Simulation decision-making system for airport parking apron employee task order dispatching

Abstract

The invention provides a simulation decision-making system for airport parking apron employee task order dispatching, and belongs to the technical field of airport scheduling methods. Comprising a database module responsible for storing and updating data, a demand module responsible for generating flight guarantee tasks, a supply module responsible for screening available employees, a scheduling module responsible for dispatching the employees, and an evaluation module responsible for recording and analyzing a scheduling result. The simulation system considers that airport parking apron employees have different professional qualification limitations and different flights can generate different guarantee task requirements, summarizes multi-source data, detects flight positions and states, and dispatches flight tasks to the parking apron employees in real time for service. Compared with the prior art, the system considers the diversity of flight manpower demands, the professional qualification limitation of airport parking apron employees and the like, simulates the real flow of airport parking apron employee scheduling in detail, and is beneficial to reducing the manpower cost and improving the airport ground operation efficiency and safety.

Description

Technical Field

[0001] The present invention belongs to the technical field of airport planning and scheduling, and particularly relates to a simulation decision-making system for task dispatching of apron employees at an airport. Background Art

[0002] With the growing importance of the air transportation industry to the global economic development, the civil aviation demand has been continuously increasing. Many hub airports around the world are undergoing continuous expansion, adding terminal buildings and apron facilities to cope with the increasing air traffic demand. For example, some super-large airports such as Shanghai Pudong International Airport have multiple terminal buildings, a large number of parking positions and boarding bridges. Although these developments have improved the airport's handling capacity, they have also significantly increased the complexity and pressure of operational services, especially in the ground handling service area of the flight area.

[0003] Airport ground handling services play a crucial role in ensuring the efficient operation of airports. The ground handling services in the airport flight area cover various functions, such as boarding bridge guarantee for flights, cabin cleaning, baggage handling, and security inspection. Different types of ground handling services have different requirements for the professional qualifications and skills of staff. If ground handling tasks are assigned to personnel who do not meet the professional qualification restrictions, there will be potential safety hazards, which makes the scheduling of flight ground handling service personnel very complex. In addition, there is a high degree of uncertainty in the personnel allocation process. On the one hand, busy periods and extreme weather may lead to the randomness of flights. On the other hand, there may also be uncertainties in the personnel list. Against this background, it is particularly important to efficiently arrange the airport apron staff. This is not only related to the safety and punctuality of passengers getting on and off the plane, but also directly affects the passenger satisfaction and the flight punctuality rate.

[0004] In terms of airport simulation, scholars have constructed various simulation frameworks from different perspectives such as ground handling operations and flight area safety. Cavada et al. (2017) proposed a simulation platform for the baggage handling system, integrating all baggage-related subsystems, covering the processes from passenger arrival to check-in queuing, baggage check-in, security screening, sorting, transportation to the aircraft and loading. Mota et al. (2017) analyzed Lelystad Airport based on a simulation model, tested three apron layouts, and studied the use of ground handling service vehicles in the model, as well as different demand levels and different allocations to aircraft, to determine the optimal configuration of the airport. Damgacioglu et al. (2018) proposed a fixed-path network simulation framework aimed at analyzing the impact of interference events such as runway closures or extreme weather on aircraft taxiing times. Liu et al. (2023) proposed a simulation-based optimization modeling framework to help airport shuttle operators effectively deploy electric buses. Tian et al. (2024) proposed an airport surface traffic operation simulation framework for aircraft-vehicle collaborative operation conflicts, based on the Monte Carlo simulation method, and realized the simulation of mixed traffic flow including aircraft and vehicles.

[0005] In summary, most of the current research rarely focuses specifically on the dispatching of apron employees. Previous research mainly focuses on the dispatching of single types of workers, often neglecting the diversity of the specific tasks and operational skills of apron employees. On the other hand, existing research mostly belongs to tactical planning, that is, planning is carried out several weeks or months before actual operations, rarely considering the real-time allocation of employees.

[0006] Therefore, there is a need for a method that can assist in the real-time dispatching decision-making of airport apron personnel and meet the requirements of as many work tasks as possible as quickly as possible. Summary of the Invention

[0007] The object of the present invention is to provide a simulation decision-making system for task dispatching of airport apron employees, which is characterized by including five major modules: a database module constructed based on airport geographic information systems, flight data, employee data, etc., a demand module responsible for generating flight support task requirements, a supply module responsible for screening available employees, a scheduling module responsible for dispatching employees, and an evaluation module responsible for recording and analyzing the scheduling results.

[0008] Furthermore, the simulation decision-making system includes: setting the time scale for system decision-making as ΔT, that is, every ΔT time, the system updates the flight information and personnel information and implements scheduling decisions.

[0009] Furthermore, the database module is responsible for storing and updating the data information of the simulation decision-making system, specifically including:

[0010] An airport geographic information database that records the location information of each apron and employee lounge at the airport;

[0011] An ADS-B database, that is, an Automatic Dependent Surveillance - Broadcast database, which records the real-time position information of aircraft, including the data collection time, the real-time longitude and latitude coordinates of the aircraft, the real-time altitude information, the departure airport of the aircraft route, and the arrival airport;

[0012] A flight information database, including the flight schedule (estimated arrival / departure time), flight number, aircraft type, parking position, and affiliated airline of the flight;

[0013] An airline information database, including the names of the airlines given by the airport and the flight support requirements stipulated by each airline;

[0014] An employee information database, including the names, numbers, affiliated lounges, airport jurisdiction areas of the affiliated lounges, and professional qualifications mastered by employees;

[0015] The task information database includes the name of the flight guarantee task, the apron for the guarantee task, professional qualification requirements, service time window requirements, task duration, and maximum task waiting time.

[0016] Furthermore, the demand module is responsible for generating flight guarantee tasks, specifically including:

[0017] Observing flight information in advance, observing flights that are about to take off or land within a certain period of time in the future through the flight schedule or real-time flight data ADS-B data of the flight;

[0018] Generating guarantee tasks corresponding to the observed flights. After obtaining the flight data, the ground handling tasks of the flight generate one or more guarantee tasks required according to the airline and aircraft type information, including boarding bridge connection and evacuation operations, aircraft maintenance services, Chinese and English liaison, equipment charging services, baggage services, and sewage services. All the guarantee tasks corresponding to these flights constitute the set of tasks to be completed at this moment and are uploaded to the task information database.

[0019] Furthermore, observing flight information in advance is specifically as follows:

[0020] Assume the current time is T, and obtain flights that are about to take off within the next T observe time through the flight schedule;

[0021] Use the flight ADS-B data to observe the longitude, latitude, and altitude information of the aircraft in real time. When the distance of an inbound flight from the airport center is less than D and the altitude drops below H, obtain the flight that is about to land.

[0022] Furthermore, the supply module responsible for screening available employees specifically includes: for each task to be completed, screening the list of available apron employees for this task, screening employees who meet the professional qualification requirements and service time window constraints. These employees constitute the list of available employees for this task.

[0023] Furthermore, screening employees who meet the service time window constraints specifically includes:

[0024] First, screen the apron employees who meet the professional qualification requirements of the task;

[0025] Secondly, screen the apron employees who meet the service time window constraints of the task. If an apron employee is in an available state (not performing other tasks), or an apron employee is performing other tasks but can end the task within the maximum task waiting time and is in the same airport jurisdiction area as the task to be served, then this employee is added to the list of available employees for this task.

[0026] Furthermore, the scheduling module responsible for dispatching employees is specifically as follows:

[0027] The to-be-completed guarantee tasks generated by the input requirement module and the list of available personnel for each task generated by the supply module use a heuristic algorithm based on manual experience to achieve the matching of guarantee tasks and apron employees;

[0028] When a task is matched with an employee, the task is removed from the task information database, and the status of the employee is modified to non-idle; when there is no available employee to match a task, the task remains in the task information database waiting for the next round of matching.

[0029] Furthermore, the heuristic algorithm based on manual experience is specifically as follows: for each guarantee task requirement, define the time length from the end of the last task completion of an employee as the idle time, and preferentially match the available employee with the longest idle time among the employees in the same airport jurisdiction area as the task. Secondly, consider matching the available employees in the adjacent airport jurisdiction areas of the task. Finally, consider dispatching the available employees in other airport jurisdiction areas.

[0030] Furthermore, the evaluation module responsible for recording and analyzing the scheduling results specifically includes:

[0031] Visual display, including displaying the flight guarantee requirement information at each moment, the list of available apron employees at each moment, the cumulative workload of each employee, and the total number of tasks completed by the employees in each lounge;

[0032] Human-computer interaction, including controlling parameters such as the simulation speed, starting and pausing the simulation process.

[0033] Compared with the prior art, the beneficial effects of the present invention are mainly reflected in:

[0034] 1. The present invention provides a simulation decision-making system for task dispatching of airport apron employees, which details the real process of airport apron employee scheduling, couples flight trajectory monitoring, the generation of flight guarantee task requirements, and the dispatching of apron employees to assist the real-time dispatching decision-making of airport apron personnel.

[0035] 2. In the proposed simulation decision-making system, fully consider the diversity of flight manpower requirements, the professional qualification restrictions of airport apron employees, the time window restrictions of flight services and other characteristics, and assist airport managers in scheduling apron employees through real-time decision-making.

[0036] 3. The dispatching of apron personnel adopts a simple heuristic method based on manual experience to match work tasks and staff to meet as many work task requirements as possible as quickly as possible. Description of the Drawings

[0037] Figure 1Schematic diagram of the process framework of a simulation decision-making system for task dispatching to airport apron employees according to the present invention;

[0038] Figure 2 Schematic diagram of the demand module in the present invention;

[0039] Figure 3 Schematic diagram of the advance observation of flight information in the demand module of the present invention;

[0040] Figure 4 Schematic diagram of the supply module in the present invention;

[0041] Figure 5 Schematic diagram of the scheduling module in the present invention;

[0042] Figure 6 Schematic diagram of the heuristic algorithm based on manual experience in the scheduling module of the present invention;

[0043] Figure 7 Schematic diagram of the evaluation module in the present invention;

[0044] Figure 8 Example diagram of the visualization page in the evaluation module of the present invention. Detailed implementation manners

[0045] The following will describe in more detail a simulation decision-making system for task dispatching to airport apron employees according to the present invention with reference to the schematic diagrams, in which the preferred embodiments of the present invention are shown. It should be understood that those skilled in the art can modify the present invention described herein while still achieving the advantageous effects of the present invention. Therefore, the following description should be understood as a broad guidance for those skilled in the art and not as a limitation to the present invention.

[0046] Embodiment

[0047] As Figure 1 shown, a simulation decision-making system for task dispatching to airport apron employees specifically includes: a database module constructed based on the airport geographic information system, flight data, employee data, etc., a demand module responsible for generating flight support tasks, a supply module responsible for screening available employees, a scheduling module responsible for dispatching employees, and an evaluation module responsible for recording and analyzing the scheduling results.

[0048] The simulation decision-making system includes: setting the time scale for system decision-making as ΔT = 1 min, that is, the system updates the flight information and personnel information every 1 minute and implements scheduling decisions.

[0049] The database module is responsible for storing and updating the data information of the simulation decision-making system, specifically including:

[0050] The airport geographic information database records the location information of each apron and staff lounge in the airport;

[0051] The ADS-B database, i.e., the Automatic Dependent Surveillance - Broadcast database, records the real-time position information of aircraft, including the real-time longitude and latitude coordinates of the aircraft, real-time altitude information, the departure airport and the arrival airport of the aircraft route;

[0052] The flight information database includes the schedule of the flight (expected arrival / departure time), flight number, aircraft type, parking position, and the airline company to which it belongs;

[0053] The airline company information database includes the names of each airline company given by the airport and the flight guarantee requirements stipulated by each airline company;

[0054] The staff information database includes the name, number, affiliated lounge, the airport jurisdiction area of the affiliated lounge, and the professional qualifications mastered by the staff;

[0055] The task information database includes the name of the flight guarantee task, the parking position of the guarantee task, professional qualification requirements, service time window requirements, task duration, and maximum waiting time of the task.

[0056] As Figure 2 shown, the said demand module is responsible for generating flight guarantee tasks, specifically including:

[0057] Observing flight information in advance, observing flights that are about to take off or land within a certain period of time in the future through the flight schedule or real-time flight data of the aircraft (ADS-B data);

[0058] Generating guarantee tasks corresponding to the observed flights. After obtaining flight data, the ground service guarantee tasks of the flight generate one or more guarantee tasks it needs according to the airline company and aircraft type information, including but not limited to boarding bridge connection and evacuation operations, equipment charging services, Chinese and English liaison officers, etc. All the guarantee tasks corresponding to these flights constitute the task set to be completed at this moment and are uploaded to the task information database.

[0059] Table 1 shows the flight demand information at a certain moment.

[0060]

[0061] Table 1

[0062] As Figure 3 shown, the specific method of observing flight information in advance is:

[0063] Assume the current time is T, and obtain the future T through the flight schedule observe= There is a flight about to take off within 15 minutes;

[0064] Use the flight ADS - B data to observe the longitude, latitude and altitude information of the aircraft in real - time. When the distance of an inbound flight from the airport center is less than D = 30 km and the altitude drops below H = 4000 m, obtain the flight about to land.

[0065] As Figure 4 shown, the supply module responsible for screening available employees specifically includes:

[0066] For each task to be completed, screen the list of available apron employees for this task, and screen the employees who meet the professional qualification requirements and the service time window constraints. These employees constitute the list of available employees for this task.

[0067] The screening of employees who meet the service time window constraints specifically includes:

[0068] First, screen the apron employees who meet the professional qualification requirements of the task;

[0069] Secondly, screen the apron employees who meet the service time window constraints of the task. If an apron employee is in an available state (not performing other tasks), or an apron employee is performing other tasks, but can complete the task within the maximum waiting time of the task (assuming the maximum waiting time of the task is 15 minutes), and is in the same airport jurisdiction area as the task to be served, then this employee is added to the list of available employees for this task. Table 2 shows the list of available employees for Task 1 in Table 1.

[0070] Serial Number Name Lounge Professional Qualification Free Time 1 Tian XX 60 (Airport Area A) Boarding Bridge Connection and Evacuation 58 min 2 Yan XX 60 (Airport Area A) Boarding Bridge Connection and Evacuation 45 min 3 Gong XX 60 (Airport Area A) Boarding Bridge Connection and Evacuation 38 min 4 Deng XX 60 (Airport Area A) Boarding Bridge Connection and Evacuation 20 min 5 Zhang XX 88 (Airport Area B) Boarding Bridge Connection and Evacuation 50 min 6 Pan XX 88 (Airport Area B) Boarding Bridge Connection and Evacuation 44 min 7 Xi XX 88 (Airport Area B) Boarding Bridge Connection and Evacuation 42 min 8 Xu XX 88 (Airport Area B) Boarding Bridge Connection and Evacuation 21 min

[0071] Table 2

[0072] As Figure 5 shown, the scheduling module responsible for dispatching employees is specifically:

[0073] Input the to - be - completed guarantee tasks generated by the demand module and the list of available personnel for each task generated by the supply module, and use a heuristic algorithm based on manual experience to achieve the matching of guarantee tasks and apron employees;

[0074] When a task is matched with an employee, remove the task from the task information database and modify the status of this employee to non - idle; when a task has no available employees for matching, the task remains in the task information database waiting for the next round of matching.

[0075] As Figure 6 shown, the heuristic algorithm based on manual experience is specifically:

[0076] For each security task requirement, define the length of time since the employee's last task ended as the idle time. First, preferentially match the available employee with the longest idle time among those in the same airport jurisdiction area as the task. Second, consider matching the available employees in the adjacent airport jurisdiction areas of the task. Finally, consider dispatching the available employees in other airport jurisdiction areas. Figure 6 Task i in Figure 6 will be matched with Employee 1, who has the longest idle time and is in the same area as Task i. That is, Task 1 in Table 1 is matched with Employee 1 in Table 2.

[0077] As Figure 7 shown, the evaluation module responsible for recording and analyzing the scheduling results specifically includes:

[0078] Visual display, including showing the flight security requirement information at each moment, the list of available apron employees at each moment, the cumulative workload of each employee, and the total number of tasks completed by the employees in each lounge; human-computer interaction, including controlling parameters such as the simulation speed and starting and pausing the simulation process. Among them Figure 8 shows an example diagram of a visual page, including controlling the simulation speed, starting and pausing the simulation, showing the demand flight information and security personnel information in the matching results, visualizing the workload of employees and the workload of lounges, etc.

[0079] The above is only the preferred embodiment of the present invention and does not impose any limitation on the present invention. Any technical employee in the technical field concerned, without departing from the technical solution of the present invention, makes any form of equivalent substitution or modification and other changes to the technical solution and technical content disclosed by the present invention, which are still within the content of the technical solution of the present invention and still fall within the protection scope of the present invention.

Claims

1. A simulation decision system for dispatching tasks to airport apron staff, characterized in that: It includes a database module responsible for storing and updating the simulation decision system, a demand module responsible for generating flight support tasks, a supply module responsible for screening available employees, a scheduling module responsible for dispatching employees, and an evaluation module responsible for recording and analyzing scheduling results.

2. The simulation decision system for dispatching tasks for airport apron staff according to claim 1 is characterized in that: The system decision time scale of the simulation decision system is set to ΔT, that is, every ΔT time, the simulation decision system updates the flight information and employee information and implements the scheduling decision.

3. The simulation decision system for dispatching tasks for airport apron staff according to claim 1 is characterized in that: The database module includes an airport geographic information database, an ADS-B database, a flight information database, an airline information database, an employee information database, and a task information database; The airport geographic information database records the location information of each apron and employee lounge at the airport; The ADS-B database is an Automatic Dependent Surveillance-Broadcast database, which records the real-time location information of the aircraft, including the data collection time, the real-time latitude and longitude coordinates of the aircraft, the real-time altitude information, the departure airport and the arrival airport of the aircraft route; The flight information database includes the flight schedule, flight number, aircraft type, parking space and airline company of the flight; The airline information database includes the name of each airline given by the airport and the flight support requirements stipulated by each airline; The employee information database includes the employee's name, number, lounge, airport jurisdiction of the lounge, and professional qualifications; The mission information database includes the name of the flight support mission, the parking space for the support mission, professional qualification requirements, service time window requirements, mission duration, and maximum waiting time for the mission.

4. The simulation decision system for dispatching tasks for airport apron staff according to claim 1 is characterized in that: The demand module generates flight support tasks through the following steps: S1: Observe the information data of flights that will take off or land in the future within the required observation time through flight schedules or real-time flight data ADS-B data; S2: Based on the data information of the flights observed in advance, the ground support tasks of the flights generate one or more support tasks required according to the airlines and aircraft models. All support tasks corresponding to all flights constitute the task set to be completed at that moment, and the task set is uploaded to the task information database.

5. The simulation decision system for dispatching tasks for airport apron staff according to claim 4 is characterized in that: The S1 is specifically: Set the current time to T and obtain the future time T through the flight schedule observe Flights that are about to depart within Use flight ADS-B data to observe aircraft latitude, longitude and altitude information in real time. When the distance of an incoming flight from the airport center is less than D and the altitude drops below H, obtain the flight that is about to land; In S2, the support tasks include boarding bridge connection evacuation operations, aircraft maintenance services, Chinese and English liaison, equipment charging services, luggage services and sewage cleaning services.

6. The simulation decision system for dispatching tasks for airport apron staff according to claim 1 is characterized in that: The supply module is responsible for screening available employees. Specifically, for each task to be completed, the list of available employees for the task is screened, where the list of available employees is the list of available apron employees for the task. The supply module screens the employees who meet the professional qualification requirements and the service time window constraints from the list of available apron employees for the task.

7. The simulation decision system for dispatching tasks for airport apron staff according to claim 6 is characterized in that: First, we screen the apron staff that meet the professional qualification requirements of the mission. On this basis, we screen the apron staff that meet the service time window constraints of the mission. The apron staff that meet the task service time window constraints are selected in turn according to the following conditions and added to the list of available staff for the task; The ramp employee is currently available, i.e. not performing other tasks; The ramp worker is currently performing other tasks but is able to complete the task within the maximum waiting time for the task and is in the same airport jurisdiction as the task to be serviced.

8. The simulation decision system for dispatching tasks for airport apron staff according to claim 1 is characterized in that: The scheduling module matches the support tasks with the apron staff by inputting the support tasks to be completed generated by the demand module and the list of available staff for each task generated by the supply module, and using a heuristic algorithm based on human experience; When a guarantee task is matched with an available employee, the guarantee task is deleted from the task information database, and the available employee status is changed to a non-idle status; when a guarantee task is not matched with an available employee, the guarantee task is retained in the task information database, waiting for the next round of matching.

9. The simulation decision system for dispatching tasks for airport apron staff according to claim 8 is characterized in that: The heuristic algorithm is specifically: For each support task requirement, the length of time from the employee's completion of the previous task is defined as idle time. Priority is given to matching available employees with the longest idle time among those in the same airport jurisdiction as the support task. Next, consideration is given to matching available employees in the adjacent airport jurisdiction. Finally, consideration is given to dispatching available employees in other airport jurisdictions.

10. The simulation decision system for dispatching tasks for airport apron staff according to claim 1, characterized in that: The evaluation module specifically includes visual display and human-computer interaction; The visual display includes displaying the flight support task demand information at each time, the list of available apron employees at each time, the cumulative workload of each employee, and the total number of tasks completed by employees in each lounge; The manual interaction includes simulation parameters, starting and pausing the simulation process.

Images