Application of dual-sensitive decision mechanism based on queuing theory in airport taxi management

TL;DR

This paper introduces a dual-sensitive decision model and queuing models to optimize taxi management at airports, aiming to improve efficiency, balance driver income, and reduce passenger waiting times.

Contribution

It develops a novel dual-sensitive decision mechanism and queuing models specifically tailored for airport taxi management challenges.

Findings

Enhanced taxi load rate and passenger satisfaction.

Balanced driver income distribution.

Reduced passenger waiting times.

Abstract

With the rapid development of economy and global trade, flying has increasingly become the main way for people to travel, and taxi is the main transfer tool of the airport, especially in the airport with wide passenger sources and large passenger flow. However, at present, many large airports have the phenomenon of low taxi load rate, unbalanced income and long waiting time for passengers. Therefore, how can drivers make decisions to maximize their benefits, and how can management departments allocate resources and formulate management systems to improve ride efficiency and balance drivers' benefits have become urgent problems to be solved. This paper solves the above problems by establishing the taxi driver dual-sensitive decision model, the longitudinal taxi queuing model and the short-distance passenger re-return forced M/M/1 queuing model.