is the weight on the ground plus extra oil plus emergency oil, and the waiting time is input by a user and determined according to the regulations of companies and local parties. The aircraft manufacturer can give the fuel oil flow of the aircraft in unit time under the conditions of different heights, temperatures and weights, the fuel oil flow of the aircraft in unit time under any height, temperature and weight can be calculated according to a linear interpolation method, and the waiting oil can be obtained according to the waiting time and the fuel oil flow in unit time.

The initial oil carrying amount of the airplane is iteratively calculated according to the following steps:

(1) making the voyage oil be 0, and then making the emergency oil be 10% and the voyage oil be 0;

(2) taking the landing weight of the standby landing airport as the weight of the airplane without oil (the weight of the airplane plus the service load is a determined value) + extra oil + emergency oil + waiting oil as the standard, calling a vertical direction flight height and oil consumption calculation interface, and calculating the flight height and the standby landing oil of the standby landing route to obtain the landing weight of the target airport as the landing weight of the standby landing airport plus the standby landing oil;

(3) the airplane is heavy without oil, namely the target airport is heavy when landing, emergency oil, standby oil, waiting oil and extra oil. Judging whether the difference between the oil-free weight and the standard oil-free weight (the initial value of the standard oil-free weight is the weight of the airplane and the service load) is within 20kg, if so, returning the result, and otherwise, turning to (4);

(4) calling a vertical direction flight height and oil consumption calculation interface again, and calculating flight distance oil based on the landing weight of the target airport;

(5) and (5) updating the emergency oil to 10% by flight oil, and returning to the iteration of the step (2).

The steps of realizing the interface of the vertical direction flight height and oil consumption calculation are described as follows:

step 1): the takeoff weight is estimated and initialized to a known standard landing weight.

Step 2): determining TOC (cruise starting point) according to the takeoff weight, and calculating the flight time, horizontal distance, oil consumption and the like of the takeoff and climbing stages (an aircraft manufacturer can give a data table of the time, oil consumption and horizontal distance required by the aircraft to climb a certain height under different temperature and weight conditions, and the oil consumption, the time, the horizontal distance and the like required by the aircraft to climb to a certain height under any temperature and weight conditions can be calculated according to the data table by a linear interpolation and calculus method; TOD (cruise endpoint) is determined from the standard floor weight.

The TOC point calculation step is shown in FIG. 4:

step1, making the airplane initially fly to m0, obtaining the optimal flying height hm0 under the current weight, making htoc equal to hm0, and making htoc represent the height of the TOC point;

step2, calculating the weight m1 of the airplane when the airplane reaches the height htoc, and acquiring the optimal flying height hm1 corresponding to m1 (the airplane manufacturer can give the optimal flying height and the maximum flying height of the airplane under different temperature and weight conditions, and the optimal flying height of any weight can be calculated by using a linear interpolation method according to the table);

step3 if hm 1! Htoc, hm 1;

step4 step1-step3 are repeated until htoc is no longer changed.

The TOD point calculation procedure is similar to the TOC point, with TOC being a forward iteration and TOD being a reverse iteration.

Step 3): the next waypoint of the TOC point is taken as the starting point of the cruise optimization, corresponding to point a of fig. 6, and the last waypoint of the TOD is taken as the ending point of the cruise optimization, corresponding to point E of fig. 6. And forming an optimization stage by using adjacent waypoints in the cruise process, and sequentially carrying out cruise optimization stage by stage from the point A until the point E is finished. Based on a greedy strategy, a cruise optimization algorithm is designed as follows:

(1) constructing the Waypoint _ A → Waypoint _ B phase, calculating the weight of the side (the weight is the flight time, fuel consumption, etc., generally speaking, hereThe weight corresponds to the optimization target, and if the optimization target is the shortest distance, the weight can select flight time or oil consumption according to the deviation because the horizontal shortest distance is preferably selected in the front). From the cruise optimization start point (point a), all of its edges to the Waypoint _ B vertical profile node are constructed. Assume that the weight of the aircraft arriving at point A is m_A. According to the mathematical relationship between the maximum flying height and the weight of the airplane:

h_max＝f(m_A)

the flyable height h of the airplane from the point A to the Waypoint _ B satisfies the following relationship

h∈{h|h≤h_max}

In combination with the height level division of the airway (the basic road network data has fixed flyable height division for each airway segment), the finally calculated flyable heights are respectively assumed to be FL _1, FL _2, FL _3 and FL _4, and the vertical section nodes of Waypoint _ B are respectively defined as B₁、B₂、B₃、B₄Therefore, point A has 4 outgoing edges, which are respectively marked as AB₁、AB₂、AB₃、AB₄. As shown in fig. 6. And calculating the side weight (flight time, oil consumption and the like) according to the current weight, wind temperature, wind speed, Mach number and the like of the airplane.

(2) And calculating the shortest path from the A to each vertical section node of the Waypoint _ B. With B₁For example, compare A to B₁Weight of all paths (time, oil consumption). At this time, only A → B₁This path is retained as the shortest path. Other vertical section node (B)₂、B₃、B₄) This was done in the same manner.

(3) Constructing a Waypoint _ B → the Waypoint _ C phase edge, and calculating the flight time and the oil consumption of the edge. Referring to the step (1), respectively constructing B₁、B₂、B₃、B₄And calculating the edge weight (flight time, oil consumption and the like) of the edge. Suppose the vertical profile nodes of Waypoint _ C are respectively C₁、C₂、C₃、C₄As in fig. 7.

(4) And calculating the shortest path from the A to each vertical section node of the Waypoint _ C. With C₂For example, compare A to C₂The weight of all paths (time, oil consumption, etc.). All possible paths are 3: a → B₁→C₂、A→B₂→C₂、 A→B₃→C₂. Hypothesis is A → B₂→C₂If one of all paths with the shortest weight value is the shortest, other paths are removed, and the path is reserved as A to C₂The time of (2) is the most economical route. Other vertical section node (C)₂、C₃、C₄) The procedure was performed in the same manner.

(5) And then extend forward in sequence until the cruise optimization endpoint (point E).

Step 4): according to the weight, height and the like of the airplane during the TOD descent, the flight time, horizontal displacement, oil consumption and the like in the descending, approaching and landing stages are calculated (an airplane manufacturer can give a data table of the time, oil consumption and horizontal distance required by the airplane to descend at a certain altitude under different temperature and weight conditions, and the oil consumption, the time, the horizontal distance and the like required by the airplane to descend at a certain altitude under any temperature and weight conditions can be calculated through a linear interpolation and calculus method according to the data table).

Step 5): and (4) calculating the range oil, namely the range oil is equal to take-off oil consumption, climbing oil consumption, cruising oil consumption, descending oil consumption and approach and landing oil consumption.

Step 6): and (4) calculating the weight of the airplane when landing, namely landing weight is the weight of the aircraft, namely the weight of the airplane when landing is the weight of the aircraft. Comparing the calculated falling weight with the standard falling weight, and stopping iteration if the difference is not more than 20 kg; otherwise, repeating the iteration with another initial starting time, and turning to the step 1).

Fig. 8 is a flowchart of the civil aviation flight route planning method in the above embodiment, which shows the core concept of the algorithm, and the specific steps are as described above.

The following are the test data for KSFO _ ZHHHH

KSFO _ zhhhh represents a flight from san francisco to wuhan, and the data in table 1 are calculated results based on different optimization objectives, it can be seen that the ground distance of the shortest distance result is the smallest of the three results, indicating that the shortest distance optimization objective was achieved. Similarly, the time consumed by the time-saving optimization result is the minimum of the three times, and the voyage oil of the oil-saving optimization result is the minimum of the three times, so that the method achieves the optimization target.

TABLE 1

Optimizing an objective	Distance to ground	Time (min)	Voyage oil (kg)	Flying weight	Floor weight
						Shortest distance	5798.2	753.51	101701.28	330877	229176
Time is saved most	5840.46	736.24	100471.09	329334	228863
						Most fuel-saving	5840.46	739.62	99186.31	328044	228858

And (4) selecting oil consumption by the weight in the shortest distance optimization step in the table.

Control group:

the control group is calculated by lido, and the data is shown in table 2. The lido is a common flight plan calculation system at present, has reliability and can be used as a control group. It can be seen that the ground distance in the result of the shortest distance optimization of lido is consistent with the result of the method of the present invention (the result of lido output does not retain decimal, and rounding is performed), which indicates that the result of the shortest distance optimization path of the method of the present invention is correct. The other two optimization objectives are not significantly different. The difference between the time required by each optimization target and the flight oil is not too large, so that the calculation result of the algorithm is reasonable and acceptable.

TABLE 2

Optimizing an objective	Distance to ground	Time (min)	Voyage oil (kg)	Flying weight	Floor weight
						Shortest distance	5798	756	104285	333472	229187
Time is saved most	5840	740	101091	329957	228866
						Most fuel-saving	5852	741	100992	329848	228856

Claims

1. A civil aviation flight route planning method is characterized by comprising the following steps:

4) generating K horizontal shortest paths by using a KSP algorithm;

2. The civil aviation flight route planning method according to claim 1, wherein in step 2), the optimization objective is the shortest distance, the most time-saving or the least oil consumption; the step 2) is realized by the following specific steps:

(3) estimating the current weight of the airplane, wherein the estimated value of the weight of the airplane is the distance between the current edge and a landing airport and the average fuel consumption per unit distance plus the landing weight;

(9) and calculating the fuel consumption of the current height layer at the side of the navigation road, namely the fuel consumption weight value at the side of the navigation road is the flight time multiplied by the unit time fuel consumption.

3. The civil aviation flight route planning method according to claim 2, wherein the calculation of the flight height of each of the roadside on the K paths and the initial oil amount of the aircraft in step 5) includes vertical direction flight height and oil consumption calculation, and specifically includes the following steps:

A2) determining TOC according to the takeoff weight, and calculating the flight time, horizontal distance and oil consumption of the takeoff and climbing stages; determining TOD according to the standard floor weight;

A3) taking the next waypoint A of the TOC point as a starting point of cruise optimization, taking the previous waypoint E of the TOD as an end point of the cruise optimization, forming an optimization stage by two waypoints adjacent to each other in the cruise process, and sequentially carrying out cruise optimization stage by stage from the point A until the point E is finished;

A4) calculating the flight time, horizontal displacement and oil consumption of descending, approaching and landing stages according to the weight and height of the plane during the TOD descent;

A6) calculating the weight of the airplane when landing, namely landing weight is the weight of the airplane which is the weight of the airplane during the landing process, namely the weight of the airplane during the landing process is the weight of the airplane during the landing process; comparing the calculated floor weight with the standard floor weight, and stopping iteration if the difference is not more than 20 kg; otherwise, iteration is repeated with another initial flyover, proceeding to step a 1).

4. The civil aviation flight route planning method according to claim 3, wherein the specific implementation process of the step A3) is as follows:

5. The civil aviation flight path planning method according to claim 4, wherein Bi is set by:

h_max＝f(m_A)

h∈{h|h≤h_max}

6. The civil aviation flight path planning method according to claim 5, wherein the initial oil carrying capacity of the aircraft is voyage oil + emergency oil + standby oil + extra oil, the emergency oil is 10% voyage oil, the standby oil is calculated according to the weight of the aircraft and the standby time, the extra oil is constant, and the initial oil carrying capacity of the aircraft is calculated iteratively according to the following steps: