Research On Traveler’s Travel Characteristics Analysis Method Based On Urban Traffic Big Data

In order to achieve the goal of "vigorously developing shared transportation,building a service system based on mobile intelligent terminal technology,and realizing travel as a service",it is necessary to integrate multiple modes of transportation and provide one-stop travel service by means of information technology.The analysis of the travel characteristics of each traveler is a necessary prerequisite for the realization of urban multi-mode integrated travel services.This study establishes a set of universal travel characteristic methodology system,including historical travel data acquisition method,travel characteristic index system establishment method and travel rule identification,mining and visualization method,to provide method and technical support for urban multi-mode integrated travel service and other subsequent research.Firstly,this paper discusses the connotation and index selection of travel characteristics,and then discusses how to obtain complete historical travel data.In view of the incomplete data,a complete data preprocessing method is proposed,and a case study is carried out based on the map query data;in view of the complete data,the acquisition algorithm of historical travel data is proposed.Then,based on the historical trip data,this paper establishes an explicit characteristic index system,which includes four aspects: trip times,trip OD,trip time and trip mode.Based on this index system,the travel rules are mined and predicted.In this paper,the travel rules are divided into two parts: implicit characteristics and travel patterns.The implicit characteristics part discusses the travelers’ occupation,residence,work and commuting characteristics and travel preferences.The travel patterns part identifies and aggregates the travel patterns of all travelers from the perspective of aggregation and non aggregation.Based on the travel patterns after aggregation,the travel behaviors of travelers are predicted.Finally,from a practical point of view,based on the travel feature acquisition technology and travel pattern recognition technology,this paper establishes a visual platform to display the mining results of travel feature and travel pattern.