CN115456464A - Vehicle dispatching system and method thereof - Google Patents
Vehicle dispatching system and method thereof Download PDFInfo
- Publication number
- CN115456464A CN115456464A CN202211215995.4A CN202211215995A CN115456464A CN 115456464 A CN115456464 A CN 115456464A CN 202211215995 A CN202211215995 A CN 202211215995A CN 115456464 A CN115456464 A CN 115456464A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- scheduling
- flight
- service
- data information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000004458 analytical method Methods 0.000 claims abstract description 58
- 230000010354 integration Effects 0.000 claims abstract description 10
- 238000007726 management method Methods 0.000 claims description 44
- 238000012544 monitoring process Methods 0.000 claims description 16
- 230000010006 flight Effects 0.000 claims description 13
- 238000013439 planning Methods 0.000 claims description 8
- 238000011156 evaluation Methods 0.000 claims description 3
- 238000012806 monitoring device Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 3
- 238000013468 resource allocation Methods 0.000 claims description 3
- 238000007619 statistical method Methods 0.000 claims description 3
- 230000002159 abnormal effect Effects 0.000 description 4
- 238000004590 computer program Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 238000003860 storage Methods 0.000 description 3
- 238000004140 cleaning Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000003111 delayed effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G06Q50/40—
Abstract
The invention provides a vehicle dispatching system and a method thereof, wherein the system comprises: the information support module is used for acquiring multi-source heterogeneous data information in real time, and performing integration analysis on the multi-source heterogeneous data information based on preset scheduling influence factors to obtain analysis data information; and the intelligent scheduling module is used for determining the service time window of each flight based on the analysis data information, and determining the service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the scheduling rule and the limiting condition. According to the method, the multi-source heterogeneous data is integrated through the scheduling influence factors, and the scheduling rules and the limiting conditions of the guarantee vehicles in the airport are determined, so that the intelligent scheduling of the civil aviation guarantee vehicles is realized by using the vehicle scheduling decision model, and the working efficiency and the accuracy of vehicle scheduling are improved.
Description
Technical Field
The invention relates to the technical field of scheduling management, in particular to a vehicle scheduling system and a vehicle scheduling method.
Background
The rapid development of the air transport industry has made airports increasingly important as air transport network nodes. In recent years, the bottleneck restricting the increase of air traffic flow is shifted to airports by way of air routes, and the urgency of the improvement of the operation management capability of the airport flight zone is also concerned. The airport apron guarantee refers to ground operation performed by an operation guarantee unit around airplanes, goods, luggage and the like, such as aviation fuel filling, luggage unloading and the like, and relates to three types of flights of starting, station passing and after aviation.
Because the large airport has large parking apron area, heavy parking apron guarantee tasks and limited vehicle types and quantity, the parking apron vehicle dispatching command is very complicated work. In addition, because of the operation space and time constraint required by safety operation regulations, the dispatching efficiency is low and command errors are easy to occur due to the fact that the dispatching is carried out only by means of manual experience. Additionally, at present, most airport information sources mainly depend on flight information and part of monitoring information, and information is not updated timely, so that information analysis and mining are not enough, and accuracy of vehicle scheduling is guaranteed to be low.
Disclosure of Invention
The invention provides a vehicle dispatching system and a method thereof, aiming at solving the technical problems of low efficiency and low accuracy of vehicle dispatching which are ensured by only depending on manual experience dispatching.
The invention provides a vehicle dispatching system, comprising:
the information support module is used for acquiring multi-source heterogeneous data information in real time, and performing integration analysis on the multi-source heterogeneous data information based on preset scheduling influence factors to obtain analysis data information;
and the intelligent scheduling module is used for determining the service time window of each flight based on the analysis data information, and determining a service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, a preset scheduling rule and a limiting condition.
According to the vehicle scheduling system provided by the invention, the vehicle scheduling system further comprises a task management module, and the task management module is used for generating and distributing scheduling job tasks based on the service flight sequence, and monitoring the job progress of the scheduling job tasks.
According to the vehicle dispatching system provided by the invention, the limiting conditions at least comprise limiting conditions for ensuring that a vehicle returns to the original place of the parking lot after finishing a dispatching task from the parking lot, performing primary guarantee service on the same flight, finishing the guarantee service on all flights in respective corresponding service time windows, and limiting conditions corresponding to the service quantity upper limit of each flight for ensuring vehicle service and the working time of operation support personnel.
According to the vehicle scheduling system provided by the invention, the scheduling targets of the intelligent scheduling module are that the number of guaranteed vehicles is the minimum, the service time consumption of the guaranteed vehicles is the minimum, and the number of guaranteed vehicles for serving flights is less than the upper limit of the service number, wherein the service time consumption represents the travel time consumption of the guaranteed vehicles from the parking lot to the parking lot after the scheduling task is finished.
According to the vehicle scheduling system provided by the invention, the information support module comprises a flight management unit, an airport management unit, a vehicle management unit, a personnel management unit and a monitoring equipment unit; wherein:
the multi-source heterogeneous data information comprises flight planning inbound time, flight planning outbound time, model and shutdown machine position corresponding to flights, airport road network information and road speed rule information corresponding to airport management units, vehicle positions and guaranteed vehicle information corresponding to vehicle management units, operation guarantee personnel information of personnel management units, monitoring information corresponding to monitoring and guaranteeing vehicles of monitoring equipment units and meteorological data of external service systems, wherein the flight planning inbound time and the flight planning outbound time correspond to the flight management units.
According to the vehicle scheduling system provided by the invention, the analysis data information comprises the running distance between each shutdown machine position, the average speed of the guaranteed vehicle, the service time consumption, the operation time of different operation guarantee personnel, the operation time of different machine types and the operation time under different meteorological conditions.
According to the vehicle dispatching system provided by the invention, the dispatching rules at least comprise an important flight priority rule, a formal flight priority rule, a departure time priority rule, a normal flight priority rule, a task balance distribution rule, an emergency priority rule and a comprehensive resource allocation optimal rule.
According to the vehicle dispatching system provided by the invention, the vehicle dispatching system also comprises an operation analysis module,
the operation analysis module is used for carrying out statistical analysis on the completion degree of the scheduling job task and the utilization rate of the guarantee vehicles;
and the operation analysis module is also used for carrying out guarantee evaluation analysis on service consumed time, waiting time and flight delay time of the guarantee vehicle based on the scheduling operation task.
The invention provides a vehicle scheduling method, which comprises the following steps:
integrating and analyzing the multi-source heterogeneous data information acquired in real time based on preset scheduling influence factors to obtain analyzed data information;
determining a service time window for each flight based on the analysis data information;
and determining a service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition.
According to the vehicle scheduling method provided by the invention, after the service flight sequence corresponding to the guaranteed vehicle is determined by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition, the method further comprises the following steps:
and generating and distributing a scheduling job task based on the service flight sequence, and monitoring the job progress of the scheduling job task.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a vehicle scheduling method as in any one of the above.
The vehicle scheduling system and the vehicle scheduling method provided by the invention comprise an information support module, a data analysis module and a data analysis module, wherein the information support module is used for acquiring multi-source heterogeneous data information in real time, and carrying out integration analysis on the multi-source heterogeneous data information based on preset scheduling influence factors to obtain analysis data information; and the intelligent scheduling module is used for determining the service time window of each flight based on the analysis data information, and determining the service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition. The integration of multi-source heterogeneous data through the scheduling influence factors is realized, so that data information having influence on scheduling is obtained, and the scheduling rules and the limiting conditions of the guarantee vehicles in civil aviation are determined, so that the intelligent scheduling of the guarantee vehicles in civil aviation is realized, the scheduling working efficiency and the utilization rate of the guarantee vehicles are improved, and the coordination efficiency and the flight punctuality rate of various guarantee vehicles in an airport are improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a system framework diagram of a vehicle dispatch system provided by the present invention;
fig. 2 is a schematic flow chart of a vehicle scheduling method provided by the invention.
The reference numbers illustrate:
001: an information support module; 002: an intelligent scheduling module; 003: a task management module; 004: an operation analysis module; 011: a flight management unit; 012: an airport management unit; 013: a vehicle management unit; 014: a personnel management unit; 015: and monitoring the equipment unit.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the one or more embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the invention. As used in one or more embodiments of the present invention, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present invention refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that, although the terms first, second, etc. may be used herein to describe various information in one or more embodiments of the present invention, such information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first aspect may be termed a second aspect, and, similarly, a second aspect may be termed a first aspect, without departing from the scope of one or more embodiments of the present invention. The word "if" as used herein may be interpreted as "at … …" or "at … …" depending on the context.
An exemplary embodiment of the present invention will be described in detail below with reference to fig. 1.
FIG. 1 is a system block diagram of a vehicle dispatch system in accordance with the present invention. As shown in fig. 1, the vehicle dispatching system includes an information support module 001 and an intelligent dispatching module 002, the information support module 001 is in communication connection with the intelligent dispatching module 002, the information support module 001 at least includes a flight management unit 011, an airport management unit 012, a vehicle management unit 013, a personnel management unit 014 and a monitoring device unit 015, wherein the flight management unit 011 is configured to obtain, in real time, flight scheduled arrival time, flight scheduled departure time, model and shutdown position corresponding to the flight to be reached, the airport management unit 012 is configured to try to obtain airport road network information and road speed rule information on the airport, the road speed rule information represents an upper limit of a road traveling speed, the vehicle management unit 013 is configured to obtain, in real time, information such as vehicle position, type of a guarantee vehicle, vehicle traveling speed and vehicle state of each guarantee vehicle on the parking lot, different types of guarantee vehicles have different operation capacities (such as refueling vehicles with different volumes), and the personnel management unit 014 is configured to collect information of guarantee personnel, such as status and guarantee operation efficiency information corresponding to the guarantee vehicles on the airport 015, and monitor each road in the monitoring device process.
Further, in order to more clearly describe the operation principle of the vehicle dispatching system, the following description is provided in detail.
The information support module 001 is used for acquiring multi-source heterogeneous data information in real time, and performing integration analysis on the multi-source heterogeneous data information based on preset scheduling influence factors to obtain analysis data information;
it should be noted that the vehicle is related to weather factors during the dispatching process. The system is also in communication connection with an external service system corresponding to weather so as to obtain current weather data in real time, and additionally, the system also obtains airport road network information and road speed rule information corresponding to the airport management unit 012, guarantee vehicle information corresponding to the vehicle management unit 013, operation support personnel information of the personnel management unit 014 and monitoring information corresponding to the support vehicles monitored by the monitoring equipment unit 015 in real time based on the flight plan inbound time, flight plan outbound time, model and shutdown position corresponding to the flight plan corresponding to the flight management unit 011, and further forms the multi-source heterogeneous data information according to the information, so that support of real-time information query and information maintenance is provided for dispatchers and managers.
Further, it is necessary to determine scheduling influence factors in the vehicle scheduling process, where the scheduling influence factors are factors that influence scheduling and guarantee operations in the airport environment, and the factors include flight types, flight scheduled arrival times, flight scheduled departure times, flight statuses, emergency events, flight seat statuses, vehicle statuses, operator statuses, weather conditions, airport environment, and the like.
And then the integration analysis comprises processing modes such as data cleaning, data processing completion, data disambiguation, data classification, data preprocessing and the like, specifically, based on the scheduling influence factors, classifying information such as flights, models, personnel and security vehicles in the multi-source heterogeneous data information to obtain classification information, and further, preprocessing and analyzing the classification information to obtain information such as the travel distance between each shutdown position, the average speed of the security vehicles, the service time consumption, the operation time length of different operation security personnel, the operation time length of different models, the operation time length under different meteorological conditions and the like.
The intelligent scheduling module 002 is configured to determine a service time window of each flight based on the analysis data information, and determine a service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, a preset scheduling rule, and a limitation condition.
It should be noted that, because the scheduled inbound time and/or the scheduled outbound time of the different flights of the aircraft are different, the service time windows corresponding to the different flights of the aircraft are different during the flight guarantee, and each task is completed within the predetermined service time window.
Due to the requirement of safety operating regulations, some operation tasks are not allowed to be simultaneously expanded, and the constraint of a tandem relation needs to be met, for example, the filling of the aviation oil is carried out after the passengers leave, and the filling is finished before the passengers leave. And some operation tasks, such as the maintenance of the aircraft and the cleaning of the passenger cabin, are allowed to be simultaneously performed, and the operation tasks are completed within a preset station passing time period of the aircraft as much as possible so as not to influence the flight of the aircraft in the next flight period.
Specifically, based on the operation duration of different types in the analysis data information, in cooperation with the cooperation of other support units, a service time window of each flight is determined, wherein the service time window represents the earliest starting time and the latest starting time of support services, and further, based on the service time window of each flight, the analysis data information, preset scheduling rules and limiting conditions, a service flight sequence corresponding to a support vehicle is determined by using a vehicle scheduling decision model, wherein the limiting conditions at least comprise that the support vehicle returns to a parking lot after finishing a scheduling operation task from the parking lot, the same flight performs primary support services, all flights complete support services in the service time window corresponding to each flight, the service quantity upper limit of each support vehicle service flight and the limiting conditions corresponding to the working duration of operation support personnel, and the service quantity upper limit of each support vehicle service flight is set, so that balanced scheduling of each support vehicle is realized.
The vehicle scheduling decision model is a multi-objective optimization model, and as an implementable mode, firstly, a geographic information system is adopted to topologically divide airport road network information into discrete graphic elements according to the distribution of special roads and machine positions of airport security vehicles to obtain a set of accessible areas of security vehicles, and then the vehicle scheduling decision model is constructed by combining flight, security vehicle information, security operator information and the like based on the set. The dispatching goal of the model is to ensure that the number of vehicles is minimum and the service time consumption of the vehicles is minimum, wherein the service time consumption is the running time consumed by the vehicles to return to the original place of the parking lot after starting from the parking lot and completing the dispatching task, and the number of the vehicles on the service flights is smaller than the upper limit of the service number, so that the balanced dispatching of each vehicle is realized.
Further, the scheduling rules comprise scheduling rules of flight, operation environment and guaranteed vehicle, wherein the scheduling rules corresponding to the flight comprise important flight priority rules, departure time sequence dispatching, normal flight prior delay and delayed flight, special flight or emergency priority rules and the like; the dispatching rules corresponding to the working environment comprise formal machine position priority rules, vehicle-to-machine position distance priority rules, non-interference working environment priority dispatching rules and the like; the scheduling rules corresponding to the vehicles comprise rules such as task balance distribution rules, priority vehicle dispatching with short vehicle distance, comprehensive resource allocation optimal rules and the like.
The vehicle scheduling system further comprises a task management module 003, wherein the task management module 003 is configured to generate and distribute a scheduling job task based on the service flight sequence, and monitor a job progress of the scheduling job task.
Specifically, after a service flight sequence output by a vehicle scheduling decision model is utilized, a scheduling job task is generated based on the service flight sequence and then automatically issued to a corresponding guarantee vehicle, after a determination instruction of a dispatcher is received, the scheduling job task is notified to a driver of the guarantee vehicle or is sent to a vehicle-mounted terminal of the guarantee vehicle in a data chain mode, in addition, in the process of guaranteeing service, the job progress of the scheduling job task needs to be monitored, if an abnormal condition occurs in the task process, field workers and the dispatcher or manager of a vehicle scheduling system carry out voice talkback, vehicle adjustment and task updating are carried out reasonably in time, and the abnormal condition is processed.
The vehicle scheduling system further comprises an operation analysis module 004, and the operation analysis module 004 is used for carrying out statistical analysis on the completion degree of the scheduling job task and the utilization rate of the guaranteed vehicle.
The operation analysis module 004 is further configured to perform guarantee evaluation analysis on service consumption time, waiting time and flight delay time of the guaranteed vehicle based on the scheduling job task.
It should be noted that, when the guarantee vehicle is not allocated, the guarantee vehicle is located in the parking area when the scheduling job task is not allocated, once the scheduling job task is allocated, the guarantee vehicle immediately goes to the designated machine location to perform the job, and in the scheduling stage, it is assumed that the guarantee vehicle leaves the parking area once the guarantee vehicle returns to the parking area until the assigned task is completed, and the service time consumption mainly includes the time consumption for traveling between the machine locations and the time consumption for traveling between the refueling area or the passenger and cargo area and the machine location.
In addition, the service consumption after the guarantee vehicle executes the scheduling job task, the waiting time and the flight delay time in the process of executing the scheduling job task can be guaranteed, evaluated and analyzed, and the analysis results are displayed on a vehicle scheduling system, so that a dispatcher and a manager can visually know the scheduling details of the guarantee vehicle and realize the refined management degree based on the analysis results.
Through the scheme, the embodiment of the invention comprises the following steps: the information support module is used for acquiring multi-source heterogeneous data information in real time, and performing integration analysis on the multi-source heterogeneous data information based on preset scheduling influence factors to obtain analysis data information; and the intelligent scheduling module is used for determining the service time window of each flight based on the analysis data information, and determining the service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition. The integration of multi-source heterogeneous data through scheduling influence factors is achieved, and special scheduling rules and limiting conditions of guarantee vehicles in civil aviation are made clear, so that intelligent scheduling of the guarantee vehicles in civil aviation is achieved, the scheduling work efficiency and the operating vehicle utilization rate are improved, and the coordination efficiency and the flight punctuality rate of various guarantee vehicles in airports are improved.
Fig. 2 is a schematic flow chart of a vehicle dispatching method provided by the invention, and as shown in fig. 2, the vehicle dispatching method includes:
step 21, integrating and analyzing the multi-source heterogeneous data information acquired in real time based on preset scheduling influence factors to obtain analyzed data information;
and step 23, determining a service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition.
Specifically, the current weather information needs to be obtained in real time based on the flight plan entry time, the flight plan exit time, the model and the shutdown machine position corresponding to the flight, the airport road network information and the road speed rule information corresponding to the airport management unit 012, the safeguard vehicle information corresponding to the vehicle management unit 013, the operation safeguard personnel information of the personnel management unit 014, and the monitoring information corresponding to the safeguard vehicle monitored by the monitoring equipment unit 015, so that the multi-source heterogeneous data information is analyzed based on the scheduling influence factors to obtain the analysis data information such as the travel distance between the shutdown machine positions, the average speed of the safeguard vehicle, the service time consumption, the operation time of different operation safeguard personnel, the operation time of different models, the operation time under different weather conditions, and the like. And then calculating to obtain a service time window of each flight based on the flight plan inbound time and the flight plan outbound time of each flight in the analysis data information, and further determining a service flight sequence corresponding to the guarantee vehicle by using a vehicle scheduling decision model corresponding to multi-objective optimization based on the service time window of each flight, the analysis data information, preset scheduling rules and limiting conditions, so as to obtain the optimal guarantee vehicle of each flight and realize intelligent scheduling of the guarantee vehicle.
And additionally, in the process of guaranteeing service, the operation progress of the scheduling operation task needs to be monitored, and if the situation that the task performing process is abnormal is monitored, field workers and dispatchers or managers of the vehicle scheduling system speak in voice, vehicle adjustment and task updating are carried out reasonably in time, and the abnormal situation is processed.
According to the scheme, the integration of multi-source heterogeneous data through the scheduling influence factors is achieved, so that data information having influence on scheduling is obtained, and the special scheduling rules and limiting conditions of the guarantee vehicles in the civil aviation are defined, so that the intelligent scheduling of the guarantee vehicles in the civil aviation is achieved, the scheduling work efficiency and the utilization rate of the operation vehicles are improved, and the coordination efficiency and the flight punctuality rate of various guarantee vehicles in an airport are improved.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to perform the vehicle scheduling method provided by the above methods.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above technical solutions substantially or otherwise contributing to the prior art may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the embodiments or some parts of the embodiments, the method including: integrating and analyzing the multisource heterogeneous data information acquired in real time based on preset scheduling influence factors to obtain analysis data information; determining a service time window for each flight based on the analysis data information; and determining a service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A vehicle dispatch system, comprising:
the information support module is used for acquiring multi-source heterogeneous data information in real time, and performing integration analysis on the multi-source heterogeneous data information based on preset scheduling influence factors to obtain analysis data information;
and the intelligent scheduling module is used for determining the service time window of each flight based on the analysis data information, and determining the service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition.
2. The vehicle scheduling system of claim 1, further comprising a task management module configured to generate and distribute scheduled job tasks based on the sequence of service flights and to monitor job progress of the scheduled job tasks.
3. The vehicle dispatching system of claim 2, wherein the limiting conditions at least include limiting conditions corresponding to the service time of the guarantee vehicle, the guarantee vehicle returns to the original place of the parking lot after finishing the dispatching task from the parking lot, the same flight performs one-time guarantee service, all flights complete the guarantee service in the respective corresponding service time window, the service number upper limit of each guarantee vehicle service flight, and the working time of the operation support staff.
4. The vehicle scheduling system of claim 3, wherein the scheduling objectives of the intelligent scheduling module are that the number of guaranteed vehicles is the minimum, the service time consumption of the guaranteed vehicles is the minimum, and the number of guaranteed vehicles on service flights is less than the upper limit of the service number, wherein the service time consumption represents the travel time of the guaranteed vehicles from the parking lot to the parking lot after the scheduling task is completed.
5. The vehicle dispatching system of claim 1, wherein the information support module comprises a flight management unit, an airport management unit, a vehicle management unit, a personnel management unit, and a monitoring device unit; wherein:
the multi-source heterogeneous data information comprises flight planning inbound time, flight planning outbound time, model and shutdown machine position corresponding to flights, airport road network information and road speed rule information corresponding to airport management units, vehicle positions and guaranteed vehicle information corresponding to vehicle management units, operation guarantee personnel information of personnel management units, monitoring information corresponding to monitoring and guaranteeing vehicles of monitoring equipment units and meteorological data of external service systems, wherein the flight planning inbound time and the flight planning outbound time correspond to the flight management units.
6. The vehicle dispatching system of claim 1, wherein the analysis data information comprises travel distance between each shutdown position, average speed of the guarantee vehicle, service time, operation time of different operation support personnel, operation time of different models and operation time under different meteorological conditions.
7. The vehicle dispatching system of claim 1, wherein the dispatching rules comprise at least important flight priority rules, official flight priority rules, departure time priority rules, normal flight priority rules, task balance allocation rules, emergency priority rules, and comprehensive resource allocation optimization rules.
8. The vehicle dispatching system of claim 2, further comprising an operational analysis module,
the operation analysis module is used for carrying out statistical analysis on the completion degree of the scheduling job task and the utilization rate of the guarantee vehicles;
and the operation analysis module is also used for carrying out guarantee evaluation analysis on service time consumption, waiting time and flight delay time of the guaranteed vehicle based on the scheduling job task.
9. A vehicle scheduling method applied to the vehicle scheduling system according to any one of claims 1 to 8, comprising:
integrating and analyzing the multi-source heterogeneous data information acquired in real time based on preset scheduling influence factors to obtain analyzed data information;
determining a service time window for each flight based on the analyzed data information;
and determining a service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition.
10. The vehicle scheduling method according to claim 9, wherein after determining a service flight sequence corresponding to the guaranteed vehicle by using a vehicle scheduling decision model based on the service time window of each flight, the analysis data information, the preset scheduling rule and the limiting condition, the method further comprises:
and generating and distributing a scheduling job task based on the service flight sequence, and monitoring the job progress of the scheduling job task.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211215995.4A CN115456464A (en) | 2022-09-30 | 2022-09-30 | Vehicle dispatching system and method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211215995.4A CN115456464A (en) | 2022-09-30 | 2022-09-30 | Vehicle dispatching system and method thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115456464A true CN115456464A (en) | 2022-12-09 |
Family
ID=84308780
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211215995.4A Pending CN115456464A (en) | 2022-09-30 | 2022-09-30 | Vehicle dispatching system and method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115456464A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116258354A (en) * | 2023-05-15 | 2023-06-13 | 民航成都信息技术有限公司 | Execution method, device, equipment and medium of flight ground service node |
| CN116862139A (en) * | 2023-06-01 | 2023-10-10 | 中国航空油料集团有限公司 | Intelligent scheduling decision method, device and system for fuelling vehicle |
-
2022
- 2022-09-30 CN CN202211215995.4A patent/CN115456464A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116258354A (en) * | 2023-05-15 | 2023-06-13 | 民航成都信息技术有限公司 | Execution method, device, equipment and medium of flight ground service node |
| CN116258354B (en) * | 2023-05-15 | 2023-09-19 | 中国民用航空总局第二研究所 | Execution method, device, equipment and medium of flight ground service node |
| CN116862139A (en) * | 2023-06-01 | 2023-10-10 | 中国航空油料集团有限公司 | Intelligent scheduling decision method, device and system for fuelling vehicle |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107169677B (en) | Centralized dispatching command system for civil airport apron security vehicles | |
| CN115456464A (en) | Vehicle dispatching system and method thereof | |
| US20190108758A1 (en) | System and method for flight delay prediction | |
| US10522045B2 (en) | Flight schedule disruption awareness systems and methods | |
| EP3115945A1 (en) | Method and system for managing personnel work disruption in safety critical industries | |
| WO2018196700A1 (en) | Flight assignment system and method based on candidate mechanism | |
| US10607496B2 (en) | System and method to assist pilots in determining aircraft phase transition time based on monitored clearance information | |
| Denery et al. | The center-tracon automation system: Simulation and field testing | |
| CN111062644A (en) | Airport ground service vehicle management and control system and method based on high-precision navigation positioning | |
| CN112700070A (en) | Management and control method and system for automatic driving vehicle of airport | |
| CN110827582A (en) | System and method for automatically acquiring flight landing point in emergency | |
| CN115759605A (en) | Method for realizing dynamic adjustment of guarantee node based on key path algorithm | |
| CN110349444B (en) | Air traffic flow management method based on big data | |
| CN112700071A (en) | Control method and system for automatically driving passenger ferry vehicle in airport | |
| EP3418959A1 (en) | Flight schedule determining systems and methods | |
| CN112767726A (en) | Control method and system for manned and automatic driving vehicles in airport | |
| Chao et al. | Simulation study on airfield system capacity analysis using SIMMOD | |
| Kwasiborska | Development of an algorithm for determining the aircraft pushback sequence | |
| CN115049100A (en) | Airport resource allocation optimization method, device, equipment and readable storage medium | |
| Alonso Tabares et al. | Intelligent and fuzzy applications in aircraft handling services with aviation 4.0 | |
| Mota et al. | Improving airport performance through a model-based analysis and optimization approach | |
| CN117291318B (en) | Flight delay prediction method and system based on multi-factor time judgment logic | |
| Narendra | Improving the operational performance efficiency index of an airport by managing and reducing controllable delays: A case study of Delhi International Airport Limited, India | |
| Donahue | The US Air Transportation System: A Bold Vision for Change | |
| Gosling | Development of a framework for assessing the benefits of airport surface traffic automation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB03 | Change of inventor or designer information | ||
| CB03 | Change of inventor or designer information |
Inventor after: Wang Lei Inventor after: Yu Huiyang Inventor after: Guan Dasheng Inventor after: Liu Cong Inventor after: Yu Bin Inventor before: Li Yanzhen Inventor before: Li Lin Inventor before: Li Chengzhong Inventor before: Zhang Yu Inventor before: Zhao Huan |
|
| TA01 | Transfer of patent application right |
Effective date of registration: 20240402 Address after: 201613 Building 2, No. 55, Huahua Road, Songjiang District, Shanghai Applicant after: SHANGHAI CHENGFEI AVIATION SPECIAL EQUIPMENT Co.,Ltd. Country or region after: China Address before: 266107 No. 2, Xiangtan Road, Danshan Industrial Park, Chengyang District, Qingdao, Shandong Applicant before: Inspur Communication Technology Co.,Ltd. Country or region before: China |