The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis
How to efficiently guide passengers and ensure the order of airport operation is an urgent transport problem for airport management. Based on the analysis of the factors that affect the driver’s decision-making, this paper deeply explores the collaborative association of the core factors, such as th...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2022/4542299 |
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| _version_ | 1832567763767394304 |
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| author | Xiaobing Ding Zhigang Liu Gan Shi Hua Hu Jiaping Chen Kaihe Yang Su Wan Jinlong Wu |
| author_facet | Xiaobing Ding Zhigang Liu Gan Shi Hua Hu Jiaping Chen Kaihe Yang Su Wan Jinlong Wu |
| author_sort | Xiaobing Ding |
| collection | DOAJ |
| description | How to efficiently guide passengers and ensure the order of airport operation is an urgent transport problem for airport management. Based on the analysis of the factors that affect the driver’s decision-making, this paper deeply explores the collaborative association of the core factors, such as the number of flight arrivals in different periods and the average seeking distance of taxis. Firstly, according to the GPS data of taxis, the paper uses clustering algorithm to get the average passenger-seeking time from the airport and makes matching interaction between the number of flights based on time distribution and the average passenger-carrying capacity of vehicles in the parking garage, so as to build a decision-making model based on the number of taxis N; secondly, it takes passenger safety and traffic order as the priority and uses M/M/S queuing model to integrate the two factors. Taking the maintenance cost and passenger evacuation time as constraints, the judgment condition of minimum cost Zmin and the optimal number of boarding points Sm are solved. Finally, taking the flight and taxi data of Shanghai Hongqiao Airport as an example, the driver’s decision-making standard is simulated, and the accuracy of the model is verified by the deviation rate. It can provide decision-making support for taxi management of urban transportation hub and rapid evacuation of airport passengers, so as to realize the collaborative optimization of airport flight arrival and taxi carrying order. |
| format | Article |
| id | doaj-art-e5c49ceedf0c4700a48bb4fc4e4384ba |
| institution | Kabale University |
| issn | 1607-887X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-e5c49ceedf0c4700a48bb4fc4e4384ba2025-02-03T01:00:46ZengWileyDiscrete Dynamics in Nature and Society1607-887X2022-01-01202210.1155/2022/4542299The Optimization of Airport Management Based on Collaborative Optimization of Flights and TaxisXiaobing Ding0Zhigang Liu1Gan Shi2Hua Hu3Jiaping Chen4Kaihe Yang5Su Wan6Jinlong Wu7School of Naval ArchitectureSchool of Urban Railway TransportationSchool of Urban Railway TransportationSchool of Urban Railway TransportationSchool of Urban Railway TransportationSchool of Urban Railway TransportationSchool of Urban Railway TransportationSchool of Transportation EngineeringHow to efficiently guide passengers and ensure the order of airport operation is an urgent transport problem for airport management. Based on the analysis of the factors that affect the driver’s decision-making, this paper deeply explores the collaborative association of the core factors, such as the number of flight arrivals in different periods and the average seeking distance of taxis. Firstly, according to the GPS data of taxis, the paper uses clustering algorithm to get the average passenger-seeking time from the airport and makes matching interaction between the number of flights based on time distribution and the average passenger-carrying capacity of vehicles in the parking garage, so as to build a decision-making model based on the number of taxis N; secondly, it takes passenger safety and traffic order as the priority and uses M/M/S queuing model to integrate the two factors. Taking the maintenance cost and passenger evacuation time as constraints, the judgment condition of minimum cost Zmin and the optimal number of boarding points Sm are solved. Finally, taking the flight and taxi data of Shanghai Hongqiao Airport as an example, the driver’s decision-making standard is simulated, and the accuracy of the model is verified by the deviation rate. It can provide decision-making support for taxi management of urban transportation hub and rapid evacuation of airport passengers, so as to realize the collaborative optimization of airport flight arrival and taxi carrying order.http://dx.doi.org/10.1155/2022/4542299 |
| spellingShingle | Xiaobing Ding Zhigang Liu Gan Shi Hua Hu Jiaping Chen Kaihe Yang Su Wan Jinlong Wu The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis Discrete Dynamics in Nature and Society |
| title | The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis |
| title_full | The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis |
| title_fullStr | The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis |
| title_full_unstemmed | The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis |
| title_short | The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis |
| title_sort | optimization of airport management based on collaborative optimization of flights and taxis |
| url | http://dx.doi.org/10.1155/2022/4542299 |
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