The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis

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 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.

Airport Cab Drivers' Passenger Carrying Strategy Selection Based on Mathematically Derived Theoretical Models

“…Some scholars construct a decision support model from the perspective of opportunity cost, taking into account the relevant factors affecting the cab driver's decision-making, and constructing a linear logarithmic regression model of the passenger's willingness to take a cab and the cab driver's opportunity cost [3]. Based on the analysis of the factors affecting drivers' decisionmaking, the synergistic association between the number of flight arrivals in different periods and the average cab-seeking distance and other core factors is deeply explored [4]. Based on the cost-benefit analysis method and multilevel grid division algorithm, the factors affecting the decision-making of cab drivers were identified [5,6].…”

Estimating the Lag Time Between Flight Arrivals and Parking Exit Volumes at a Major Airport: A Practical Approach

“…The lag time estimates also help evaluate airport service levels, as time indicators are key performance parameters in many previous studies [16]. To achieve the collaborative optimization of airport flight arrival and taxi carrying order, Ding et al established a matching interaction model based on flight and taxi data from Shanghai Hongqiao Airport [17]. However, to the best of our knowledge, no study has been conducted on flight arrivals and parking exit volumes, which have growing importance due to the increasing usage of online vehicles.…”