Research On Methodology Of Capacity Matching Prediction And Parking Guidance For Airport Taxi

With the rapid development of China’s economy and the continuous improvement of consumption levels,more and more passengers choose to travel by plane.As an important part of the land-side transportation system,the taxi has become one of the main transportation options for passengers due to their strong service flexibility,strong accessibility,and fast speed.However,the increasingly prominent problem of capacity mismatching has caused a great impact on the normal operation of the airport.On one hand,in case of special circumstances,such as flight delays,and insufficient taxi capacity will result in a large number of passengers delayed at the airport.On the other hand,capacity of taxi is excessive during some other time,causing the parking lot to be congested and difficult to manage.The methods,such as prediction and analysis of capacity matching,timely warning of potential capacity mismatching phenomena,and dynamic induction of parking for airport taxis,can provide theoretical support for relevant airport management departments to take corresponding measures in time.The main research contents of this thesis are as follows:(1)Airport taxi capacity matching prediction.The taxi capacity prediction models based on LSTM,GRU,and GS-SVR are established respectively.The results show that GRU model is best and the minimum MAPE is 12.9%.Finally,the predicted total capacity and total demand of taxis are matched and analyzed,and the results show that the supply of taxi capacity is greater than the demand during certain periods,and taxi management needs to be guided.(2)Establishment of taxi parking guidance model based on Stackelberg game.On the premise of meeting the demand of taxi capacity,the objective functions of minimizing the parking amount of taxi parking lot at peak time and maximizing the comprehensive income of taxi drivers are used to establish a taxi parking guidance game model.The results show that when meeting the demand of taxi capacity,the model can reduce the parking volume of taxi parking lots by 30.5% during peak hours on while maximizing the revenue of taxi drivers.(3)The development of a prototype system for airport taxi capacity dynamic prediction and parking information.This thesis builds an airport taxi capacity dynamic prediction and parking information releasing prototype system.It can collect,clean,and store relevant data,and dynamically runs the airport taxi capacity prediction model to realize the taxi capacity dynamic prediction and result visualization;and it can dynamically release the parking information of the taxi parking lot to provide a basis for the taxi driver to make decisions.