Airport scene operation simulation and evaluation software platform system

Abstract

The invention discloses an airport scene operation simulation and evaluation software platform system which comprises a tool layer subsystem, an application layer subsystem and a user layer subsystem and supports user requests. The user layer receives system configuration information and a decision request input by a user, and transmits the system configuration information and the decision request to the application layer through a multivariate data interface of the tool layer. And the application layer triggers automatic establishment of a simulation scene and other application modules according to a user request, calls a modular simulation component and an index model library in the tool layer for implementation, and finally feeds back an analogue simulation process and an analysis result to the user layer for visualization and analysis result display. The modular simulation assembly automatically constructs an airport scene operation simulation model based on a discrete event simulation modeling method and a modular technology, and simulates aircraft sliding according to user requirements. According to the system, airport scene simulation is efficiently realized, the airport operation condition is scientifically evaluated, comprehensive scene reproduction and prediction analysis are provided for airport management operation, and the safety and efficiency of decision making are remarkably improved.

Description

Technical Field

[0001] The invention belongs to the field of airport surface operation simulation, and in particular relates to an airport surface operation simulation and evaluation software platform system. Background Art

[0002] With the booming global aviation industry, airports are expanding in size and traffic volume, and the variety of aircraft types is also increasing. The resulting conflicts pose significant challenges to the management of aircraft operations on the airport surface. Traditional airport ground operations management relies primarily on manual scheduling and command. However, with the increasing flight density and diverse aircraft types at airports, manual scheduling is no longer sufficient to meet the requirements for operational efficiency and safety. Therefore, the use of advanced simulation technology to simulate and optimize aircraft operations on the airport surface has become a new solution. Through simulation technology, we can better understand the problems existing in airport operations, design reasonable operations management plans, and verify the feasibility and effectiveness of these plans through simulation experiments, thereby improving the safety and efficiency of aircraft operations on the airport surface.

[0003] Airport surface operations simulation uses computer technology to construct airfield ground operations scenarios. Under specific operating rules, it simulates flight ground operations and takeoff and landing processes to evaluate the operational efficiency of each subsystem within the airfield and its overall performance. For example, this can include analyzing the operational efficiency of taxiway and apron systems, or analyzing flight delay levels, taxi times, takeoff and landing clearance efficiency, and airport ground operations capacity at existing airports.

[0004] Currently, domestic and international research focuses on two main approaches to airport surface operations simulation. One is to establish a simulation model describing the airfield ground system based on certain theories and use the model to calculate various indicators. The other is to use existing simulation software (such as TAAM software developed in Australia, AIRTOP software developed in Belgium, and SIMMOD software developed in the United States) to simulate the airfield ground operation process using the software's functions, thereby conducting operational efficiency analysis and evaluating various performance indicators.

[0005] However, the increasingly complex surface operation environment presents significant challenges for airport operations. Uncertain factors such as extreme weather, emergencies, and flight delays make describing and constructing airport surface operation simulation models extremely difficult. Furthermore, my country is still in the process of promoting and applying applicable airport surface operation simulation technology and is heavily reliant on commercially available software from abroad.

[0006] In summary, the existing achievements have laid a good foundation for airport surface simulation technology and surface capacity assessment technology, but the following research gaps still exist:

[0007] (1) Under high-density flight and passenger traffic, uncertainty factors such as extreme weather, emergencies, and aircraft operations interact, overlap, and propagate with each other, making the scene operation process more complicated and difficult to predict future operation trends, which brings huge challenges to scene operation simulation.

[0008] (2) Existing capacity assessment technologies take influencing factors as static inputs. Considering the differences in aircraft stand types and the impact of dynamic factors, studying the dynamic capacity measurement of airport surfaces is crucial for the expansion and renovation of airport aircraft stands and the improvement of surface operation efficiency.

[0009] (3) Considering that the capacity assessment method involves the integration of multivariate and complex data in the temporal and spatial dimensions, no research has yet proposed an integrated method for dynamic capacity assessment and prediction methods with system simulation technology, making it difficult to implement. Summary of the Invention

[0010] To address the aforementioned problems in the prior art, the present invention provides an airport surface operation simulation and evaluation software platform system. The technical problems to be solved by the present invention are achieved through the following technical solutions:

[0011] An airport surface operation simulation and evaluation software platform system includes: a tool layer subsystem, an application layer subsystem and a user layer subsystem; wherein,

[0012] The tool layer subsystem is used to respond to the simulation modeling and statistical analysis requirements of the application layer subsystem and provide a multivariate data interface between the various subsystems. The simulation modeling constructs an airport scene and an airport scene operation simulation model by calling modular simulation components, simulating the operation process of aircraft at the airport scene when arriving or departing, and obtaining simulation calculation results. The modular simulation components are constructed based on discrete event simulation modeling methods and modular technology, and include runway modules, taxiway modules, apron modules, connecting road modules and generator modules required for the airport scene, as well as an aircraft taxiing path search algorithm. The simulation calculation results include the position and status of each aircraft at each time point. The statistical analysis is achieved by calling the indicator model library of the tool layer subsystem to count and calculate key performance indicators during the simulation process.

[0013] The application layer subsystem is configured to call the modular simulation components, multivariate data interface, and indicator model library of the tool layer subsystem based on the data input by the user layer subsystem to build an airport scene, trigger simulation and statistical analysis based on user requests from the user layer subsystem, perform simulation calculations and capacity assessments on the user requests, output analysis results, and feed them back to the user layer subsystem;

[0014] The user layer subsystem is used to receive system configuration information and user requests input by users and send them to the application layer subsystem; wherein, the system configuration information includes airport surface configuration information and system simulation configuration information, and the user request includes multiple indicator analyses including airfield design scheme comparison, airfield dynamic capacity assessment, and high-frequency bottleneck points; the user layer subsystem is also used to receive the simulation calculation and capacity assessment results output by the application layer subsystem in response to the user request, and to perform visual display.

[0015] This embodiment of the present invention proposes an airport surface operation simulation and assessment software platform system, aiming to address the existing difficulty in coping with complex airport operating environments while filling gaps in simulation and capacity assessment technologies. Based on discrete event simulation modeling and modularization technology, the platform independently developed a high-precision, flexible, and universal airport surface operation simulation model. This model enables efficient simulation and scenario rehearsal of airport surface operations in complex and uncertain environments. It also evaluates airport surface operations based on simulations, providing a reliable scientific basis for layout design and operational decision-making for airport expansion, new construction, and existing scenarios. The platform also integrates various user requests, such as airfield design scheme comparison, dynamic capacity assessment, and high-frequency bottleneck analysis. By leveraging actual airport operational data and dynamic influencing factors, it implements dynamic capacity assessment and aircraft stand capacity demand forecasting, further improving airport operational efficiency and resource optimization. The system can restore historical airport operational scenarios and simulate and evaluate airport surface operations based on historical flight data. Furthermore, by continuously recording aircraft positions and status during simulations, it supports the assessment of key airport surface performance and optimizes resource allocation.

[0016] In addition, the present invention integrates the airport scene operation mechanism and multi-dimensional heterogeneous data, designs a data interaction interface that integrates scene operation simulation technology and dynamic capacity assessment methods, and realizes the automatic conversion and efficient collaborative analysis between scene parameters and evaluation indicators. It not only solves the technical bottlenecks of traditional simulation software in data integration and evaluation, but also significantly improves the responsiveness to user needs and application flexibility. Based on this, the system of the present invention is developed using a browser / server architecture, which has good versatility, openness and scalability, and provides users with visual display and multi-level decision support functions. In summary, the present invention not only breaks through the limitations of existing technologies and provides important support for the intelligent and digital development of airport operations, but also will play an important role in promoting the optimization of domestic airport operation efficiency and technological progress, and has significant social and economic value. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A relationship diagram of the research contents of an embodiment of the present invention;

[0018] Figure 2 A technical roadmap for an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of the airport system;

[0020] Figure 4 This is a schematic diagram showing how the entire aircraft operation process at an airport is divided into five modules using a .NET-based discrete event simulation framework according to an embodiment of the present invention;

[0021] Figure 5a This is a schematic diagram of the airport;

[0022] Figure 5b This is a brief schematic diagram of the airport plan;

[0023] Figure 6 Flowchart of a glide path search algorithm according to an embodiment of the present invention;

[0024] Figure 7 Schematic diagram of three types of conflicts that may be encountered by an aircraft during taxiing according to an embodiment of the present invention;

[0025] Figure 8 A schematic diagram of taxiing conflict resolution using Xiamen Gaoqi International Airport as an example in an embodiment of the present invention;

[0026] Figure 9 This is a modular event diagram using the arrival module and runway module as examples in an embodiment of the present invention;

[0027] Figure 10 The result of comparing the estimated take-off time of the aircraft obtained by the simulation model with the actual planned take-off time and the actual take-off time according to the embodiment of the present invention;

[0028] Figure 11 is the airport delay level under the actual airport slot allocation strategy;

[0029] Figure 12 Output analysis results of airport delays under the landing priority strategy according to an embodiment of the present invention;

[0030] Figure 13 Output analysis results of airport delays under the takeoff priority strategy according to an embodiment of the present invention;

[0031] Figures 14a to 14c Comparison of delay levels under three slot allocation strategies;

[0032] Figure 15 This is a schematic diagram of the architecture of an airport surface operation simulation and evaluation software platform system provided by an embodiment of the present invention;

[0033] Figure 16A schematic diagram of the working principle of the airport surface operation simulation and evaluation software platform system provided by an embodiment of the present invention;

[0034] Figure 17 This is an analysis of the simulation results of the waiting time for incoming flights according to an embodiment of the present invention;

[0035] Figure 18 This is an analysis of simulation results for waiting time of departing flights according to an embodiment of the present invention;

[0036] Figure 19 The following is an analysis and comparison of simulation results of the waiting time for arriving and departing flights according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The present invention will be further described in detail below with reference to specific examples, but the embodiments of the present invention are not limited thereto.

[0038] In order to cope with the increasingly complex airport surface operation environment, effectively evaluate the surface operation capacity and improve the operation efficiency, and explore the bottleneck factors that restrict the surface operation system, the present invention focuses on the two key technologies of airport surface operation simulation and capacity assessment to carry out research. The research content consists of three parts: First, carry out environmental analysis, build and verify the airport surface operation simulation model, collect and analyze various input parameters required for the simulation model design, and perform modular design based on discrete event simulation technology and verify the effectiveness of the model; secondly, evaluate the efficiency and capacity of the surface operation, identify the key factors affecting the surface capacity and design a dynamic capacity assessment method; finally, design a diversified data conversion interface to integrate the simulation model, operation efficiency and capacity assessment method. On this basis, a decision support platform is developed to realize an airport surface operation simulation and assessment software platform system to support the application of surface operation situation preview, dynamic capacity assessment and prediction and other functions, and complete the testing of the platform system. The research content of the present invention is as follows: Figure 1 shown.

[0039] This paper takes statistics and operations research as its theoretical foundation, and designs corresponding research plans based on the massive actual operation data of airports, and comprehensively applies case analysis, regression analysis, system simulation and algorithm design methods and technologies. The overall technical route is as follows: Figure 2 shown.

[0040] Specifically, based on simulation modeling and capacity assessment related to airport surfaces, this paper analyzes the shortcomings of existing research through a literature review. Furthermore, through field research at airports with different configurations and operating modes, this paper identifies research questions that meet practical needs. This invention then designs corresponding technical routes for the three sub-technical solutions.

[0041] (1) Technical Solution 1: Airport surface operation environment analysis. Technical Solution 1 is based on my country's civil aviation operation specifications and relevant regulations and existing operation data to identify static scene elements of the airport surface, sort out relevant operation rules, and identify random factors. Based on this, the various types of data collected are fitted with parameters and the data format is determined through probability distribution fitting, regression analysis and other technologies.

[0042] Specifically, before simulation design, it is necessary to clarify the static scene input parameters, random factors and system operation rules involved in the simulation system, that is, environmental analysis.

[0043] against Figure 2 Regarding the identification of layout elements in 1.1 and the identification of uncertain factors in 1.2, the present invention conducts field research on airports of different configurations and operating modes, refers to the airport operation guidelines and relevant regulations, analyzes the surface operation characteristics of different types of airports, clarifies the key parameters of layout elements such as runways, taxiways, and aprons, and identifies and organizes various uncertain factors in the surface operation process, including flight delays, aircraft taxiing time, extreme weather (such as hail, thunderstorms, heavy fog, sandstorms), and emergencies (such as runway incursions, aircraft failures, and fires), so as to further collect key surface operation data and analyze the patterns.

[0044] Regarding static scene parameter information within an airport, airports of different configurations have different layout characteristics, and different types of aircraft have different attribute configurations. An airport runway is an extremely long, narrow area within an airport where aircraft take off or land. There are three typical basic runway configurations at large airports: parallel runways, intersecting runways, and open "V" runways. For single-runway airports, cross-stack scheduling of takeoff and landing aircraft must be considered. Multi-runway airports typically have separate runways for takeoff and landing, requiring further consideration of the specific runway selection. Taxiways are complex road networks that can be broken down into multiple sections. After determining the runway and parking position for an aircraft, corresponding taxiing paths must be quickly planned to avoid conflicts between aircraft. Furthermore, taxiways are crucial areas for flights entering and exiting parking positions, and their smooth operation is directly related to the efficiency of airport ground operations. Parking stands are divided into close stands and far stands. Far stands require more towing costs. The setting of the stands needs to consider the aircraft type category, such as B, C, D, E and F. Usually, they can be backward compatible with one aircraft model. The stand attributes are also divided into international, domestic, cargo, business, etc.

[0045] Identifying random factors primarily involves delays caused by factors such as traffic control, inclement weather, airline adjustments, late arrivals of previous flights, and passenger delays. Furthermore, due to differences in pilot operating habits, aircraft taxi speeds can vary even within the same area. This serves as a significant uncertainty factor guiding aircraft movement within high-precision airport surface operations simulation models.

[0046] Regarding 1.3 Surface operation rules and 1.4 Data collection and statistics, generally speaking, the airport surface system operation rules include two parts, namely flight arrival and departure.

[0047] In reality, when a flight arrives at an airport, it first selects an appropriate runway for landing based on the airport's runway layout. The runway system ensures the flight lands safely and as planned. After landing, the aircraft exits the runway via the connecting runway system and enters the taxiway connected to its target parking position. The aircraft then taxis along the planned taxiway to the designated parking position, completing the arrival process. During this process, the airport dispatches and manages the flight path and parking position in real time based on information such as the flight's scheduled arrival time, actual arrival time, and target parking position.

[0048] Departures follow the reverse process of arrivals. Flights first select a taxiway and taxi to the departure holding point, where they queue for takeoff clearance. Depending on runway availability, the flight then proceeds to the appropriate takeoff runway and takes off. The departure process is also strictly monitored based on scheduled and actual departure times to ensure every flight completes its takeoff on time.

[0049] As air traffic increases, airports face increasingly complex tasks. Especially with high-density flight traffic, managing the movement of each flight across various subsystems (such as runways, taxiways, and parking stands) becomes particularly important. Efficiently scheduling and managing these limited resources to ensure efficient and safe flight flow becomes crucial.

[0050] To address this issue, a software platform for simulating and evaluating airport surface operations has emerged. This system simulates key airport infrastructure, including runway layouts, taxiway layouts, and aircraft stand layouts. Combined with actual flight operational data, such as flight number, aircraft type, planned arrival time, and actual arrival time, it provides real-time feedback on flight arrivals and departures. This system accurately records and calculates each flight's target stand, planned off-block time, planned takeoff time, and actual takeoff time. By assessing the airport surface operations, it provides decision support for airport managers and helps optimize flight scheduling and ground resource utilization.

[0051] In this way, scheduling based on this system can help managers reduce resource conflicts between subsystems under high-density flight traffic, and improve safety and operational efficiency.

[0052] This paper analyzes the current status of airport surface operations through case analysis and literature review. Based on civil aviation operation specifications and actual operation data, it sorts out the detailed processes of flight arrival and departure and establishes the interaction mode between various subsystems. Then, under the operation guidelines and regulations, corresponding operation strategies are designed to control the operation processes within and between different subsystems, such as first-come, first-served and emergency flight priority. In addition, technical means such as probability distribution fitting and regression analysis are used to conduct detailed operation analysis of the airport surface and parameter fitting of relevant random factors.

[0053] Based on this, this paper uses Xiamen Gaoqi Airport as an example for simulation modeling, selecting a single lane as the runway and conducting detailed modeling of the actual runway, taxiway, and apron structure at Gaoqi Airport. The relevant modeling logic will be further explained below.

[0054] (2) Technical Solution 2: Airport Surface Operation Simulation Modeling and Verification: Based on discrete event simulation and other technologies, an airport surface operation simulation model is constructed, and the effectiveness of the simulation model is tested using steady-state analysis and sensitivity analysis methods.

[0055] Specifically, to improve airport operational efficiency and safety, this paper aims to establish a comprehensive airport surface operations simulation model. This model covers all aspects of airport surface operations. Through precise modeling and validation, it aims to identify bottlenecks that restrict surface aircraft stand capacity and operational capabilities, thereby improving airport operational efficiency.

[0056] against Figure 2 2.1 Scheduling Strategy Design: To ensure smooth and efficient aircraft taxiing from the runway to the parking bay, this paper studies aircraft scheduling strategies on the ground, including aircraft taxi path search strategies, aircraft anti-collision scheduling strategies, and parking bay allocation strategies. These scheduling strategies will be described in detail later.

[0057] against Figure 2 2.2 System Simulation Model Design, after sorting out the elements and operation rules existing in the discrete system, the present invention designs the simulation model of the system, and divides the airport surface system into three subsystems: runway, taxiway and apron, such as Figure 3As shown. Each subsystem represents a key part of airport operations, with different functions and operating characteristics. The runway subsystem is mainly responsible for the takeoff and landing of aircraft, requiring efficient traffic management and strict safety measures. The taxiway subsystem connects the runway and the apron, and is responsible for the ground taxiing of aircraft, requiring precise path planning and conflict avoidance. The apron subsystem is used for aircraft docking and ground services, and must take into account aircraft parking allocation and resource optimization. During the simulation model design process, the functions and operating rules of these subsystems need to be integrated into an overall system to accurately simulate the actual airport operations, and to evaluate the efficiency and reliability of the system through simulation data.

[0058] This invention considers discrete event operations such as aircraft takeoff, landing, taxiing, and docking. Therefore, it employs discrete event simulation to simulate and evaluate aircraft operations on the airport surface. Modeling is performed using a .NET-based discrete event simulation framework, whose event-driven core accurately simulates the system's structure and behavior. This invention modularizes each subsystem and its internal events. Because aircraft arrivals require additional data processing and the queueing order for entering and exiting the airport follows specific rules, the aircraft arrival and queuing systems are separated. Combined with the three aforementioned subsystems, the entire airport surface is divided into multiple modules.

[0059] Specifically, in the embodiment of the present invention, the design process of the airport surface operation simulation model includes:

[0060] The airport surface system is divided into runway subsystem, taxiway subsystem and apron subsystem;

[0061] Based on the logical associations among the runway subsystem, the taxiway subsystem, and the apron subsystem and their internal events, a discrete event simulation modeling method is used to divide the aircraft's operation process on the airport surface into five modules, including a generator module, a runway module, a connecting road module, a taxiway module, and an apron module. For each of the five modules, corresponding classes are created in the program. Class definitions and interactions between classes are represented using modular event graphs. The simulation in each module is triggered by discrete events. The taxiway module and the connecting road module form the airport's surface taxiway path network, into which an aircraft taxiway path search algorithm and an aircraft anti-collision scheduling strategy are embedded to determine the aircraft's taxiway path and target parking position, thereby completing the construction of the airport surface operation simulation model.

[0062] Verify the validity of the airport surface operation simulation model and feed it back to the application layer subsystem after passing the verification.

[0063] The process of constructing the airport's surface taxi path network includes:

[0064] defining control points in the surface taxi path network;

[0065] Define paths in the surface taxi path network. When defining a path, only control points that can be reached from the current control point are considered. Corresponding control points are connected to form a path to avoid path duplication. Furthermore, a Boolean property is added to the path class to indicate the path direction, thereby distinguishing between landing and takeoff taxi path networks.

[0066] Specifically, the generator module generates approaching aircraft using pre-processed data. These aircraft then enter the runway module's queue system, wait, and upon receiving instructions, enter the runway system. They then glide onto the apron according to the corresponding taxi path and arrive at their assigned parking position. An overall framework is constructed based on the logical event relationships between the various subsystems. Simulations within each module are still triggered by discrete events, which are further modularized to facilitate the driving and transfer of events.

[0067] The above five modules are as follows Figure 4 As shown in the figure. For example, upon arrival, an aircraft will first land on the runway, then proceed from the runway to the taxiway, and finally taxi to a pre-designated parking stand. For example, during a takeoff, an aircraft will request departure from the parking stand, then proceed from the stand to the taxiway, then taxi to the runway for the takeoff aircraft, and finally take off from the runway. Airport regulations require that both takeoff and landing aircraft be directed in the same direction.

[0068] In the simulation model, the aircraft is written as a class, which contains attributes such as flight number, parking position, aircraft type, operation type (takeoff or landing), whether it is an overnight stop, taxi speed, required taxiway capacity, and a list of taxi paths.

[0069] A path network (surface taxiway network) is also a class, with attributes including path start point, path end point, path capacity, remaining capacity, path length, path direction, path availability, path congestion, and path type. The path network is constructed by connecting each control point in the airport, each representing an inflection point in the airport surface. In this application, the availability of runways, connecting roads, and taxiways refers to whether the capacity of these paths can meet aircraft requirements.

[0070] Specifically, the present invention uses a discrete event simulation framework based on .Net to build an airport taxi path network and perform path search. The road network consists of control points and paths. First, a set is created to store all control points, and then the paths between the control points are gradually added to the path set, and the overall taxi path network is gradually built. In this process, the present invention only focuses on other control points that can be reached from the current control point to avoid repeated addition of paths. In order to ensure the directionality of the path, a Boolean attribute is added to the path class to indicate the direction of the path. The taxi paths for landing and takeoff are distinguished by different Boolean values.

[0071] Take Xiamen Gaoqi International Airport as an example to construct the airport's taxiway network. Please refer to Figure 5a and Figure 5b Understand. Among them, Figure 5a This is the floor plan of Xiamen Gaoqi International Airport. Figure 5b A simple schematic diagram of the road network is provided to facilitate understanding.

[0072] Assume that all aircraft land in the direction indicated by the arrows in the diagram. This taxiway network consists of control points and directed paths. Civil aviation regulations require aircraft to maintain a consistent orientation when taking off and landing on the same runway. Assuming all aircraft land in the direction shown, the available exit taxiways are A6, A7, A8, A9, and A10; aircraft must enter the runway using connecting taxiways A1, A2, or A3.

[0073] When building a network, if an incoming aircraft chooses to taxi off runway A7 after landing, upon reaching control point A7_1, it can choose either A7_2 or A7_3. In this way, control points are gradually connected via different paths, ultimately completing the entire taxi path network. When defining paths, only the control points reachable from the current control point are considered, and these are connected, thus avoiding path duplication.

[0074] On the basis of the road network being constructed, the aircraft taxiing path search algorithm and the aircraft anti-collision scheduling strategy in the embodiment of the present invention are respectively described below.

[0075] 1. Aircraft glide path search strategy

[0076] Aircraft taxi path search aims to establish an efficient and safe taxi path for the aircraft, ensuring smooth movement from the parking stand to the runway or vice versa. This process not only considers the length of the path, but also ensures its safety and feasibility.

[0077] The aircraft taxi path search strategy is implemented based on an aircraft taxi path search algorithm and taxi path constraints. The aircraft taxi path search algorithm uses a static path search algorithm to find the optimal taxi path with the shortest path length based on a constructed surface taxi path network, given the known aircraft taxi start and end points. The taxi path constraints are aircraft-specific and include: the time interval between preceding and succeeding aircraft using the same runway must be greater than the wake turbulence interval, and different taxiways have corresponding wingspan restrictions.

[0078] In real-world airports, aircraft routing is subject to various constraints. First, as mentioned above, the time interval between consecutive aircraft using the same runway must be greater than the wake turbulence separation, which depends on the aircraft type. Second, different taxiways have different wingspan restrictions, which are also closely related to the aircraft type. The Airport Operations Manual provides detailed regulations on taxiway wingspan restrictions and taxi routing for various aircraft types. Please refer to Table 1 for details.

[0079] Table 1 Examples of restrictions on aircraft wingspan due to taxiways

[0080] taxiway Aircraft Station Restrictions T3,T5,T6,T14 ≤65 meters T4 ≤61 meters T2,T7 ≤38 meters T8-T10,T12,T13,T15-T18 ≤36 meters

[0081] Therefore, when searching for a path, it is first necessary to eliminate the glide path that does not meet the wingspan limit according to the aircraft model to ensure that the aircraft does not collide with other objects during the glide process.

[0082] Specifically, the taxi path search algorithm of the present invention is based on a constructed airport ground network and, given the known taxi start and end points, searches for the optimal taxi path. The optimal path generally refers to the path that minimizes taxi time while meeting safety and regulatory requirements.

[0083] For the glide path search algorithm of the embodiment of the present invention, please refer to Figure 6 As shown, the algorithm is used to find the optimal taxi path from a known aircraft taxi start point to a known destination based on a constructed airport surface network (surface taxi path network). The algorithm recursively traverses all possible taxi paths by progressively searching for adjacent control points near the start point until all feasible paths are found. The shortest path is then selected as the optimal path based on its length. This algorithm simultaneously considers path capacity, direction, and taxi demand, ensuring that the search results meet the actual needs of aircraft taxiing, thereby improving airport surface operation efficiency.

[0084] 2. Aircraft anti-collision scheduling strategy

[0085] The aircraft anti-collision scheduling strategy designed in this paper aims to ensure the safety and efficiency of multiple aircraft during taxiing by identifying and resolving potential conflicts within the surface taxi path network. This strategy constructs a surface taxi path network, defines conflict paths, and incorporates a dynamic judgment mechanism to prevent conflicts and optimize scheduling during taxiing.

[0086] a. Definition and application of wake separation

[0087] Wake separation is one of the important constraints in the scheduling strategy, which is used to ensure that the impact of the wake vortex generated by the leading aircraft on the following aircraft can be dissipated or minimized. The wake separation refers to the minimum time or distance interval required for the wake vortex generated by the leading aircraft to affect the following aircraft. The wake vortex is an air disturbance caused by the lift generated by the aircraft's wings during flight. Its intensity is closely related to the aircraft's weight, wingspan and flight speed. The setting of the wake separation is intended to avoid instability or loss of control of the following aircraft due to entering the wake area of ​​the leading aircraft.

[0088] In the present invention, wake separation is defined as an important constraint in the taxiing path scheduling and operation process. Specifically, in the field taxiing path network or field operation simulation, the aircraft must meet the minimum requirements of wake separation during takeoff, landing and taxiing, that is, to ensure that the subsequent aircraft can enter the same path or area only when the influence of the wake vortex of the preceding aircraft dissipates or the distance is safe enough. The size of the interval time or distance depends on the wake intensity level of the preceding aircraft (such as light, medium or heavy aircraft) and the anti-wake capability of the following aircraft. The wake separation standard is set with reference to the wake requirements of different aircraft models in Tables 2 and 3 to ensure safety.

[0089] Table 2 Wake turbulence separation standards for the same runway (takeoff)

[0090]

[0091] Table 3 Wake turbulence separation standards for the same runway (landing)

[0092]

[0093] b. Identification of multiple conflict types

[0094] In an embodiment of the present invention, the aircraft anti-collision scheduling strategy is based on multiple types of conflicts preset during the taxiing process, and defines conflict paths in a constructed scene taxiing path network; the multiple types of conflicts include intersection conflicts, same-direction conflicts, and opposite-direction conflicts.

[0095] The above implementation process includes:

[0096] The aircraft anti-collision scheduling strategy is based on the various types of conflicts and defines multiple attributes including conflict paths, path capacity, and minimum time interval in the constructed scene taxiing path network. When the aircraft is taxiing, its taxiing path is judged according to the aircraft taxiing path search algorithm to determine the conflict path, and then decide in advance whether the aircraft should wait to prevent conflicts.

[0097] Specifically, in the surface taxi path network, the aircraft may encounter the following three main types of conflicts, see Figure 7 :

[0098] Intersection conflict: Two or more aircraft request to use a taxiway intersection at the same time, and two or more aircraft meet at the taxiway intersection;

[0099] Same-direction conflict: Two or more aircraft request the same taxi segment at the same time, and the taxiing interval does not meet the minimum safety interval standard. That is, the taxiing path and direction of the two or more aircraft are the same;

[0100] Head-on conflict: If two aircraft are expected to arrive at the same taxiway at the same or similar time, and the two aircraft are taxiing in opposite directions, a head-on conflict will occur.

[0101] In this invention, a conflicting path refers to a path that intersects, competes for resources, or conflicts with the target path. By defining conflicting paths in the surface taxi path network, the aircraft can determine in real time whether the current path status meets the taxiing requirements during taxiing. The judgment process includes the following key checks:

[0102] Is the path capacity sufficient? Check whether the remaining capacity of the current path can meet the taxiing requirements of the aircraft.

[0103] Whether the conflicting path is occupied: Check whether the target path and its conflicting path are occupied by other aircraft.

[0104] Whether the minimum time interval is met: Determine whether the target path and the conflicting path meet the wake interval requirements.

[0105] Specifically, when both the target path and the conflicting path are available, the aircraft is allowed to enter the target path; otherwise, the aircraft needs to wait at the current control point until the conditions are met before taxiing. Figure 8 As shown in the model of Xiamen Gaoqi International Airport, the taxi paths from B7 to B7_1 and from A7_3 to B7_1 are conflicting paths. If an aircraft enters the path from A7_3 to B7_1, the path from B7 to B7_1 will be marked as unavailable, and the subsequent aircraft will need to wait at the B7 control point.

[0106] Furthermore, the wingspan restrictions for different glide paths need to be verified based on the aircraft type. For example, aircraft with larger wingspans will be excluded from glide paths that do not meet the wingspan requirements to ensure the rationality and safety of path selection.

[0107] This scheduling strategy is reflected in the taxiway module simulation, and the scheduling logic is specifically expressed through pseudocode. During the simulation, the aircraft determines the path availability in real time and dynamically adjusts the taxiing decision according to preset rules. For example, when an aircraft enters a taxiing path, the path and its conflicting paths will be marked as unavailable. When the aircraft reaches the end of the current path and waits to enter the next path, the conflicting path of the current path will be automatically released and marked as available. The simulation combines the dynamic status of the scene taxiing path network (path capacity, conflicting paths, time intervals, etc.) for real-time judgment and dynamic scheduling.

[0108] Through this dynamic decision-making mechanism, the anti-collision scheduling strategy of the present invention effectively ensures the safety and smoothness of aircraft taxiing, takeoff, and landing, improving the efficiency and stability of airport operations. It also provides a reliable technical foundation for further optimizing airport scheduling and operations.

[0109] 3. Aircraft allocation strategy

[0110] Slot allocation is the process of assigning a set of known flight activities to a set of available slots, while meeting various airport operational requirements. The goal is to improve metrics such as bridge landing rate and proximity slot utilization. Slot allocation strategies involve allocating taxi paths and parking slots to different aircraft, optimizing the use of airport resources. This process requires balancing taxi time, taxi distance, and fuel consumption to ensure that aircraft needs and priorities are met while also improving overall operational efficiency and safety.

[0111] In actual airport operations, flight stand scheduling is influenced by many factors, including the Civil Aviation Administration's requirements for guaranteed docking rates, the number of airport flight towing crews, and the rules governing the operation of flights between adjacent stands. Therefore, when allocating stands, it's important to comprehensively consider both actual needs and limitations to avoid conflicts during flight operations.

[0112] In an embodiment of the present invention, the stand allocation strategy adopts a heuristic algorithm to minimize the cost of flight stand usage and is implemented using a preset algorithm strategy. The stand allocation strategy includes landing priority and takeoff priority; wherein the preset algorithm strategy includes a genetic algorithm and a greedy strategy.

[0113] The present invention takes the perspective of airlines and, based on information such as the daily flight estimated landing time, estimated departure time, and airport stand distribution, adopts a heuristic algorithm to minimize the flight stand usage cost and flight towing cost, and provides an efficient stand allocation solution.

[0114] By designing the aforementioned aircraft taxi path search strategy and anti-collision scheduling strategy, the present invention effectively addresses the path selection and conflict issues faced by aircraft taxiing on the airport surface. Based on these scheduling strategies, the present invention constructs a comprehensive airport surface operation simulation model using discrete event simulation technology.

[0115] This simulation model takes the airport surface system as the research object and divides the airport operation into multiple subsystems through a modular modeling method, covering the entire process of aircraft operation from arrival at the runway to taxiing, parking, and takeoff. By embedding the scheduling strategy into the simulation model, the present invention can dynamically simulate complex surface operation scenarios, verify the actual effect of the scheduling strategy, and evaluate the airport operation efficiency and bottleneck factors. Next, the module design and key implementation of the simulation model in the embodiment of the present invention will be described in detail. As mentioned above, the simulation model is mainly divided into five modules:

[0116] ① Generator module: The generator generates arrival events according to the pre-set event time. At this time, the aircraft will send an entry request to the runway. After receiving the request, the runway will begin to determine whether it can accept the aircraft to land.

[0117] ② Runway Module: Most airports typically have only one runway for takeoff and landing. Xiamen Gaoqi Airport, simulated in this case, also has only one runway. Therefore, when a runway receives a request for use from an aircraft, its first task is to determine whether the request is from an aircraft preparing to take off or landing, as the subsequent processing procedures for these two types of aircraft differ.

[0118] Next, taking the landing event as an example, the simulation logic of the runway module is introduced.

[0119] After the runway receives the landing request of aircraft A, it will first determine the type of the aircraft. If aircraft A is landing, the system will evaluate the required wake separation time t_need and the actual separation time t_bet between the current two aircraft based on the type of the previous aircraft B using the runway and the type of the requesting aircraft A. If the runway is idle and the separation time between the two aircraft is greater than the required wake separation time, i.e., t_bet > t_need, then aircraft A is allowed to land on the runway. If the runway is occupied, aircraft A needs to be put into the waiting queue and wait for the runway to be idle; if the wake separation time does not meet the requirements, i.e., t_bet < t_need, then aircraft A needs to wait until the wake separation time meets the standard and then resend the request to enter the runway.

[0120] After the runway module allows aircraft A to land, aircraft A starts to complete the landing process according to the randomly generated landing time t_land based on the relevant distribution. After aircraft A completes the landing, it will initiate a request to enter the taxiway, which is the next module (for the landing event). If aircraft A is allowed to enter by the taxiway module, the runway will be released immediately. If there are other aircraft in the waiting queue of the runway requesting to use the runway at this time, the system will call the runway module again to handle the new request.

[0121] This process ensures the efficiency and safety of runway use and reflects the complexity of real airport operations. In summary, to implement the simulation events of the runway part, the runway module of the present invention example mainly consists of a function F1 responsible for requests, a function F2 responsible for the start of events, a function F3 responsible for the end of events, and a function F4 responsible for recording the departure of aircraft from the runway. The connection relationship between the functions is as Figure 4 shown.

[0122] The control points are each inflection point of the airport surface. In this article, the idle states of the runway, taxiway, and apron referred to are that the path capacities of the runway, taxiway, and apron meet the capacities of the aircraft.

[0123] For the landing event, the pseudocode of the runway module is as follows:

[0124] <0OO0300>

[0125]

[0126] The overall function call logic between the modules is as Figure 9 , in the present invention example, the modules are connected by being triggered by something. The event that actively triggers other events can be regarded as a key, and the event that is passively triggered can be regarded as a lock. Whenever the lock event is triggered, it will automatically unlock the event of another module.

[0127] To clearly describe the meaning of the symbols in the picture, they can be explained as follows:

[0128] Blue lines represent the logical connections between the runway module and external modules when executing a landing event. This means that when external factors (a generator module requesting a landing event) prompt an aircraft to request a landing, these triggering conditions are communicated to the runway module via the blue lines.

[0129] Yellow lines: represent the logical connection between the runway module and external modules when running the takeoff event. For example, RequestToStart is the communication between the runway module and the runway module to send a request for the aircraft to use the runway for takeoff.

[0130] Circles: Indicates that the runway module is receiving a trigger from an external module. Whether it's a landing or takeoff event, when the runway module receives a request or instruction from an external system, this interaction is represented by a circle symbol. This indicates that the runway module is responding to the external trigger and has begun processing the corresponding aircraft takeoff or landing request.

[0131] Semicircular Arcs: These represent events within the Runway module that trigger events in external modules. For example, after a successful landing, the Runway module sends a request to the Connector module to leave the runway. These actions, initiated from within the Runway module and affecting external modules, are represented by semicircular arcs.

[0132] Tilde: Indicates that corresponding conditional judgment is required when triggering an event.

[0133] Equal sign: The opposite of the tilde sign, indicating that no conditional judgment is required when triggering the event.

[0134] The English modules on the connecting line indicate that the functions and modules are triggered to transmit information. P stands for aircraft and tw stands for path.

[0135] In this way, the symbols in the diagram systematically demonstrate how the runway module interacts with the external environment and other airport systems, and the role it plays in handling aircraft landing and takeoff. This visual representation helps understand the complexity of runway management and the logical relationship between the various steps.

[0136] ③ Connector Module: The airport's connecting road is the road that aircraft must pass through to enter the taxiway from the runway. For airports, the connecting roads used by landing aircraft and takeoff aircraft are generally different.

[0137] Taking the landing event as an example, the internal logic of the contact channel module is introduced.

[0138] When aircraft A on a runway completes landing and issues an entry request to the runway module, the system first checks which runways are currently available. If all runways are occupied, aircraft A will pause on the runway and be added to the runway landing event waiting list until a free runway becomes available. If a runway is available, the system evaluates the required wake turbulence separation time based on the type of aircraft B that previously passed through the runway and the type of aircraft A entering the runway. If the time interval between the two aircraft meets safety criteria, the runway is marked as available. Once an available runway is confirmed, the system selects the nearest available runway to allow aircraft A to enter the taxiway. The selected runway entrance closes, and a message is sent to the runway module indicating that the aircraft has begun entering the runway. Simultaneously, the system randomly generates a time t2 to simulate the aircraft's taxiing time on the runway, taking into account the cold time t_cold caused by whether the aircraft previously stopped (if not, t_cold is 0). Ultimately, the total time t3 spent by the aircraft on the runway and taxiway is calculated. During this period, the system starts from the end of the runway and uses the aircraft's own parking space information as the end point to retrieve the shortest feasible taxiing path, excluding routes that are inaccessible due to the aircraft's large wingspan. After time t3, the aircraft arrives at the end of the runway and initiates an entry request to the taxiway. If the taxiway module approves entry, the runway module will check whether the waiting queue is empty. If not, it will continue to process the next aircraft's request to enter the runway. Throughout the entire process, the runway module mainly implements the above logic through four functions: F5 (request processing), F6 (event start), F7 (event end), and F8 (recording aircraft leaving the runway), ensuring the safety and efficiency of airport surface operations. In summary, the runway mainly includes four functions: F5 for request processing, F6 for event start, F7 for event end, and F8 for recording aircraft leaving the runway.

[0139] Taking the landing event as an example, the pseudo code of the contact channel module is as follows:

[0140]

[0141]

[0142] ④ Taxiway Module: Taxiways are a key component of the airport's ground transportation network, responsible for guiding aircraft from access roads to parking stands and vice versa. This section details the taxiway module's operational logic when handling landing events.

[0143] When an aircraft completes taxiing on a taxiway and reaches its destination, Exit_end_CP, it transmits its information and the location of the taxiway's destination to the taxiway module. Upon receiving the request and information, the taxiway module first checks whether the current node, Exit_end_CP, is the aircraft's destination, End_CP. If so, the aircraft initiates a request to enter the parking stand. Otherwise, the aircraft's information is written to the PendingListByCP of the Exit_end_CP control point.

[0144] For a non-empty waiting queue, _PendingListByCP, the system prioritizes the first aircraft in the queue, aircraft A. For aircraft A, the system first determines whether its next path, NextPath_1, is available and meets the wake turbulence separation requirements. If the path is not occupied and the wake turbulence separation requirements are met, the aircraft is allowed to begin entering NextPath_1. Otherwise, the aircraft remains in place until the requirements are met, then initiates a taxiway entry request.

[0145] Once the aircraft is allowed to enter the taxiway, it will notify the connecting path module that it has left and remove its information from _PendingListByCP. Then it will officially enter the taxiway. After the aircraft enters the taxiway, the connecting path module will update the occupancy status of the NextPath_1 path and its conflicting paths to occupied (true). The time t4 for the aircraft to taxi along NextPath_1 is calculated by dividing the path length by the taxiing speed. Taking into account the possible cold start time t_cold (that is, the delay caused by the aircraft staying on the previous path), the total taxiing time t5 of the aircraft on NextPath_1 is equal to t4 plus t_cold. After time t5, the aircraft arrives at the end of NextPath_1. At this time, the system adds the information of aircraft A to the departure request queue OutPendingList of the current path and sends a request to leave the path NextPath_1.

[0146] After receiving a departure path request, the taxiway module begins processing the departure path event. It first checks whether the OutPendingList queue for the current path, NextPath_1, is empty. If it is, aircraft A, which issued the earliest departure request, is selected based on the first-come, first-served (FCFS) principle. The system then verifies whether the next path, NextPath_2, for aircraft A exists. If not, aircraft A has reached the end of the taxiway, and will then send a request to the apron module to enter the parking position.

[0147] If NextPath_2 exists, the system checks whether the path is free. If NextPath_2 is occupied, aircraft A will wait at the end point of NextPath_1 and add its information to the request of NextPath_2 into the waiting list InPendingList. At the same time, in order to avoid deadlock, the occupancy status of path Path_3, which is in conflict with NextPath_1, will be set to unoccupied (False). If NextPath_2 is not occupied, the system will further confirm whether the time interval between aircraft A and the last aircraft B passing through NextPath_2 meets the wake interval requirements. When the conditions are met, the occupancy status of NextPath_1 and its related conflicting paths will be updated to unoccupied, and the departure from path NextPath_1 and entry into path NextPath_2 will be triggered; otherwise, aircraft A needs to wait until the wake interval conditions are met before initiating the request again.

[0148] After Aircraft A enters NextPath_2, its glide time t6 is calculated based on the path length and glide speed. Taking into account the cold start time t_cold, the total glide time t7 on NextPath_2 is equal to t6 plus t_cold. Upon reaching the end of NextPath_2, Aircraft A sends a request to leave NextPath_2, and the module repeats the above process.

[0149] Additionally, whenever an aircraft leaves a path, such as NextPath_1, and prepares to enter the next path, NextPath_2, the taxiway module evaluates the start node of NextPath_1 and its conflicting paths, ControlPoint_Start. If this node is a connecting road or apron, the module processes ControlPoint_Start's pending queue, PendingListByCP, repeating the above process to ensure that subsequent aircraft can enter smoothly.

[0150] In summary, the taxiway module has six main functions: AttemptToEnter, Enter, Arrive, Complete, AttemptToDepart, and Depart. The module pseudo code is as follows:

[0151]

[0152]

[0153]

[0154] ⑤ Apron Module: Real-world aprons are equipped with numerous parking bays to meet the needs of aviation operations. When aircraft A requests access to a specific parking bay T, the system's Apron Management Module first checks whether the bay is occupied. If bay T is available, the system authorizes aircraft A to enter and notifies the Taxiway Management Module to confirm that the aircraft has been transferred from the taxiway to the designated bay.

[0155] For aircraft that do not stay overnight at the airport—that is, those scheduled to depart before the end of the simulation day—the apron management module automatically triggers the aircraft's takeoff process after the scheduled departure time t6. This process ensures that the aircraft can complete all ground operations, from landing to takeoff, in an orderly manner.

[0156] To handle landing events, the apron management module features a pair of key functions: F9 and F10. F1, the request handler, responds to and processes aircraft requests to enter a parking stand; while F2, the taxi-into-stand function, guides the aircraft safely and accurately into its designated position. The collaborative work of these two functions ensures that all landing aircraft can complete the ground parking process efficiently and safely.

[0157] The following is the pseudo code for the landing event portion of the apron module.

[0158]

[0159] against Figure 2 The simulation verification in 2.3 is to input the flight data of actual known flights as input data into the airport surface operation simulation model, compare the predicted data output by the model with the input data, and test the effectiveness of the simulation from the perspective of different selected indicator parameters, and use steady-state analysis and sensitivity analysis to measure whether the model performance meets the requirements. In an embodiment of the present invention, actual data can be input into the model to trigger related discrete events, and then simulated data can be generated and compared with the actual data to verify the model performance of the airport surface operation simulation model. Specifically, verifying the effectiveness of the airport surface operation simulation model includes:

[0160] ① Using flight data of actual known flights as input data, running the airport scene operation simulation model, and outputting simulation deduction data;

[0161] The airport surface operation simulation model is trained based on the airport data and historical flight data of the target airport; the target airport refers to the airport to be analyzed and processed.

[0162] ② For selected indicator parameters, compare the simulation data with the input data, and verify whether the effectiveness of the airport surface operation simulation model meets the requirements based on the comparison results, wherein the selected indicator parameters include aircraft simulated landing time, take-off time, taxi-into the apron time, and push-out from the apron time. Of course, the selected indicator parameters are not limited to the above.

[0163] The table below shows some of the results of the airport surface operation simulation model. It clearly shows the time when each aircraft executes each discrete event, that is, the time axis.

[0164] Table 4 Partial operation results of the airport surface operation simulation model

[0165] time event 0001 / 1 / 1 11:07:28 #MF8576 flight enters route A63-B630 0001 / 1 / 1 11:07:44 #FM9536 flight needs to enter the next path B2_1-B2_2 0001 / 1 / 1 11:07:44 #FM9536 flight departs B3_1-B21 0001 / 1 / 1 11:07:44 #FM9536 flight enters path B2_1-B2_20 0001 / 1 / 1 11:07:44 #FM9536 flight enters contact road A2 0001 / 1 / 1 11:07:48 #SC2226 flight needs to enter the next route B12-B113 0001 / 1 / 1 11:07:48 #SC2226 flight departs A10-B12 0001 / 1 / 1 11:07:48 #SC2226 Flight access path B12-B11-30 0001 / 1 / 1 11:08:20 #SC2226 flight needs to enter the next route B11-3-T17 0001 / 1 / 1 11:08:20 #SC2226 flight departs from B12-B113 0001 / 1 / 1 11:08:20 #SC2226 flight access path B113-T170 0001 / 1 / 1 11:08:29 #MF8576 flight needs to enter the next path B6_3-B5_1 0001 / 1 / 1 11:08:29 #MF8576 flight departs A6_3-B63 0001 / 1 / 111:08:29 #MF8576 flight enters route B63-B510 0001 / 1 / 1 11:08:38 #SC2226 flight needs to enter the next path T17-225 0001 / 1 / 1 11:08:38 #SC2226 flight departs B113-T17 0001 / 1 / 1 11:08:38 #SC2226 flight access path T17-2250 0001 / 1 / 1 11:08:39 Runway is occupied, #FM9536 waiting for Runway 1 0001 / 1 / 1 11:09:03 Flight #SC2172 enters exit taxiway A100 0001 / 1 / 1 11:09:03 #SC2172 flight ends runway taxiing 0001 / 1 / 1 11:09:03 Considering wake turbulence separation, #FM9536 is waiting for the runway 0001 / 1 / 1 11:09:36 #SC2226 flight entered parking position 225, total time spent 00:09:36.6054715 number of inbound flights 26 0001 / 1 / 1 11:09:57 #SC2172 flight preparing to enter taxiway 0001 / 1 / 1 11:09:57 #A10 free 0001 / 1 / 1 11:09:57 #SC2172 Flight access route A10-B120 0001 / 1 / 1 11:10:00 Considering wake turbulence separation, #MF8341 is waiting for the runway 0001 / 1 / 1 11:10:03 #MF8341 flight begins landing 0001 / 1 / 1 11:10:03 Runway is occupied, #FM9536 waiting for runway 1 0001 / 1 / 111:10:05 #MF8576 flight needs to enter the next path B5_1-B5 0001 / 1 / 1 11:10:05 #MF8576 flight departs B63-B51

[0166] The following is an exemplary description of the simulation model verification.

[0167] The embodiment of the present invention compares the estimated take-off time of the aircraft obtained by the simulation model with the actual planned take-off time and the actual take-off time to verify whether the model is effective and feasible. Figure 10 It can be seen that the time obtained by the model is slightly different from the actual time, which shows that the simulation model is effective.

[0168] In order to analyze the output of the simulation model, the embodiment of the present invention also conducts simulation evaluation on different slot allocation strategies. Figures 11 to 14a 、 Figure 14b 、 Figure 14c Understand the pictures.

[0169] 1) Landing priority

[0170] Landing priority means that when allocating parking spaces for incoming flights, the apron area closer to the runway exit is given priority. The output analysis results of airport delays under the landing priority strategy can be found in Figure 12 's various figures;

[0171] 2) Takeoff priority

[0172] Takeoff priority means that when allocating parking spaces for incoming flights, priority is given to parking spaces closer to the runway threshold. The output analysis results of airport delays under the takeoff priority strategy can be found in Figure 13 's various figures;

[0173] 3) Comparison of airport delay levels under different slot allocation strategies. See the results. Figures 14a to 14c In each figure, the upper and lower parts correspond to arrivals and departures respectively.

[0174] Taking the landing priority strategy as an example, it can be seen from the figure that compared with the actual data, the cycle time and waiting time of arriving aircraft are reduced, while the time of departing aircraft is increased.

[0175] The overall delay situation at the airport surface shows that departure delays are particularly significant under the landing-first strategy. This is because arriving aircraft are scheduled to park at stands closer to the runway exit, which reduces the travel time from the exit to the stand. Consequently, these stands are further from the runway threshold, which can lead to increased congestion on the airport ground during departures and longer delays. The opposite is true for the takeoff strategy. Based on this, an evaluation system can be established to comprehensively evaluate different strategies and select the optimal one.

[0176] (3) Technical Solution 3: Research on Capacity Assessment Methods and Platform Development. Research Content 3 identifies the key factors that affect the operating capacity of airport surfaces, and based on dynamic capacity assessment methods and operational efficiency assessment indicators, evaluates the developed simulation model, adjusts design parameters, and compares the scheduling strategies involved to improve the capacity of airport surface operations. Next, the development of the airport surface capacity assessment platform is carried out. The platform development part aims to promote the implementation and transformation of research results, and provide feasible and executable solutions for improving the capacity and operational efficiency of existing and designed airport surfaces. This invention takes a certain actual airport surface as the research object, and verifies and preliminarily applies the designed simulation model and dynamic capacity assessment method.

[0177] Based on the above research, the embodiment of the present invention provides an airport surface operation simulation and evaluation software platform system, such as Figure 15 As shown, the software platform system can include tool layer subsystem, application layer subsystem and user layer subsystem; its working principle can be seen in Figure 16 Understanding, among others,

[0178] The tool layer subsystem is used to respond to the simulation modeling and statistical analysis requirements of the application layer subsystem and provide a multivariate data interface between the various subsystems. The simulation modeling constructs an airport scene and an airport scene operation simulation model by calling modular simulation components, simulating the operation process of aircraft at the airport scene when arriving or departing, and obtaining simulation calculation results. The modular simulation components are constructed based on discrete event simulation modeling methods and modular technology, and include runway modules, taxiway modules, apron modules, connecting road modules and generator modules required for the airport scene, as well as an aircraft taxiing path search algorithm. The simulation calculation results include the position and status of each aircraft at each time point. The statistical analysis is achieved by calling the indicator model library of the tool layer subsystem to count and calculate key performance indicators during the simulation process.

[0179] The application layer subsystem is configured to call the modular simulation components, multivariate data interface, and indicator model library of the tool layer subsystem based on the data input by the user layer subsystem to build an airport scene, trigger simulation and statistical analysis based on user requests from the user layer subsystem, perform simulation calculations and capacity assessments on the user requests, output analysis results, and feed them back to the user layer subsystem;

[0180] The user layer subsystem is used to receive system configuration information and user requests input by users and send them to the application layer subsystem; wherein, the system configuration information includes airport surface configuration information and system simulation configuration information, and the user request includes a multi-index analysis including airfield design scheme comparison, airfield dynamic capacity assessment, and high-frequency bottleneck point analysis; the user layer subsystem is also used to receive the simulation calculation and capacity assessment results output by the application layer subsystem in response to the user request, and to perform visual display.

[0181] Specifically, the core functional development of this airport surface operations simulation and assessment software platform system, focused on improving airport surface operation efficiency and capacity, relies on the key technologies and theoretical research results generated from the aforementioned research. To ensure independent control of the prototype system's core technology and independence from foreign technology and software, the system was developed using the .NET programming language and a browser / server architecture (browser / server model). This system offers excellent versatility, openness, and scalability, with minimal reliance on the application environment, facilitating future expansion and secondary development for different airport scenarios.

[0182] This airport surface operations simulation and assessment software platform utilizes a three-tier architecture, with each subsystem functionally independent and communicating via interfaces. Following the basic platform development process, the present invention addresses overall system architecture design, foundational platform design, interface design, database design, application development, visualization module development, packaging and integration of related components, and front-end design. By decoupling airport data, business rules, and application functions into a layered implementation, the system addresses industry technical challenges such as comprehensive support for complex business scenarios, interpretable business solutions, real-time early warning and automatic resolution of business conflicts, and high-performance real-time computing.

[0183] Based on specific functional requirements, the user layer subsystem can connect to relevant external data and provide the external data to the application layer subsystem for subsequent simulation. The external data includes system configuration information. Specifically, the system configuration information includes airport surface configuration information and system simulation configuration information. The system simulation configuration information includes flight number, aircraft type, planned arrival time, actual arrival time, target parking stand for inbound flights, planned off-block time, planned departure time, actual departure time, simulation time, etc. For example, flight data can be obtained through China Aviation Information Network data, or other flight-related apps can also obtain relevant data. The airport surface configuration information includes the airport's runway distribution, taxiway distribution, and aircraft stand distribution (i.e., airport parking stand topology) and aircraft stand status, etc. For the airport to be processed, relevant airport surface configuration information can be obtained in advance. The user layer subsystem is equipped with a data interface to receive external data and store the corresponding data. At the same time, it can interact with the application layer subsystem and send external data to the application layer subsystem. The user layer subsystem has a built-in communication network to implement communication transmission functions.

[0184] At the same time, the user layer subsystem is also used to schedule the various simulation computing tasks being executed. Since the application layer subsystem may perform multiple simulation computing tasks at the same time, corresponding scheduling can be performed according to demand to achieve different task priorities.

[0185] The user can send a user request to the network server through the browser. After the user layer subsystem receives the user request, the network server processes the user request, analyzes the relevant evaluation information required by the user, and returns the result information required by the user (i.e., the simulation and evaluation results output by the application layer subsystem in response to the user request) to the browser. The user layer subsystem performs visualization, which can be achieved in a two-dimensional dynamic form, and the simulation calculation results are displayed accordingly in the form of data charts, etc.

[0186] At the same time, the user layer subsystem also receives system configuration information performed by the user, such as aircraft stand design configuration, such as the number and location of remote aircraft stands, the number and location of close aircraft stands, aircraft stand size and carrying capacity, etc., system simulation configuration, such as flight scheduled arrival time, flight model, flight scheduled departure time, etc., and simulation execution parameters, such as simulation time, number of simulations, etc., and sends it to the application layer subsystem for building a simulation environment and setting simulation parameters.

[0187] Among them, user requests include airfield design scheme comparison, airfield dynamic capacity assessment and high-frequency bottleneck point analysis; specifically,

[0188] Airfield design scheme comparison refers to the input of multiple airport surface design schemes (including runway layout, parking space layout, taxiway layout, historical flight data, etc.) into the system for a planned new or expanded airport. The optimal surface design scheme is selected based on the surface capacity and operation efficiency results output by the evaluation model. The existing design scheme can also be fed back and improved based on evaluation indicators such as taxiway usage frequency.

[0189] The dynamic capacity assessment of the airfield refers to establishing a baseline model of the existing airport, evaluating the simulated operation data and actual operation statistical data, establishing a corresponding relationship between the actual release normal rate and the standard delay time of simulated departure flights, and then determining the dynamic capacity of the airport surface under a specific airport service level (specific flight release normal rate).

[0190] High-frequency bottleneck point analysis means that for existing airports, high-load scenario parameters (peak flight arrival rate, average dwell time, etc.) are input into the system. Through simulation, the system counts and outputs the taxiways with high usage frequency or nodes with high delay frequency obtained through evaluation, providing a decision-making basis for the airport to identify key improvement nodes, so as to improve the airport's surface operation efficiency and transit guarantee capabilities.

[0191] The application layer subsystem is primarily used for data analysis and system simulation. Based on data sent by the tool layer and user layer subsystems, the application layer subsystem invokes the airport surface operation simulation model. Based on the simulation requirements represented by user requests, it simulates the operation of aircraft arriving or departing at the airport surface, generating corresponding simulation calculations and capacity assessment results.

[0192] Among them, the airport scene operation simulation model is a discrete event simulation model built based on the .Net framework and using modular simulation modeling technology, and is implemented by considering the aircraft taxi path search strategy, aircraft anti-collision scheduling strategy and aircraft stand allocation strategy; the simulation calculation results include the position and status of each aircraft at each time point.

[0193] Furthermore, the simulation calculation results also include:

[0194] Taking into account the differences in aircraft stand types and the influence of dynamic factors, based on the constructed airport surface operation simulation model, by obtaining airport surface configuration information and system simulation configuration information, the airport operation is simulated and calculated to obtain preset indicators for measuring airport performance and efficiency levels. The preset indicators include average take-offs and landings, hourly capacity, hourly peak flights, and average apron occupancy time of flights. The preset indicators are used to evaluate the ability of the airport surface to accept flight demand.

[0195] The output analysis of the simulation model is illustrated by taking the flight ground delay time as an example.

[0196] 1) For incoming flights, the taxiing delay of the aircraft at the airport is analyzed, that is, the waiting time of the aircraft during the entire take-off or landing process. The waiting time analyzed in the model includes the time the aircraft waits for the runway and taxiway. The sum of the two represents the total waiting time of the aircraft. Among them, the cycle time represents the total time required for the aircraft to complete the entire take-off or landing process. After analyzing the delays of individual flights, the delays of incoming flights at the airport are also studied in hours, such as Figure 17 The runway waiting time represents the total waiting time on the runway, and the taxiway waiting time represents the total waiting time on the taxiway.

[0197] Table 5 Waiting time for incoming flights

[0198] name Value (minutes) Average waiting time 0.6 Average runway waiting time 0.1 Average taxiway waiting time 0.6 Maximum waiting time 13.4 Maximum runway holding time 1.0 Maximum taxiway waiting time 12.9

[0199] 2) For departing flights, the waiting time analysis results are as follows: Figure 18 This is shown in Figures 6 and Table 6. It can be seen that the proportion of delayed flights is greater for departing flights than for arriving flights.

[0200] Table 6 Waiting time for incoming flights

[0201] name Value (minutes) Average waiting time_total 1.0 Average waiting time_RW(runway) 0.2 Average waiting time_TW(taxiway) 0.8 Maximum wait time_total 8.6 Maximum waiting time_RW(runway) 1.7 Maximum waiting time_TW(taxiway) 8.2

[0202] 3) Comparison of arriving and departing flights. To make the comparison more intuitive, you can compare arriving and departing flights on the same chart. Please see Figure 19 The average waiting time for departing flights is longer than that for arriving flights, indicating that the delays for departing flights are generally more serious. However, sometimes the delays for arriving flights are greater, such as Figure 19 At 8 p.m., when there is less outbound demand and more inbound demand, the waiting time for inbound flights will increase accordingly.

[0203] Among the three levels, the main functions and business logic of the system are processed in the application layer, which calls the surface safety operation strategy set (aircraft taxi path search strategy, aircraft anti-collision scheduling strategy and aircraft stand allocation strategy) and the system simulation model (airport surface operation simulation model). These have been introduced in detail above and provide intelligent decision support for improving airport surface capacity and operation efficiency, bottleneck analysis and other evaluation methods.

[0204] The embodiment of the present invention proposes an airport surface operation simulation and evaluation software platform system based on the .Net framework, aiming to explore the bottleneck factors that restrict surface aircraft stand capacity and operating capabilities under the complex operation environment of the airport, and fill the gaps in related simulation technology and capacity evaluation technology.

[0205] On the one hand, based on the discrete event simulation method and .Net programming language, the present invention independently develops a high-precision, flexible, and universal airport scene operation system simulation model, and independently develops and realizes airport scene operation simulation in a complex and uncertain environment. It can realize the preview of the operation situation of the airport scene through simulation means; it can use simulation technology to guide airport layout and design for airport reconstruction, expansion, etc.

[0206] On the other hand, for different user requests such as airfield design scheme comparison, airfield dynamic capacity assessment, control operation strategy selection and high-frequency bottleneck point analysis, this invention explores how to achieve accurate and effective analysis and assessment. By combining actual airport operation data, it effectively identifies and introduces various dynamic influencing factors into the simulation model, realizing functions such as dynamic capacity assessment and aircraft stand capacity demand forecasting.

[0207] On the other hand, the present invention integrates multi-source heterogeneous data such as airport surface operation mechanism and operation space-time information, designs a data interaction interface that integrates surface operation simulation technology with dynamic capacity assessment method, realizes diversified data collaboration in the simulation model, and can realize the automatic conversion of scene parameters to evaluation indicators.

[0208] In summary, the present invention not only solves the limitations of existing simulation software, but also provides strong support for the intelligent and digital development of airports, which will have a profound impact on the operational optimization and technological progress of domestic airports.

Claims

1. An airport surface operation simulation and evaluation software platform system, characterized in that: include: Tool layer subsystem, application layer subsystem and user layer subsystem; among them, The tool layer subsystem is used to respond to the simulation modeling and statistical analysis requirements of the application layer subsystem and provide a multivariate data interface between the various subsystems. The simulation modeling constructs an airport scene and an airport scene operation simulation model by calling modular simulation components, simulating the operation process of aircraft at the airport scene when arriving or departing, and obtaining simulation calculation results. The modular simulation components are constructed based on discrete event simulation modeling methods and modular technology, and include runway modules, taxiway modules, apron modules, connecting road modules and generator modules required for the airport scene, as well as an aircraft taxiing path search algorithm. The simulation calculation results include the position and status of each aircraft at each time point. The statistical analysis is achieved by calling the indicator model library of the tool layer subsystem to count and calculate key performance indicators during the simulation process. The application layer subsystem is configured to call the modular simulation components, multivariate data interface, and indicator model library of the tool layer subsystem based on the data input by the user layer subsystem to build an airport scene, trigger simulation and statistical analysis based on user requests from the user layer subsystem, perform simulation calculations and capacity assessments on the user requests, output analysis results, and feed them back to the user layer subsystem; The user layer subsystem is used to receive system configuration information and user requests input by users and send them to the application layer subsystem; wherein, the system configuration information includes airport surface configuration information and system simulation configuration information, and the user request includes multiple indicator analyses including airfield design scheme comparison, airfield dynamic capacity assessment, and high-frequency bottleneck points; the user layer subsystem is also used to receive the simulation calculation and capacity assessment results output by the application layer subsystem in response to the user request, and to perform visual display.

2. The airport surface operation simulation and evaluation software platform system according to claim 1 is characterized in that: The airport surface configuration information includes the airport's runway distribution, taxiway distribution, and aircraft stand distribution; the system simulation configuration information includes flight number, aircraft type, planned arrival time, actual arrival time, target parking stand for incoming flights, planned block removal time, planned takeoff time, actual takeoff time, and simulation time.

3. The airport surface operation simulation and evaluation software platform system according to claim 2 is characterized in that: The design process of the airport surface operation simulation model includes: The airport surface system is divided into runway subsystem, taxiway subsystem and apron subsystem; Based on the logical associations among the runway subsystem, the taxiway subsystem, and the apron subsystem and their internal events, a discrete event simulation modeling method is used to divide the aircraft's operation process on the airport surface into five modules, including a generator module, a runway module, a connecting road module, a taxiway module, and an apron module. For each of the five modules, corresponding classes are created in the program. Class definitions and interactions between classes are represented using modular event graphs. The simulation in each module is triggered by discrete events. The taxiway module and the connecting road module form the airport's surface taxiway path network, into which an aircraft taxiway path search algorithm and an aircraft anti-collision scheduling strategy are embedded to determine the aircraft's taxiway path and target parking position, thereby completing the construction of the airport surface operation simulation model. Verify the validity of the airport surface operation simulation model and feed it back to the application layer subsystem after passing the verification.

4. The airport surface operation simulation and evaluation software platform system according to claim 3 is characterized in that: Verify the effectiveness of the airport surface operation simulation model, including: Using flight data of actual known flights as input data, running the airport scene operation simulation model, and outputting simulation deduction data; For selected indicator parameters, the simulation data and the input data are compared, and based on the comparison results, it is verified whether the effectiveness of the airport surface operation simulation model meets the requirements, wherein the selected indicator parameters include the simulated landing time, take-off time, taxi-in time, and push-out time of the aircraft.

5. The airport surface operation simulation and evaluation software platform system according to claim 3 or 4, characterized in that: The process of constructing the surface taxi path network of the airport includes: defining control points in the surface taxi path network; Define paths in the surface taxi path network. When defining a path, only control points that can be reached from the current control point are considered. Corresponding control points are connected to form a path to avoid path duplication. Furthermore, a Boolean property is added to the path class to indicate the path direction, thereby distinguishing between landing and takeoff taxi path networks.

6. The airport surface operation simulation and evaluation software platform system according to claim 5 is characterized in that: The aircraft taxi path search strategy is implemented based on an aircraft taxi path search algorithm and taxi path constraints. The aircraft taxi path search algorithm uses a static path search algorithm to find the optimal taxi path with the shortest path length based on a constructed surface taxi path network, given the known aircraft taxi start and end points. The taxi path constraints are aircraft-specific and include: the time interval between preceding and succeeding aircraft using the same runway must be greater than the wake turbulence interval, and different taxiways have corresponding wingspan restrictions.

7. The airport surface operation simulation and evaluation software platform system according to claim 6 is characterized in that: The aircraft anti-collision scheduling strategy is based on multiple types of conflicts preset during the taxiing process, including cross conflicts, same-direction conflicts, and opposite-direction conflicts, and defines conflict paths in the constructed surface taxiing path network. The process includes: the aircraft anti-collision scheduling strategy is based on the multiple types of conflicts, and defines multiple attributes including conflict paths, path capacity, and minimum time interval in the constructed surface taxiing path network. When the aircraft is taxiing, its taxiing path is determined according to the aircraft taxiing path search algorithm to determine the conflict path, and then decide in advance whether the aircraft should wait to prevent conflicts.

8. The airport surface operation simulation and evaluation software platform system according to claim 7 is characterized in that: The stand allocation strategy adopts a heuristic algorithm to minimize the flight stand usage cost and flight towing cost, and is implemented using a preset algorithm strategy. The stand allocation strategy includes landing priority and takeoff priority; wherein the preset algorithm strategy includes a genetic algorithm and a greedy algorithm.

9. The airport surface operation simulation and evaluation software platform system according to claim 1 is characterized in that: The airport surface operation simulation and evaluation software platform system is developed based on the .NET programming language and adopts a B / S architecture. The subsystems at each level are independent in function and realize data communication through interfaces.

10. The airport surface operation simulation and evaluation software platform system according to claim 1, characterized in that: The simulation calculation results also include: Taking into account the differences in aircraft stand types and the influence of dynamic factors, based on the constructed airport surface operation simulation model, by obtaining airport surface configuration information and system simulation configuration information, the airport operation is simulated and calculated to obtain preset indicators for measuring airport performance and efficiency levels. The preset indicators include average take-offs and landings, hourly capacity, hourly peak flights, and average apron occupancy time of flights. The preset indicators are used to evaluate the ability of the airport surface to accept flight demand.

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