| The study of passenger flow analysis of urban rail transit lines plays an important role in maintaining the operation of urban rail transit networks.It is a strong support for the optimization of operation maps and the decision-making of station passenger flow organization.The choice of urban rail transit plan refers to the sequence of trains and corresponding stations that passengers choose to ride in sequence during travel.Based on the basic concepts of urban rail transit passenger flow analysis and the influencing factors of passenger flow,this paper uses graph theory to represent the urban rail transit network,estimates the elements of passenger travel time,classifies effective routes,and establishes the basis for The travel path selection classification model of the KNN-DPC algorithm,and the effective path travel time estimation result is matched with the center travel time of various clusters through the fuzzy pattern recognition method to obtain the real travel paths corresponding to various clusters,according to the classification of effective paths On the basis of this,a model for choosing a ride plan based on train capacity limitations is constructed,which depicts the trajectory of passengers,and solves the problem of tracking the trajectory of staying passengers.Indeed,the accuracy and authenticity of subsequent passenger flow analysis.The specific research is as follows:1.Based on the analysis of passenger flow analysis of urban rail transit at home and abroad,research on line passenger flow analysis.Firstly,the research status of passenger flow analysis at home and abroad is introduced,and according to the research methods in this paper,the research situation of urban rail transit ride selection is summarized and compared with the characteristics of existing ride selection models.2.Construct a map of the urban rail transit road network,analyze the components of passenger travel time in detail,determine the parameter estimation methods for each component,determine the estimated travel time of each effective path,search for the effective paths in the road network,and The effective paths are classified to lay a theoretical foundation for the selection rules of the ride plan.3.Compare and analyze various clustering algorithms,and use KNN-DPC clustering method for clustering analysis of AFC data to obtain the number of passengers in each cluster and the travel time of the cluster center.Use the travel time of the cluster center The fuzzy recognition processing method matches the estimated travel time of the effective route to obtain the number of passengers for each route.4.Based on the different effective route classifications,determine the rules for the selection of different effective routes.Based on the transfer OD pairs with reserved reservations,propose the rules for the rides based on the train capacity limit and establish a model for the choice of rides.And determine the passenger flow index of urban rail transit lines and the distribution of passenger flow characteristics,and analyze the passenger flow of urban rail transit lines.5.Analyze the situation of Chengdu’s urban rail transit line,analyze the passenger flow of Chengdu Urban Rail Transit Line 2 and make reasonable suggestions based on the selection scheme of the ride plan and the theory of passenger flow analysis of the line.In this paper,the passenger travel time extracted from AFC data is used as the research object,and the travel results are directly analyzed,which is closer to the actual passenger travel route selection and ride selection,and the line passenger flow characteristics are better analyzed.Realistic significance.This article studies passenger flow data based on the ride plan selection model,analyzes the travel results,and more realistically simulates and reproduces the passenger travel route selection and ride selection,and better analyzes the characteristics of the line passenger flow.. |
