Research And Software Development Of Multi Traffic Transfer Method In Terminal Of Airline Hub

With the rapid development of the civil aviation industry,the passenger throughput of airports continues to increase,and the construction of the comprehensive transportation system of the hub airport continues to improve.Therefore,higher demands are placed on the quality of passenger services at airports,and transfer services with multiple modes of transportation have become one of the research hotspots.At present,the existing domestic smart terminals for transfer services at domestic airports mainly have functions such as location display,outdoor route planning and other related functions,and there are few service terminals for the traffic transfer process in the terminal.This article studies the multi-transport transfer process.The main research methods involve traffic recommendation and navigation path planning in the terminal.In terms of traffic recommendation,the situation of inbound passengers is complicated and the transportation modes are complicated.The personalized service quality of the hub airport is difficult to match the needs of passengers.It is urgent to use modern technologies such as passenger feature portraits,passenger flow big data and passenger behavior deduction to optimize;In terms of path navigation in the terminal,the traditional indoor navigation path planning mainly considers the geometric information of the indoor layout,and rarely considers the multi-floor path planning strategy and multi-object path optimization,and proposes new challenges to the location service in the terminal.Based on the above-mentioned problems and challenges,the research work of this article is mainly carried out from the following aspects:(1)Constructing a road network model suitable for the complex space in the terminal building: This paper analyzes the multi-floor indoor space and cross-floor transfer requirements in the terminal building,then studies the method of building an indoor road network model.Next,this paper constructs the topological road network of the terminal building by using a graph model,which is used as the basis of the method research in this paper.(2)Proposing a method for recommending traffic transfer based on KNN: In this paper,a large number of questionnaires are distributed to collect passenger big data behavioral situation characteristics,and KNN classification algorithm to process passenger heterogeneous characteristic data are used.Finally,this paper establishs a passenger transfer behavior classifier,and the prediction accuracy rate can reach 72.5%.(3)Proposing a route planning method for traffic transfer and navigation in the terminal based on improved genetic algorithm: Based on the spatial characteristics of the terminal building and changes in the environment,this paper establishes a two-way network with the weight of the path and the density of the flow of people as the weight,and weighs the three factors of path distance,passenger congestion,time cost and multi-objective path optimization model.Finally,this paper uses the genetic algorithm fused with BFS to optimize the multi-target path in the terminal building in the multi-layer road network established in this paper,and generates the optimal path considering path distance,congestion and time cost.(4)Realizing the construction and test verification of multi-transport transfer software in the terminal building: Based on the above hub airport needs,this paper builds a multi-transport mode transfer software in the terminal building,and tests and verifies the traffic mode recommendation algorithm and multi-object path optimization method in this paper for different scenarios.The verification results show that the traffic recommendation algorithm in this paper can achieve the optimal recommendation for the transfer of traffic mode;The optimal path planning method in the terminal building can present three single-objective optimal paths with the smallest path distance,the lowest congestion and the least time cost,and the multi-objective optimal path which weighs the three one.Figure 34,table 24,reference 81.