A method for dispatching an airport shuttle vehicle with manned and unmanned coexistence

Abstract

The present application relates to a kind of airport shuttle dispatching method with manned and unmanned coexistence, comprising: obtaining airport shuttle information, flight information, environmental information;According to environmental information, vehicle scene sensing is carried out, and the driving mode of vehicle for realizing shuttle service is confirmed;According to shuttle information, flight information, environmental information and setting related parameters, establish airport any unmanned shuttle mixed dispatching model, determine target shuttle;According to target shuttle, based on real-time communication, carry out shuttle task, and feedback task execution situation.The present application carries out shuttle dispatching in the new scene of manned vehicle and unmanned vehicle coexistence, so as to solve the vehicle scheduling problem in the manned shuttle and unmanned shuttle coexistence scene, realize scheduling cost minimization, enhance vehicle operation safety performance, improve airport ground service support capability.

Description

Technical Field

[0001] This invention relates to the field of vehicle scheduling technology, and in particular to a method for scheduling airport shuttle buses that combines manned and unmanned operation. Background Technology

[0002] With the continuous development of air transport, the number and frequency of flights at airports are constantly increasing. Achieving scientific and efficient airport support vehicle scheduling within a limited time has become a major practical problem that urgently needs to be solved. Traditional ground service vehicle scheduling technology mainly relies on manual scheduling and static planning methods. However, manual scheduling is generally based on dispatchers' experience-based judgments according to transportation demand and vehicle status, which leads to defects such as incomplete information acquisition, low efficiency, and high cost. Static planning usually uses rules and heuristic algorithms for path planning, but it cannot adapt to real-time changes in traffic and vehicle status.

[0003] In recent years, the accelerated development of artificial intelligence and automation technologies has led to the gradual application of rule-based and optimization-based intelligent scheduling methods in airport vehicle dispatching. Currently, the construction of smart airports incorporates many advanced technologies, such as autonomous driving and real-time collaborative dispatching. As a relatively enclosed area, the airport flight area has a defined spatial structure, a flat surface, and relatively low vehicle speeds, providing advantages for the implementation of autonomous driving technology. Combined with real-time collaborative dispatching technology, a higher level of automated dispatching and collaboration can be achieved, significantly optimizing vehicle dispatching, reducing flight delays, improving civil aviation service quality, and enhancing economic efficiency.

[0004] Currently, research on airport shuttle bus scheduling mainly focuses on various operations research methods to obtain optimized shuttle vehicle allocation and scheduling schemes to maximize their utilization. In 2020, Liu Yi, based on shuttle bus service processes, airport resource allocation, and related ground service constraints, established a multi-objective scheduling model with the objectives of minimizing shuttle bus transfer distance, achieving optimal task balance, and minimizing flight delay time. He proposed a pre-allocation scheduling algorithm combining NSGA-II with parameter adaptive strategies and local search strategies for solving the problem. In 2022, Lü Ning, when studying the airport shuttle bus scheduling problem, incorporated time windows and multiple trips, establishing a mixed integer programming model and designing a corresponding metaheuristic algorithm for solving it. In 2023, Shen Weiming et al. published an airport shuttle bus scheduling method based on variable neighborhood search, aiming to minimize the weighted comprehensive delay of inbound / outbound flight shuttle services. This method can effectively improve the scheduling efficiency of shuttle buses. Currently, most research focuses on optimizing the scheduling algorithm of the shuttle buses themselves, often neglecting the driving objects of the shuttle buses. In 2023, Bai Zhiheng et al. disclosed an airport congestion scheduling method based on the separation of people and vehicles. Unlike most scheduling algorithms based on the "fixed person-vehicle" model, this patented method takes personnel into account, allowing the same employee to be matched with multiple vehicles, thereby reducing flight delays by improving personnel rotation efficiency. With the rapid development of new technologies such as 5G communication and autonomous driving, driverless shuttle buses are gradually emerging. In 2021, Yu Xiaodong et al. disclosed an autonomous passenger shuttle bus for airports, effectively addressing the problem of high traffic accident rates for manually driven vehicles. They also disclosed a management and control method for autonomous passenger shuttle buses, applying vehicle-road-cloud integrated control technology to airports to ensure the safety, efficiency, and controllability of shuttle services.

[0005] The existing airport shuttle bus scheduling technologies mentioned above only consider purely manned or purely driverless scenarios. However, with the emergence of driverless shuttle buses, a new scenario where manned and driverless vehicles coexist is inevitable for a long time to come. In this new scenario, how to efficiently schedule manned and driverless shuttle buses has become an urgent practical need to be addressed. Summary of the Invention

[0006] Therefore, the technical problem to be solved by the present invention is to overcome the problems in the prior art that do not consider the scheduling situation when manned shuttle buses and unmanned shuttle buses exist at the same time; do not consider the situation of using only manned shuttle buses and using only unmanned shuttle buses; and do not consider the specific safety distance between manned shuttle buses and unmanned shuttle buses.

[0007] To address the aforementioned technical problems, this invention provides a method for scheduling airport shuttle buses that combines manned and unmanned operations, comprising:

[0008] Obtain airport shuttle bus information, flight information, and environmental information, and update the list of flights awaiting service in real time;

[0009] Based on environmental information, the vehicle usage scenario perception is performed to confirm the vehicle driving mode for the shuttle service, namely, manned driving, driverless driving, or both manned and driverless driving.

[0010] Based on shuttle bus information and flight information, decision variables are determined, and environmental information is incorporated to construct a vehicle driving cost function; based on flight information and environmental information, penalty coefficients are set, a time window penalty function is created, and based on the decision variables, a flight delay cost function is constructed; the cost of hiring drivers is obtained, and a manual driving cost function is constructed; based on the vehicle driving cost, flight delay cost, and manual driving cost functions, an objective function is constructed.

[0011] Based on the acquired information, constraints are established, including: setting the shuttle service time required for the current flight; obtaining the transfer distance between the shuttle bus serving the current flight and the next flight based on environmental information, and calculating the travel time required for the shuttle bus to travel the transfer distance based on the current shuttle bus speed; and obtaining the time when the current shuttle bus starts serving the current flight and the time when the current shuttle bus starts serving the next flight based on flight information, and establishing general constraints.

[0012] Get the information of manned shuttle buses from the shuttle bus information, and based on the maximum number of manned shuttle buses, the driving speed and maximum speed of manned shuttle buses, and the maximum working time of manned shuttle buses, set the duration of the shuttle bus's complete service for the current flight, and determine whether the shuttle bus is leaving the parking area for the first time, establish specific constraints for manned shuttle buses.

[0013] Information on driverless shuttle buses is obtained from the shuttle bus information. Based on the maximum number of driverless shuttle buses, the driving speed of driverless shuttle buses and their maximum driving speed, it is determined whether the shuttle bus is driving out of the parking area for the first time, and specific constraints on driverless shuttle buses are established.

[0014] Based on the objective function and constraints, a hybrid scheduling model for manned and unmanned shuttle buses at the airport is established. Based on the results of vehicle usage scenario perception, the model is solved to minimize the scheduling cost of all shuttle tasks and determine the target shuttle bus.

[0015] Based on the target shuttle bus situation, the shuttle task is executed through real-time communication, and the task execution status is reported back. Among them, for any two shuttle buses at any time, the following must be met: at the same moment, the difference between the position of the first shuttle bus and the position of the second shuttle bus is greater than or equal to the length of the shuttle bus and the minimum safe distance.

[0016] In one embodiment of the present invention, the airport shuttle bus information, flight information, and environmental information include:

[0017] The shuttle bus information includes the shuttle bus number, shuttle bus driving mode, maximum working time of manned shuttle buses, shuttle bus speed, shuttle bus location, and shuttle bus status; among which, a corresponding set of shuttle buses is formed based on the shuttle bus number.

[0018] Flight information includes flight number, flight service type, shuttle service start time, shuttle service end time, shuttle service start location, and shuttle service end location; among which, a corresponding flight set is formed based on the flight number;

[0019] Environmental information includes airport road traffic conditions, ground road conditions, infrastructure conditions, weather conditions, and traffic activities of other road users.

[0020] In one embodiment of the present invention, the step of performing vehicle usage scenario perception based on environmental information and confirming the vehicle driving mode for implementing the shuttle service includes:

[0021] Meteorological information, including rain, wind, ice, snow, and fog, is obtained from the weather intelligence system. Based on this information, a comprehensive safety indicator system is established, and corresponding safety risk values ​​are calculated. A safety assessment is conducted on both manned and unmanned shuttle bus services. If the safety risk of the manned shuttle bus service is higher than that of the unmanned shuttle bus service, the current usage scenario is determined to be a severe weather scenario, and the current usage scenario is set as Scenario 1. Under this scenario, it is determined that only unmanned shuttle buses will be used.

[0022] Obtain traffic condition information, including accident vehicles and emergency vehicles; based on the emergency information in the traffic condition information, manually determine the demand for manned and unmanned shuttle services. When the unmanned shuttle vehicle is not capable of handling the situation, the current usage scenario is determined to be an emergency usage scenario, and the current usage scenario is set as scenario 2; under this scenario, it is determined that only manned shuttle vehicles will be used.

[0023] If neither of the above two scenarios exists, the current vehicle usage scenario is determined to be a general vehicle usage scenario, and the current vehicle usage scenario is set to scenario 3. Under this scenario, it is determined that either a manned shuttle bus or an unmanned shuttle bus can be used.

[0024] In one embodiment of the present invention, the steps of determining decision variables based on shuttle bus information and flight information, constructing a vehicle driving cost function in conjunction with environmental information; setting penalty coefficients based on flight information and environmental information, creating a time window penalty function, constructing a flight delay cost function in conjunction with decision variables; and obtaining the cost of hiring a driver and constructing a manual driving cost function include:

[0025] During the vehicle driving process, the driving cost is related to the driving route, which includes the effective service distance and the necessary transfer distance; when the dispatching task is determined, the starting and ending points of the ferry service will be determined accordingly, that is, the effective service distance is fixed, and only the necessary transfer distance needs to be considered; among them, the necessary transfer distance is obtained according to the environmental information.

[0026] According to the ferry information and flight information, determine the decision variables, which are expressed as

[0027]

[0028] Among them, Take 1 when the ferry s serves flight f, otherwise take 0;

[0029] According to the obtained ferry set, flight set, the starting and ending points of the ferry service, and the decision variables, considering the necessary transfer distance in the driving route, construct the vehicle driving cost F Dis , and its function formula is

[0030]

[0031] Among them, f, l, i are flight numbers; H is the set of flights to be served; D f,l is the transfer distance of the ferry from serving flight f to serving flight l immediately afterwards; s is the ferry number; S is the set of ferries; D 0,l is the transfer distance of the ferry from the parking point to flight l; is the decision variable; Y f,l is a 0-1 variable. When the ferry first serves flight f and then serves flight l immediately afterwards, Y f,l takes 1, otherwise takes 0, and its expression is as follows:

[0032]

[0033] In the formula, respectively represent the decision variables corresponding to flights f, l, i, takes 1 when the ferry s serves flights f and l successively and the two tasks are closely connected, otherwise takes 0; f < i < l represents that the service start time of flight i is between flights f and l; that is, when there is any flight i between flights f and l and the ferry s serves flight i, then represents that at this time the ferry s serves flights f and l successively, but the two service tasks are not connected; when there is no flight i between flights f and l or there is a flight i but the ferry s does not serve flight i, then represents that at this time the ferry s serves flights f and l successively, and the two tasks are closely connected;

[0034] Regarding flight delays, whether it is a manned or unmanned shuttle bus, the cost of flight delays is related to the gap between the vehicle's arrival time and the scheduled service time.

[0035] Based on traffic information from flight and environmental data, and considering passenger demand, the earliest and latest arrival times of the shuttle bus are obtained; early arrival penalty coefficients and late arrival penalty coefficients are set, and a time window penalty function W is created. s,f Its definition is as follows:

[0036]

[0037] Where w is the early arrival penalty coefficient, n is the late arrival penalty coefficient, and d f The actual arrival time of shuttle bus service for flight f, a f b is the earliest time the shuttle bus arrives. f This is the latest time the shuttle bus will arrive;

[0038] Based on decision variables and time window functions, construct the flight delay cost F. Del Its formula is

[0039]

[0040] Among them, W s,f For time window penalty function, For decision variables;

[0041] When considering the cost of manual driving, we are referring to the labor costs associated with manned shuttle buses; for driverless shuttle buses, the cost of manual driving is not considered. Therefore, based on the cost of hiring drivers, we construct the manual driving cost function F. Man Its formula is

[0042]

[0043] Where R represents the cost of hiring a driver; It is a 0-1 variable, taking the value 1 when a manned shuttle bus is in use, and 0 otherwise.

[0044] In one embodiment of the present invention, the construction objective function includes:

[0045] Considering vehicle operating costs, flight delay costs, and manual driving costs, construct the objective function F:

[0046] F = minαF Dis +βF Del +γF Man

[0047] Among them, F DisF represents the vehicle's operating cost function; Del Let F represent the cost function for flight delays. Man Let represent the cost function of manual driving; α, β, and γ are adjustment variables.

[0048] In one embodiment of the present invention, establishing constraints based on the acquired information includes:

[0049] Based on airport service level factors, the required shuttle service time for the current flight is set; based on environmental information, the transfer distance between the shuttle bus serving the current flight and the next flight is obtained, and combined with the current shuttle bus speed, the required travel time for the current shuttle bus is calculated, where the maximum speed is assumed by default; simultaneously, based on flight information, the times when the current shuttle bus starts serving the current flight and the times when it starts serving the next flight are obtained, and general constraints are established, which are expressed as follows:

[0050]

[0051]

[0052] in, The time when shuttle bus s begins service for flight f; t f The shuttle service time required for flight f; t f,l The travel time from mission f to mission l. The time when shuttle bus S begins service for flight L; This means that each flight shuttle service is provided by the shuttle bus only once. This ensures that there is sufficient service and transfer time between two consecutive flights;

[0053] Retrieve information on manned shuttle buses from the shuttle bus information database. Based on the maximum number of manned shuttle buses, their speed and maximum speed, and their maximum operating time, combined with the duration of a complete shuttle bus service for the current flight, and determining whether a shuttle bus is departing from its parking area for the first time, establish specific constraints for manned shuttle buses, denoted as:

[0054]

[0055] 0≤v M ≤v M,max

[0056]

[0057] Where M represents a collection of manned shuttle buses; Y 0,sQ is a 0-1 variable, set to 1 when the shuttle bus s first leaves the parking area, and 0 otherwise; M,max This represents the maximum number of manned shuttle buses, i.e., the total number of manned shuttle buses in the shuttle bus set; v M The speed of a manned shuttle bus; v M,max e is the maximum speed of a manned shuttle bus. s A collection of flights serving shuttle bus s; The duration of the shuttle bus service for the entire flight; L M This represents the maximum acceptable working hours for the driver; wherein, the duration of a complete shuttle bus service for a flight is consistent with the shuttle service time required for that flight; ∑ s∈S Y 0,s ≤Q M,max This indicates that the number of manned shuttle buses exiting the parking lot does not exceed the maximum number of existing vehicles; 0 ≤ v M ≤v M,max This ensures that the vehicle speed remains within an acceptable range when driven by a human; This indicates that the shuttle service hours are within the maximum working hours that the driver can accept;

[0058] Information on driverless shuttle buses is obtained from the shuttle bus information. Based on the maximum number of driverless shuttle buses, their travel speeds and maximum speeds, and whether a shuttle bus is departing from a parked vehicle for the first time, specific constraints are established for the driverless shuttle buses, which are represented as follows:

[0059]

[0060] 0≤v U ≤v U,max

[0061] Where U represents the collection of driverless shuttle vehicles; Y 0,s Q is a 0-1 variable, set to 1 when the shuttle bus s first leaves the parking area, and 0 otherwise; U,max This represents the maximum number of driverless shuttle buses, i.e., the total number of driverless shuttle buses in the shuttle bus set; v U v represents the speed at which the driverless shuttle bus travels. U,max This represents the maximum speed of the driverless shuttle bus; ∑ s∈U Y 0,s ≤Q U,max This indicates that the number of driverless shuttle buses exiting the parking lot does not exceed the maximum number of existing vehicles; 0 ≤ v U ≤v U,max This ensures that the vehicle speed remains within an acceptable range for autonomous driving.

[0062] In one embodiment of the present invention, the step of solving the model based on the vehicle usage scenario perception results to minimize the scheduling cost of all shuttle tasks and determining the target shuttle vehicle includes:

[0063] If the airport has m manned shuttle buses and u driverless shuttle buses, N f Flights at remote gates require shuttle bus service. One shuttle bus should be allocated to each flight waiting for shuttle service to minimize the scheduling cost of all shuttle tasks.

[0064] When in scenario 1, it is determined that an unmanned shuttle bus will be used, i.e., S = U. The target unmanned shuttle bus is determined by solving the model.

[0065] When in scenario 2, it is determined that a manned shuttle bus will be used, i.e., S=M. The target manned shuttle bus is determined by solving the model.

[0066] When in scenario 3, it is determined that either a manned or unmanned shuttle bus can be used, i.e., S = U∪M. By solving the model, the target unmanned or manned shuttle bus can be determined.

[0067] In one embodiment of the present invention, the step of executing the shuttle task based on real-time communication according to the target shuttle vehicle situation and providing feedback on the task execution status includes:

[0068] When it is determined that the dispatch vehicle is an unmanned shuttle bus, the dispatch platform sends the route planning results to the target unmanned shuttle bus. The vehicle starts on its own and performs the task according to the route. During the journey, the vehicle uses onboard radar or cameras to detect the surrounding conditions in real time and feeds them back to the dispatch platform.

[0069] When it is determined that the dispatched vehicle is a manned shuttle bus, the dispatch platform sends the route planning results to the driver. The driver starts the vehicle and performs the task according to the route. During the journey, the driver maintains real-time contact with the dispatch platform through communication equipment.

[0070] The communication module enables real-time location sharing and real-time traffic information sharing among all shuttle buses; among these, for any two shuttle buses at any given time, the following conditions must be met:

[0071] x f (t)-x l (t+τ l )≥L+D

[0072] In the formula, x f (t) represents the position of the previous shuttle bus at time t, x l (t+τ l ) represents the position of the next shuttle bus at time t, and τ represents the position of the next shuttle bus at time t. lLet L be the perception and reaction time of shuttle bus l, L be the length of shuttle bus, and D be the minimum safe distance.

[0073] When the next shuttle bus is a manned shuttle bus, τ l =τ M , τ M For manned shuttle buses, the perception and reaction time is τ; when the next shuttle bus is an unmanned shuttle bus, τ l =τ U , τ U For the perception and reaction time of the driverless shuttle vehicle; obviously, τ M >τ U .

[0074] If the conditions are not met, the next shuttle bus will adjust its speed. If it is an unmanned shuttle bus, it will automatically sense and slow down. If it is a manned shuttle bus, the dispatch platform will issue a warning to the driver, who will then slow down.

[0075] This invention also provides an airport shuttle bus dispatching system that allows for both manned and unmanned operations, comprising:

[0076] Information Acquisition Module: Used to acquire real-time information on shuttle buses, flights, and the environment.

[0077] Shuttle bus dispatching platform: It is used to obtain module information based on the information module, determine the target shuttle bus to perform the shuttle task through the round-trip dispatching model of manned and unmanned shuttle buses at the airport, and monitor the operation of the shuttle bus in real time.

[0078] Communication module: used for real-time communication between manned shuttle buses, between driverless shuttle buses, between manned and driverless shuttle buses, and between shuttle buses and the dispatch platform, including wireless communication equipment, mobile communication equipment, and GPS devices;

[0079] Shuttle vehicles: used to perform dispatching tasks, divided into manned shuttle vehicles and driverless shuttle vehicles; manned shuttle vehicles only send their own vehicle information; driverless shuttle vehicles are equipped with OBUs, which achieve direct connection through vehicle-to-everything (V2X) communication, and can send their own vehicle information and obtain information from other vehicles, including location, speed and acceleration, road conditions, and historical operation data.

[0080] This invention also provides an airport shuttle bus dispatching device that allows for both manned and unmanned operations, comprising:

[0081] Memory, used to store computer programs;

[0082] A processor, configured to execute the computer program to implement the steps of the airport shuttle bus scheduling method as described in any one of claims 1 to 8.

[0083] The technical solution of the present invention has the following advantages compared with the prior art:

[0084] (1) The airport shuttle bus scheduling method with both manned and unmanned vehicles described in this invention fully considers the current development status and future development trend of airport shuttle buses. Through vehicle-road collaboration, real-time communication, and optimized hybrid scheduling, it improves the transition from traditional airport environment to completely unmanned airport environment. The proposed airport shuttle bus scheduling method with both manned and unmanned vehicles can effectively cope with the new airport scenarios, realize shuttle bus scheduling in a safe, efficient and controllable manner to the greatest extent possible, reduce flight delay rate and accident rate, optimize the efficiency of airport ground support services, and promote the intelligent development of four types of airports.

[0085] (2) The airport shuttle bus scheduling method for the coexistence of manned and unmanned vehicles described in this invention first conducts vehicle usage scenario perception before constructing the hybrid scheduling model of manned and unmanned airport shuttle buses. It fully considers the special scenarios of using only manned shuttle buses and using only unmanned shuttle buses, and has a certain emergency response capability for special situations. It is more in line with the actual situation and enhances its practicality.

[0086] (3) The airport shuttle bus scheduling method with both manned and unmanned vehicles described in this invention constructs a hybrid scheduling model for manned and unmanned airport shuttle buses. This model fully considers the specific constraints of manned and unmanned shuttle buses, distinguishes the two driving modes of shuttle buses, realizes a hybrid scheduling that is more in line with reality, gives full play to the advantages of both manned and unmanned shuttle buses, and improves the overall scheduling efficiency.

[0087] (4) The airport shuttle bus scheduling method of the present invention, which allows for the coexistence of manned and unmanned vehicles, fully discusses the distance between adjacent manned and unmanned shuttle buses based on real-time communication when the target shuttle bus is performing the shuttle task, thereby further improving the operational safety between vehicles. Attached Figure Description

[0088] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings, wherein...

[0089] Figure 1 This is a flowchart of the airport shuttle bus scheduling method with both manned and unmanned vehicles provided by the present invention;

[0090] Figure 2 This is a schematic diagram of an airport scene provided by the present invention;

[0091] Figure 3This is a schematic diagram of the overall architecture of the airport shuttle bus dispatching system that allows for both manned and unmanned operations, provided by this invention. Detailed Implementation

[0092] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0093] Example 1

[0094] Reference Figure 1 As shown, Figure 1 The flowchart illustrates the airport shuttle bus scheduling method for both manned and unmanned operations provided by this invention; the specific operation steps are as follows:

[0095] S1: Obtain shuttle bus information, flight information, and environmental information, and update the list of flights to be served in real time;

[0096] The shuttle bus information includes shuttle bus number, driving mode, maximum operating time, speed, location, and status. The shuttle bus number is a unique identifier used to distinguish and manage shuttle buses, forming a corresponding set of shuttle buses. Driving mode includes manned and unmanned modes. Maximum operating time specifically refers to the maximum operating time for manned shuttle buses. Speed ​​refers to the shuttle bus's speed at any given time. Location refers to the geographical location of a person within the airport at any given moment. Status indicates whether shuttle bus service is in operation; the period from passenger boarding to passenger disembarking is defined as operating, and the rest as idle.

[0097] Flight information includes flight number, flight service type, service start time, service end time, service start location, and service end location. The flight number is a unique identifier used to distinguish and manage flights, forming a corresponding flight set. Flight service type includes departure and arrival. Service start time refers to the earliest start time of the shuttle service. Service end time refers to the latest end time of the shuttle service. Service start location is the corresponding aircraft parking position or terminal. Service end time is the aircraft parking position or terminal.

[0098] Environmental information includes airport road traffic conditions, ground road conditions, infrastructure conditions, weather conditions, and traffic activities of other road users.

[0099] S2: Based on environmental information, perform vehicle usage scenario perception to confirm the vehicle driving mode for the shuttle service, i.e., manned driving, driverless driving, or both manned and driverless driving are all acceptable;

[0100] Meteorological information, including rain, wind, ice, snow, and fog, is obtained from the weather intelligence system. Based on this information, a comprehensive safety indicator system is established, and corresponding safety risk values ​​are calculated. A safety assessment is conducted on both manned and unmanned shuttle bus services. If the safety risk of the manned shuttle bus service is higher than that of the unmanned shuttle bus service, the current usage scenario is determined to be a severe weather scenario, and the current usage scenario is set as Scenario 1. Under this scenario, it is determined that only unmanned shuttle buses will be used.

[0101] Obtain traffic condition information, including accident vehicles and emergency vehicles; based on the emergency information in the traffic condition information, manually determine the demand for manned and unmanned shuttle services. When the unmanned shuttle vehicle is not capable of handling the situation, the current usage scenario is determined to be an emergency usage scenario, and the current usage scenario is set as scenario 2; under this scenario, it is determined that only manned shuttle vehicles will be used.

[0102] If neither of the above two scenarios exists, the current vehicle usage scenario is determined to be a general vehicle usage scenario, and the current vehicle usage scenario is set to scenario 3. Under this scenario, it is determined that either a manned shuttle bus or an unmanned shuttle bus can be used.

[0103] S3: Based on shuttle bus information, flight information, and environmental information, create an objective function and constraints to establish a hybrid scheduling model for manned and unmanned shuttle buses at the airport; based on the results of vehicle usage scenario perception, solve the model to determine the target shuttle bus;

[0104] S31: Constructing the objective function

[0105] (1) During the vehicle's operation, the operating cost is mainly related to the operating route, which includes the effective service distance and the necessary transfer distance. When the scheduling task is determined, the service start and end points of the shuttle bus will be determined accordingly, that is, the effective service distance is fixed and only the necessary transfer distance needs to be considered. Among them, the necessary transfer distance is obtained based on environmental information.

[0106] Based on shuttle bus information and flight information, decision variables are determined, which are represented as follows:

[0107]

[0108] in, Use 1 when shuttle bus s serves flight f, otherwise use 0;

[0109] Based on the obtained shuttle bus set, flight set, shuttle bus service start and end points, and decision variables, and considering the necessary transfer distances in the travel route, the vehicle travel cost F is constructed. Dis Its function formula is

[0110]

[0111] Among them, f, l, and i are flight numbers; H is the set of flights to be served; D f,l is the transfer distance of the shuttle bus from serving flight f to serving flight l immediately afterwards; s is the shuttle bus number; S is the set of shuttle buses; D 0,l is the transfer distance of the shuttle bus from the parking point to flight l; is a decision variable; Y f,l is a 0-1 variable. When the shuttle bus serves flight f first and then serves flight l immediately afterwards, Y f,l takes 1, otherwise it takes 0, and its representation is as follows:

[0112]

[0113] In the formula, respectively represent the decision variables corresponding to flights f, l, and i, takes 1 when the shuttle bus s serves flights f and l successively and the two tasks are consecutive, otherwise it takes 0; f < i < l means that the service start time of flight i is between flights f and l; that is, when there is any flight i between flights f and l and the shuttle bus s serves flight i, then indicates that at this time the shuttle bus s serves flights f and l successively, but the two service tasks are not connected; when there is no flight i between flights f and l or there is a flight i but the shuttle bus s does not serve flight i, then indicates that at this time the shuttle bus s serves flights f and l successively, and the two tasks are closely connected;

[0114] (2) In terms of flight delays, whether it is a manned shuttle bus or an unmanned shuttle bus, the flight delay cost is mainly related to the gap between the vehicle arrival time and the specified service time;

[0115] According to the flight information and the traffic condition information in the environmental information, and considering the passenger demand at the same time, obtain the earliest arrival time and the latest arrival time of the shuttle bus; set the early arrival penalty coefficient and the late arrival penalty coefficient, and create a time window penalty function W s,f , and its definition is as follows:

[0116]

[0117] Among them, w is the early arrival penalty coefficient, n is the late arrival penalty coefficient, d f is the actual arrival time of the shuttle bus s when serving flight f, a f is the earliest arrival time of the shuttle bus, b f is the latest arrival time of the shuttle bus;

[0118] Construct the flight delay cost F Del , and its formula is

[0119]

[0120] Among them, W s,f For time window penalty function, For decision variables;

[0121] (3) When considering the cost of manual driving, the main consideration is the labor cost of manned shuttle buses; when considering unmanned shuttle buses, the cost of manual driving does not need to be considered; therefore, the cost function F of manual driving is constructed based on the cost of hiring drivers. Man Its formula is

[0122]

[0123] Where R represents the cost of hiring a driver; It is a 0-1 variable, taking the value 1 when a manned shuttle bus is in use, and 0 otherwise.

[0124] In summary, based on the vehicle operating cost, flight delay cost, and manual driving cost functions, the objective function F is constructed as follows:

[0125] F = minαF Dis +βF Del +γF Man

[0126] Among them, α, β, and γ are adjustment variables.

[0127] S32: Establish constraints

[0128] (1) Based on airport service level factors, set the shuttle service time required for the current flight; based on environmental information, obtain the transfer distance between the shuttle bus serving the current flight and the next flight, and calculate the travel time required for the shuttle bus to travel the transfer distance based on the current shuttle bus speed, where the maximum speed is taken by default; simultaneously, based on flight information, obtain the time when the current shuttle bus starts serving the current flight and the time when the current shuttle bus starts serving the next flight, and establish general constraints, which are expressed as follows:

[0129]

[0130]

[0131] in, The time when shuttle bus s begins service for flight f; t f The shuttle service time required for flight f; t f,l The travel time from mission f to mission l. The time when shuttle bus S begins service for flight L; This means that each flight shuttle service is provided by the shuttle bus only once. This ensures that there is sufficient service and transfer time between two consecutive flights;

[0132] (2) Obtain manned shuttle bus information from the shuttle bus information. Based on the maximum number of manned shuttle buses, their speed and maximum speed, and their maximum operating time, combined with the duration of a complete shuttle bus service for the current flight, and determining whether the shuttle bus is departing from its parking area for the first time, establish specific constraints for manned shuttle buses, expressed as follows:

[0133]

[0134] 0≤v M ≤v M,max

[0135]

[0136] Where M represents a collection of manned shuttle buses; Y 0,s Q is a 0-1 variable, set to 1 when the shuttle bus s first leaves the parking area, and 0 otherwise; M,max This represents the maximum number of manned shuttle buses, i.e., the total number of manned shuttle buses in the shuttle bus set; v M The speed of a manned shuttle bus; v M,max e is the maximum speed of a manned shuttle bus. s A collection of flights serving shuttle bus s; The duration of the shuttle bus service for the entire flight; L M This represents the maximum acceptable working hours for the driver; wherein, the duration of a complete shuttle bus service for a flight is consistent with the shuttle service time required for that flight; ∑ s∈S Y 0,s ≤Q M,max This indicates that the number of manned shuttle buses exiting the parking lot does not exceed the maximum number of existing vehicles; 0 ≤ v M ≤v M,max This ensures that the vehicle speed remains within an acceptable range when driven by a human; This indicates that the shuttle service hours are within the maximum working hours that the driver can accept;

[0137] (3) Obtain driverless shuttle bus information from the shuttle bus information. Based on the maximum number of driverless shuttle buses, their driving speed, and their maximum speed, and simultaneously determine whether a shuttle bus is leaving a parked vehicle for the first time, establish specific constraints for the driverless shuttle bus, which are expressed as follows:

[0138]

[0139] 0≤v U ≤v U,max

[0140] Where U represents the collection of driverless shuttle vehicles; Y 0,s Q is a 0-1 variable, set to 1 when the shuttle bus s first leaves the parking area, and 0 otherwise; U,max This represents the maximum number of driverless shuttle buses, i.e., the total number of driverless shuttle buses in the shuttle bus set; v U v represents the speed at which the driverless shuttle bus travels. U,max This represents the maximum speed of the driverless shuttle bus; ∑ s∈U Y 0,s ≤Q U,max This indicates that the number of driverless shuttle buses exiting the parking lot does not exceed the maximum number of existing vehicles; 0 ≤ v U ≤v U,max This ensures that the vehicle speed remains within an acceptable range for autonomous driving.

[0141] S33: Based on the vehicle usage scenario perception results, solve the model to minimize the scheduling cost of all shuttle tasks and determine the target shuttle vehicles, including:

[0142] If the airport has m manned shuttle buses and u driverless shuttle buses, N f Flights at remote gates require shuttle bus service. One shuttle bus should be allocated to each flight waiting for shuttle service to minimize the scheduling cost of all shuttle tasks.

[0143] When in scenario 1, it is determined that an unmanned shuttle bus will be used, i.e., S = U. The target unmanned shuttle bus is determined by solving the model.

[0144] When in scenario 2, it is determined that a manned shuttle bus will be used, i.e., S=M. The target manned shuttle bus is determined by solving the model.

[0145] When in scenario 3, it is determined that either a manned or unmanned shuttle bus can be used, i.e., S = U∪M. By solving the model, the target unmanned or manned shuttle bus can be determined.

[0146] S4: Based on the target shuttle vehicle's status, execute the shuttle task using real-time communication and provide feedback on the task execution status. Specifically, when the dispatched vehicle is determined to be an unmanned shuttle vehicle, the dispatch platform sends the route planning results to the target unmanned shuttle vehicle, which starts automatically and executes the task according to the route. During the journey, the vehicle uses onboard radar or cameras to detect the surrounding conditions in real time and provides feedback to the dispatch platform. When the dispatched vehicle is determined to be a manned shuttle vehicle, the dispatch platform sends the route planning results to the driver, who starts the vehicle and executes the task according to the route. During the journey, the driver maintains real-time communication with the dispatch platform through communication equipment.

[0147] The communication module enables real-time location sharing and real-time traffic information sharing among all shuttle buses; among these, for any two shuttle buses at any given time, the following conditions must be met:

[0148] x f (t)-x l (t+τ l )≥L+D

[0149] In the formula, x f (t) represents the position of the previous shuttle bus at time t, x l (t+τ l ) represents the position of the next shuttle bus at time t, and τ represents the position of the next shuttle bus at time t. l Let L be the perception and reaction time of shuttle bus l, L be the length of shuttle bus, and D be the minimum safe distance.

[0150] When the next shuttle bus is a manned shuttle bus, τ l =τ M , τ M For manned shuttle buses, the perception and reaction time is τ; when the next shuttle bus is an unmanned shuttle bus, τ l =τ U , τ U For the perception and reaction time of the driverless shuttle vehicle; obviously, τ M >τ U ;

[0151] If the conditions are not met, the next shuttle bus will adjust its speed. If it is an unmanned shuttle bus, it will automatically sense and slow down. If it is a manned shuttle bus, the dispatch platform will issue a warning to the driver, who will then slow down.

[0152] Example 2

[0153] Based on the above embodiments, in this embodiment, the airport shuttle bus scheduling problem with both manned and unmanned vehicles can be described as follows: If the airport has m manned shuttle buses and u unmanned shuttle buses, N fFlights requiring remote parking positions need to be served by shuttle buses. One shuttle bus should be allocated to each flight waiting for shuttle service to minimize the scheduling cost of all shuttle tasks.

[0154] To simplify the problem, the following assumptions are made: all manned and unmanned shuttle buses are identical in shape and driving performance; only one shuttle bus is needed for each flight; neither manned nor unmanned shuttle buses experience malfunctions; and there is only one shuttle bus parking area containing both manned and unmanned shuttle buses.

[0155] This embodiment uses the time period of 13:00-13:30, with 3 manned shuttle buses, 1 unmanned shuttle bus, and 3 remote gate flights as an example. The airport scene is illustrated as follows. Figure 2 As shown in Table 1; the flight information at 13:00 is shown in Table 2; and other necessary parameter values ​​are shown in Table 3.

[0156] Table 1 Flight Information at 13:00

[0157]

[0158] Table 2 Shuttle Bus Information at 13:00

[0159]

[0160] Table 3 Required Parameter Values

[0161]

[0162] Step 1: Obtain basic information on airport shuttle buses and flights, and update the list of flights awaiting service in real time;

[0163] The information acquisition module obtains the set of airport shuttle buses S = {M1, M2, M3, U1}, where shuttle bus M1 is in manned mode, has a maximum working time of 4 hours, a speed of 0-25 km / h, is located at point A, and is in working status; shuttle bus M2 is in manned mode, has a maximum working time of 4 hours, a speed of 0-25 km / h, is located at the shuttle bus parking point, and is in idle status; shuttle bus M3 is in manned mode, has a maximum working time of 4 hours, a speed of 0-25 km / h, is located at the shuttle bus parking point, and is in idle status; and shuttle bus U1 is in unmanned mode, has a speed of 0-20 km / h, is located at point O, and is in idle status.

[0164] The information acquisition module obtains the flight set H = {f1, f17, f4}, where flight f1 is a departure flight with a service type of departure, a service start time of 12:58, a service end time of 13:08, a service start location of the terminal building, and a service end location of gate number 1; flight f17 is an arrival flight with a service type of arrival, a service start time of 13:07, a service end time of 13:17, a service start location of gate number 17, and a service end location of the terminal building; flight f4 is an arrival flight with a service type of arrival, a service start time of 13:20, a service end time of 13:30, a service start location of gate number 4, and a service end location of the terminal building.

[0165] At this time, update the set of flights to be served, H. s ={f17,f4}.

[0166] Step 2: Vehicle usage scenario perception to confirm the driving mode of the vehicle implementing the shuttle service, i.e., manned, unmanned, or both manned and unmanned; among them, weather information is obtained through the information acquisition module, and the safety risk of manned shuttle service is no higher than that of unmanned shuttle service, which is not scenario 1 where only unmanned shuttle vehicles are used; no emergencies are found through the monitoring video of the dispatch platform, which is not scenario 2 where only manned shuttle vehicles can be used; therefore, this embodiment is scenario 3, which means that both manned and unmanned shuttle vehicles can be used.

[0167] Step 3: Establish a hybrid scheduling model for manned and driverless shuttle buses at the airport, and determine the target shuttle buses based on the model; the model is established as follows:

[0168] F = minαF Dis +βF Del +γF Man

[0169] st

[0170]

[0171]

[0172]

[0173] 0≤v M ≤v M,max

[0174]

[0175]

[0176] 0≤v U ≤v U,max

[0177]

[0178]

[0179]

[0180]

[0181] Where S = U∩M, M = {M1}, U = U1};

[0182] In the solution process, we set α = 0.1, β = 1, γ = 1, w = 1, n = 2, and the vehicle travels at maximum speed during the transfer. For flight f17, the cost function value of manned shuttle bus M1 is 156.8, the cost function value of manned shuttle bus M2 is 372, the cost function value of manned shuttle bus M3 is 372, and the cost function value of unmanned shuttle bus U1 is 300. Therefore, the target shuttle bus is M1. For flight f4, the cost function value of manned shuttle bus M1 is 392, the cost function value of manned shuttle bus M2 is 392, the cost function value of manned shuttle bus M3 is 392, and the cost function value of unmanned shuttle bus U1 is 320. Therefore, the target shuttle bus is U1.

[0183] Step 4: The target shuttle vehicle executes the shuttle task based on real-time communication and reports the task execution status;

[0184] The manned shuttle bus M1 is started by a driver and performs tasks according to the route planning results issued by the dispatch platform. During the journey, it maintains real-time contact with the dispatch platform through communication equipment. The unmanned shuttle bus U1 starts on its own and performs tasks according to the route planning results issued by the dispatch platform. During the journey, it detects the surrounding conditions in real time through onboard radar or cameras and feeds them back to the dispatch platform.

[0185] Through the communication module, when the distance between adjacent shuttle buses does not meet the condition x f (t)-x l (t+τ l When L ≥ D, if the following vehicle is an unmanned shuttle bus, it will automatically sense and slow down; if it is a manned shuttle bus, the dispatch platform will issue a warning to the driver, who will then slow down.

[0186] Example 3

[0187] Please refer to Figure 3 , Figure 3 This is a schematic diagram of the overall framework of an airport shuttle bus dispatching system that combines manned and unmanned vehicles, provided in an embodiment of the present invention. Specifically, it includes:

[0188] An airport shuttle bus dispatching system that combines manned and unmanned vehicles consists of an information acquisition module, a shuttle bus dispatching platform, a communication module, unmanned shuttle buses, and manned shuttle buses.

[0189] Information acquisition module: used to acquire shuttle bus information, flight information, and environmental information in real time;

[0190] The shuttle bus information includes the shuttle bus's number, driving mode, maximum operating time, speed, location, and status. The number is a unique identifier used to distinguish and manage the shuttle bus. There are two driving modes: manual and driverless. The maximum operating time specifically refers to the maximum working time for a manually driven shuttle bus. The speed refers to the shuttle bus's speed at any given time. The location refers to its geographical position within the airport at any given time. The status indicates whether shuttle service is in operation; the period from passenger boarding to passenger disembarking is defined as operating, and the rest as idle.

[0191] Flight information includes flight number, flight service type, service start time, service end time, service start location, and service end location. The flight number is a unique identifier used to distinguish and manage flights; there are two flight service types: departure and arrival; the service start time refers to the earliest start time of the shuttle service; the service end time refers to the latest end time of the shuttle service; the service start location is the corresponding aircraft gate or terminal; and the service end time is the corresponding aircraft gate or terminal.

[0192] Environmental information mainly refers to airport road traffic conditions, including ground road conditions, infrastructure conditions, weather conditions, and traffic activities of other road users;

[0193] Shuttle bus dispatching platform: It is used to obtain module information based on the information module, determine the target shuttle bus to perform the shuttle task through the round-trip dispatching model of manned and unmanned shuttle buses at the airport, and monitor the operation of the shuttle bus in real time.

[0194] Communication module: Used for real-time communication between manned shuttle buses, between driverless shuttle buses, between manned and driverless shuttle buses, and between shuttle buses and the dispatch platform, including wireless communication equipment (such as vehicle-mounted communication equipment), mobile communication equipment (such as vehicle-mounted communication terminals), and GPS devices.

[0195] Shuttle vehicles: used to perform dispatching tasks, divided into manned shuttle vehicles and driverless shuttle vehicles; manned shuttle vehicles only send their own vehicle information; driverless shuttle vehicles are equipped with OBUs, which are directly connected through vehicle-to-everything (V2X) communication, and can send their own vehicle information and obtain information from other vehicles, including location, speed and acceleration, road conditions, and historical operation data.

[0196] Example 4

[0197] A specific embodiment of the present invention also provides an airport shuttle bus scheduling device that allows for both manned and unmanned vehicles to coexist, comprising: a memory for storing a computer program; and a processor for executing the computer program to implement the steps of the aforementioned airport shuttle bus scheduling method that allows for both manned and unmanned vehicles to coexist.

[0198] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0199] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0200] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0201] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0202] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for scheduling airport shuttle buses that combines manned and unmanned operations, characterized in that, include: Obtain airport shuttle bus information, flight information, and environmental information, and update the list of flights awaiting service in real time; Based on environmental information, the vehicle usage scenario perception is performed to confirm the driving mode of the vehicle that can provide the shuttle service, namely, manned driving, driverless driving, or both manned and driverless driving. Based on shuttle bus information and flight information, decision variables are determined, and combined with environmental information, a vehicle driving cost function is constructed. Based on flight and environmental information, penalty coefficients are set, a time window penalty function is created, and a flight delay cost function is constructed by combining decision variables; the cost of hiring drivers is obtained, and a manual driving cost function is constructed. Construct an objective function based on the vehicle driving cost function, flight delay cost function, and manual driving cost function; Based on the acquired information, constraints are established, including: setting the shuttle service time required for the current flight; obtaining the transfer distance between the shuttle bus serving the current flight and the next flight based on environmental information, and calculating the travel time required for the shuttle bus to travel the transfer distance based on the current shuttle bus speed; and obtaining the time when the current shuttle bus starts serving the current flight and the time when the current shuttle bus starts serving the next flight based on flight information, and establishing general constraints. Get the information of manned shuttle buses from the shuttle bus information, and based on the maximum number of manned shuttle buses, the driving speed and maximum speed of manned shuttle buses, and the maximum working time of manned shuttle buses, set the duration of the shuttle bus's complete service for the current flight, and determine whether the shuttle bus is leaving the parking area for the first time, establish specific constraints for manned shuttle buses. Information on driverless shuttle buses is obtained from the shuttle bus information. Based on the maximum number of driverless shuttle buses, the driving speed of driverless shuttle buses and their maximum driving speed, it is determined whether the shuttle bus is driving out of the parking area for the first time, and specific constraints on driverless shuttle buses are established. Based on the objective function and constraints, a hybrid scheduling model for manned and unmanned shuttle buses at the airport is established. Based on the results of vehicle usage scenario perception, the model is solved to minimize the scheduling cost of all shuttle tasks and determine the target shuttle bus. Based on the target shuttle bus situation, the shuttle task is executed based on real-time communication, and the task execution status is reported back; among them, for any two shuttle buses at any time, the following must be met: at the same moment, the difference between the position of the first shuttle bus and the position of the second shuttle bus is greater than or equal to the shuttle bus length and the minimum safe distance. The step of executing the shuttle task based on the target shuttle vehicle's status and providing feedback on the task execution status includes: When it is determined that the dispatch vehicle is an unmanned shuttle bus, the dispatch platform sends the route planning results to the target unmanned shuttle bus. The vehicle starts on its own and performs the task according to the route. During the journey, the vehicle uses onboard radar or cameras to detect the surrounding conditions in real time and feeds them back to the dispatch platform. When it is determined that the dispatched vehicle is a manned shuttle bus, the dispatch platform sends the route planning results to the driver. The driver starts the vehicle and performs the task according to the route. During the journey, the driver maintains real-time contact with the dispatch platform through communication equipment. The communication module enables real-time location sharing and real-time traffic information sharing among all shuttle buses; among these, for any two shuttle buses at any given time, the following conditions must be met: ； In the formula, For the previous shuttle bus time Location, For the time of the next shuttle bus Location, For shuttle bus Perception and reaction time, For the shuttle bus driver, Minimum safe distance; When the next shuttle bus is a manned shuttle bus , This refers to the perception and reaction time of a manned shuttle bus; when the next shuttle bus is an unmanned shuttle bus... , This is to allow for the perception and reaction time of the driverless shuttle bus; obviously... ; If the conditions are not met, the next shuttle bus will adjust its speed. If it is an unmanned shuttle bus, it will automatically sense and slow down. If it is a manned shuttle bus, the dispatch platform will issue a warning to the driver, who will then slow down.

2. The airport shuttle bus scheduling method with both manned and unmanned vehicles as described in claim 1, characterized in that, The airport shuttle bus information, flight information, and environmental information include: The shuttle bus information includes the shuttle bus number, shuttle bus driving mode, maximum working time of manned shuttle buses, shuttle bus speed, shuttle bus location, and shuttle bus status; among which, a corresponding set of shuttle buses is formed based on the shuttle bus number. Flight information includes flight number, flight service type, shuttle service start time, shuttle service end time, shuttle service start location, and shuttle service end location; among which, a corresponding flight set is formed based on the flight number; Environmental information includes airport road traffic conditions, ground road conditions, infrastructure conditions, weather conditions, and traffic activities of other road users.

3. The airport shuttle bus scheduling method with both manned and unmanned vehicles as described in claim 2, characterized in that, The step of recognizing the vehicle usage scenario based on environmental information and confirming the vehicle driving mode for providing the shuttle service includes: Meteorological information, including rain, wind, ice, snow, and fog, is obtained from the weather intelligence system. Based on this information, a comprehensive safety indicator system is established, and corresponding safety risk values ​​are calculated. A safety assessment is conducted on both manned and unmanned shuttle bus services. If the safety risk of the manned shuttle bus service is higher than that of the unmanned shuttle bus service, the current usage scenario is determined to be a severe weather scenario, and the current usage scenario is set as Scenario 1. Under this scenario, it is determined that only unmanned shuttle buses will be used. Obtain traffic condition information, including accident vehicles and emergency vehicles; based on the emergency information in the traffic condition information, manually determine the demand for manned and unmanned shuttle services. When the unmanned shuttle vehicle is not capable of handling the situation, the current usage scenario is determined to be an emergency usage scenario, and the current usage scenario is set as scenario 2; under this scenario, it is determined that only manned shuttle vehicles will be used. If neither of the above two scenarios exists, the current vehicle usage scenario is determined to be a general vehicle usage scenario, and the current vehicle usage scenario is set to scenario 3. Under this scenario, it is determined that either a manned shuttle bus or an unmanned shuttle bus can be used.

4. The airport shuttle bus scheduling method with both manned and unmanned vehicles as described in claim 1, characterized in that, The process involves determining decision variables based on shuttle bus information and flight information, combining them with environmental information to construct a vehicle driving cost function; setting penalty coefficients based on flight information and environmental information, creating a time window penalty function, and combining them with decision variables to construct a flight delay cost function. Obtain the cost of hiring a driver and construct a human driving cost function, including: During vehicle operation, the operating cost is related to the operating route, which includes the effective service distance and the necessary transfer distance. When the scheduling task is determined, the service start and end points of the shuttle bus will also be determined, that is, the effective service distance is fixed and only the necessary transfer distance needs to be considered. The necessary transfer distance is obtained based on environmental information. Based on shuttle bus information and flight information, decision variables are determined, which are represented as follows: ； in, When the shuttle bus Service flights The value is 1 if the condition is met, otherwise it is 0. Based on the obtained shuttle bus set, flight set, shuttle bus service start and end points, and decision variables, and considering the necessary transfer distances in the travel route, a vehicle travel cost is constructed. Its function formula is ； in, For flight number; Gathering of flights awaiting service; For shuttle buses after serving flights The following service flights The transfer distance; Number the shuttle buses; Gather for the shuttle bus; For shuttle buses from the parking lot to the flight The transfer distance; For decision variables; The variable is 0-1; when the shuttle bus has served all the flights... The following service flights hour, The value is 1 if it is not 0, and it is represented as follows: ； In the formula, These are respectively represented as the corresponding flights. Decision variables, on the shuttle bus Flights served in succession and The value is 1 if the two tasks are consecutive, and 0 otherwise. Representative flights Service start time is during flight and Between; that is, when on a flight and Between, there exists any one flight And shuttle bus Service flights ,but , This indicates that the shuttle bus is at this time. Flights served in succession and However, the two service tasks are not connected; when on a flight and There were no flights in between. Or there are flights But the shuttle bus Service flights ,but , This indicates that the shuttle bus is at this time. Flights served in succession and And these two tasks are closely linked; Regarding flight delays, whether it is a manned or unmanned shuttle bus, the cost of flight delays is related to the gap between the vehicle's arrival time and the scheduled service time. Based on traffic information from flight and environmental data, and considering passenger demand, the earliest and latest arrival times of the shuttle bus are obtained; early arrival penalty coefficients and late arrival penalty coefficients are set, and a time window penalty function is created. Its definition is as follows: ； in, Early arrival penalty coefficient, The penalty coefficient for being late. For shuttle bus Service flights The actual arrival time of the hour. The earliest time the shuttle bus arrives. This is the latest time the shuttle bus will arrive; Based on decision variables and time window functions, construct the cost of flight delays. Its formula is ； in, For time window penalty function, For decision variables; When considering the cost of manual driving, we are referring to the labor costs associated with manned shuttle buses; for driverless shuttle buses, the cost of manual driving is not considered. Therefore, a cost function for manual driving is constructed based on the cost of hiring drivers. Its formula is ； in, This indicates the cost of hiring a driver; It is a 0-1 variable, taking the value 1 when a manned shuttle bus is in use, and 0 otherwise.

5. The airport shuttle bus scheduling method with both manned and unmanned vehicles as described in claim 1, characterized in that, The objective function for construction includes: Considering vehicle operating costs, flight delay costs, and manual driving costs, construct an objective function. : ； in, Represents the vehicle's operating cost function; The function representing the cost of flight delays Represents the cost function of manual driving; , , As a moderating variable.

6. A method for scheduling airport shuttle buses with both manned and unmanned operation as described in claim 4, characterized in that, The establishment of constraints based on the acquired information includes: Based on airport service level factors, the required shuttle service time for the current flight is set; based on environmental information, the transfer distance between the shuttle bus serving the current flight and the next flight is obtained, and combined with the current shuttle bus speed, the travel time required for the current shuttle bus to travel the transfer distance is calculated, where the maximum speed is used by default; simultaneously, based on flight information, the time when the current shuttle bus starts serving the current flight and the time when the current shuttle bus starts serving the next flight are obtained, and general constraints are established, which are expressed as follows: ； ； in, For shuttle bus Commence service flights Time; For flights The required shuttle service time; For flights Mission to Flight The mission's travel time, For shuttle bus Commence service flights Time; This means that each flight shuttle service is provided by the shuttle bus only once. This ensures that there is sufficient service and transfer time between two consecutive flights; Retrieve information on manned shuttle buses from the shuttle bus information database. Based on the maximum number of manned shuttle buses, their speed and maximum speed, and their maximum operating time, combined with the duration of a complete shuttle bus service for the current flight, and determining whether a shuttle bus is departing from its parking area for the first time, establish specific constraints for manned shuttle buses, expressed as follows: ； ； ； in, For manned shuttle buses to gather; It is a 0-1 variable, when the shuttle bus The value is 1 when the vehicle first leaves the parking area; otherwise, it is 0. This represents the maximum number of manned shuttle buses, which is the total number of manned shuttle buses in the shuttle bus set. The speed at which a manned shuttle bus travels; This is the maximum speed at which a manned shuttle bus can travel. For shuttle bus The service's flight collection; For shuttle bus Duration of a full service flight; This represents the maximum working time that the driver can accept; wherein, the duration of the complete shuttle bus service for a flight is consistent with the shuttle service time required for the flight. This indicates that the number of manned shuttle buses exiting the parking lot does not exceed the maximum number of existing vehicles; This ensures that the vehicle speed remains within an acceptable range when driven by a human; This indicates that the shuttle service hours are within the maximum working hours that the driver can accept; Information on driverless shuttle buses is obtained from the shuttle bus information. Based on the maximum number of driverless shuttle buses, their travel speeds and maximum speeds, and whether a shuttle bus is departing from a parked vehicle for the first time, specific constraints are established for the driverless shuttle buses, expressed as follows: ； ； in, For the assembly of driverless shuttle buses; It is a 0-1 variable, when the shuttle bus The value is 1 when the vehicle first leaves the parking area; otherwise, it is 0. This represents the maximum number of driverless shuttle buses, which is the total number of driverless shuttle buses in the shuttle bus set. The speed at which the driverless shuttle bus travels; This is the maximum speed at which the driverless shuttle bus can travel. This indicates that the number of driverless shuttle buses exiting the parking lot will not exceed the maximum number of existing vehicles; This ensures that the vehicle speed remains within an acceptable range for autonomous driving.

7. A method for scheduling airport shuttle buses with both manned and unmanned operation as described in claim 6, characterized in that, The model is solved based on the vehicle usage scenario perception results to minimize the scheduling cost of all shuttle tasks, and the target shuttle vehicles are determined as follows: If the airport has A manned shuttle bus and A driverless shuttle bus Flights at remote gates require shuttle bus service. One shuttle bus should be allocated to each flight waiting for shuttle service to minimize the scheduling cost of all shuttle tasks. When in scenario 1, it is determined that an unmanned shuttle bus will be used, i.e. By solving the model, the target driverless shuttle bus is determined. When in scenario 2, it is determined that a manned shuttle bus will be used, i.e. By solving the model, the target manned shuttle bus was determined. In scenario 3, it is determined that either a manned or unmanned shuttle bus can be used, i.e. By solving the model, the target unmanned shuttle bus or the target manned shuttle bus can be determined.

8. An airport shuttle bus scheduling system that combines manned and unmanned operation, used to implement the airport shuttle bus scheduling method that combines manned and unmanned operation as described in any one of claims 1 to 7, characterized in that, include: Information Acquisition Module: Used to acquire real-time information on shuttle buses, flights, and the environment. Shuttle bus dispatching platform: It is used to obtain module information based on the information module, determine the target shuttle bus to perform the shuttle task through the round-trip dispatching model of manned and unmanned shuttle buses at the airport, and monitor the operation of the shuttle bus in real time. Communication module: used for real-time communication between manned shuttle buses, between driverless shuttle buses, between manned and driverless shuttle buses, and between shuttle buses and the dispatch platform, including wireless communication equipment, mobile communication equipment, and GPS devices; Shuttle vehicles: used to perform dispatching tasks, divided into manned shuttle vehicles and driverless shuttle vehicles; manned shuttle vehicles only send their own vehicle information; driverless shuttle vehicles are equipped with OBUs, which achieve direct connection through vehicle-to-everything (V2X) communication, and can send their own vehicle information and obtain information from other vehicles, including location, speed and acceleration, road conditions, and historical operation data.

9. An airport shuttle bus dispatching system that allows for both manned and unmanned operations, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the airport shuttle bus scheduling method as described in any one of claims 1 to 7.

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