The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis. (4th February 2022)

• Record Type: Journal Article
• Authors: Ding, Xiaobing; Liu, Zhigang; Shi, Gan; Hu, Hua; Chen, Jiaping; Yang, Kaihe; Wan, Su; Wu, Jinlong
• Other Names: Xu Zeshui Academic Editor.
• Is Part Of: Discrete dynamics in nature and society. Volume 2022(2022)
• Publication Date: 2022-02-04
• Subjects: System analysis -- Periodicals; Dynamics -- Periodicals; Chaotic behavior in systems -- Periodicals; Differentiable dynamical systems -- Periodicals; 003.05
• DOI: 10.1155/2022/4542299
• Languages: English
• ISSNs: 1026-0226

Abstract

Abstract : 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 S m 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.